A meta-analysis investigating the prevalence and moderators of migraines among people with bipolar disorder

Journal of Affective Disorders 178 (2015) 88–97

Contents lists available at ScienceDirect

Journal of Affective Disorders journal homepage: www.elsevier.com/locate/jad

Special review article

A meta-analysis investigating the prevalence and moderators of migraines among people with bipolar disorder Michele Fornaro a,b,n, Brendon Stubbs c a

New York Psychiatric Institute, Columbia University, NYC, USA Department of Education Sciences, University of Catania, Italy c Faculty of Education and Health, University of Greenwich, Southwood Site, Avery Hill Road, Eltham, London SE9 2UG, UK b

art ic l e i nf o

a b s t r a c t

Article history: Received 19 February 2015 Accepted 26 February 2015 Available online 9 March 2015

Background: Uncertainty exists regarding the prevalence and moderators of migraine comorbidity among people with bipolar disorder (BD). We conducted a meta-analysis and meta-regression to investigate the prevalence and moderators of migraine among people with BD. Method: Two authors independently searched major electronic databases from inception till 02/2015. Articles were included that reported the prevalence of migraine in people with BD with or without a control group. A random effects meta-analysis and exploratory meta-regression were conducted. Results: Fourteen studies were included encompassing 3976 individuals with BD (mean age 35.5 years, SD 7.6, 29% male). The overall pooled prevalence of migraine was 34.8% (95% CI ¼25.54–44.69). The prevalence of migraine was higher among people with BD-II (54.17%, 95% CI ¼31.52–75.95, n ¼742) compared to BD-I (32.7%, 95% CI ¼18.16–49.19, n ¼ 2138, z ¼3.97, p o0.0001). The prevalence of migraine was 33.9% (95% CI ¼26.02–42.44), 39.5% (95% CI ¼18.81–62.39) and 47.11% (95% CI¼ 22.24–72.77) in North America, Europe and South America respectively. The prevalence of migraine was higher when classified according to recognized criteria at 47.91% (95% CI¼ 32.51–63.5) compared to non-recognized criteria (20.0%, 95% CI¼ 12.44–29.06, z ¼  8.40, po 0.0001). Meta regression suggests mean age may be a potential moderator. Conclusion: Migraine is common and burdensome among people with BD. People with BD-II appear to be particularly affected. Nonetheless, future research is required to better understand these relationships, with a special emphasis toward the course specifiers of comorbid migraine cases of either BD-I vs. BD-II. & 2015 Elsevier B.V. All rights reserved.

Keywords: Migraine Bipolar disorder (BD) Comorbidity Prevalence Meta-analysis

Contents 1. 2.

3.

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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Material and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Eligibility criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Information sources and searches. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Study selection. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4. Data collection process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5. Risk of bias in individual studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6. Meta-analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7. Quality assessment and risk of bias across the studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Study selection. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Included study and participant characteristics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Quality score and quality differentiation results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4. Meta-analysis of the prevalence of migraine in people with bipolar disorder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5. Sub-group analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Correspondence to: New York Psychiatric Institute, Columbia University, 1051 Riverside Drive, New York, NY 10032, unit 2712, USA. Tel.: þ 1 646 774 7652. E-mail addresses: [email protected] (M. Fornaro), [email protected] (B. Stubbs).

http://dx.doi.org/10.1016/j.jad.2015.02.032 0165-0327/& 2015 Elsevier B.V. All rights reserved.

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3.5.1. Prevalence of migraine according to BPD diagnosis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 3.5.2. Prevalence of migraine according to geographical location . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 3.5.3. Prevalence of migraine according to criteria used . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 3.6. Meta-regression analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 3.7. Risk of bias within and across studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 4. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 4.1. Migraine associated to BD-II: specific findings and related clinical implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 4.2. Migraine–BD comorbidity and subjective pain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 4.3. Additional findings and major implication of the quantitative synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 4.4. Study limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 Role of funding source . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 Conflict of interest. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96

1. Introduction Migraine is one the oldest ailments known to mankind (Mandal, 2014). Some of the earliest cases of painful headaches were recorded by the ancient Egyptians and date back as far as 1200 B.C. (Karenberg and Leitz, 2001). Much later, in around 400 B.C., Hippocrates referred to the visual disturbances that can precede a migraine such as flashing lights or blurred vision (“aura”) (Breitenfeld et al., 2014). However, the credit for migraine “discovery” was given to Aretaeus of Cappadocia who described in the second century the one sided or unilateral headaches that are typical of migraines as well as the associated vomiting and the windows of time between migraines that are symptom free (Koehler and van de Wiel, 2001). The word “migraine” itself derived from the Latin word “hemicrania” meaning “half” (hemi) “skull” (crania). This term was first used by Galenus of Pergamon to describe the pain felt across one side of the head during a migraine (Isler, 1992). Yet the documentation of “migraine” features, already documented even in course of “mood disturbances”, was not unique to Western cultures, as recorded by the Chinese surgeon Hua Tuo (late Han Dynasty, second century A.D.) who was the first to successfully use acupuncture needles to relieve the “recurrent” migraines complained by the “irritable, moody” and “tyrannical” founder of his kingdom (Fu, 2002). Similarly, the Islamic philospher Avicenna described migraine in his textbook on medicine “El Qanoon fel teb”, a treatise which is also nowadays considered one of the earliest texts on “melancholia and mania” (Omrani et al., 2012), documenting how eating, drinking, sounds and light all worsened the pain felt during a migraine (Abokrysha, 2009), a report that should nowadays appear clinically intriguing also considering that “hyperesthesia” (sensory over-sensitivity) has been recently linked even to anxious, irritable and mood disturbances (Sylvia et al., 2014). Avicenna described how these patients tended to rest alone in a dark room until the attack passed, but it was Abu Bakr Mohamed Ibn Zakariya Râzi who pointed to an association between migraine and hormones when he referred to how such headaches would occur during menopause, after childbirth or during dysmenorrhea (Mandal, 2014), all conditions that would nowadays potentially linked to the broad definition of bipolar spectrum when leading to “maternity blues”, “post-partum depression” or menstrual disturbances (Akiskal and Mallya, 1987; Di Florio et al., 2013; Fornaro and Perugi, 2010). Yet, it was not until the publication of the results from large studies in carried in Zurich (Merikangas et al., 1990) and Detroit (Breslau et al., 1994) that migraine was systematically documented to be more frequent in mood disorder patients, including bipolar disorder (BD) cases, than in controls. According to the International Classification of Headache Disorders, 2nd edition (ICHD-2), migraine refers to different phenotypes having in common a low threshold to the development of headache among migraineurs, usually being characterized for a recurring pattern, frequent free-interval, and usually provoked by stereotyped

