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Emerging effects of comorbidities on multiple sclerosis
Review
Emerging effects of comorbidities on multiple sclerosis Ruth Ann Marrie, Ralph I Horwitz Lancet Neurol 2010; 9: 820–28 Health Sciences Center, Winnipeg, MB, Canada (R A Marrie MD); and Stanford University, Stanford, CA, USA (Prof R I Horwitz MD) Correspondence to: Ruth Ann Marrie, Health Sciences Center, GF-533, 820 Sherbrook Street, Winnipeg, MB R3A 1R9, Canada [email protected]
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Although the interaction between comorbidities and chronic diseases is strong, the effect of comorbidities receives little attention in many chronic diseases. In multiple sclerosis (MS), an increasing amount of evidence suggests that physical and mental comorbidities, and adverse health factors such as smoking and obesity, are common and can affect the disease. These comorbid diseases and lifestyle factors affect clinical phenotype, the diagnostic delay between symptom onset and diagnosis, disability progression, and health-related quality of life. Future studies of comorbidity and MS should consider comorbidities and health behaviours and should take into account the modifying effects of socioeconomic status, ethnic origin, and cultural factors. Studies of the frequency of comorbidities in patients with MS should be population based, incorporating appropriate comparator groups. These studies should expand the range of comorbidities assessed, and examine how the frequency of comorbidities is changing over time. Further research is needed to answer many other questions about comorbidities and their associations with MS, including the best way to measure and analyse comorbidities to understand these associations.
Introduction
Mechanisms for comorbidities in MS
Important associations exist between comorbidities and chronic diseases but for many chronic diseases comorbidities are given little consideration.1 Typically, comorbidity refers to the total burden of illness other than the specific disease of interest,1 and is distinct from complications of the disease. In the general population, comorbidities are common and their frequency increases with age.2 Many adverse health outcomes are associated with comorbidities, including reduced functional status, increased use of health-care services, reduced quality of life, and increased mortality.1 The adverse effects of a comorbidity are not limited to any particular index disease or population of patients.1 In neurological disorders, recognition of the frequency and importance of comorbidities is increasing. Patients with epilepsy commonly have psychiatric disorders, and such patients more frequently use health-care services.3 Migraine and sleep disorders are also common comorbidities in patients with epilepsy. Some of these comorbidities can affect control of seizures; untreated obstructive sleep apnoea can be associated with refractory epilepsy and treatment can improve control of seizures.4 In patients with Alzheimer’s disease, vascular factors can increase the rate of disease progression.5 Multiple sclerosis (MS) is a chronic, progressively disabling disease of the CNS, estimated to affect more than 2·5 million people worldwide.6,7 It is the most common non-traumatic cause of disability in young adults,8 and the societal costs of this disease are higher than are those for patients with stroke or Alzheimer’s disease.9 Patients with MS are also likely to be affected by comorbidities, but little knowledge exists about which comorbidities are most common or how they affect treatment decisions, treatment responses, or health outcomes. This is a crucial gap in knowledge for patients and clinicians, and is an opportunity to improve patients’ health status. In this Review, we examine data on the association between comorbidities and MS, and provide recommendations for further research.
A detailed examination of the mechanisms that might underlie the coexistence of MS and another disorder in the same individual, and the evidence for these mechanisms, is beyond the scope of this Review, although we will briefly discuss the general mechanisms (Valderas and colleagues10 provide further discussion). First, two disorders might co-occur simply by chance alone. Second, patients with one chronic disease might be more likely to be diagnosed with a second disorder because of increased use of health services. Third, diseases might co-occur owing to one of several aetiological mechanisms, including direct causation, associated risk factors, heterogeneity, and independence. In direct causation, one disorder directly leads to another, and this mechanism can be used to describe comorbidities arising directly from a disease (eg, MS) or its treatments. Common risk factors can lead to increased co-occurrence of disease; common genetic susceptibility to immune disorders has been proposed as the mechanism underlying the increased frequency of comorbid autoimmune disease in patients with MS,11 although common environmental factors, such as smoking, are another possible explanation. Other independent factors such as age, obesity, and poor diet can be associated with increased co-occurrence of disease (heterogeneity). Alternatively, two disorders might coexist because they are consequences of a third, as yet undiagnosed disease (independence). Finally, Berkson’s bias, a selection bias that occurs when hospital controls are used in a case-control study, might also lead to an increase in observed comorbidities among the controls owing to a higher probability of the combination of exposure to a risk factor and occurrence of disease having led to their hospitalisation.
Frequency of comorbidities Autoimmune comorbidities Several initial investigations of comorbidities in MS have examined whether autoimmune diseases occur more frequently in patients with MS than would be expected in www.thelancet.com/neurology Vol 9 August 2010
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the general population.12–14 Findings about autoimmune disease are conflicting, possibly because of differences in study design.15 In two population-based studies,16,17 patients with inflammatory bowel disease had an increased risk of incident and prevalent demyelinating disease, which contrasts with findings from previous studies.18,19 In several small studies,11,14,20 co-occurrence of rheumatoid arthritis ranged from 0·9% to 4·4%. Few studies had adequate sample sizes to establish whether systemic lupus erythematosus occurs more frequently in patients with MS than expected; in the New York State Multiple Sclerosis Consortium,20 2·1% of 3019 patients with MS had comorbid lupus. Thyroid disease is reported to occur more often than expected in patients with MS, with frequencies of up to 9% in a study of 353 patients;21 however, only two21,22 of four studies with a control or reference group identified an increased risk.19,21–23 The absolute frequency of most of these autoimmune diseases is low enough that they are unlikely to have a substantial effect on MS at the population level. Thyroid disease is potentially more important than are the other autoimmune diseases because of its higher frequency and potential contributions to fatigue, a common disabling symptom in MS.
Physical comorbidities Physical comorbidities other than autoimmune diseases seem to be common in patients with MS.24 Participants in the North American Research Committee on Multiple Sclerosis (NARCOMS) registry24 provide information about their MS on a continual basis. In 2006, 8983 participants in the NARCOMS registry reported their comorbidities;25 the most frequent were hypercholesterolaemia (37%), hypertension (30%), arthritis (16%), irritable bowel syndrome (13%), and chronic lung disease (13%). This list includes three of the five leading causes of disability in the general population: hypertension, lung disease, arthritis, back or spine problems, and heart disease.26 After standardisation for age, many of these comorbidities seem to occur at similar frequencies to those in the general population.27 Limitations of this study include use of a volunteer sample, absence of a control group, and the fact that these comorbidities were self-reported. In the nationally representative Canadian Community Health Survey,28 302 respondents with MS reported comorbidities that included back problems (35%), non-food allergies (29%), arthritis (26%), hypertension (17%), and migraine (14%). This study also relied on self-report. Data from several studies have indicated that sleep disorders are more common in patients with MS than in the general population.29 Restless legs syndrome, for example, occurs with a frequency ranging from 13·3% to 37·5% depending on the population studied.30–34 In most of these studies, restless legs syndrome occured substantially more often in individuals with MS than in the general population. Nishino and colleagues35 reviewed 116 symptomatic cases of narcolepsy and found that ten (9%) were associated with MS. Among 16 074 US www.thelancet.com/neurology Vol 9 August 2010
veterans with MS, 940 (6%) had sleep disorders compared with 3% of veterans without MS, in whom sleep disturbance was defined as the presence of at least one diagnostic polysomnogram or sleep disorder during the study period.36
Psychiatric and behavioural comorbidities In addition to physical comorbidities, psychiatric comorbidities are common in patients with MS. The lifetime incidence of depression in patients with MS is 50%,37 nearly three times higher than in the general population.38 The 12-month prevalence of depression in patients with MS is as high as 14%,38 twice that of the reported prevalence in the general population of 5·9–7·3%.37 The lifetime incidence of anxiety disorders, including social phobias, is as high as 35% in patients with MS,39,40 compared with 16·6% in the general population.41 Bipolar disorder affects 0·30% to 13% of patients with MS, depending on the population studied.42,43 Results from a study that used administrative insurance claims data from a Canadian province found that 0·8% of 10 367 patients with MS had non-organic psychoses.44 Other studies of psychosis in patients with MS relied on hospital-based populations and had inadequate numbers of patients to establish reliable estimates.45 Despite the well recognised frequency of psychiatric comorbidities, they remain underdiagnosed.39 Data from several studies have indicated that smoking is a risk factor for MS; in one study that used data from the NARCOMS registry, 4867 (54%) of the 8983 responders with MS were reported to have ever smoked.46 In a study of 140 patients with MS, the lifetime incidence of alcohol misuse was reported as 13·6%, while problem drinking was reported to affect 14–16·4% in the MS cohort.47 About 50% of patients with MS are overweight or obese, a similar proportion to that of the general population.46,48 Participants with severe disability, however, might be at risk of being underweight.46
Recommendations for future studies Future studies of the frequency of comorbidity in MS compared with the general population should be population based. These studies should expand the range of comorbidities assessed and examine temporal changes in the frequency of comorbidity. Further study of the variation in the frequency of comorbidities across sociodemographic subgroups is also needed. Studies of the frequency of comorbidities in subgroups of people with MS should incorporate appropriate comparator groups. We need to establish which comorbidities are sufficiently prevalent across MS populations to be universally important and which have clinically relevant effects.
Effects of comorbidities on MS An increasing amount of evidence suggests that comorbidities and lifestyle factors might affect the diagnostic delay between MS onset and diagnosis, the 821
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clinical phenotype of MS, disability progression, healthrelated quality of life (HRQoL), and treatment decisions.
Diagnosis In participants in the NARCOMS registry, the presence of comorbidities and adverse health behaviours affected the diagnostic delay between MS symptom onset and diagnosis.49 The presence of obesity, smoking, and physical or mental comorbidities was associated with increased diagnostic delays of nearly 11 years for some comorbidities. After accounting for demographic and clinical characteristics, long diagnostic delays persisted. The reasons for this finding are uncertain, but there are several possible explanations. Pre-existing disease could mask the symptoms of MS, or the existing burden of illness could negatively affect access to care. In some cancers, a comorbidity is associated with delayed referrals to specialists by general practitioners, possibly because new symptoms are mistakenly attributed to the pre-existing condition.50 The amount of time and testing needed to diagnose MS could also be affected by a comorbidity.
Clinical presentation In a study of 1465 patients with MS, including 780 who have never smoked, 428 ex-smokers, and 257 who currently smoke, current smokers (odds ratio [OR] 2·42, 95% CI 1·09–5·35) and ex-smokers (1·91, 1·02–3·58) were more likely to present with primary-progressive MS than with relapsing-remitting MS.51 Unfortunately, investigators of this study did not examine potential confounders such as comorbid obesity or vascular risk factors. In the NARCOMS registry, participants with any physical comorbidity at the time of MS diagnosis were more likely to report moderate disability than mild disability at diagnosis, and the likelihood of moderate disability increased with the number of comorbidities reported (OR 1·13, 1·03–1·23).49 When studied in more detail, vascular, musculoskeletal, and psychiatric comorbidities and obesity were associated with increased severity of disability at diagnosis. After adjustment, the OR for moderate disability compared with mild disability at diagnosis was 1·51 (95% CI 1·12–2·05) in participants with a vascular comorbidity and 1·38 (1·02–1·87) in those with obesity. The OR for severe disability compared with mild disability was 1·81 (1·25–2·63) in participants with a musculoskeletal comorbidity, and 1·62 (1·23–2·14) in those with a psychiatric comorbidity. These findings need to be replicated in population-based cohorts with other approaches such as medical records review for measurement of comorbidities.
