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Mirror, Mirror On the Wall: What effectiveness research shows us about headache care
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PAIN 152 (2011) 1695–1696
www.elsevier.com/locate/pain
Commentary
Mirror, Mirror On the Wall: What effectiveness research shows us about headache care The challenge of integrating the newest interventions, procedures, and devices and applying them to a varied and complex patient population is indeed a part of what makes working in the pain and headache field both artful and rewarding. However, the greatest challenge may be to look into the mirror and reflecting on the fact that we are not as effective as we would hope to be. So how do you measure the effectiveness or outcomes of your clinic? Some say the complexity of defining and measuring outcomes in a mixed population of disorders and treatments is not possible, but the ability to name our successes and identify opportunities for improvement would both affirm what we do well and provide greater attention to areas requiring improvement. The emerging field of Comparative Effectiveness Research (CER) promises to facilitate direct comparisons of competing treatment forms, in an efficient manner, and to use this evidence to influence quickly health care delivery decisions. Posing the rising cost of health care as a threat to national economic health, the Obama administration has designated $1.1 billion of funds for CER, and recent national health care reform legislated the creation of a Patient-Centered Outcomes Research Institute to guide the immediate expansion of CER research. In this issue of PAIN, Lewis and colleagues used complex statistical methods to look at treatment outcomes in a headache subspecialty clinic [4]. This clinic operated under a medical model, focused on the diagnosis of primary headache disorders and the treatment of frequent or severe headache with acute abortive and long-term prophylactic medications. The most commonly prescribed prophylactics were tricyclics and anticonvulsants, with beta-blockers, other antidepressants, and calcium channel blockers as other options. The likely agents vary among headache centers, and they have changed over time, but they are probably similar to the prescribing patterns of most headache subspecialty clinics. The authors draw upon the broad field of growth models, and in particular, a special case of Latent Curve Analysis, known as Growth Mixture Modeling (GMM). The origins of this relatively new method are in the developmental and social sciences, where researchers are often interested in how individuals change over time, and in describing and understanding the heterogeneity of change. The overall goals of this methodology are to identify previously unknown (that is, latent) groups based upon the outcomes (or trajectories) of the individual members, describe the longitudinal patterns within each group, and to allow for examination of group differences [2]. The iterative numerical estimation methods employed to obtain parameter estimates and individual group membership probabilities are numerically complex and require special software. Empirically, GMM has thus far been applied
sparingly, but the technique is becoming more commonly used as practice catches up to methodological advancements [6]. The first key step in this methodology is to determine how many trajectory groups (if any) are present in the sample. Among the 1-, 2-, and 3-group scenarios considered, the authors conclude that the 3 trajectory group model was the best fit (despite their hypothesis that the two-group model would be best). Once the authors determined the three different treatment trajectories, they labeled the groups by their clinical characteristics. The criteria for inclusion into the clinical categories could be debated, but the clinical descriptors are mostly self-explanatory. Their relative proportions are interesting. There are the High Disability Improvers (11%), the High Disability non-improvers (34%), and the Moderate Disability Improvers (55%). For the last group, it is reassuring that for the most part those who are concerned about their headaches, but are relatively well, are likely to improve somewhat, but the numbers reflect a rather modest gain. However, among those with high disability, there is only a small proportion where subspecialty headache care had a meaningful impact. The authors used a relatively new and exploratory methodology that has not yet been widely applied to pain research, and the methods should certainly be repeated with more current data from other clinics to see if comparable results can be replicated and generalized to a wider population. But with all those qualifications it is worth reflecting on the factors associated with the apparent modest effect that was measured in this study. To do so steps outside of the realm of the present study, but it is worthwhile to reflect upon these factors [5]. So why does subspecialty headache care have such a low measured effectiveness? The first answer is that patients referred to headache subspecialty clinic are difficult to treat, having already failed the first or second lines of treatment. The second answer is that the medical model described here does not go far enough. Patients with high disability from headache have a complex mix of risk factors and medication overuse histories, so that the addition of a prophylactic agent may only have an incremental effect. For these patients, an expanded range of interventions, including inpatient hospitalization and intravenous infusions, and localized pain interventions may be more likely to have a game-changing impact on the condition [3]. One caution to the generality of these findings is the narrow range of diagnoses observed in the study. Among the 219 patients in the sample, 211 received the diagnosis of some combination of migraine or tension-type headache. Only 1 patient had a primary diagnosis of ‘‘other,’’ which by exclusion would have to include the diagnoses of cluster headache, a group of trigeminal autonomic cephalalgias characterized by their responsiveness to indomethacin,
0304-3959/$36.00 Ó 2011 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved. doi:10.1016/j.pain.2011.03.009
1696
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Commentary / PAIN 152 (2011) 1695–1696
and several other diagnoses with distinct and effective treatment strategies, such as hypnic headache, cough headache, and spontaneous intracranial hypotension. The narrow range of diagnoses may reflect the relatively small sample size used to conduct the study, but their absence from even a sample this size is a concern [8]. For those who present to subspecialty care with one of these uncommon but disabling disorders, the impact of receiving a specific diagnosis and the highly effective treatment associated with it is dramatic. Finally, the concept of advanced headache care would be incomplete without going beyond the purely medical model represented in this study [1]. An interdisciplinary model would identify and treat many relevant risk factors for chronic headache, incorporating a range of skills that involve alterations in lifestyle and outlook. Because these alterations are typically more challenging than medical prophylaxis, successful treatment requires multiple disciplines to work closely [7], and can include physical therapy, nutrition, psychology, psychiatry, otolaryngology, endodontic dentistry, sleep medicine, gynecology, pain medicine, and neurosurgery. Though uncommon, various versions of comprehensive, interdisciplinary headache care do exist and deliver excellent results [3]. Although we can measure and compare the effectiveness of currently available approaches, it is always worth considering more integrated interdisciplinary interventions, if that is what is required. Conflict of interest statement The authors declare that they have no conflicts of interest.
