Rethinking headache chronification

Deep and unbiased proteomics, pathway enrichment analysis, and protein-protein interaction of biomarker signatures in migraine

Background

Currently, there are no biomarkers for migraine.

Objectives

We aimed to identify proteomic biomarker signatures for diagnosing, subclassifying, and predicting treatment response in migraine.

Design

This is a cross-sectional and longitudinal study of untargeted serum and cerebrospinal fluid (CSF) proteomics in episodic migraine (EM; n = 26), chronic migraine (CM; n = 26), and healthy controls (HC; n = 26).

Methods

We developed classification models for biomarker identification and natural clusters through unsupervised classification using agglomerative hierarchical clustering (AHC). Pathway analysis of differentially expressed proteins was performed.

Results

Of 405 CSF proteins, the top five proteins that discriminated between migraine patients and HC were angiotensinogen, cell adhesion molecule 3, immunoglobulin heavy variable (IGHV) V-III region JON, insulin-like growth factor binding protein 6 (IGFBP-6), and IGFBP-7. The top-performing classifier demonstrated 100% sensitivity and 75% specificity in differentiating the two groups. Of 229 serum proteins, the top five proteins in classifying patients with migraine were immunoglobulin heavy variable 3-74 (IGHV 3-74), proteoglycan 4, immunoglobulin kappa variable 3D-15, zinc finger protein (ZFP)-814, and mediator of RNA polymerase II transcription subunit 12. The best-performing classifier exhibited 94% sensitivity and 92% specificity. AHC separated EM, CM, and HC into distinct clusters with 90% success. Migraine patients exhibited increased ZFP-814 and calcium voltage-gated channel subunit alpha 1F (CACNA1F) levels, while IGHV 3-74 levels decreased in both cross-sectional and longitudinal serum analyses. ZFP-814 remained upregulated during the CM-to-EM reversion but was suppressed when CM persisted. CACNA1F was pronounced in CM persistence. Pathway analysis revealed immune, coagulation, glucose metabolism, erythrocyte oxygen and carbon dioxide exchange, and insulin-like growth factor regulation pathways.

Conclusion

Our data-driven study provides evidence for identifying novel proteomic biomarker signatures to diagnose, subclassify, and predict treatment responses for migraine. The dysregulated biomolecules affect multiple pathways, leading to cortical spreading depression, trigeminal nociceptor sensitization, oxidative stress, blood-brain barrier disruption, immune response, and coagulation cascades.

Trial registration

NCT03231241, ClincialTrials.gov.

Reductions in acute medication use and healthcare resource utilization in patients with chronic migraine: a secondary analysis of a phase 3, randomized, double-blind, placebo-controlled study of galcanezumab with open-label extension (REGAIN)

AIMS

To analyze secondary objectives of the REGAIN study related to acute headache medication use and healthcare resource utilization (HCRU) in patients with chronic migraine treated with galcanezumab, a monoclonal antibody to calcitonin gene-related peptide.

METHODS

Adults with chronic migraine (N = 1,113) were randomized (2:1:1) and treated with double-blind monthly injections of placebo, galcanezumab-120 mg, or galcanenzumab-240 mg for 3 months, followed by a 9-month open-label extension with 120 or 240 mg/month galcanezumab. Headache and medication information was collected by daily eDiary. HCRU was reported for the 6 months before randomization, monthly thereafter, and converted to rate per 100-patient-years.

RESULTS

At baseline, 63-64% of patients met criteria for acute headache medication overuse. At Month 3, incidence of headache medication overuse in the galcanezumab groups (33% and 33%) was significantly lower than in the placebo group (46%, both p < .001) and was 16% and 23% in the previous-galcanezumab groups at Month 12. From a baseline of 14.5 to 15.5, reduction in mean number of monthly migraine headache days with acute headache medication use was also significantly greater in the galcanezumab groups at Month 3 (-4.2 and -4.9) than in placebo (-2.6, both p < .001), with reductions of -6.8 and -7.6 in the previous-galcanezumab groups at Month 12. Migraine-specific HCRU rates decreased for all groups, with no significant between-group differences at Month 3. At Month 12, in the two previous-galcanezumab groups, emergency room visits decreased by 58% and 75%, hospital admissions by 100%, and healthcare professional visits by 54% and 67%.