Disability progression Comorbidity is also associated with increased progression of disability. In a population-based study of patients with MS, those with asthma were more likely to have more rapid progression to early gait dysfunction than 822
were patients without asthma (p=0·0277).52 Vascular comorbidities, including diabetes, hypertension, hypercholesterolaemia, heart disease, and peripheral vascular disease, are associated with more rapid progression of ambulatory disability than in the absence of these comorbidities.53 Compared with patients with MS who did not develop a vascular comorbidity, individuals who reported the presence of one or more vascular comorbidities at the time of their diagnosis of MS had a more than 1·5-times increased risk of needing a cane to walk (hazard ratio [HR] 1·68, 95% CI 1·51–1·87). These findings were similar for patients who developed a vascular comorbidity at any point during their disease course (HR 1·54; 1·44–1·65). During a 3-year observational study, patients who were newly diagnosed with MS and musculoskeletal comorbidities had greater declines in physical functioning (5-point decline on the motor scale of the functional independence measure) than did those without such comorbidities (2-point decline).54 Results from several studies suggest that smoking is associated with an increased risk of disability progression in patients with MS. In a study using information from the General Practice Research Database,55 smokers with relapsing-remitting MS were three times more likely to develop secondary-progressive disease than were nonsmokers (HR 3·6, 95% CI 1·3–9·9), whereas only 20 of 179 patients who were never-smokers or ever-smokers had a progressive course. In another study of 122 individuals with newly diagnosed MS, 72% of eversmokers who began smoking before the age of 15 years developed secondary-progressive MS after a median of 6 years of follow-up.56 40% of ever-smokers who began smoking after the age of 15 years developed secondaryprogressive MS, whereas only 26% of those who had never smoked progressed. Di Pauli and colleagues57 followed up 129 patients with a clinically isolated syndrome who were at high risk of developing MS on the basis of findings from MRI and CSF examination. After 3 years, 75% of smokers developed MS compared with only 51% of non-smokers (HR 1·8, 95% CI 1·2–2·8). By contrast, Sena and colleagues58 examined 205 women with definite MS from Portugal and noted that smoking had a protective effect in women who had the apolipoprotein E ε4 isoform; smokers had lower scores on the expanded disability status scale (p=0·033) and multiple sclerosis severity score (p=0·023) than did nonsmokers. The study was restricted to women from a clinic-based population and needs to be replicated. Only one study, by Pittas and colleagues,59 accounted for the potential confounding effects of other health behaviours.59 In two studies,51,60 smoking was associated with an increased number of gadolinium-enhancing lesions, increased T2-weighted lesion volume, and greater brain atrophy. Neither study included a control group of smokers without MS to facilitate the assessment of whether smoking has additive or multiplicative effects on brain imaging measures such as brain volume. www.thelancet.com/neurology Vol 9 August 2010
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Health-related quality of life HRQoL is lower in patients with MS than it is in the general population and other chronic disease populations.61 Age, sex, socioeconomic status, and disability status affect HRQoL in patients with MS.62 Although comorbidities are associated with reduced HRQoL in other chronic diseases,1 little is known about their effects in MS. In a study of 262 patients with relapsing-remitting MS, poor HRQoL, as measured by the short form-36 health survey, was associated with comorbidities. Patients with comorbid musculoskeletal and respiratory disorders had worse physical HRQoL than did those without such disorders; additionally, headaches and urinary and digestive tract problems were associated with worse mental HRQoL.63 Of 335 people with MS who responded to the Canadian Community Health Survey,28 patients without a comorbidity had a mean HRQoL score of 0·64, as measured by the health utilities index mark III version, which was higher than the mean score of 0·52 for participants with one or more comorbidities. Both studies were cross-sectional and did not clearly distinguish between comorbidities and complications of MS.
Treatment decisions As well as affecting disease status, comorbidities can affect treatment decisions, including the choice of whether to start treatment, the specific choice of treatment, and its subsequent effectiveness. Liver disease and severe depression, for example, are contraindications to the use of interferon beta.64 Many clinical trials in patients with MS exclude individuals with severe comorbidities or substance use disorders;65 thus, the safety, tolerability, and effectiveness of most drugs is not known in such patients. Patients with several chronic health disorders report many barriers to care,66 so compliance with treatment might also be adversely affected, reducing the already limited benefits of treatment. Comorbid depression is already recognised to reduce adherence to disease-modifying treatment.67
Benefits of studying comorbidities in MS Several potential benefits can be gained from the study of comorbidities in patients with MS, including improved prognosis, individualised disease management, insights into the causes and pathophysiology of MS, and new treatment approaches. Natural history studies have focused on the prognostic value of clinical characteristics of this disorder,68 but prognosis early in the disease course remains poor. Inclusion of comorbidity information could improve prognosis by explaining heterogeneity in disease outcomes, which would enable clinicians to provide individual patients with better information about the clinical course of their disease and to make informed treatment choices. In other diseases, understanding the effects of comorbidities has led to disease management www.thelancet.com/neurology Vol 9 August 2010
guidelines based on the presence of specific comorbidities, as shown in the 2003 national hypertension guidelines;69 the target blood pressure is lowered for individuals with diabetes or chronic renal disease, and the choice of antihypertensive therapy depends on the presence or absence of comorbidities such as diabetes, previous myocardial infarction, and heart failure.69 If particular diseases or combinations of diseases have a greater effect on disability progression than do other diseases, novel insights could be gained into the causes and pathophysiology of MS. Diabetes, for example, might affect the brain by increasing susceptibility to oxidative stress, increasing inflammatory responses, and altering blood vessel function.70 If diabetes were associated with increased disability in MS, then this connection would suggest that insulin-related and hyperglycaemia-related mechanisms should be studied. Finally, if a particular comorbidity substantially affects outcome for patients with MS, aggressive treatment of the comorbidity could be a new approach to improve those outcomes.
Theoretical and methodological considerations The main goal of determining the associations between comorbidities and MS is to improve the health of the patient with MS. So far, we have focused specifically on comorbidities. To understand these associations, we need to consider a broader approach that takes into account the comorbidity, treatments for the comorbidity, treatments for MS, environmental factors such as socioeconomic status, and their combined effects on the status of the patient (figure).
Definitions We previously defined comorbidity as the total burden of illness other than the specific disease of interest,1 but this definition does not include comorbid health behaviours and lifestyle factors such as smoking, alcohol intake, and physical activity. Health behaviours substantially affect the risk and outcomes of chronic disease and contribute to health disparities in individuals of different ethnic origins.71 These behaviours might affect health outcomes independently of comorbid diseases. For example, smokers with lung cancer have a worse survival outcome than non-smokers independent of smoking-associated comorbidities, cancer stage, and treatment.72 We propose that future studies of comorbidity should also encompass health behaviours. The definition of comorbidity also distinguishes comorbid diseases and complications of the index disease. From a clinical perspective, the distinction between comorbidities and complications is relevant because the interventions can differ; if the comorbidity worsens the outcome, the focus should be on treatment of the comorbidity, but if the complication worsens the outcome, then the focus should be on treatment of the primary disease in addition to treatment of the complication. From a broader clinical perspective, the 823
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MS-associated disability and related treatments
Comorbidity and related treatments
Global status of patient
Complications of MS and related treatments
Socioeconomic status
Figure: Factors that affect the health status of patients with multiple sclerosis MS=multiple sclerosis.
primary disease and related complications, comorbidities, and their respective treatments collectively contribute to the overall health status of the patient; thus, in some situations it might be appropriate to assess the effect of all these factors (figure). Although we emphasise the need to distinguish comorbidities from complications of disease clinically, this differentiation can be difficult, particularly given the unknown pathogenesis of MS. As the knowledge of the pathogenesis of MS improves, the classification of conditions as comorbidities or complications will also need to improve. This will be particularly important for studies of the mechanisms underlying comorbidities and complications of disease and their effects on MS. Although comorbidities or their treatments can affect MS, MS and its treatments can also affect the diagnosis, risk, or severity of comorbidity. In the same way that preexisting comorbidities can adversely affect the diagnostic delay between onset and diagnosis of MS, the diagnosis of comorbidities could be delayed by mistakenly attributing neurological symptoms such as progressive inability to walk, pain, or seizures to the pre-existing diagnosis of MS. Corticosteroids used for relapses, for example, might worsen diabetes, lead to the development of cataracts, or contribute to weight gain. Physical disability can restrict physical activity, contributing to the risk of the individual becoming overweight or obese.73
Factors that modify associations between comorbidities and MS Characteristics such as age, sex, race, ethnic origin, and socioeconomic status will modify associations between 824
comorbidities and MS outcomes. In view of the association of age with MS outcomes such as ambulatory disability and relapse rate,74,75 and the association of age with comorbidities and problems such as frailty, age should be dealt with carefully in any study of comorbidities and MS. Although the adverse effects of MS on employment and relationships are recognised,76,77 and there are many important social determinants of health including socioeconomic status, these are understudied in MS. Socioeconomic status is a complex, multifactorial construct that describes a person’s position in society.78 Although most commonly measured by a combination of income and education, these factors do not completely represent socioeconomic status.78 Socioeconomic status is a fundamental determinant of health, and is associated with leading causes of death, functional status, and health behaviours.79,80 In the participants from the NARCOMS registry, differences in disease severity between individuals of different ethnic origins were overestimated by up to 25% when socioeconomic status was not taken into account.81 Patients with MS who have a low socioeconomic status are at a higher risk of having a comorbidity, might undergo fewer investigations for MS-related symptoms, and receive fewer symptomatic therapies than those with high socioeconomic status,25,82 all of which might adversely affect functional status. Thus, future studies of comorbidities should measure these characteristics.