References [1] Biondi DM. Physical treatments for headache: a structured review. Headache 2005;45:738–76. [2] Grimm KJ, Ram N. A second-order growth mixture model for developmental research. Res Human Dev 2009;6:121–43. [3] Lake AE, Saper JR, Hamel RL. Comprehensive inpatient treatment of refractory chronic daily headache. Headache 2009;49:555–62. [4] Lewis KN, Heckman BD, Himawan L. Multimodal logistic regression analysis for differentiating 3 treatment outcome trajectory groups for headache-associated disability. Pain 2011;152:1718–26. [5] Lipton RB, Silberstein SD, Saper JR, Bigal ME, Goadsby PJ. Why headache treatment fails. Neurology 2003;60:1064–70. [6] Nagin DS, Odgers CL. Group-based trajectory modeling in clinical research. Annu Rev Clin Psychol 2010;6:109–38. [7] Nicholson RA, Buse DC, Andrasik F, Lipton RB. Nonpharmacologic treatments for migraine and tension-type headache: how to choose and when to use. Curr Treat Options Neurol 2011;13:28–40. [8] Robbins MS, Lipton RB. The epidemiology of primary headache disorders. Semin Neurol 2010;30:107–19.
Andrew H. Ahn Department of Neurology and Neuroscience, University of Florida College of Medicine 100 S. Newell Dr., Box 100236, Gainesville, FL 32610, USA Tel.: +1 352 273 9526; fax: +1 352 273 5575 E-mail address: [email protected]fl.edu John A. Kairalla Department of College of Medicine, and Biostatistics, University of Florida Colleges of Medicine and Public Health & Health Professions, Gainesville, Florida, USA
PAIN 152 (2011) 1695–1696
www.elsevier.com/locate/pain
Commentary
Mirror, Mirror On the Wall: What effectiveness research shows us about headache care The challenge of integrating the newest interventions, procedures, and devices and applying them to a varied and complex patient population is indeed a part of what makes working in the pain and headache field both artful and rewarding. However, the greatest challenge may be to look into the mirror and reflecting on the fact that we are not as effective as we would hope to be. So how do you measure the effectiveness or outcomes of your clinic? Some say the complexity of defining and measuring outcomes in a mixed population of disorders and treatments is not possible, but the ability to name our successes and identify opportunities for improvement would both affirm what we do well and provide greater attention to areas requiring improvement. The emerging field of Comparative Effectiveness Research (CER) promises to facilitate direct comparisons of competing treatment forms, in an efficient manner, and to use this evidence to influence quickly health care delivery decisions. Posing the rising cost of health care as a threat to national economic health, the Obama administration has designated $1.1 billion of funds for CER, and recent national health care reform legislated the creation of a Patient-Centered Outcomes Research Institute to guide the immediate expansion of CER research. In this issue of PAIN, Lewis and colleagues used complex statistical methods to look at treatment outcomes in a headache subspecialty clinic [4]. This clinic operated under a medical model, focused on the diagnosis of primary headache disorders and the treatment of frequent or severe headache with acute abortive and long-term prophylactic medications. The most commonly prescribed prophylactics were tricyclics and anticonvulsants, with beta-blockers, other antidepressants, and calcium channel blockers as other options. The likely agents vary among headache centers, and they have changed over time, but they are probably similar to the prescribing patterns of most headache subspecialty clinics. The authors draw upon the broad field of growth models, and in particular, a special case of Latent Curve Analysis, known as Growth Mixture Modeling (GMM). The origins of this relatively new method are in the developmental and social sciences, where researchers are often interested in how individuals change over time, and in describing and understanding the heterogeneity of change. The overall goals of this methodology are to identify previously unknown (that is, latent) groups based upon the outcomes (or trajectories) of the individual members, describe the longitudinal patterns within each group, and to allow for examination of group differences [2]. The iterative numerical estimation methods employed to obtain parameter estimates and individual group membership probabilities are numerically complex and require special software. Empirically, GMM has thus far been applied
sparingly, but the technique is becoming more commonly used as practice catches up to methodological advancements [6]. The first key step in this methodology is to determine how many trajectory groups (if any) are present in the sample. Among the 1-, 2-, and 3-group scenarios considered, the authors conclude that the 3 trajectory group model was the best fit (despite their hypothesis that the two-group model would be best). Once the authors determined the three different treatment trajectories, they labeled the groups by their clinical characteristics. The criteria for inclusion into the clinical categories could be debated, but the clinical descriptors are mostly self-explanatory. Their relative proportions are interesting. There are the High Disability Improvers (11%), the High Disability non-improvers (34%), and the Moderate