triggers (Headache Classification Subcommittee of the International Headache Society, 2004). Nonetheless, while a conclusive definition of migraine remains elusive, especially due to the heterogeneity of some of the frequently associated neurological and psychiatric comorbidities, a three-fold increase in migraine prevalence in patients with BD has been ascertained (Merikangas et al., 1993), as outlined by a recent systematic review about the prevalence of migraine comorbidity among people with BD (Fornaro et al., 2015). This latter systematic review, first of its kind at writing time, whilst helpful, updated and informative, did not undertake a meta-analysis, nor was there any attempt to stratify the results according to diagnosis (BD-I vs. BD-II), setting or location. Information about how the prevalence of migraine may be influenced according to the classification of BD, geographical location and the criteria used to define a migraine are nonetheless clinically relevant, and conducting meta-analyses offers the potential to provide the most accurate effect size of an actual phenomenon and enable researchers to make wider conclusions than considering individual studies in isolation. Given the burden of migraine among people with BD, there is a need to better understand the prevalence and moderators of migraine. Therefore, to the best of our knowledge, we set out to conduct the first meta-analysis to investigate the prevalence and moderators of migraine comorbidity among people with BD.

2. Material and methods The present meta-analysis adhered to the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guidelines (Stroup et al., 2000). The current paper followed the inclusion and exclusion criteria already adopted for our recent Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) systematic review (Fornaro et al., 2015), but extended the inclusion criteria to account also for contributes indexed in PubMed since inception. In addition, searches were updated on all databases. Please refer to PROSPERO registration number: CRD42014009335 at http://www.crd.york.ac. uk/PROSPERO/ for further reference and to the following lines for a brief summary of the adopted criteria. 2.1. Eligibility criteria We included observational studies published in the English language that fulfilled the following criteria: 1) Included adults with BD (either type I or type II) diagnosed according to recognized diagnostic criteria (e.g., DSM-IV (APA, 1994) or ICD-10 (WHO, 2010)) or through medical record review with or without a control group without mental illness. 2) Reported the prevalence of migraine. We accepted any assessment of migraine including self-report physician diagnosis or recognized criteria such as the 1988 and the 2004 editions of the

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International Headache criteria (Headache Classification Subcommittee of the International Headache Society, 2004, 1988). No publication date of publication restrictions was placed upon the searches. Papers covering cases of migraine–BD comorbidity associated with additional disorders (either psychiatric, neurological [including migraine due to epilepsy, Tourette's syndrome or schizophrenia] or to other somatic disorders/diseases) were also evaluated wherever available. We excluded studies that reported the prevalence of BD among people with migraine and other biased samples. We also excluded case reports, papers not including BD migraine co-occurring cases, those merely focusing on neurobiological, genetic or pharmacological aspects of either migraine or BD; including only children or adolescents; or without an accurate description about the diagnostic definitions of either migraine and BD. 2.2. Information sources and searches Two independent reviewers searched PubMed/Medline, Scopus, PsycLit, PsycInfo, Embase, and Cochrane library from inception until February 2015. We used the following key words or their combination in the search strategy: “migraine AND”, either in the title and abstract (or in the key words where specified). The adopted PubMed string was: “(Migraine [Title/Abstract]) AND Bipolar Disorder [Title/Abstract]”. Contact with study authors was planned if ever needed. In addition, the reference lists of all eligible articles and recent systematic reviews (Fornaro et al., 2015; Stubbs et al., 2015) were manually screened. 2.3. Study selection Two independent reviewers screened the titles and abstracts of all potentially eligible articles. When a title and/or an abstract appeared suggestive for inclusion, the full text reprint was obtained and examined to assess its relevance according to our inclusion/ exclusion criteria. Both authors applied the eligibility criteria, and a list of full text articles was developed through consensus. The two reviewers then considered the full texts of these articles and the final list of included articles was reached through consensus. 2.4. Data collection process A two-step literature search examined all titles and abstracts, accessing the full texts of potentially relevant papers. Upon data collection and extraction, the appointed authors compared their own results with each other to reach a final consensus based on consensual inclusion and exclusion criteria. Data was sought for the following characteristics: Participants, Interventions, Comparisons, Outcomes, and Study design (PICOS), as well as funding sources. Specifically, the recorded variables for each article included in the quantitative synthesis included the following: author(s), year publication, study design, sample size, number of patients with BD-I vs. BD-II vs. BD Not Otherwise Specified (BD-NOS), number of patients with- or without-comorbid migraine (stratified for type of BD and/or type of migraine whenever the information available), and pharmacological history (including class of current medication, if ever). Additionally, the presence of any eventual follow-up or control group, outcome measures, conclusions, limitations, quality score, and quality differentiation were reordered wherever available.