LIMITATIONS

Only 3 months of double-blind, placebo-controlled data, a longer HCRU recall period for baseline than postbaseline, and patients receiving care in the clinical trial itself, may limit generalizability.

CONCLUSIONS

Treatment with galcanezumab resulted in significant reductions in headache medication overuse and migraine headache days requiring acute medication use, with notable reductions in migraine-specific HCRU.

Continuous updating of individual headache forecasting models using Bayesian methods

OBJECTIVE

To illustrate the benefits of deploying individual headache forecasting models using continuous updating with Bayesian methods.

BACKGROUND

The ability to reliably forecast headache attacks within an individual over time would enhance the study of attacks and allow preemptive treatment. However, deploying a suitable forecasting model in a clinical setting will likely involve several unique challenges related to heterogeneity in the predictor weights, limited or sparse data, and the need for a quick "warm-up." The use of Bayesian methods offers solutions to each of these specific challenges.

METHODS

This was a post hoc analysis of a cohort study of individuals with episodic migraine attacks. Individuals completed daily diaries that allowed the estimation of several forecasting models, each using different types of ancillary information incorporated into formal prior probability distributions. An in silico analysis was conducted that mimicked the deployment of these models in a clinical-like setting where the parameters of the models were continuously updated and evaluated each day using root mean square error (RMSE).

RESULTS

Individuals (N = 95) were followed for 50 days and contributed 3359 days of nonmissing diary data. During the observation period, there were 1293/3359 (38.5%) days with a headache attack. Self-reported baseline headache frequency was associated with the corresponding predicted probability of future attacks, r = 0.15-0.39. At Day 25, the correlation between baseline information and predicted attack likelihood was r = 0.29 (95% CI: 0.09-0.47). Additionally, the use of prior probability distributions for model parameters improved the model fit, especially early in the deployment of the models (e.g., Day 5 RMSE 0.45 vs. 0.43). Models using informative prior probability distributions outperformed the models estimated without this information during the first 42 days of observation, although performance became more similar as more data were collected.

CONCLUSIONS

This analysis demonstrates the value of Bayesian methods in using additional available information to improve forecasting model performance, especially early in the deployment of a forecasting model. To obtain the full value of such models or to apply any model in clinical settings, a model with adequate discrimination and calibration will be needed.

Neuroimaging features of whole-brain functional connectivity predict attack frequency of migraine

Migraine is a chronic neurological disorder characterized by attacks of moderate or severe headache accompanying functionally and structurally maladaptive changes in brain. As the headache days/month is often measured by patient self‐report and tends to be overestimated than actually experienced, the possibility of using neuroimaging data to predict migraine attack frequency is of great interest. To identify neuroimaging features that could objectively evaluate patients' headache days, a total of 179 migraineurs were recruited from two data center with one dataset used as the training/test cohort and the other used as the validating cohort. The guidelines for controlled trials of prophylactic treatment of chronic migraine in adults were used to identify the frequency of attacks and migraineurs were divided into low (MOl) and high (MOh) subgroups. Whole‐brain functional connectivity was used to build multivariate logistic regression models with model iteration optimization to identify MOl and MOh. The best model accurately discriminated MOh from MOl with AUC of 0.91 (95%CI [0.86, 0.95]) in the training/test cohort and 0.79 in the validating cohort. The discriminative features were mainly located within the limbic lobe, frontal lobe, and temporal lobe. Permutation tests analysis demonstrated that the classification performance of these features was significantly better than chance. Furthermore, the indicator of functional connectivity had a higher odds ratio than behavioral variables with implementing a holistic regression analysis. The current findings suggested that the migraine attack frequency could be distinguished by using machine‐learning algorithms, and highlighted the role of brain functional connectivity in revealing underlying migraine‐related neurobiology.