Measurement of comorbidities An important question for future studies is the way in which comorbidities should be measured. Sources of comorbidity data include medical records, self-report, and administrative databases; none of these sources is clearly established as the gold standard in all situations. The validity of these data sources varies depending on the comorbidities of interest.83 The validity of self-reported comorbidities varies substantially by disorder: they are reasonably accurate for well defined, chronic disorders that require ongoing care or that cause disability, but are less accurate for diseases with less explicit diagnostic criteria, such as arthritis.83 Self-reported data, however, might be more accessible and less costly than other approaches in large studies, and might predict quality of life and functional status more accurately than medical records data.84 Administrative data are an accessible and efficient data source compared with primary data collection. Although administrative insurance claims data might not accurately report comorbidities compared with medical records,85 these data are more reliable than a review of the records of a single provider. Thus, no data source is ideal for all research studies; establishing the validity of each data source for the comorbidities of interest is crucial. Little work has examined measurement of comorbidities in patients with MS, including the concerns of validity and whether the ideal method of comorbidity www.thelancet.com/neurology Vol 9 August 2010
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measurement differs according to the outcome or research question of interest. Results from several studies indicate that patients with MS can accurately report their diagnoses of MS (κ coefficient of level of agreement=0·86, 95% CI 0·81–0·91),86 year of symptom onset, type of clinical course, and some aspects of their disability status (eg, correlation between physician-scored expanded disability status scale score and patient-determined disease steps is 0·94).87 As reported in other populations, agreement between patient-reported chronic disorders— such as diabetes, hypertension, hyperlipidaemia, autoimmune thyroid disease, heart disease, and chronic lung disease—and those reported in medical records of the MS population is moderate to high (κ=0·52–0·88).88 This finding suggests that self-report can be used as a data source in studies of these common comorbidities. Algorithms developed with information from the Canadian administrative health claims databases86 and the Veterans Administration databases have been used to identify people with MS with reasonable sensitivity (93%) and specificity (92%).89 Although further validation is needed for studies of comorbidities that use administrative data, previous studies in other chronic diseases can provide some insights.90 Administrative data might be particularly useful when evaluating the effect of rare comorbidities and when the outcomes of interest relate to mortality and use of health-care services, for which substantial experience with administrative data already exists. There are three general methods to classify comorbidity analytically—a simple count of disorders, use of a comorbidity index, or consideration of each comorbidity as a distinct entity91—each of which has strengths and weaknesses. A comorbidity count is easy to understand and obtain, and predicts outcomes of use of health-care services.91 This method, however, assumes that any given comorbidity has an equal effect on outcome in terms of magnitude and direction, and does not take into account differential effects of disease severity. A comorbidity index is a summary measure that captures the number of comorbidities and the severity of those comorbidities.91 An index can be weighted to apply greater importance to a particular disorder or can be unweighted. A generic index is intended as an easy measurement approach for many populations without adaptation, but presumes an equal effect of each component irrespective of the index disease or population.91 In a generic index, complications that indicate the severity of the index disease might be mistakenly defined as comorbidities. A disease-specific comorbidity index avoids these problems. These summary measures omit comorbid health behaviours or lifestyle factors. None of the existing comorbidity indexes has been validated for use in MS. A measure used in another population could be used, but would need to be adapted and validated before use. As most MS care is provided in ambulatory settings, a measure validated in an outpatient population would have greater use than would one www.thelancet.com/neurology Vol 9 August 2010
developed in an inpatient population. One comorbidity measure is unlikely to be equally appropriate for all health outcomes;92 therefore, a series of measures might be necessary, each sharing common core elements. The final option is to treat each of the comorbidities separately when predicting health outcomes. This approach facilitates the study of interactions between specific pairs of diseases and is likely to improve predictive ability of multivariable models,93 but sample size might be a limiting factor. To understand the potentially additive, synergistic, or antagonistic associations between multiple Panel: Summary and recommendations for the design of future studies of comorbidities in patients with MS Research questions Establish the frequency of comorbidities in MS • Choose a population-based design when appropriate • Expand the range of comorbidities assessed • Examine temporal trends and variation across sociodemographic subgroups • Examine variation in comorbidities according to clinical characteristics of MS • Include appropriate comparator groups (eg, studies of whether a comorbidity is more common in MS than in the general population should use general population controls) Establish the effects of comorbidities on MS • Examine the effect of comorbidities on all aspects of physical and cognitive impairment and health-related quality of life at diagnosis and throughout the disease course • Examine the effect of comorbidities on disease-modifying treatment in MS, including choice of therapy, response to therapy, tolerability, and adherence • Examine the effect of comorbidities on symptomatic treatment in MS, including choice of therapy, response to therapy, tolerability, and adherence • Account for age, sex, race, ethnic origin, and social determinants of health • Compare the effect of comorbidities in MS with the effect of comorbidities in other chronic neurological and autoimmune diseases Establish the effect of MS on comorbidities • Examine the effect of MS on diagnosis and treatment of comorbidities • Account for age, sex, race, ethnic origin, and social determinants of health • Compare the effect of comorbidities in MS with the effect of comorbidities in other chronic neurological and immune-mediated diseases Methodological questions Develop a clear definition of comorbidity • Define comorbidities broadly and clearly • Incorporate comorbid health behaviours • Identify which comorbid health behaviours are most important to incorporate Identify the best methods for the measurement of comorbidities in MS • Examine the validity of medical records review, self-report, and administrative data sources for measuring comorbidity, and establish whether participant characteristics affect validity • Identify which data sources for comorbidity are appropriate for which research question (outcome) of interest • Identify the best analytical methods for comorbidity adjustment for studies that adjust for comorbidity as a potential confounder MS=multiple sclerosis.
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Search strategy and selection criteria We identified references for this Review by searches of PubMed with the following search terms: “comorbidity”, “multimorbidity”, “comorbid”, “autoimmune”, “inflammatory bowel disease”, “systemic lupus erythematosus”, “rheumatoid arthritis”, “thyroid”,“ sleep”, “restless legs syndrome”, “narcolepsy”, “depression”, “anxiety”, “bipolar”, “psychosis”, “schizophrenia”, “smoking”, “overweight”, “obesity”, “alcohol”, “hypertension”, “musculoskeletal”, “diabetes”, “gastrointestinal”, “irritable bowel syndrome”, “arthritis”, “fibromyalgia”, “peptic ulcer disease”, “liver”, and “kidney” in combination with the following search terms: “cancer”, “neurodegenerative”, “multiple sclerosis”, “epilepsy”, “Alzheimer’s disease”, and “quality of life” from 1966 until May, 2010. We also identified articles through searches of our own files. Only papers published in English were reviewed. Articles were chosen on the basis of originality and relevance to the topics covered in this Review.
comorbid diseases and MS, use of individual adjustment for each comorbidity might be a more effective approach, incorporating comorbidity severity if possible. We favour this approach until the associations between MS and comorbidities are better understood.
Conclusions and future directions Although the evidence on the associations between comorbidities and MS is increasing, further studies are needed to improve our knowledge (panel). We need to broadly identify which comorbidities occur in patients with MS, which are most common, and whether they occur with greater or less frequency than in the general population. By assessment of whether these comorbidities occur at certain ages, we might be able to understand the mechanistic associations between some comorbidities and MS. Further work is needed to establish whether preexisting comorbidities affect the risk and phenotype of MS and, if so, how. Data from some studies indicate that comorbidities and health behaviours also affect disease progression. These findings need to be verified, and a broader range of disability outcomes, such as upper extremity and cognitive function, need to be taken into account. From a therapeutic perspective, important questions include whether comorbidities affect treatment choice, response, tolerability, and adherence, and whether we should use different treatment strategies in the presence of a comorbidity. Research is also needed to determine the best way to measure and analyse comorbidities to understand their associations with the index disease, but until these links are better understood, individual adjustment for each comorbidity might be the best approach. Contributors Both authors designed the idea for this paper and made revisions. RAM undertook the literature search and drafted the paper.
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Conflicts of interest We have no conflicts of interest. Acknowledgments RAM is supported by a Rudy Falk Clinician Scientist Award from the University of Manitoba, Canada. References 1 Gijsen R, Hoeymans N, Schellevis FG, Ruwaard D, Satariano WA, van den Bos GA. Causes and consequences of comorbidity: a review. J Clin Epidemiol 2001; 54: 661–74. 2 Hoffman C, Rice D, Sung HY. Persons with chronic conditions. Their prevalence and costs. JAMA 1996; 276: 1473–79. 3 Lacey CJ, Salzberg MR, Roberts H, Trauer T, D’Souza WJ. Psychiatric comorbidity and impact on health service utilization in a community sample of patients with epilepsy. Epilepsia 2009; 50: 1991–94. 4 Devinsky O, Ehrenberg B, Barthlen GM, Abramson HS, Luciano D. Epilepsy and sleep apnea syndrome. Neurology 1994; 44: 2060–64. 5 Mielke MM, Rosenberg PB, Tschanz J, et al. Vascular factors predict rate of progression in Alzheimer disease. Neurology 2007; 69: 1850–58. 6 Dean G. How many people in the world have multiple sclerosis. Neuroepidemiology 1994; 13: 1–7. 7 Beck CA, Metz LM, Svenson LW, Patten SB. Regional variation of multiple sclerosis prevalence in Canada. Mult Scler 2005; 11: 516–19. 8 Leary SM, Porter B, Thompson AJ. Multiple sclerosis: diagnosis and the management of acute relapses. Postgrad Med J 2005; 81: 302–08. 9 Pugliatti M, Rosati G, Carton H, et al. The epidemiology of multiple sclerosis in Europe. Eur J Neurol 2006; 13: 700–22. 10 Valderas JM, Starfield B, Sibbald B, Salisbury C, Roland M. Defining comorbidity: implications for understanding health and health services. Ann Fam Med 2009; 7: 357–63. 11 Barcellos LF, Kamdar BB, Ramsay PP, et al. Clustering of autoimmune diseases in families with a high-risk for multiple sclerosis: a descriptive study. Lancet Neurol 2006; 5: 924–31. 12 Edwards LJ, Constantinescu CS. A prospective study of conditions associated with multiple sclerosis in a cohort of 658 consecutive outpatients attending a multiple sclerosis clinic. Mult Scler 2004; 10: 575–81. 13 Midgard R, Gronning M, Riise T, Kvale G, Nyland H. Multiple sclerosis and chronic inflammatory diseases. A case-control study. Acta Neurol Scand 1996; 93: 322–28. 14 Seyfert S, Klapps P, Meisel C, Fischer T, Junghan U. Multiple sclerosis and other immunologic diseases. Acta Neurol Scand 1990; 81: 37–42. 15 Marrie RA. Autoimmune disease and multiple sclerosis: methods, methods, methods. Lancet Neurol 2007; 6: 575–76. 16 Gupta G, Gelfand JM, Lewis JD. Increased risk for demyelinating diseases in patients with inflammatory bowel disease. Gastroenterology 2005; 129: 819–26. 17 Bernstein CN, Wajda A, Blanchard JF. The clustering of other chronic inflammatory diseases in inflammatory bowel disease: a population-based study. Gastroenterology 2005; 129: 827–36. 18 Kimura K, Hunter S, Thollander MS, et al. Concurrence of inflammatory bowel disease and multiple sclerosis. Mayo Clin Proc 2000; 75: 802–06. 19 Broadley SA, Deans J, Sawcer SJ, Clayton D, Compston DAS. Autoimmune disease in first-degree relatives of patients with multiple sclerosis. A UK survey. Brain 2000; 123: 1102–11. 20 Jacobs LD, Wende KE, Brownscheidle CM, et al. A profile of multiple sclerosis: the New York State Multiple Sclerosis Consortium. Mult Scler 1999; 5: 369–76. 21 Niederwieser G, Buchinger W, Bonelli RM, et al. Prevalence of autoimmune thyroiditis and non-immune thyroid disease in multiple sclerosis. J Neurol 2003; 250: 672–75. 22 Sloka JS, Pryse-Phillips WEM, Stefanelli M, Joyce C. Co-occurrence of autoimmune thyroid disease in a multiple sclerosis cohort. J Autoimmune Dis 2005; 2: 9. 23 De Keyser J. Autoimmunity in multiple sclerosis. Neurology 1988; 38: 371–74. 24 Consortium of Multiple Sclerosis Centers. NARCOMS Multiple Sclerosis Registry, 2008. http://www.mscare.org/cmsc/CMSCNARCOMS-Information.html (accessed Jan 5, 2008).