Disability Improvers (55%). For the last group, it is reassuring that for the most part those who are concerned about their headaches, but are relatively well, are likely to improve somewhat, but the numbers reflect a rather modest gain. However, among those with high disability, there is only a small proportion where subspecialty headache care had a meaningful impact. The authors used a relatively new and exploratory methodology that has not yet been widely applied to pain research, and the methods should certainly be repeated with more current data from other clinics to see if comparable results can be replicated and generalized to a wider population. But with all those qualifications it is worth reflecting on the factors associated with the apparent modest effect that was measured in this study. To do so steps outside of the realm of the present study, but it is worthwhile to reflect upon these factors [5]. So why does subspecialty headache care have such a low measured effectiveness? The first answer is that patients referred to headache subspecialty clinic are difficult to treat, having already failed the first or second lines of treatment. The second answer is that the medical model described here does not go far enough. Patients with high disability from headache have a complex mix of risk factors and medication overuse histories, so that the addition of a prophylactic agent may only have an incremental effect. For these patients, an expanded range of interventions, including inpatient hospitalization and intravenous infusions, and localized pain interventions may be more likely to have a game-changing impact on the condition [3]. One caution to the generality of these findings is the narrow range of diagnoses observed in the study. Among the 219 patients in the sample, 211 received the diagnosis of some combination of migraine or tension-type headache. Only 1 patient had a primary diagnosis of ‘‘other,’’ which by exclusion would have to include the diagnoses of cluster headache, a group of trigeminal autonomic cephalalgias characterized by their responsiveness to indomethacin,
0304-3959/$36.00 Ó 2011 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved. doi:10.1016/j.pain.2011.03.009
1696
Ò
Commentary / PAIN 152 (2011) 1695–1696
and several other diagnoses with distinct and effective treatment strategies, such as hypnic headache, cough headache, and spontaneous intracranial hypotension. The narrow range of diagnoses may reflect the relatively small sample size used to conduct the study, but their absence from even a sample this size is a concern [8]. For those who present to subspecialty care with one of these uncommon but disabling disorders, the impact of receiving a specific diagnosis and the highly effective treatment associated with it is dramatic. Finally, the concept of advanced headache care would be incomplete without going beyond the purely medical model represented in this study [1]. An interdisciplinary model would identify and treat many relevant risk factors for chronic headache, incorporating a range of skills that involve alterations in lifestyle and outlook. Because these alterations are typically more challenging than medical prophylaxis, successful treatment requires multiple disciplines to work closely [7], and can include physical therapy, nutrition, psychology, psychiatry, otolaryngology, endodontic dentistry, sleep medicine, gynecology, pain medicine, and neurosurgery. Though uncommon, various versions of comprehensive, interdisciplinary headache care do exist and deliver excellent results [3]. Although we can measure and compare the effectiveness of currently available approaches, it is always worth considering more integrated interdisciplinary interventions, if that is what is required. Conflict of interest statement The authors declare that they have no conflicts of interest.
References [1] Biondi DM. Physical treatments for headache: a structured review. Headache 2005;45:738–76. [2] Grimm KJ, Ram N. A second-order growth mixture model for developmental research. Res Human Dev 2009;6:121–43. [3] Lake AE, Saper JR, Hamel RL. Comprehensive inpatient treatment of refractory chronic daily headache. Headache 2009;49:555–62. [4] Lewis KN, Heckman BD, Himawan L. Multimodal logistic regression analysis for differentiating 3 treatment outcome trajectory groups for headache-associated disability. Pain 2011;152:1718–26. [5] Lipton RB, Silberstein SD, Saper JR, Bigal ME, Goadsby PJ. Why headache treatment fails. Neurology 2003;60:1064–70. [6] Nagin DS, Odgers CL. Group-based trajectory modeling in clinical research. Annu Rev Clin Psychol 2010;6:109–38. [7] Nicholson RA, Buse DC, Andrasik F, Lipton RB. Nonpharmacologic treatments for migraine and tension-type headache: how to choose and when to use. Curr Treat Options Neurol 2011;13:28–40. [8] Robbins MS, Lipton RB. The epidemiology of primary headache disorders. Semin Neurol 2010;30:107–19.
Andrew H. Ahn Department of Neurology and Neuroscience, University of Florida College of Medicine 100 S. Newell Dr., Box 100236, Gainesville, FL 32610, USA Tel.: +1 352 273 9526; fax: +1 352 273 5575 E-mail address: [email protected]fl.edu John A. Kairalla Department of College of Medicine, and Biostatistics, University of Florida Colleges of Medicine and Public Health & Health Professions, Gainesville, Florida, USA