unrepresentativeness or inhomogeneity of the sample size or lack of control group, and selection by indication bias (nonrandom assignment of the exposure where applicable) (McGauran et al., 2010). 2.6. Meta-analysis We pooled individual study data using a DerSimonian–Laird proportion method (DerSimonian and Laird, 1988) with StatsDirects. Due to anticipated heterogeneity, a random effects metaanalysis was employed. If there were 3 or more studies with relevant data, we planned to calculate the relative risk (RR) to investigate prevalence of migraine in those with and without BD. In addition, we conducted numerous subgroup analyses to establish if the prevalence of migraine differed according to the geographical region, type of bipolar disorder (BD-I vs. BD-II) and according to the assessment of migraine criteria (International Headache Society criteria (editions 1988 or 2004) vs. other criteria). Finally, we conducted several meta-regression analyses (if N Z3) to investigate potential moderators (age and percentage males) with Comprehensive Meta-Analysiss (version 3). We assessed publication bias with a visual inspection of funnel plots and calculation of the Egger test and Begg test. 2.7. Quality assessment and risk of bias across the studies The studies were rated for quality using the following eligibility criteria: (i) representativeness of the sample (0–1 points); (ii) presence of BD patients only in the sample (0–2 points); (iii) a priori study design with the goal of evaluating the epidemiology of migraine–BD comorbidity (or vice versa) (0–2 points); (iv) extension of the followup (longitudinal studies)/clinical records (retrospective studies) 41 year (0–2 points); (v) validation of the clinical diagnosis and the used treatment (if applicable) (0–2 points); (vi) inclusion and control of all the available variables for potential confounders/effect modifiers that may had influenced outcome (if applicable) (0–2 points); (vii) reliability of the information gathered for the identification of BD cases/recall bias (0–2 points); (viii) accuracy of the study was to discern between manic, hypomanic, mixed, and depressive episodes in BD (0–2 points); (ix) appropriateness of the number of comorbid cases reported as results/sample size (0–2 points). Quality rating had 17 as the maximum score. Studies were also differentiated in the following way: (i) good quality: most or all criteria being fulfilled, and when they were not met, the study conclusions were thought to be very unlikely to alter (12–17 points); (ii) moderate quality: some criteria being fulfilled, and where they were not met, the study conclusions were thought to be unlikely to alter (7–11 points); (iii) poor quality: few criteria fulfilled but the conclusions of the study were thought to be very likely to alter (0–6 points). Any eventual bias affecting cumulative evidence (e.g. publication bias, selective reporting within studies) was assessed through the study evaluation process and accounted in the discussion of the present manuscript.

3. Results

2.5. Risk of bias in individual studies

3.1. Study selection

Potential major confounding biases in the studies were ascertained at study level focusing on the following: measurement/ diagnostic bias (e.g. lack of reliable diagnostic tools to make the diagnosis of either migraine or BD), confounding bias (e.g. lack of stratification and multivariate control for specific socio-demographic, vital or clinical features), information (especially recall) bias,

The search in PubMed generated 134 papers, and 595 results in Scopus. Thirteen additional results were obtained through search either in Cochrane (n¼ 7), PsycLit, PsycInfo or reference textbooks/ manual search. Refer to Fig. 1 for a synthetic flow chart of the multi-step selection procedure which allowed to retain 14 final original studies accounted in our quantitative analysis.

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3.2. Included study and participant characteristics With the sole exception of three retrospective studies (Holland et al., 2011; Munoli et al., 2014; Saunders et al., 2014), crosssectional design was the only method of report we could detect in the 14 results accounted for the present quantitative synthesis. The mean sample size across the included studies was 283.69 (range 27–1461). Overall, 3976 people with bipolar disorder were included across the meta-analysis. The sample included 2161 and 647 people identified with BD-I and BD-II respectively. The remainder of participants were mixed bipolar disorder or it was unclear within the original studies. Overall, the mean percentage of male participants was 29% (SD 10) and the mean age was 35.5 (SD 7.6). 3.3. Quality score and quality differentiation results Based on the quality differentiation, original studies were ranked as follows: “poor” (n¼ 5, mean total score¼ 4.3), “moderate” (n¼ 5, mean total score¼8.5) or “good” quality (n¼4, mean total score¼14). No longitudinal follow-up study was found. Details about “good quality” original studies have been summarized in Table 1 alongside with their major limitations and/or biases nonetheless. 3.4. Meta-analysis of the prevalence of migraine in people with bipolar disorder It was possible to pool data from 14 studies accounting for 3976 unique people with bipolar disorder. Overall, the pooled prevalence of migraine was 34.8% (95% CI ¼25.54–44.69, Q¼292.58

(df¼13); p r0.0001, Fig. 2a). The funnel plot was broadly symmetrical (Fig. 2b) and neither the Begg–Mazumdar (Kendall's τ ¼0.384, p ¼0.08) or Egger: bias (¼5.66, p¼ 0.1017) were significant indicating no evidence of publication bias. 3.5. Sub-group analyses 3.5.1. Prevalence of migraine according to BPD diagnosis It was possible to pool data investigating the prevalence of migraine among 2138 unique participants with bipolar disorder I to establish a pooled prevalence of 32.7% (95% CI¼18.16–49.19). There was no evidence of publication bias (Egger: bias¼ 2.744, p¼0.72). The pooled prevalence of migraine among 742 people with BPD II was 54.17% (95% CI¼ 31.52–75.95) which was significantly higher than the prevalence in BPD I (z¼3.97, po0.0001). No evidence of publication bias was evident (Egger: bias¼ 3.77868, p¼0.2831). 3.5.2. Prevalence of migraine according to geographical location The pooled prevalence of migraine comorbidity was 33.9% in North America (95% CI ¼26.0291–42.44, Q¼26.26 (df¼ 3); pr 0.0001, n ¼1215). There was no evidence of publication bias (Egger: bias ¼7.614, p ¼0.14). The pooled prevalence of migraine comorbidity in Europe among 2069 participants with bipolar disorder was 39.5% (95% CI ¼18.81–62.39, Q¼115.5 (df¼ 5); pr 0.0001) with no evidence of publication bias (Egger: bias ¼3.677; p ¼ 0.514). Moreover, there was no statistically significant difference in the prevalence of migraine comorbidity among bipolar participants in North American and European participants (p 40.05). Data from 530 participants with bipolar

Identification

Adaptation of the PRISMA 2009 Flow Diagram (Moher et al., 2009).

Records identified through database searching (n = 729)

Additional records identified through other sources (n = 13) (Edited books, contact with

the authors, manual search)

Eligibility

Screening

Records after duplicates removed

Included

91

(n = 632)

Records screened (n = 116)

References assessed for eligibility

Records excluded (e.g. not related content) (n = 51)

Sources further excluded (e.g. inaccurate definitions) (n = 41)

(n = 65)

Sources included in qualitative synthesis (n = 14)

Included in Meta-analysis (n = 14) Fig. 1. Flow chart of review procedures for the quantitative synthesis (Moher et al., 2009).