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45
46
47 48
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50
Marrie RA, Horwitz R, Cutter G, Tyry T, Campagnolo D, Vollmer T. Comorbidity, socioeconomic status, and multiple sclerosis. Mult Scler 2008; 14: 1091–98. Centers for Disease Control and Prevention. Prevalence of disability and associated health conditions, United States, 1991–1992. MMWR Morb Mortal Wkly Rep 1994; 40: 730–31, 737–39. Marrie RA. The influence of comorbid diseases and health behaviors on clinical characteristics, disability at diagnosis, and disability progression in multiple sclerosis. PhD thesis, Case Western Reserve University, 2007; 1–547. Warren SA, Turpin KV, Pohar SL, Jones CA, Warren KG. Comorbidity and health-related quality of life in people with multiple sclerosis. Int J MS Care 2009; 11: 6–16. Brass SD, Duquette P, Proulx-Therrien J, Auerbach S. Sleep disorders in patients with multiple sclerosis. Sleep Med Rev 2010; 14: 121–29. Manconi M, Ferini-Strambi L, Filippi M, et al, the Italian REMS Study Group. Multicenter case-control study on restless legs syndrome in multiple sclerosis: the REMS study. Sleep 2008; 31: 944–52. Deriu M, Cossu G, Molari A, et al. Restless legs syndrome in multiple sclerosis: a case-control study. Mov Disord 2009; 24: 697–701. Auger C, Montplaisir J, Duquette P. Increased frequency of restless legs syndrome in a French-Canadian population with multiple sclerosis. Neurology 2005; 65: 1652–53. Gomez-Choco M, Iranzo A, Blanco Y, Graus F, Santamaria J, Saiz A. Prevalence of restless legs syndrome and REM sleep behavior disorder in multiple sclerosis. Mult Scler 2007; 13: 805–08. Manconi M, Fabbrini M, Bonanni E, et al. High prevalence of restless legs syndrome in multiple sclerosis. Eur J Neurol 2007; 14: 534–39. Nishino S, Kanbayashi T. Symptomatic narcolepsy, cataplexy and hypersomnia, and their implications in the hypothalamic hypocretin/ orexin system. Sleep Med Rev 2005; 9: 269–310. Ajayi OF, Chang-McDowell T-Y, Culpepper WJ, Royal W, Bever C. High prevalence of sleep disorders in Veterans with multiple sclerosis. Neurology 2008; 70 (suppl 1): A333. Goldman Consensus Group. The Goldman Consensus statement on depression in multiple sclerosis. Mult Scler 2005; 11: 328–37. Kessler RC, Berglund P, Demler O, et al. The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R). JAMA 2003; 289: 3095–105. Korostil M, Feinstein A. Anxiety disorders and their clinical correlates in multiple sclerosis patients. Mult Scler 2007; 13: 67–72. Poder K, Ghatavi K, Fisk J, et al. Social anxiety in a multiple sclerosis clinic population. Mult Scler 2009; 15: 393–98. Somers JM, Goldner EM, Waraich P, Hsu L. Prevalence and incidence studies of anxiety disorders: a systematic review of the literature. Can J Psychiatry 2006; 51: 100–13. Fisk J, Morehouse SA, Brown MG, Skedgel C, Murray TJ. Hospital-based psychiatric service utilization and morbidity in multiple sclerosis. Can J Neurol Sci 1998; 25: 230–35. Joffe RT, Lippert GP, Gray TA, Sawa G, Horvath Z. Mood disorder and multiple sclerosis. Arch Neurol 1987; 44: 376–78. Patten SB, Svenson LW, Metz LM. Psychotic disorders in MS: population-based evidence of an association. Neurology 2005; 65: 1123–25. Pine DS, Douglas CJ, Charles E, Davies MB, Kahn D. Patients with multiple sclerosis presenting to psychiatric hospitals. J Clin Psychiatry 1995; 56: 297–306. Marrie RA, Horwitz R, Cutter G, Tyry T, Campagnolo D, Vollmer T. High frequency of adverse health behaviors in multiple sclerosis. Mult Scler 2009; 15: 105–13. Quesnel S, Feinstein A. Multiple sclerosis and alcohol: a study of problem drinking. Mult Scler 2004; 10: 197–201. Khurana SR, DiGiacomo AM, Rohini V, et al. Prevalence of overweight and obesity among Veterans with multiple sclerosis. Int J MS Care 2006; 8: 59. Marrie RA, Horwitz RI, Cutter G, Tyry T, Campagnolo D, Vollmer T. Comorbidity delays diagnosis and increases disability at diagnosis in MS. Neurology 2009; 72: 117–24. Bjerager M, Palshof T, Dahl R, Vedsted P, Olesen F. Delay in diagnosis of lung cancer in clinical practice. Br J Gen Pract 2006; 56: 863–68.
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Healy BC, Ali EN, Guttmann CRG, et al. Smoking and disease progression in multiple sclerosis. Arch Neurol 2009; 66: 858–64. Kirby S, Brown MG, Murray TJ, et al. Progression of multiple sclerosis in patients with other autoimmune diseases. Mult Scler 2005; 11 (suppl 1): S28–29. Marrie RA, Rudick R, Horwitz R, et al. Vascular comorbidity is associated with more rapid disability progression in multiple sclerosis. Neurology 2010; 74: 1041–47. Dallmeijer AJ, Beckerman H, de Groot V, van de Port IG, Lankhorst GJ, Dekker J. Long-term effect of comorbidity on the course of physical functioning in patients after stroke and with multiple sclerosis. J Rehabil Med 2009; 41: 322–26. Hernan MA, Jick SS, Logroscino G, Olek MJ, Ascherio A, Jick H. Cigarette smoking and the progression of multiple sclerosis. Brain 2005; 128: 1461–65. Sundstrom P, Nystrom L. Smoking worsens the prognosis in multiple sclerosis. Mult Scler 2008; 14: 1031–35. Di Pauli F, Reindl M, Ehling R, et al. Smoking is a risk factor for early conversion to clinically definite multiple sclerosis. Mult Scler 2008; 14: 1026–30. Sena A, Couderc R, Ferret-Sena V, et al. Apolipoprotein E polymorphism interacts with cigarette smoking in progression of multiple sclerosis. Eur J Neurol 2009; 16: 832–37. Pittas F, Ponsonby AL, van der Mei IA, et al. Smoking is associated with progressive disease course and increased progression in clinical disability in a prospective cohort of people with multiple sclerosis. J Neurol 2009; 256: 577–85. Zivadinov R, Weinstock-Guttman B, Hashmi K, et al. Smoking is associated with increased lesion volumes and brain atrophy in multiple sclerosis. Neurology 2009; 73: 504–10. Hermann B, Vickrey B, Hays RD, et al. A comparison of healthrelated quality of life in patients with epilepsy, diabetes and multiple sclerosis. Epilepsy Res 1996; 25: 113–18. Wu N, Minden SL, Hoaglin DC, Hadden L, Frankel D. Quality of life in people with multiple sclerosis: data from the Sonya Slifka Longitudinal Multiple Sclerosis Study. J Health Hum Serv Adm 2007; 30: 233–67. Turpin KV, Carroll LJ, Cassidy JD, Hader WJ. Deterioration in the health-related quality of life of persons with multiple sclerosis: the possible warning signs. Mult Scler 2007; 13: 1038–45. Francis G. Benefit-risk assessment of interferon-b therapy for relapsing multiple sclerosis. Expert Opin Drug Saf 2004; 3: 289–303. Rudick RA, Stuart WH, Calabresi PA, et al. Natalizumab plus interferon beta-1a for relapsing multiple sclerosis. N Engl J Med 2006; 354: 911–23. Bayliss EA, Steiner JF, Fernald DH, Crane LA, Main DS. Descriptions of barriers to self-care by persons with comorbid chronic diseases. Ann Fam Med 2003; 1: 15–21. Gulick EE. Emotional distress and activities of daily living functioning in persons with multiple sclerosis. Nurs Res 2001; 50: 147–54. Weinshenker BG, Rice GP, Noseworthy JH, Carriere W, Baskerville J, Ebers GC. The natural history of multiple sclerosis: a geographically based study. 3. Multivariate analysis of predictive factors and models of outcome. Brain 1991; 114: 1045–56. Chobanian AV, Bakris GL, Black HR, et al. Seventh report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure. Hypertension 2003; 42: 1206–52. Launer LJ. Diabetes and brain aging: epidemiologic evidence. Curr Diab Rep 2005; 5: 59–63. National Center for Health Statistics. Health, United States, 2005. With chartbook on Trends in the Health of Americans. Hyattsville, MD: 2005. US Department of Health and Human Services, 2005: 1–535 http://www.cdc.gov/nchs/data/hus/hus05.pdf (accessed July 28, 2010). Tammemagi CM, Neslund-Dudas C, Simoff M, Kvale P. Smoking and lung cancer survival. The role of comorbidity and treatment. Chest 2004; 125: 27–37. Weil E, Wachterman M, McCarthy EP, et al. Obesity among adults with disabling conditions. JAMA 2002; 288: 1265–68. Trojano M, Liguori M, Bosco Zimatore G, et al. Age-related disability in multiple sclerosis. Ann Neurol 2002; 51: 475–80.
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Tremlett H, Zhao Y, Joseph J, Devonshire V. Relapses in multiple sclerosis are age- and time-dependent. J Neurol Neurosurg Psychiatr 2008; 79: 1368–74. Pfleger CCH, Flachs EM, Koch-Henriksen N. Social consequences of multiple sclerosis (1): early pension and temporary unemployment—a historical prospective cohort study. Mult Scler 2010; 16: 121–26. Pfleger CCH, Flachs EM, Koch-Henriksen N. Social consequences of multiple sclerosis: clinical and demographic predictors: a historical prospective cohort study. Eur J Neurol 2010; published online April 9. DOI:10.1111/j.1468-1331.2010.03020.x. Braveman PA, Cubbin C, Egerter S, et al. Socioeconomic status in health research: one size does not fit all. JAMA 2005; 294: 2879–88. Steenland K, Hu S, Walker J. All-cause and cause-specific mortality by socioeconomic status among employed persons in 27 US states, 1984–1997. Am J Public Health 2004; 94: 1037–42. Minkler M, Fuller-Thomson E, Guralnik JM. Gradient of disability across the socioeconomic spectrum in the United States. N Engl J Med 2006; 355: 695–703. Marrie RA, Cutter G, Tyry T, Vollmer T, Campagnolo D. Does multiple sclerosis-associated disability differ between races? Neurology 2006; 66: 1235–40. Marrie RA, Cutter G, Tyry T, Vollmer T, Campagnolo D. Disparities in the management of multiple sclerosis-related bladder symptoms. Neurology 2007; 68: 1971–78. Okura Y, Urban LH, Mahoney DW, Jacobsen SJ, Rodeheffer RJ. Agreement between self-report questionnaires and medical record data was substantial for diabetes, hypertension, myocardial infarction and stroke but not for heart failure. J Clin Epidemiol 2004; 57: 1096–103. Bayliss EA, Ellis JL, Steiner JF. Subjective assessments of comorbidity correlate with quality of life health outcomes: initial validation of a comorbidity assessment instrument. Health Qual Life Outcomes 2005; 2: 51.
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Klabunde CN, Warren JL, Legler JM. Assessing comorbidity using claims data: an overview. Med Care 2002; 40 (8 suppl): IV-26–35. Marrie RA, Yu N, Blanchard JF, Leung S, Elliott L. The rising prevalence and changing age distribution of multiple sclerosis in Manitoba. Neurology 2010; 74: 465–71. Hohol MJ, Orav EJ, Weiner HL. Disease steps in multiple sclerosis: a longitudinal study comparing disease steps and EDSS to evaluate disease progression. Mult Scler 1999; 5: 349–54. Horton M, Rudick RA, Hara-Cleaver C, Marrie RA. Validation of a self-report comorbidity questionnaire for multiple sclerosis. Neuroepidemiology 2010; 35: 83–90. Culpepper WJ, Ehrmantraut M, Wallin MT, Flannery K, Bradham DD. Veterans Health Administration multiple sclerosis surveillance registry: the problem of case-finding from administrative databases. J Rehabil Res Dev 2006; 43: 17–24. Bernstein CN, Blanchard JF, Rawsthorne P, Wajda A. Epidemiology of Crohn’s disease and ulcerative colitis in a central Canadian province: a population-based study. Am J Epidemiol 1999; 149: 916–24. de Groot V, Beckerman H, Lankhorst GJ, Bouter LM. How to measure comorbidity: a critical review of available methods. J Clin Epidemiol 2003; 56: 221–29. Byles JE, D’Este C, Parkinson L, O’Connell R, Treloar C. Single index of multimorbidity did not predict multiple outcomes. J Epidemiol 2005; 58: 997–1005. Grunau GL, Sheps S, Goldner EM, Ratner PA. Specific comorbidity risk adjustment was a better predictor of 5-year acute myocardial infarction mortality than general methods. J Clin Epidemiol 2006; 59: 274–80.
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Emerging effects of comorbidities on multiple sclerosis Ruth Ann Marrie, Ralph I Horwitz Lancet Neurol 2010; 9: 820–28 Health Sciences Center, Winnipeg, MB, Canada (R A Marrie MD); and Stanford University, Stanford, CA, USA (Prof R I Horwitz MD) Correspondence to: Ruth Ann Marrie, Health Sciences Center, GF-533, 820 Sherbrook Street, Winnipeg, MB R3A 1R9, Canada [email protected]
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Although the interaction between comorbidities and chronic diseases is strong, the effect of comorbidities receives little attention in many chronic diseases. In multiple sclerosis (MS), an increasing amount of evidence suggests that physical and mental comorbidities, and adverse health factors such as smoking and obesity, are common and can affect the disease. These comorbid diseases and lifestyle factors affect clinical phenotype, the diagnostic delay between symptom onset and diagnosis, disability progression, and health-related quality of life. Future studies of comorbidity and MS should consider comorbidities and health behaviours and should take into account the modifying effects of socioeconomic status, ethnic origin, and cultural factors. Studies of the frequency of comorbidities in patients with MS should be population based, incorporating appropriate comparator groups. These studies should expand the range of comorbidities assessed, and examine how the frequency of comorbidities is changing over time. Further research is needed to answer many other questions about comorbidities and their associations with MS, including the best way to measure and analyse comorbidities to understand these associations.
Introduction
Mechanisms for comorbidities in MS
Important associations exist between comorbidities and chronic diseases but for many chronic diseases comorbidities are given little consideration.1 Typically, comorbidity refers to the total burden of illness other than the specific disease of interest,1 and is distinct from complications of the disease. In the general population, comorbidities are common and their frequency increases with age.2 Many adverse health outcomes are associated with comorbidities, including reduced functional status, increased use of health-care services, reduced quality of life, and increased mortality.1 The adverse effects of a comorbidity are not limited to any particular index disease or population of patients.1 In neurological disorders, recognition of the frequency and importance of comorbidities is increasing. Patients with epilepsy commonly have psychiatric disorders, and such patients more frequently use health-care services.3 Migraine and sleep disorders are also common comorbidities in patients with epilepsy. Some of these comorbidities can affect control of seizures; untreated obstructive sleep apnoea can be associated with refractory epilepsy and treatment can improve control of seizures.4 In patients with Alzheimer’s disease, vascular factors can increase the rate of disease progression.5 Multiple sclerosis (MS) is a chronic, progressively disabling disease of the CNS, estimated to affect more than 2·5 million people worldwide.6,7 It is the most common non-traumatic cause of disability in young adults,8 and the societal costs of this disease are higher than are those for patients with stroke or Alzheimer’s disease.9 Patients with MS are also likely to be affected by comorbidities, but little knowledge exists about which comorbidities are most common or how they affect treatment decisions, treatment responses, or health outcomes. This is a crucial gap in knowledge for patients and clinicians, and is an opportunity to improve patients’ health status. In this Review, we examine data on the association between comorbidities and MS, and provide recommendations for further research.
A detailed examination of the mechanisms that might underlie the coexistence of MS and another disorder in the same individual, and the evidence for these mechanisms, is beyond the scope of this Review, although we will briefly discuss the general mechanisms (Valderas and colleagues10 provide further discussion). First, two disorders might co-occur simply by chance alone. Second, patients with one chronic disease might be more likely to be diagnosed with a second disorder because of increased use of health services. Third, diseases might co-occur owing to one of several aetiological mechanisms, including direct causation, associated risk factors, heterogeneity, and independence. In direct causation, one disorder directly leads to another, and this mechanism can be used to describe comorbidities arising directly from a disease (eg, MS) or its treatments. Common risk factors can lead to increased co-occurrence of disease; common genetic susceptibility to immune disorders has been proposed as the mechanism underlying the increased frequency of comorbid autoimmune disease in patients with MS,11 although common environmental factors, such as smoking, are another possible explanation. Other independent factors such as age, obesity, and poor diet can be associated with increased co-occurrence of disease (heterogeneity). Alternatively, two disorders might coexist because they are consequences of a third, as yet undiagnosed disease (independence). Finally, Berkson’s bias, a selection bias that occurs when hospital controls are used in a case-control study, might also lead to an increase in observed comorbidities among the controls owing to a higher probability of the combination of exposure to a risk factor and occurrence of disease having led to their hospitalisation.
Frequency of comorbidities Autoimmune comorbidities Several initial investigations of comorbidities in MS have examined whether autoimmune diseases occur more frequently in patients with MS than would be expected in www.thelancet.com/neurology Vol 9 August 2010
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the general population.12–14 Findings about autoimmune disease are conflicting, possibly because of differences in study design.15 In two population-based studies,16,17 patients with inflammatory bowel disease had an increased risk of incident and prevalent demyelinating disease, which contrasts with findings from previous studies.18,19 In several small studies,11,14,20 co-occurrence of rheumatoid arthritis ranged from 0·9% to 4·4%. Few studies had adequate sample sizes to establish whether systemic lupus erythematosus occurs more frequently in patients with MS than expected; in the New York State Multiple Sclerosis Consortium,20 2·1% of 3019 patients with MS had comorbid lupus. Thyroid disease is reported to occur more often than expected in patients with MS, with frequencies of up to 9% in a study of 353 patients;21 however, only two21,22 of four studies with a control or reference group identified an increased risk.19,21–23 The absolute frequency of most of these autoimmune diseases is low enough that they are unlikely to have a substantial effect on MS at the population level. Thyroid disease is potentially more important than are the other autoimmune diseases because of its higher frequency and potential contributions to fatigue, a common disabling symptom in MS.
Physical comorbidities Physical comorbidities other than autoimmune diseases seem to be common in patients with MS.24 Participants in the North American Research Committee on Multiple Sclerosis (NARCOMS) registry24 provide information about their MS on a continual basis. In 2006, 8983 participants in the NARCOMS registry reported their comorbidities;25 the most frequent were hypercholesterolaemia (37%), hypertension (30%), arthritis (16%), irritable bowel syndrome (13%), and chronic lung disease (13%). This list includes three of the five leading causes of disability in the general population: hypertension, lung disease, arthritis, back or spine problems, and heart disease.26 After standardisation for age, many of these comorbidities seem to occur at similar frequencies to those in the general population.27 Limitations of this study include use of a volunteer sample, absence of a control group, and the fact that these comorbidities were self-reported. In the nationally representative Canadian Community Health Survey,28 302 respondents with MS reported comorbidities that included back problems (35%), non-food allergies (29%), arthritis (26%), hypertension (17%), and migraine (14%). This study also relied on self-report. Data from several studies have indicated that sleep disorders are more common in patients with MS than in the general population.29 Restless legs syndrome, for example, occurs with a frequency ranging from 13·3% to 37·5% depending on the population studied.30–34 In most of these studies, restless legs syndrome occured substantially more often in individuals with MS than in the general population. Nishino and colleagues35 reviewed 116 symptomatic cases of narcolepsy and found that ten (9%) were associated with MS. Among 16 074 US www.thelancet.com/neurology Vol 9 August 2010
veterans with MS, 940 (6%) had sleep disorders compared with 3% of veterans without MS, in whom sleep disturbance was defined as the presence of at least one diagnostic polysomnogram or sleep disorder during the study period.36
Psychiatric and behavioural comorbidities In addition to physical comorbidities, psychiatric comorbidities are common in patients with MS. The lifetime incidence of depression in patients with MS is 50%,37 nearly three times higher than in the general population.38 The 12-month prevalence of depression in patients with MS is as high as 14%,38 twice that of the reported prevalence in the general population of 5·9–7·3%.37 The lifetime incidence of anxiety disorders, including social phobias, is as high as 35% in patients with MS,39,40 compared with 16·6% in the general population.41 Bipolar disorder affects 0·30% to 13% of patients with MS, depending on the population studied.42,43 Results from a study that used administrative insurance claims data from a Canadian province found that 0·8% of 10 367 patients with MS had non-organic psychoses.44 Other studies of psychosis in patients with MS relied on hospital-based populations and had inadequate numbers of patients to establish reliable estimates.45 Despite the well recognised frequency of psychiatric comorbidities, they remain underdiagnosed.39 Data from several studies have indicated that smoking is a risk factor for MS; in one study that used data from the NARCOMS registry, 4867 (54%) of the 8983 responders with MS were reported to have ever smoked.46 In a study of 140 patients with MS, the lifetime incidence of alcohol misuse was reported as 13·6%, while problem drinking was reported to affect 14–16·4% in the MS cohort.47 About 50% of patients with MS are overweight or obese, a similar proportion to that of the general population.46,48 Participants with severe disability, however, might be at risk of being underweight.46
Recommendations for future studies Future studies of the frequency of comorbidity in MS compared with the general population should be population based. These studies should expand the range of comorbidities assessed and examine temporal changes in the frequency of comorbidity. Further study of the variation in the frequency of comorbidities across sociodemographic subgroups is also needed. Studies of the frequency of comorbidities in subgroups of people with MS should incorporate appropriate comparator groups. We need to establish which comorbidities are sufficiently prevalent across MS populations to be universally important and which have clinically relevant effects.
Effects of comorbidities on MS An increasing amount of evidence suggests that comorbidities and lifestyle factors might affect the diagnostic delay between MS onset and diagnosis, the 821
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clinical phenotype of MS, disability progression, healthrelated quality of life (HRQoL), and treatment decisions.
Diagnosis In participants in the NARCOMS registry, the presence of comorbidities and adverse health behaviours affected the diagnostic delay between MS symptom onset and diagnosis.49 The presence of obesity, smoking, and physical or mental comorbidities was associated with increased diagnostic delays of nearly 11 years for some comorbidities. After accounting for demographic and clinical characteristics, long diagnostic delays persisted. The reasons for this finding are uncertain, but there are several possible explanations. Pre-existing disease could mask the symptoms of MS, or the existing burden of illness could negatively affect access to care. In some cancers, a comorbidity is associated with delayed referrals to specialists by general practitioners, possibly because new symptoms are mistakenly attributed to the pre-existing condition.50 The amount of time and testing needed to diagnose MS could also be affected by a comorbidity.
Clinical presentation In a study of 1465 patients with MS, including 780 who have never smoked, 428 ex-smokers, and 257 who currently smoke, current smokers (odds ratio [OR] 2·42, 95% CI 1·09–5·35) and ex-smokers (1·91, 1·02–3·58) were more likely to present with primary-progressive MS than with relapsing-remitting MS.51 Unfortunately, investigators of this study did not examine potential confounders such as comorbid obesity or vascular risk factors. In the NARCOMS registry, participants with any physical comorbidity at the time of MS diagnosis were more likely to report moderate disability than mild disability at diagnosis, and the likelihood of moderate disability increased with the number of comorbidities reported (OR 1·13, 1·03–1·23).49 When studied in more detail, vascular, musculoskeletal, and psychiatric comorbidities and obesity were associated with increased severity of disability at diagnosis. After adjustment, the OR for moderate disability compared with mild disability at diagnosis was 1·51 (95% CI 1·12–2·05) in participants with a vascular comorbidity and 1·38 (1·02–1·87) in those with obesity. The OR for severe disability compared with mild disability was 1·81 (1·25–2·63) in participants with a musculoskeletal comorbidity, and 1·62 (1·23–2·14) in those with a psychiatric comorbidity. These findings need to be replicated in population-based cohorts with other approaches such as medical records review for measurement of comorbidities.