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Table 1 Summary of good quality studies included in the quantitative synthesis. Author, date. Study design

Aim/Hypothesis

Low et al., 2003. Crosssectional study.

Ortiz et al., 2010. Crosssectional study.

To explore the crossprevalence of migraine in BD-I and BD-II patients (study 1), then to explore the prevalence of comorbid psychiatric disorders (including BDs) in migraine patients (study 2).

Sample size

Main results

Conclusions

Limitations

Quality score

A hundred and eight To investigate the prevalence and clinical BD patients (17 BD-II). correlates of comorbid migraine in BD patients vs. noncomorbid bipolar patients.

BD-II patients, especially females, had a higher prevalence of family history of depression and a lower chance/ propensity to be on lithium or other mood stabilizers rather than atypical antidepressants.

BD-II patients with migraine may be at higher risk for MDD misdiagnosis, family history for psychiatric disorder, have an overall higher burden and chance to receive antidepressant alone rather mood stabilizers.

I ¼1 II ¼2 Good quality. III¼ 2 IV¼ 0 V¼2 VI¼ 2 VII ¼0 VIII ¼ 2 IX ¼1 Total¼12

Study N ¼ 214 subjects (BD-I ¼126, BD-II¼ 61, BD NOS or schizoaffective disorder, n¼ 27). Study 2, 102 patients, of whom, 0 had a current BD-I, 7 a current BD-II and 5 had a lifetime BD-I vs. 8 with a lifetime BD-II).

Up to 24.5% BD patients had comorbid migraine; those with BD-II had a higher prevalence (34.8%) compared to BD-I (19.1%), p r 0.005). Psychiatric comorbidities and suicidal behavior were also common.

Migraine is prevalent among BD patients, especially BD-II cases. Risk for suicidal behavior and comorbid Anxiety disorders is also high.

Nguyen and Low, 2013. Retrospective study.

N ¼36.984 patients To carry between(Canadian Community group and amonggroup comparisons of Health Survey 1.2). migraine in BD according to lifetime mood episode(s)/ combination of mood episode(s) in affective disorder patients (including BD) vs. firstdegree relative vs. general population.

Migraine comorbidity in BD was associated with an earlier age of onset of BD itself, especially with depressive polarity of first episode, as well as with a higher number of psychiatric additional comorbidities.

Saunders et al., 2014. Retrospective study.

To explore whether the BD patients, n¼ 412, higher comorbidity of healthy controls, migraine in BD women n¼ 157. vs. BD men documented by most of the previous evidence would be associated with specific features of illness and psychosocial risk factors that would differ by gender and impact outcome.

Overall, compared with controls, the adjusted OR of having migraine was 2.0 (95% CI ¼ 1.4–2.8) for manic episodes alone, 1.9 (95% CI ¼1.6–2.1) for depressive episodes alone, and 3.0 (95% CI ¼ 2.3–3.9) for subjects with both manic and depressive episodes. Compared to with those with manic episodes alone and depressive episodes alone, the odds of having migraine were significantly increased in subjects with both manic and depressive episodes (OR 1.5 vs. manic episodes alone; 1.8 vs. depressive episodes alone). Interestingly, this was also the first study specifically exploring mixed symptoms, which were found in 102 (36%) of nonmigraine cases vs. 63 (50%) of comorbid cases. With respect to gender distribution, there was no statistically significant difference between rates of migraine in the BD-II group vs. BDI one in the women (OR ¼1.6; 95%, 0.8–3.0, yet group differences between women with BD and migraine vs. those without comorbid migraine included a marginally higher rate of mixed symptoms (OR¼ 0.19, 95% CI, 1.0–3.7).

Unrepresentativeness of the BD-II subset. Overrepresentation of females in the included set. Recall bias. Use of outdated IHS criteria for the questionnaire adopted for the diagnosis of migraine. Lack of detailed report about different psychiatric drugs. The diagnosis of migraine was made by a self-assessment questionnaire. Overrepresentation of BD-I and female cases. The interviews were partially conducted in a clinic specialized in the treatment of migraine (chance of Berkson's bias). Post-hoc retrospective chart review. Recall bias.

Since migraine was more common in BD subjects (31%) vs. controls (6%) and had an elevated risk in BD women compared to men (OR ¼3.5; 95% CI, 2.1–5.8), the presence of migraine, especially in course of mixed symptoms, may prompt clinicians to account migraine as a common comorbidity which may ultimately affect the long-term course of BD itself.

Self-reported, physician made, diagnoses of migraine (recall bias). The sample included patients with BD followed over time, meaning that the most severe end of the bipolar spectrum may have not been represented; risk of Berkson's bias. Control group size smaller that studied population. Overrepresentation of BD-I cases.

BD¼ Bipolar Disorder; MDD¼ Major Depressive Disorder; MDE¼ Major Depressive Episode; NOS¼ Not Otherwise Specified.

Quality differentiation

I ¼1 II ¼2 Good quality. III¼ 3 IV¼ 0 V¼1 VI¼ 2 VII ¼1 VIII ¼ 2 IX ¼2 Total¼16

I ¼1 II ¼1 Good quality. III¼ 0 IV¼ 2 V¼2 VI¼ 2 VII ¼0 VIII ¼ 2 IX ¼2 Total¼12

I ¼1 II ¼2 Good quality. III¼ 2 IV¼ 2 V¼2 VI¼ 2 VII ¼1 VIII ¼ 2 IX ¼2 Total¼16

M. Fornaro, B. Stubbs / Journal of Affective Disorders 178 (2015) 88–97

93

Proportion meta analysis plot [random effects] Oedegaard KJet al., (2005)

0.78 (0.71, 0.84)

Bapt ist a T et al., (2012)

0.61 (0.53, 0.68)

Fasmer O.B. & Oedegaard K.J. (2001)

0.56 (0.45, 0.66)

D ilsaver SC et al., (2008)

0.54 (0.43, 0.65)

Fasmer O.B. (2001)

0.44 (0.25, 0.65)

Low NC et al., (2003)

0.40 (0.31, 0.50)

Briet zke E. et al., (2012)

0.34 (0.29, 0.39)

Jet t e N et al., (2008)

0.32 (0.27, 0.37)

Saunders EF et al., (2014)

0.31 (0.26, 0.36)

Mahmood T. et al., (1999)

0.26 (0.17, 0.37)

Gordon-Smith K et al. (2015)

0.25 (0.23, 0.27)

Ort iz A et al., (2010)

0.24 (0.20, 0.30)

Holland J et al., (2011)

0.05 (0.02, 0.09) 0.02 (3.0E -3, 0.09)

Munoli RN et al., (2014) c ombined

0.35 (0.26, 0.45) 0.0

0.3

0.6

0.9

proportion (95% confidence interval)

Fig. 2. (a) Pooled prevalence of migraine comorbidity among included participants. (b) Funnel plot for the main analysis.

disorder in South America revealed a pooled prevalence of 47.11% (95% CI ¼22.24–72.77, Q¼35, po 0.001).