Disability progression Comorbidity is also associated with increased progression of disability. In a population-based study of patients with MS, those with asthma were more likely to have more rapid progression to early gait dysfunction than 822
were patients without asthma (p=0·0277).52 Vascular comorbidities, including diabetes, hypertension, hypercholesterolaemia, heart disease, and peripheral vascular disease, are associated with more rapid progression of ambulatory disability than in the absence of these comorbidities.53 Compared with patients with MS who did not develop a vascular comorbidity, individuals who reported the presence of one or more vascular comorbidities at the time of their diagnosis of MS had a more than 1·5-times increased risk of needing a cane to walk (hazard ratio [HR] 1·68, 95% CI 1·51–1·87). These findings were similar for patients who developed a vascular comorbidity at any point during their disease course (HR 1·54; 1·44–1·65). During a 3-year observational study, patients who were newly diagnosed with MS and musculoskeletal comorbidities had greater declines in physical functioning (5-point decline on the motor scale of the functional independence measure) than did those without such comorbidities (2-point decline).54 Results from several studies suggest that smoking is associated with an increased risk of disability progression in patients with MS. In a study using information from the General Practice Research Database,55 smokers with relapsing-remitting MS were three times more likely to develop secondary-progressive disease than were nonsmokers (HR 3·6, 95% CI 1·3–9·9), whereas only 20 of 179 patients who were never-smokers or ever-smokers had a progressive course. In another study of 122 individuals with newly diagnosed MS, 72% of eversmokers who began smoking before the age of 15 years developed secondary-progressive MS after a median of 6 years of follow-up.56 40% of ever-smokers who began smoking after the age of 15 years developed secondaryprogressive MS, whereas only 26% of those who had never smoked progressed. Di Pauli and colleagues57 followed up 129 patients with a clinically isolated syndrome who were at high risk of developing MS on the basis of findings from MRI and CSF examination. After 3 years, 75% of smokers developed MS compared with only 51% of non-smokers (HR 1·8, 95% CI 1·2–2·8). By contrast, Sena and colleagues58 examined 205 women with definite MS from Portugal and noted that smoking had a protective effect in women who had the apolipoprotein E ε4 isoform; smokers had lower scores on the expanded disability status scale (p=0·033) and multiple sclerosis severity score (p=0·023) than did nonsmokers. The study was restricted to women from a clinic-based population and needs to be replicated. Only one study, by Pittas and colleagues,59 accounted for the potential confounding effects of other health behaviours.59 In two studies,51,60 smoking was associated with an increased number of gadolinium-enhancing lesions, increased T2-weighted lesion volume, and greater brain atrophy. Neither study included a control group of smokers without MS to facilitate the assessment of whether smoking has additive or multiplicative effects on brain imaging measures such as brain volume. www.thelancet.com/neurology Vol 9 August 2010
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Health-related quality of life HRQoL is lower in patients with MS than it is in the general population and other chronic disease populations.61 Age, sex, socioeconomic status, and disability status affect HRQoL in patients with MS.62 Although comorbidities are associated with reduced HRQoL in other chronic diseases,1 little is known about their effects in MS. In a study of 262 patients with relapsing-remitting MS, poor HRQoL, as measured by the short form-36 health survey, was associated with comorbidities. Patients with comorbid musculoskeletal and respiratory disorders had worse physical HRQoL than did those without such disorders; additionally, headaches and urinary and digestive tract problems were associated with worse mental HRQoL.63 Of 335 people with MS who responded to the Canadian Community Health Survey,28 patients without a comorbidity had a mean HRQoL score of 0·64, as measured by the health utilities index mark III version, which was higher than the mean score of 0·52 for participants with one or more comorbidities. Both studies were cross-sectional and did not clearly distinguish between comorbidities and complications of MS.
Treatment decisions As well as affecting disease status, comorbidities can affect treatment decisions, including the choice of whether to start treatment, the specific choice of treatment, and its subsequent effectiveness. Liver disease and severe depression, for example, are contraindications to the use of interferon beta.64 Many clinical trials in patients with MS exclude individuals with severe comorbidities or substance use disorders;65 thus, the safety, tolerability, and effectiveness of most drugs is not known in such patients. Patients with several chronic health disorders report many barriers to care,66 so compliance with treatment might also be adversely affected, reducing the already limited benefits of treatment. Comorbid depression is already recognised to reduce adherence to disease-modifying treatment.67
Benefits of studying comorbidities in MS Several potential benefits can be gained from the study of comorbidities in patients with MS, including improved prognosis, individualised disease management, insights into the causes and pathophysiology of MS, and new treatment approaches. Natural history studies have focused on the prognostic value of clinical characteristics of this disorder,68 but prognosis early in the disease course remains poor. Inclusion of comorbidity information could improve prognosis by explaining heterogeneity in disease outcomes, which would enable clinicians to provide individual patients with better information about the clinical course of their disease and to make informed treatment choices. In other diseases, understanding the effects of comorbidities has led to disease management www.thelancet.com/neurology Vol 9 August 2010
guidelines based on the presence of specific comorbidities, as shown in the 2003 national hypertension guidelines;69 the target blood pressure is lowered for individuals with diabetes or chronic renal disease, and the choice of antihypertensive therapy depends on the presence or absence of comorbidities such as diabetes, previous myocardial infarction, and heart failure.69 If particular diseases or combinations of diseases have a greater effect on disability progression than do other diseases, novel insights could be gained into the causes and pathophysiology of MS. Diabetes, for example, might affect the brain by increasing susceptibility to oxidative stress, increasing inflammatory responses, and altering blood vessel function.70 If diabetes were associated with increased disability in MS, then this connection would suggest that insulin-related and hyperglycaemia-related mechanisms should be studied. Finally, if a particular comorbidity substantially affects outcome for patients with MS, aggressive treatment of the comorbidity could be a new approach to improve those outcomes.
Theoretical and methodological considerations The main goal of determining the associations between comorbidities and MS is to improve the health of the patient with MS. So far, we have focused specifically on comorbidities. To understand these associations, we need to consider a broader approach that takes into account the comorbidity, treatments for the comorbidity, treatments for MS, environmental factors such as socioeconomic status, and their combined effects on the status of the patient (figure).
Definitions We previously defined comorbidity as the total burden of illness other than the specific disease of interest,1 but this definition does not include comorbid health behaviours and lifestyle factors such as smoking, alcohol intake, and physical activity. Health behaviours substantially affect the risk and outcomes of chronic disease and contribute to health disparities in individuals of different ethnic origins.71 These behaviours might affect health outcomes independently of comorbid diseases. For example, smokers with lung cancer have a worse survival outcome than non-smokers independent of smoking-associated comorbidities, cancer stage, and treatment.72 We propose that future studies of comorbidity should also encompass health behaviours. The definition of comorbidity also distinguishes comorbid diseases and complications of the index disease. From a clinical perspective, the distinction between comorbidities and complications is relevant because the interventions can differ; if the comorbidity worsens the outcome, the focus should be on treatment of the comorbidity, but if the complication worsens the outcome, then the focus should be on treatment of the primary disease in addition to treatment of the complication. From a broader clinical perspective, the 823
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MS-associated disability and related treatments
Comorbidity and related treatments
Global status of patient
Complications of MS and related treatments
Socioeconomic status
Figure: Factors that affect the health status of patients with multiple sclerosis MS=multiple sclerosis.
primary disease and related complications, comorbidities, and their respective treatments collectively contribute to the overall health status of the patient; thus, in some situations it might be appropriate to assess the effect of all these factors (figure). Although we emphasise the need to distinguish comorbidities from complications of disease clinically, this differentiation can be difficult, particularly given the unknown pathogenesis of MS. As the knowledge of the pathogenesis of MS improves, the classification of conditions as comorbidities or complications will also need to improve. This will be particularly important for studies of the mechanisms underlying comorbidities and complications of disease and their effects on MS. Although comorbidities or their treatments can affect MS, MS and its treatments can also affect the diagnosis, risk, or severity of comorbidity. In the same way that preexisting comorbidities can adversely affect the diagnostic delay between onset and diagnosis of MS, the diagnosis of comorbidities could be delayed by mistakenly attributing neurological symptoms such as progressive inability to walk, pain, or seizures to the pre-existing diagnosis of MS. Corticosteroids used for relapses, for example, might worsen diabetes, lead to the development of cataracts, or contribute to weight gain. Physical disability can restrict physical activity, contributing to the risk of the individual becoming overweight or obese.73
Factors that modify associations between comorbidities and MS Characteristics such as age, sex, race, ethnic origin, and socioeconomic status will modify associations between 824
comorbidities and MS outcomes. In view of the association of age with MS outcomes such as ambulatory disability and relapse rate,74,75 and the association of age with comorbidities and problems such as frailty, age should be dealt with carefully in any study of comorbidities and MS. Although the adverse effects of MS on employment and relationships are recognised,76,77 and there are many important social determinants of health including socioeconomic status, these are understudied in MS. Socioeconomic status is a complex, multifactorial construct that describes a person’s position in society.78 Although most commonly measured by a combination of income and education, these factors do not completely represent socioeconomic status.78 Socioeconomic status is a fundamental determinant of health, and is associated with leading causes of death, functional status, and health behaviours.79,80 In the participants from the NARCOMS registry, differences in disease severity between individuals of different ethnic origins were overestimated by up to 25% when socioeconomic status was not taken into account.81 Patients with MS who have a low socioeconomic status are at a higher risk of having a comorbidity, might undergo fewer investigations for MS-related symptoms, and receive fewer symptomatic therapies than those with high socioeconomic status,25,82 all of which might adversely affect functional status. Thus, future studies of comorbidities should measure these characteristics.