3.5.3. Prevalence of migraine according to criteria used It was possible to pool data from 7 studies representing 1094 participants with bipolar disorder to establish a pooled prevalence of migraine of 47.91% (95% CI ¼32.51–63.5, Q¼ 92, po 0.001)

with no evidence of publication bias (Egger: bias ¼4.545, p ¼0.29) (see Fig. 3). The pooled prevalence of migraine according to selfreport/ nonstandardized criteria among 2882 participants with bipolar disorder was 20.0% (95% CI ¼12.44–29.06, Q¼129, po 0.001, Egger: bias ¼0.369; p ¼0.97) which was significantly lower than the prevalence of migraine reported in studies using standardized criteria (z¼  8.40, p o0.0001). Refer to the forest plot depicted in Fig. 3 for further details.

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M. Fornaro, B. Stubbs / Journal of Affective Disorders 178 (2015) 88–97

Proportion meta analysis plot [random effects] Oedegaard KJ et al., (2005)

0.78 (0.71, 0.84)

Baptista T et al., (2012)

0.61 (0.53, 0.68)

Fasmer O.B. & Oedegaard K.J. (2001)

0.56 (0.45, 0.66)

Di lsaver SC et al., (2008)

0.54 (0.43, 0.65)

Fasmer O.B. (2001)

0.44 (0.25, 0.65)

Low NC et al., (2003)

0.40 (0.31, 0.50)

Mahmood T. et al., (1999)

0.26 (0.17, 0.37)

O rt iz A et al., (2010)

0.24 (0.20, 0.30)

c ombined

0.48 (0.33, 0.64) 0.0

0.2

0.4

0.6

0.8

1.0

proportion (95% confidence interval)

Fig. 3. Pooled prevalence of migraine comorbidity according to the International Headache Society criteria (1988 or 2004).

Regression of Logit event rate on Mean age

4.00 3.00

Logit event rate

2.00 1.00 0.00 -1.00 -2.00 -3.00 -4.00 -5.00 -6.00 10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

50.0

Mean age Fig. 4. Meta-regression analysis of mean age.

3.6. Meta-regression analyses In the exploratory meta regression analysis, there was a trend for mean age to moderate the prevalence of migraine among the entire sample (coefficient ¼ 0.0474, 95% CI  0.0972 to 0.0025, p ¼0.06, R2 ¼0.21, see Fig. 4). The percentage of males across the samples was not associated with the prevalence of migraine (coefficient  0.023, 95% CI  0.0689 to 0.0228, p ¼0.33, R2 ¼ 0). Refer to Fig. 4 for details. 3.7. Risk of bias within and across studies Comorbidities are best studied in representative samples because the prevalence of disease and the association among disorders may be sometimes altered in clinic-based samples or primary care settings (Wittchen et al., 1999). Also, a Berkson's bias leading to under-estimation (or over-estimation) of the rate of occurrence of

migraine–BD comorbidity may have occurred across the studies since most severe cases usually tend to seek medical care instead of participating in population-based studies instead of and this is seen more in clinic-based ones (Berkson, 1946). Moreover, incidence rates of a number of comorbid conditions increase with the frequency of migraine attacks, being higher for episodic vs. chronic migraine (Aamodt et al., 2007). An additional bias potentially often encountered in such studies and accounted for in this systematic review, especially retrospective ones, is recall bias, due to the chance of neglect or poor regard of some BD patients towards their own previous (hypo-)manic episodes, which may ultimately affect even the prevalence estimates actually documented for migraine–BD comorbidity itself. Furthermore, a gender-related publication bias may have been occurred due to the unrepresentativeness of females subjects (clearly) documented to be follicular phase of the menstrual cycle (Lay and Payne, 2007); similarly a potential confounding bias may be related to under-reported epileptic spikes eventually

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associated to some cases with migraine–BD comorbidity (Belcastro et al., 2013). The afore mentioned biases potentially occurring within the studies may also affect between-studies comparisons, especially due to the lack of clearly detectable effect sizes/z-scores in most of the selected studies. There is also inconsistency of the diagnostic criteria adopted for the definition of BD-II (sometimes broadened to include affective temperaments too) or IHS editions for the diagnosis of migraine, as well the inaccurate distinction between BD-I and BDII or specific types of migraines by some studies, especially in lowpowered and post-hoc studies.

4. Discussion The current meta-analysis is to our knowledge a first and established that overall approximately one third of people with BD are affected by comorbid migraine (34.8%, 955% CI¼25.54– 44.69, n¼3976). Of particular interest, we have established that higher prevalence of migraine exists among people with BD-II (54%) vs. those with BD-I (32.7%, po0.0001). Interestingly, we also established for the first time that the prevalence of migraine is substantially higher in studies utilizing recognized criteria (e.g. International headache society criteria, 47.9%) compared to non-standardized criteria such as self-report (20.0%, po0.0001). This may mean that studies that rely on non-standardized criteria to record migraine are underestimates and provide rationale for the need to employ recognized criteria to investigate migraines in people with BD with the ultimate goal to provide an early recognition and an early therapeutic management of BD–migraine comorbidity, whenever occurring. Also, the exploratory meta-regression analyses suggest that mean age may be an important moderator of migraine prevalence. The prevalence of migraine appears comparable in North America and Europe; yet the paucity of equivalent evidence in non-Western societies hinders the appreciation of a cultural-bias in the presentation and self-reported rates of migraine across different regions, if ever existing, therefore soliciting further comparative studies on the matter. Of particular importance, there was insufficient data to perform a meaningful comparative metaanalysis investigating migraine among people with BD and matched controls from the general population. 4.1. Migraine associated to BD-II: specific findings and related clinical implications Based on the main findings of the present meta-analytic summary, the prevalence of comorbid migraine among people with BD is remarkably high, particularly among people with BD II. This latter finding, though in line with a narrative review (Fornaro et al., 2015), acquires further clinical relevance nonetheless, especially considering that type-II BD is way more common in the outpatient setting compared to BD-I patients. Moreover, the onset of BD involves a major depressive episode (MDE) in approximately half of type-I (BD-I) patients, and three-quarters of those diagnosed with BD-II (Baldessarini et al., 2013; Goodwin and Jamison, 2007; Koukopoulos et al., 2013; Tondo et al., 2014), meaning that BD-II patients are at increased risk to receive a delayed diagnosis of BD-II rather MDD, despite relevant treatment implications associated to failure to promptly recognize BD in depressed patients include under-prescription of mood-stabilizers, an increased risk of rapid cycling, increased cost of care due to ineffective treatment and increased risk for suicide (Fornaro et al., 2015; Merikangas et al., 1993). In this respect, the present meta-analytic confirmation of a stronger association between migraine and BD-II vs. BD-I cases should ultimately pave the ground to novel quantitative comparative studies between MDD and BD-I vs. BD-II comorbid–migraine cases too, especially considering that most of the available reference

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still rely on unreliable comparisons, unrepresentative samples or on non-controlled, post-hoc reports (Fornaro et al., 2015). Furthermore, the results coming from the present quantitative synthesis highlighted the need for further studies focusing on migraine–BD-II comorbidity including well-matched control cases with or with-out rapid cycling features too. In fact, the only post-hoc evidence made recently available on the matter (Gordon-Smith et al., 2015) included a disproportionally high number of BD-I vs. BD-II cases, despite the overall, yet still debated, wisdom of a much more frequent occurring of “rapid cycling” being associated to BD-II rather than BD-I cases (Carvalho et al., 2014). As consequence, though acknowledged as a potential subtype of BD characterized by a more unstable course of illness requiring a patient-tailored therapeutic approach and potentially allowing more etiologically oriented studies on BD itself (Gordon-Smith et al., 2015), chances are that the actual prevalence of migraine associated to BD-II vs. BD-I rapid cycling cases should be even higher. 4.2. Migraine–BD comorbidity and subjective pain The present meta-analysis also confirmed the close association between subjective pain and migraine in BD patients, as we already outlined in a recent previous meta-analytic synthesis about the prevalence of pain in BD, pointing out high levels of associated chronic pain in most of the cases (Stubbs et al., 2015), a finding which also has major clinical implications considering that an increased self-perception of pain may ultimately undermine the adherence towards prescribed medications, particularly in BD-II patients, especially among those cases with high levels of somatic complaints (Fornaro et al., 2013, 2014). In our previous meta-analysis (Stubbs et al., 2015), data pooled regarding nonmigraines (e.g. headache) found a prevalence of 14% for migraine/ headache. In addition, whilst helpful, the previous review on pain and DB (Stubbs et al., 2015) did not set out to consider migraine specifically and its focus was on pain. Thus our results clarify the high prevalence of migraine in BD for the first time in a structured manner and have for the first time considered numerous subgroup analyses of the prevalence and moderators of migraine in this at risk population. Indeed, apart from clinical and epidemiological considerations, the putative neurobiological interface between pain (including reported migraine) and BD remains elusive. Future research is needed to consider this including possible common genetic polymorphisms. 4.3. Additional findings and major implication of the quantitative synthesis The comorbidity between migraine and BD was confirmed to be preferentially associated with an index episode of depression rather than mania (Brietzke et al., 2012) and with more overall depressive episodes vs. mania (Birgenheir et al., 2013), which may further increase the chance of receiving improper antidepressant monotherapies (Jette et al., 2008) rather than mood stabilizers including valproate (Oedegaard et al., 2011) or lithium (Low et al., 2003; Oedegaard et al., 2011). With respect to overall medical and psychiatric comorbidities, with the sole exception of the report by Low et al. (2003), evidence indicated a higher number of lifetime hospitalization and lower level of education and income (McIntyre et al., 2006; Nguyen and Low, 2013), as well as a higher prevalence of family history for BD in case of comorbid migraine (Dilsaver et al., 2009). Moreover, migraine may precede BD (Ortiz et al., 2010) and the somatic presentations may be a “first-visit hallmark” for some bipolar outpatients (Tavormina, 2011) especially in case of severe somatic pain (Birgenheir et al., 2013), thus urging attention considering the stigma still associated to BD worldwide, and that the evidence

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covered by the present review almost entirely focused on Western samples, thus precluding the appreciation of any pathoplastic differential effect of migraine on BD across cultures, if ever existing (Fornaro et al., 2009) despite the “legacy” of migraine spanning across different cultures and regions worldwide (Mandal, 2014). Finally, our results also suggest that studies relaying on selfreport and non-standardized criteria report lower prevalence of migraine. This necessitates the need for clinicians and researchers to endeavor to use recognized criteria to quantify migraine such as that provided by the International Headache society, with the ultimate goal of an earlier recognition and earlier adequate management of the comorbid cases of migraine and BD. Also, our quantitative synthesis confirmed the need for more methodologically rigorous studies, especially longitudinal ones, as well as the need for additional primary research involving migraine cases of rapid-cycling BD-II. 4.4. Study limitations Most of the limitations of the present meta-analysis (first of its kind at writing time) are intrinsically related to the potential biases of the included studies and should be taken into account in the interpretations of the results discussed herein. First, there was heterogeneity in the assessment of migraine and samples included within our meta-analysis. However, in line with the MOOSE guidelines, we attempted to negate this by conducting numerous subgroup analyses. Second, most of the studies were cross sectional. Therefore, future prospective research is required to better understand the relationship between BD and migraines. Third, there was often insufficient data to conduct moderation analyses on key variables such as medication, pain and depressive symptoms which all may influence the prevalence of migraine. Fourth, there was insufficient data to conduct a comparative meta-analysis comparing the prevalence of migraine among people with BD and matched general population controls. Future research should seek to make direct head to head comparisons to quantify the risk of migraine among people with BD. Nevertheless, allowing for these caveats the current meta-analysis is the first of its kind and offers a unique insight into the important issue of migraine among people with BD.