Measurement of comorbidities An important question for future studies is the way in which comorbidities should be measured. Sources of comorbidity data include medical records, self-report, and administrative databases; none of these sources is clearly established as the gold standard in all situations. The validity of these data sources varies depending on the comorbidities of interest.83 The validity of self-reported comorbidities varies substantially by disorder: they are reasonably accurate for well defined, chronic disorders that require ongoing care or that cause disability, but are less accurate for diseases with less explicit diagnostic criteria, such as arthritis.83 Self-reported data, however, might be more accessible and less costly than other approaches in large studies, and might predict quality of life and functional status more accurately than medical records data.84 Administrative data are an accessible and efficient data source compared with primary data collection. Although administrative insurance claims data might not accurately report comorbidities compared with medical records,85 these data are more reliable than a review of the records of a single provider. Thus, no data source is ideal for all research studies; establishing the validity of each data source for the comorbidities of interest is crucial. Little work has examined measurement of comorbidities in patients with MS, including the concerns of validity and whether the ideal method of comorbidity www.thelancet.com/neurology Vol 9 August 2010
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measurement differs according to the outcome or research question of interest. Results from several studies indicate that patients with MS can accurately report their diagnoses of MS (κ coefficient of level of agreement=0·86, 95% CI 0·81–0·91),86 year of symptom onset, type of clinical course, and some aspects of their disability status (eg, correlation between physician-scored expanded disability status scale score and patient-determined disease steps is 0·94).87 As reported in other populations, agreement between patient-reported chronic disorders— such as diabetes, hypertension, hyperlipidaemia, autoimmune thyroid disease, heart disease, and chronic lung disease—and those reported in medical records of the MS population is moderate to high (κ=0·52–0·88).88 This finding suggests that self-report can be used as a data source in studies of these common comorbidities. Algorithms developed with information from the Canadian administrative health claims databases86 and the Veterans Administration databases have been used to identify people with MS with reasonable sensitivity (93%) and specificity (92%).89 Although further validation is needed for studies of comorbidities that use administrative data, previous studies in other chronic diseases can provide some insights.90 Administrative data might be particularly useful when evaluating the effect of rare comorbidities and when the outcomes of interest relate to mortality and use of health-care services, for which substantial experience with administrative data already exists. There are three general methods to classify comorbidity analytically—a simple count of disorders, use of a comorbidity index, or consideration of each comorbidity as a distinct entity91—each of which has strengths and weaknesses. A comorbidity count is easy to understand and obtain, and predicts outcomes of use of health-care services.91 This method, however, assumes that any given comorbidity has an equal effect on outcome in terms of magnitude and direction, and does not take into account differential effects of disease severity. A comorbidity index is a summary measure that captures the number of comorbidities and the severity of those comorbidities.91 An index can be weighted to apply greater importance to a particular disorder or can be unweighted. A generic index is intended as an easy measurement approach for many populations without adaptation, but presumes an equal effect of each component irrespective of the index disease or population.91 In a generic index, complications that indicate the severity of the index disease might be mistakenly defined as comorbidities. A disease-specific comorbidity index avoids these problems. These summary measures omit comorbid health behaviours or lifestyle factors. None of the existing comorbidity indexes has been validated for use in MS. A measure used in another population could be used, but would need to be adapted and validated before use. As most MS care is provided in ambulatory settings, a measure validated in an outpatient population would have greater use than would one www.thelancet.com/neurology Vol 9 August 2010
developed in an inpatient population. One comorbidity measure is unlikely to be equally appropriate for all health outcomes;92 therefore, a series of measures might be necessary, each sharing common core elements. The final option is to treat each of the comorbidities separately when predicting health outcomes. This approach facilitates the study of interactions between specific pairs of diseases and is likely to improve predictive ability of multivariable models,93 but sample size might be a limiting factor. To understand the potentially additive, synergistic, or antagonistic associations between multiple Panel: Summary and recommendations for the design of future studies of comorbidities in patients with MS Research questions Establish the frequency of comorbidities in MS • Choose a population-based design when appropriate • Expand the range of comorbidities assessed • Examine temporal trends and variation across sociodemographic subgroups • Examine variation in comorbidities according to clinical characteristics of MS • Include appropriate comparator groups (eg, studies of whether a comorbidity is more common in MS than in the general population should use general population controls) Establish the effects of comorbidities on MS • Examine the effect of comorbidities on all aspects of physical and cognitive impairment and health-related quality of life at diagnosis and throughout the disease course • Examine the effect of comorbidities on disease-modifying treatment in MS, including choice of therapy, response to therapy, tolerability, and adherence • Examine the effect of comorbidities on symptomatic treatment in MS, including choice of therapy, response to therapy, tolerability, and adherence • Account for age, sex, race, ethnic origin, and social determinants of health • Compare the effect of comorbidities in MS with the effect of comorbidities in other chronic neurological and autoimmune diseases Establish the effect of MS on comorbidities • Examine the effect of MS on diagnosis and treatment of comorbidities • Account for age, sex, race, ethnic origin, and social determinants of health • Compare the effect of comorbidities in MS with the effect of comorbidities in other chronic neurological and immune-mediated diseases Methodological questions Develop a clear definition of comorbidity • Define comorbidities broadly and clearly • Incorporate comorbid health behaviours • Identify which comorbid health behaviours are most important to incorporate Identify the best methods for the measurement of comorbidities in MS • Examine the validity of medical records review, self-report, and administrative data sources for measuring comorbidity, and establish whether participant characteristics affect validity • Identify which data sources for comorbidity are appropriate for which research question (outcome) of interest • Identify the best analytical methods for comorbidity adjustment for studies that adjust for comorbidity as a potential confounder MS=multiple sclerosis.
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Search strategy and selection criteria We identified references for this Review by searches of PubMed with the following search terms: “comorbidity”, “multimorbidity”, “comorbid”, “autoimmune”, “inflammatory bowel disease”, “systemic lupus erythematosus”, “rheumatoid arthritis”, “thyroid”,“ sleep”, “restless legs syndrome”, “narcolepsy”, “depression”, “anxiety”, “bipolar”, “psychosis”, “schizophrenia”, “smoking”, “overweight”, “obesity”, “alcohol”, “hypertension”, “musculoskeletal”, “diabetes”, “gastrointestinal”, “irritable bowel syndrome”, “arthritis”, “fibromyalgia”, “peptic ulcer disease”, “liver”, and “kidney” in combination with the following search terms: “cancer”, “neurodegenerative”, “multiple sclerosis”, “epilepsy”, “Alzheimer’s disease”, and “quality of life” from 1966 until May, 2010. We also identified articles through searches of our own files. Only papers published in English were reviewed. Articles were chosen on the basis of originality and relevance to the topics covered in this Review.
comorbid diseases and MS, use of individual adjustment for each comorbidity might be a more effective approach, incorporating comorbidity severity if possible. We favour this approach until the associations between MS and comorbidities are better understood.
Conclusions and future directions Although the evidence on the associations between comorbidities and MS is increasing, further studies are needed to improve our knowledge (panel). We need to broadly identify which comorbidities occur in patients with MS, which are most common, and whether they occur with greater or less frequency than in the general population. By assessment of whether these comorbidities occur at certain ages, we might be able to understand the mechanistic associations between some comorbidities and MS. Further work is needed to establish whether preexisting comorbidities affect the risk and phenotype of MS and, if so, how. Data from some studies indicate that comorbidities and health behaviours also affect disease progression. These findings need to be verified, and a broader range of disability outcomes, such as upper extremity and cognitive function, need to be taken into account. From a therapeutic perspective, important questions include whether comorbidities affect treatment choice, response, tolerability, and adherence, and whether we should use different treatment strategies in the presence of a comorbidity. Research is also needed to determine the best way to measure and analyse comorbidities to understand their associations with the index disease, but until these links are better understood, individual adjustment for each comorbidity might be the best approach. Contributors Both authors designed the idea for this paper and made revisions. RAM undertook the literature search and drafted the paper.
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Conflicts of interest We have no conflicts of interest. Acknowledgments RAM is supported by a Rudy Falk Clinician Scientist Award from the University of Manitoba, Canada. References 1 Gijsen R, Hoeymans N, Schellevis FG, Ruwaard D, Satariano WA, van den Bos GA. Causes and consequences of comorbidity: a review. J Clin Epidemiol 2001; 54: 661–74. 2 Hoffman C, Rice D, Sung HY. Persons with chronic conditions. Their prevalence and costs. JAMA 1996; 276: 1473–79. 3 Lacey CJ, Salzberg MR, Roberts H, Trauer T, D’Souza WJ. Psychiatric comorbidity and impact on health service utilization in a community sample of patients with epilepsy. Epilepsia 2009; 50: 1991–94. 4 Devinsky O, Ehrenberg B, Barthlen GM, Abramson HS, Luciano D. Epilepsy and sleep apnea syndrome. Neurology 1994; 44: 2060–64. 5 Mielke MM, Rosenberg PB, Tschanz J, et al. Vascular factors predict rate of progression in Alzheimer disease. Neurology 2007; 69: 1850–58. 6 Dean G. How many people in the world have multiple sclerosis. Neuroepidemiology 1994; 13: 1–7. 7 Beck CA, Metz LM, Svenson LW, Patten SB. Regional variation of multiple sclerosis prevalence in Canada. Mult Scler 2005; 11: 516–19. 8 Leary SM, Porter B, Thompson AJ. Multiple sclerosis: diagnosis and the management of acute relapses. Postgrad Med J 2005; 81: 302–08. 9 Pugliatti M, Rosati G, Carton H, et al. The epidemiology of multiple sclerosis in Europe. Eur J Neurol 2006; 13: 700–22. 10 Valderas JM, Starfield B, Sibbald B, Salisbury C, Roland M. Defining comorbidity: implications for understanding health and health services. Ann Fam Med 2009; 7: 357–63. 11 Barcellos LF, Kamdar BB, Ramsay PP, et al. Clustering of autoimmune diseases in families with a high-risk for multiple sclerosis: a descriptive study. Lancet Neurol 2006; 5: 924–31. 12 Edwards LJ, Constantinescu CS. A prospective study of conditions associated with multiple sclerosis in a cohort of 658 consecutive outpatients attending a multiple sclerosis clinic. Mult Scler 2004; 10: 575–81. 13 Midgard R, Gronning M, Riise T, Kvale G, Nyland H. Multiple sclerosis and chronic inflammatory diseases. A case-control study. Acta Neurol Scand 1996; 93: 322–28. 14 Seyfert S, Klapps P, Meisel C, Fischer T, Junghan U. Multiple sclerosis and other immunologic diseases. Acta Neurol Scand 1990; 81: 37–42. 15 Marrie RA. Autoimmune disease and multiple sclerosis: methods, methods, methods. Lancet Neurol 2007; 6: 575–76. 16 Gupta G, Gelfand JM, Lewis JD. Increased risk for demyelinating diseases in patients with inflammatory bowel disease. Gastroenterology 2005; 129: 819–26. 17 Bernstein CN, Wajda A, Blanchard JF. The clustering of other chronic inflammatory diseases in inflammatory bowel disease: a population-based study. Gastroenterology 2005; 129: 827–36. 18 Kimura K, Hunter S, Thollander MS, et al. Concurrence of inflammatory bowel disease and multiple sclerosis. Mayo Clin Proc 2000; 75: 802–06. 19 Broadley SA, Deans J, Sawcer SJ, Clayton D, Compston DAS. Autoimmune disease in first-degree relatives of patients with multiple sclerosis. A UK survey. Brain 2000; 123: 1102–11. 20 Jacobs LD, Wende KE, Brownscheidle CM, et al. A profile of multiple sclerosis: the New York State Multiple Sclerosis Consortium. Mult Scler 1999; 5: 369–76. 21 Niederwieser G, Buchinger W, Bonelli RM, et al. Prevalence of autoimmune thyroiditis and non-immune thyroid disease in multiple sclerosis. J Neurol 2003; 250: 672–75. 22 Sloka JS, Pryse-Phillips WEM, Stefanelli M, Joyce C. Co-occurrence of autoimmune thyroid disease in a multiple sclerosis cohort. J Autoimmune Dis 2005; 2: 9. 23 De Keyser J. Autoimmunity in multiple sclerosis. Neurology 1988; 38: 371–74. 24 Consortium of Multiple Sclerosis Centers. NARCOMS Multiple Sclerosis Registry, 2008. http://www.mscare.org/cmsc/CMSCNARCOMS-Information.html (accessed Jan 5, 2008).