Role of funding source The authors have no funding source to disclose in conjunction with the present work.

Conflict of interest The authors have no conflict of interest, neither financial support to disclose in conjunction with the present work.

Acknowledgments None to state.

References Aamodt, A.H., Stovner, L.J., Langhammer, A., Hagen, K., Zwart, J.A., 2007. Is headache related to asthma, hay fever, and chronic bronchitis? The head-hunt study. Headache 47, 204–212. Abokrysha, N., 2009. Ibn Sina (Avicenna) on pathogenesis of migraine compared with the recent theories. Headache 49, 923–927. Akiskal, H.S., Mallya, G., 1987. Criteria for the “soft” bipolar spectrum: treatment implications. Psychopharmacol. Bull. 23, 68–73. APA, 1994. Diagnostic and Statistical Manual for Mental Disorders, Fourth Edition (DSM-IV). APA, Washington D.C., USA. Baldessarini, R.J., Faedda, G.L., Offidani, E., Vazquez, G.H., Marangoni, C., Serra, G., Tondo, L., 2013. Antidepressant-associated mood-switching and transition from unipolar major depression to bipolar disorder: a review. J. Affect. Disord. 148, 129–135.

Belcastro, V., Striano, P., Parisi, P., 2013. Interictal and periictal headache in patients with epilepsy: migraine-triggered seizures or epilepsy-triggered headache? Eur. J. Neurol. 20, 1333–1334. Berkson, J., 1946. Limitation of the application of fourfold table analysis to hospital data. Biom. Bull. 2, 47–53. Birgenheir, D.G., Ilgen, M.A., Bohnert, A.S., Abraham, K.M., Bowersox, N.W., Austin, K., Kilbourne, A.M., 2013. Pain conditions among veterans with schizophrenia or bipolar disorder. Gen. Hosp. Psychiatry 35, 480–484. Breitenfeld, T., Jurasic, M.J., Breitenfeld, D., 2014. Hippocrates: the forefather of neurology. Neurol. Sci. 35, 1349–1352. Breslau, N., Merikangas, K., Bowden, C.L., 1994. Comorbidity of migraine and major affective disorders. Neurology 44, S17–S22. Brietzke, E., Moreira, C.L., Duarte, S.V., Nery, F.G., Kapczinski, F., Miranda Scippa, A., Lafer, B., 2012. Impact of comorbid migraine on the clinical course of bipolar disorder. Compr. Psychiatry 53, 809–812. Carvalho, A.F., Dimellis, D., Gonda, X., Vieta, E., McLntyre, R.S., Fountoulakis, K.N., 2014. Rapid cycling in bipolar disorder: a systematic review. J. Clin. Psychiatry 75, e578–e586. DerSimonian, R., Laird, N., 1988. Meta-analysis in clinical trials. Control. Clin. Trials 7, 177–188. Di Florio, A., Forty, L., Gordon-Smith, K., Heron, J., Jones, L., Craddock, N., Jones, I., 2013. Perinatal episodes across the mood disorder spectrum. JAMA Psychiatry 70, 168–175. Dilsaver, S.C., Benazzi, F., Oedegaard, K.J., Fasmer, O.B., Akiskal, K.K., Akiskal, H.S., 2009. Migraine headache in affectively ill latino adults of mexican american origin is associated with bipolarity. Prim. Care Companion J. Clin. Psychiatry 11, 302–306. Fornaro, M., Clementi, N., Fornaro, P., 2009. Medicine and psychiatry in Western culture: ancient Greek myths and modern prejudices. Ann. Gen. Psychiatry 8, 21. Fornaro, M., De Berardis, D., De Pasquale, C., Indelicato, L., Pollice, R., Valchera, A., Perna, G., Iasevoli, F., Tomasetti, C., Martinotti, G., Koshy, A.S., Fasmer, O.B., Oedegaard, K.J., 2015. Prevalence and clinical features associated to bipolar disorder–migraine comorbidity: a systematic review. Compr. Psychiatry 56, 1–16. Fornaro, M., De Berardis, D., Iasevoli, F., Pistorio, M.L., D’Angelo, E., Mungo, S., Martino, M., Ventriglio, A., Cattaneo, C.I., Favaretto, E., Del Debbio, A., Romano, A., Ciampa, G., Elassy, M., Perugi, G., De Pasquale, C., 2013. Treatment adherence towards prescribed medications in bipolar-II acute depressed patients: relationship with cyclothymic temperament and “therapeutic sensation seeking” in response towards subjective intolerance to pain. J. Affect. Disord. 151, 596–604. Fornaro, M., De Berardis, D., Iasevoli, F., Pistorio, M.L., Emanuela, D.A., Mungo, S., Martino, M., Ventriglio, A., Cattaneo, C.I., Favaretto, E., Del Debbio, A., Romano, A., Ciampa, G., Elassy, M., Perugi, G., De Pasquale, C., 2014. Corrigendum to “treatment adherence towards prescribed medications in bipolar-II acute depressed patients: relationship with cyclothymic temperament and “therapeutic sensation seeking” in response towards subjective intolerance to pain” [J. Affect. Disord. 151 (2) (November 2013), 596–604]. J. Affect. Disord. 170C, 22. Fornaro, M., Perugi, G., 2010. The impact of premenstrual dysphoric disorder among 92 bipolar patients. Eur. Psychiatry 25, 450–454. Fu, L.K., 2002. Hua Tuo, the Chinese god of surgery. J. Med. Biogr. 10, 160–166. Goodwin, F.K., Jamison, K.R., 2007. Manic-Depressive Illness, second ed. Oxford University Press, New York, NY, pp. 122–123. Gordon-Smith, K., Forty, L., Chan, C., Knott, S., Jones, I., Craddock, N., Jones, L.A., 2015. Rapid cycling as a feature of bipolar disorder and comorbid migraine. J. Affect. Disord. 175C, 320–324. Headache Classification Subcommittee of the International Headache Society, 2004. The international classification of headache disorders 2nd edition. Cephalalgia 24 (Suppl 1), 9–160. Headache Classification Committee of the International Headache Society, 1988. Classification and diagnostic criteria for headache disorders, cranial neuralgias and facial pain. Headache Classification Committee of the International Headache Society. Cephalalgia 8 (Suppl 7), S1–S96. Holland, J., Agius, M., Zaman, R., 2011. Prevalence of co-morbid bipolar disorder and migraine in a regional hospital psychiatric outpatient department. Psychiatr. Danub. 23 (Suppl 1), S23–S24. Isler, H., 1992. The Galenic tradition and migraine. J. Hist. Neurosci. 1, 227–233. Jette, N., Patten, S., Williams, J., Becker, W., Wiebe, S., 2008. Comorbidity of migraine and psychiatric disorders—a national population-based study. Headache 48, 501–516. Karenberg, A., Leitz, C., 2001. Headache in magical and medical papyri of ancient Egypt. Cephalalgia 21, 911–916. Koehler, P.J., van de Wiel, T.W., 2001. Aretaeus on migraine and headache. J. Hist. Neurosci. 10, 253–261. Koukopoulos, A., Reginaldi, D., Tondo, L., Visioli, C., Baldessarini, R.J., 2013. Course sequences in bipolar disorder: depressions preceding or following manias or hypomanias. J. Affect. Disord. 151, 105–110. Lay, C.L., Payne, R., 2007. Recognition and treatment of menstrual migraine. Neurologist 13, 197–204. Low, N.C., Du Fort, G.G., Cervantes, P., 2003. Prevalence, clinical correlates, and treatment of migraine in bipolar disorder. Headache 43, 940–949. Mandal, M., 2014. Migraine History. URL: http://www.news-medical.net/health/ Migraine-History.aspx. McGauran, N., Wieseler, B., Kreis, J., Schuler, Y.B., Kolsch, H., Kaiser, T., 2010. Reporting bias in medical research—a narrative review. Trials 11, 37. McIntyre, R.S., Konarski, J.Z., Soczynska, J.K., Wilkins, K., Panjwani, G., Bouffard, B., Bottas, A., Kennedy, S.H., 2006. Medical comorbidity in bipolar disorder:

M. Fornaro, B. Stubbs / Journal of Affective Disorders 178 (2015) 88–97

implications for functional outcomes and health service utilization. Psychiatr. Serv. 57, 1140–1144. Merikangas, K.R., Angst, J., Isler, H., 1990. Migraine and psychopathology. Results of the Zurich cohort study of young adults. Arch. Gen. Psychiatry 47, 849–853. Merikangas, K.R., Merikangas, J.R., Angst, J., 1993. Headache syndromes and psychiatric disorders: association and familial transmission. J. Psychiatr. Res. 27, 197–210. Munoli, R.N., Praharaj, S.K., Sharma, P.S., 2014. Co-morbidity in bipolar disorder: a retrospective study. Indian J. Psychol. Med. 36, 270–275. Moher, D., Liberati, A., Tetzlaff, J., Altman, D.G., Group, P., 2009. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 6, e1000097. Nguyen, T.V., Low, N.C., 2013. Comorbidity of migraine and mood episodes in a nationally representative population-based sample. Headache 53, 498–506. Oedegaard, K.J., Riise, T., Dilsaver, S.C., Lund, A., Akiskal, H.S., Fasmer, O.B., Hundal, O., 2011. A pharmaco-epidemiological study of migraine and antidepressant medications: complete one year data from the Norwegian population. J. Affect. Disord. 129, 198–204. Omrani, A., Holtzman, N.S., Akiskal, H.S., Ghaemi, S.N., 2012. Ibn Imran's 10th century treatise on melancholy. J. Affect. Disord. 141, 116–119. Ortiz, A., Cervantes, P., Zlotnik, G., van de Velde, C., Slaney, C., Garnham, J., Turecki, G., O’Donovan, C., Alda, M., 2010. Cross-prevalence of migraine and bipolar disorder. Bipolar Disord. 12, 397–403. Saunders, E., Nazir, R., Kamali, M., Ryan, K., Evans, S., Langenecker, S., Gelenberg, A., McInnis, G., 2014. Gender differences, clinical correlates, and longitudinal outcome of bipolar disorder with comorbid migraine. J. Clin. Psychiatry 75, 512–519.

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Stroup, D.F., Berlin, J.A., Morton, S.C., Olkin, I., Williamson, G.D., Rennie, D., Moher, D., Becker, B.J., Sipe, T.A., Thacker, S.B., 2000. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis of observational studies in epidemiology (MOOSE) group. J. Am. Med. Assoc. 283, 2008–2012. Stubbs, B., Eggermont, L., Mitchell, A.J., De Hert, M., Correll, C.U., Soundy, A., Rosenbaum, S., Vancampfort, D., 2015. The prevalence of pain in bipolar disorder: a systematic review and large-scale meta-analysis. Acta Psychiatr. Scand. 131, 75–88. Sylvia, L.G., Shesler, L.W., Peckham, A.D., Grandin, T., Kahn, D.A., 2014. Adjunctive deep touch pressure for comorbid anxiety in bipolar disorder: mediated by control of sensory input? J. Psychiatr. Pract. 20, 71–77. Tavormina, G., 2011. Are somatisation symptoms important evidence for an early diagnosis of bipolar spectrum mood disorders? Psychiatr. Danub. 23 (Suppl 1), S13–S14. Tondo, L., Visioli, C., Preti, A., Baldessarini, R.J., 2014. Bipolar disorders following initial depression: modeling predictive clinical factors. J. Affect. Disord. 167, 44–49. WHO, 2010. International Statistical Classification of Diseases and Related Health Problems, Tenth Edition (ICD-10). WHO, Geneve, Switzerland. Wittchen, H.U., Lieb, R., Wunderlich, U., Schuster, P., 1999. Comorbidity in primary care: presentation and consequences. J. Clin. Psychiatry 60 (Suppl 7), S29–S36, discussion 37-28.