www.thelancet.com/neurology Vol 9 August 2010
Review
25
26
27
28
29
30
31 32
33
34
35
36
37 38
39 40 41
42
43 44
45
46
47 48
49
50
Marrie RA, Horwitz R, Cutter G, Tyry T, Campagnolo D, Vollmer T. Comorbidity, socioeconomic status, and multiple sclerosis. Mult Scler 2008; 14: 1091–98. Centers for Disease Control and Prevention. Prevalence of disability and associated health conditions, United States, 1991–1992. MMWR Morb Mortal Wkly Rep 1994; 40: 730–31, 737–39. Marrie RA. The influence of comorbid diseases and health behaviors on clinical characteristics, disability at diagnosis, and disability progression in multiple sclerosis. PhD thesis, Case Western Reserve University, 2007; 1–547. Warren SA, Turpin KV, Pohar SL, Jones CA, Warren KG. Comorbidity and health-related quality of life in people with multiple sclerosis. Int J MS Care 2009; 11: 6–16. Brass SD, Duquette P, Proulx-Therrien J, Auerbach S. Sleep disorders in patients with multiple sclerosis. Sleep Med Rev 2010; 14: 121–29. Manconi M, Ferini-Strambi L, Filippi M, et al, the Italian REMS Study Group. Multicenter case-control study on restless legs syndrome in multiple sclerosis: the REMS study. Sleep 2008; 31: 944–52. Deriu M, Cossu G, Molari A, et al. Restless legs syndrome in multiple sclerosis: a case-control study. Mov Disord 2009; 24: 697–701. Auger C, Montplaisir J, Duquette P. Increased frequency of restless legs syndrome in a French-Canadian population with multiple sclerosis. Neurology 2005; 65: 1652–53. Gomez-Choco M, Iranzo A, Blanco Y, Graus F, Santamaria J, Saiz A. Prevalence of restless legs syndrome and REM sleep behavior disorder in multiple sclerosis. Mult Scler 2007; 13: 805–08. Manconi M, Fabbrini M, Bonanni E, et al. High prevalence of restless legs syndrome in multiple sclerosis. Eur J Neurol 2007; 14: 534–39. Nishino S, Kanbayashi T. Symptomatic narcolepsy, cataplexy and hypersomnia, and their implications in the hypothalamic hypocretin/ orexin system. Sleep Med Rev 2005; 9: 269–310. Ajayi OF, Chang-McDowell T-Y, Culpepper WJ, Royal W, Bever C. High prevalence of sleep disorders in Veterans with multiple sclerosis. Neurology 2008; 70 (suppl 1): A333. Goldman Consensus Group. The Goldman Consensus statement on depression in multiple sclerosis. Mult Scler 2005; 11: 328–37. Kessler RC, Berglund P, Demler O, et al. The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R). JAMA 2003; 289: 3095–105. Korostil M, Feinstein A. Anxiety disorders and their clinical correlates in multiple sclerosis patients. Mult Scler 2007; 13: 67–72. Poder K, Ghatavi K, Fisk J, et al. Social anxiety in a multiple sclerosis clinic population. Mult Scler 2009; 15: 393–98. Somers JM, Goldner EM, Waraich P, Hsu L. Prevalence and incidence studies of anxiety disorders: a systematic review of the literature. Can J Psychiatry 2006; 51: 100–13. Fisk J, Morehouse SA, Brown MG, Skedgel C, Murray TJ. Hospital-based psychiatric service utilization and morbidity in multiple sclerosis. Can J Neurol Sci 1998; 25: 230–35. Joffe RT, Lippert GP, Gray TA, Sawa G, Horvath Z. Mood disorder and multiple sclerosis. Arch Neurol 1987; 44: 376–78. Patten SB, Svenson LW, Metz LM. Psychotic disorders in MS: population-based evidence of an association. Neurology 2005; 65: 1123–25. Pine DS, Douglas CJ, Charles E, Davies MB, Kahn D. Patients with multiple sclerosis presenting to psychiatric hospitals. J Clin Psychiatry 1995; 56: 297–306. Marrie RA, Horwitz R, Cutter G, Tyry T, Campagnolo D, Vollmer T. High frequency of adverse health behaviors in multiple sclerosis. Mult Scler 2009; 15: 105–13. Quesnel S, Feinstein A. Multiple sclerosis and alcohol: a study of problem drinking. Mult Scler 2004; 10: 197–201. Khurana SR, DiGiacomo AM, Rohini V, et al. Prevalence of overweight and obesity among Veterans with multiple sclerosis. Int J MS Care 2006; 8: 59. Marrie RA, Horwitz RI, Cutter G, Tyry T, Campagnolo D, Vollmer T. Comorbidity delays diagnosis and increases disability at diagnosis in MS. Neurology 2009; 72: 117–24. Bjerager M, Palshof T, Dahl R, Vedsted P, Olesen F. Delay in diagnosis of lung cancer in clinical practice. Br J Gen Pract 2006; 56: 863–68.
www.thelancet.com/neurology Vol 9 August 2010
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53
54
55
56 57
58
59
60
61
62
63
64 65
66
67
68
69
70 71
72
73 74
Healy BC, Ali EN, Guttmann CRG, et al. Smoking and disease progression in multiple sclerosis. Arch Neurol 2009; 66: 858–64. Kirby S, Brown MG, Murray TJ, et al. Progression of multiple sclerosis in patients with other autoimmune diseases. Mult Scler 2005; 11 (suppl 1): S28–29. Marrie RA, Rudick R, Horwitz R, et al. Vascular comorbidity is associated with more rapid disability progression in multiple sclerosis. Neurology 2010; 74: 1041–47. Dallmeijer AJ, Beckerman H, de Groot V, van de Port IG, Lankhorst GJ, Dekker J. Long-term effect of comorbidity on the course of physical functioning in patients after stroke and with multiple sclerosis. J Rehabil Med 2009; 41: 322–26. Hernan MA, Jick SS, Logroscino G, Olek MJ, Ascherio A, Jick H. Cigarette smoking and the progression of multiple sclerosis. Brain 2005; 128: 1461–65. Sundstrom P, Nystrom L. Smoking worsens the prognosis in multiple sclerosis. Mult Scler 2008; 14: 1031–35. Di Pauli F, Reindl M, Ehling R, et al. Smoking is a risk factor for early conversion to clinically definite multiple sclerosis. Mult Scler 2008; 14: 1026–30. Sena A, Couderc R, Ferret-Sena V, et al. Apolipoprotein E polymorphism interacts with cigarette smoking in progression of multiple sclerosis. Eur J Neurol 2009; 16: 832–37. Pittas F, Ponsonby AL, van der Mei IA, et al. Smoking is associated with progressive disease course and increased progression in clinical disability in a prospective cohort of people with multiple sclerosis. J Neurol 2009; 256: 577–85. Zivadinov R, Weinstock-Guttman B, Hashmi K, et al. Smoking is associated with increased lesion volumes and brain atrophy in multiple sclerosis. Neurology 2009; 73: 504–10. Hermann B, Vickrey B, Hays RD, et al. A comparison of healthrelated quality of life in patients with epilepsy, diabetes and multiple sclerosis. Epilepsy Res 1996; 25: 113–18. Wu N, Minden SL, Hoaglin DC, Hadden L, Frankel D. Quality of life in people with multiple sclerosis: data from the Sonya Slifka Longitudinal Multiple Sclerosis Study. J Health Hum Serv Adm 2007; 30: 233–67. Turpin KV, Carroll LJ, Cassidy JD, Hader WJ. Deterioration in the health-related quality of life of persons with multiple sclerosis: the possible warning signs. Mult Scler 2007; 13: 1038–45. Francis G. Benefit-risk assessment of interferon-b therapy for relapsing multiple sclerosis. Expert Opin Drug Saf 2004; 3: 289–303. Rudick RA, Stuart WH, Calabresi PA, et al. Natalizumab plus interferon beta-1a for relapsing multiple sclerosis. N Engl J Med 2006; 354: 911–23. Bayliss EA, Steiner JF, Fernald DH, Crane LA, Main DS. Descriptions of barriers to self-care by persons with comorbid chronic diseases. Ann Fam Med 2003; 1: 15–21. Gulick EE. Emotional distress and activities of daily living functioning in persons with multiple sclerosis. Nurs Res 2001; 50: 147–54. Weinshenker BG, Rice GP, Noseworthy JH, Carriere W, Baskerville J, Ebers GC. The natural history of multiple sclerosis: a geographically based study. 3. Multivariate analysis of predictive factors and models of outcome. Brain 1991; 114: 1045–56. Chobanian AV, Bakris GL, Black HR, et al. Seventh report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure. Hypertension 2003; 42: 1206–52. Launer LJ. Diabetes and brain aging: epidemiologic evidence. Curr Diab Rep 2005; 5: 59–63. National Center for Health Statistics. Health, United States, 2005. With chartbook on Trends in the Health of Americans. Hyattsville, MD: 2005. US Department of Health and Human Services, 2005: 1–535 http://www.cdc.gov/nchs/data/hus/hus05.pdf (accessed July 28, 2010). Tammemagi CM, Neslund-Dudas C, Simoff M, Kvale P. Smoking and lung cancer survival. The role of comorbidity and treatment. Chest 2004; 125: 27–37. Weil E, Wachterman M, McCarthy EP, et al. Obesity among adults with disabling conditions. JAMA 2002; 288: 1265–68. Trojano M, Liguori M, Bosco Zimatore G, et al. Age-related disability in multiple sclerosis. Ann Neurol 2002; 51: 475–80.
827
Review
75
76
77
78 79
80
81
82
83
84
828
Tremlett H, Zhao Y, Joseph J, Devonshire V. Relapses in multiple sclerosis are age- and time-dependent. J Neurol Neurosurg Psychiatr 2008; 79: 1368–74. Pfleger CCH, Flachs EM, Koch-Henriksen N. Social consequences of multiple sclerosis (1): early pension and temporary unemployment—a historical prospective cohort study. Mult Scler 2010; 16: 121–26. Pfleger CCH, Flachs EM, Koch-Henriksen N. Social consequences of multiple sclerosis: clinical and demographic predictors: a historical prospective cohort study. Eur J Neurol 2010; published online April 9. DOI:10.1111/j.1468-1331.2010.03020.x. Braveman PA, Cubbin C, Egerter S, et al. Socioeconomic status in health research: one size does not fit all. JAMA 2005; 294: 2879–88. Steenland K, Hu S, Walker J. All-cause and cause-specific mortality by socioeconomic status among employed persons in 27 US states, 1984–1997. Am J Public Health 2004; 94: 1037–42. Minkler M, Fuller-Thomson E, Guralnik JM. Gradient of disability across the socioeconomic spectrum in the United States. N Engl J Med 2006; 355: 695–703. Marrie RA, Cutter G, Tyry T, Vollmer T, Campagnolo D. Does multiple sclerosis-associated disability differ between races? Neurology 2006; 66: 1235–40. Marrie RA, Cutter G, Tyry T, Vollmer T, Campagnolo D. Disparities in the management of multiple sclerosis-related bladder symptoms. Neurology 2007; 68: 1971–78. Okura Y, Urban LH, Mahoney DW, Jacobsen SJ, Rodeheffer RJ. Agreement between self-report questionnaires and medical record data was substantial for diabetes, hypertension, myocardial infarction and stroke but not for heart failure. J Clin Epidemiol 2004; 57: 1096–103. Bayliss EA, Ellis JL, Steiner JF. Subjective assessments of comorbidity correlate with quality of life health outcomes: initial validation of a comorbidity assessment instrument. Health Qual Life Outcomes 2005; 2: 51.
85 86
87
88
89
90
91
92
93
Klabunde CN, Warren JL, Legler JM. Assessing comorbidity using claims data: an overview. Med Care 2002; 40 (8 suppl): IV-26–35. Marrie RA, Yu N, Blanchard JF, Leung S, Elliott L. The rising prevalence and changing age distribution of multiple sclerosis in Manitoba. Neurology 2010; 74: 465–71. Hohol MJ, Orav EJ, Weiner HL. Disease steps in multiple sclerosis: a longitudinal study comparing disease steps and EDSS to evaluate disease progression. Mult Scler 1999; 5: 349–54. Horton M, Rudick RA, Hara-Cleaver C, Marrie RA. Validation of a self-report comorbidity questionnaire for multiple sclerosis. Neuroepidemiology 2010; 35: 83–90. Culpepper WJ, Ehrmantraut M, Wallin MT, Flannery K, Bradham DD. Veterans Health Administration multiple sclerosis surveillance registry: the problem of case-finding from administrative databases. J Rehabil Res Dev 2006; 43: 17–24. Bernstein CN, Blanchard JF, Rawsthorne P, Wajda A. Epidemiology of Crohn’s disease and ulcerative colitis in a central Canadian province: a population-based study. Am J Epidemiol 1999; 149: 916–24. de Groot V, Beckerman H, Lankhorst GJ, Bouter LM. How to measure comorbidity: a critical review of available methods. J Clin Epidemiol 2003; 56: 221–29. Byles JE, D’Este C, Parkinson L, O’Connell R, Treloar C. Single index of multimorbidity did not predict multiple outcomes. J Epidemiol 2005; 58: 997–1005. Grunau GL, Sheps S, Goldner EM, Ratner PA. Specific comorbidity risk adjustment was a better predictor of 5-year acute myocardial infarction mortality than general methods. J Clin Epidemiol 2006; 59: 274–80.
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