Predictors of episodic migraine transformation to chronic migraine: A systematic review and meta-analysis of observational cohort studies

BACKGROUND AND PURPOSE

An estimated 2.5-3.1% of people with episodic migraine develop chronic migraine in a year. Several risk factors are associated with an increased risk for this transformation. We conducted a systematic review and meta-analysis to provide quantitative and qualitative data on predictors of this transformation.

METHODS

An electronic search was conducted for published, prospective, cohort studies that reported risk factors for chronic migraine among people with episodic migraine. Risk of bias was assessed using the Newcastle-Ottawa Quality Assessment Scale. Quality of evidence was determined according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) guidelines. Effect estimates were retrieved and summarized using risk ratios.

RESULTS

Of 5695 identified publications, 11 were eligible for inclusion. The pooled analysis (GRADE system) found "high" evidence for monthly headache day frequency ≥ 10 (risk ratio = 5.95), "moderate" evidence for depression (risk ratio = 1.58), monthly headache day frequency ≥ 5 (risk ratio = 3.18), and annual household income ≥ $50,000 (risk ratio = 0.65) and "very low" evidence for allodynia (risk ratio = 1.40) and medication overuse (risk ratio = 8.82) in predicting progression to chronic migraine.

CONCLUSIONS

High frequency episodic migraine and depression have high quality evidence as predictors of the transformation from episodic migraine to chronic migraine, while annual household income over $50,000 may be protective.

Extracranial Trigger Site Surgery for Migraine: A Systematic Review With Meta-Analysis on Elimination of Headache Symptoms

Introduction: The headache phase of migraine could in selected cases potentially be treated by surgical decompression of one or more “trigger sites,” located at frontal, temporal, nasal, and occipital sites. This systematic review with subsequent meta-analysis aims at critically evaluating the currently available evidence for the surgical treatment of migraine headache and to determine the effect size of this treatment in a specific patient population.

Methods: This study was conducted following the PRISMA guidelines. An online database search was performed. Inclusion was based on studies published between 2000 and March 2018, containing a diagnosis of migraine in compliance with the classification of the International Headache Society. The treatment must consist of one or more surgical procedures involving the extracranial nerves and/or arteries with outcome data available at minimum 6 months.

Results: Eight hundred and forty-seven records were identified after duplicates were removed, 44 full text articles were assessed and 14 records were selected for inclusion. A total number of 627 patients were included in the analysis. A proportion of 0.38 of patients (random effects model, 95% CI [0.30–0.46]) experienced elimination of migraine headaches at 6–12 months follow-up. Using data from three randomized controlled trials, the calculated odds ratio for 90–100% elimination of migraine headaches is 21.46 (random effects model, 95% CI [5.64–81.58]) for patients receiving migraine surgery compared to sham or no surgery.

Conclusions: Migraine surgery leads to elimination of migraine headaches in 38% of the migraine patients included in this review. However, more elaborate randomized trials are needed with transparent reporting of patient selection, medication use, and surgical procedures and implementing detailed and longer follow-up times.

Migraine Progression: A Systematic Review

BACKGROUND

Migraine is a common and often debilitating neurological disease. It can be divided into episodic and chronic subforms based on the number of monthly headache days. Because only a subset of individuals with episodic migraine (EM) progress to chronic migraine (CM) over any given time period, understanding the factors that predict the new onset of CM or "migraine progression" may provide insights into the mechanisms, pathophysiology, prevention, and treatment of CM. In this review, we identify and summarize studies that report risk factors associated with the new onset of CM or related chronic headache diagnoses, group these risk factors and report the strength of evidence for the identified risk factors.

OBJECTIVE

To conduct a systematic review of studies that identify risk factors for the new onset of CM or related chronic headache diagnoses such as transformed migraine (TM) and chronic daily headache (CDH).

METHODS

Herein we summarize the findings of studies of risk factors associated with the new onset of CM/TM, CDH, or related diagnoses from the English language literature published before March 2018. The PubMed database was searched for relevant studies. Longitudinal studies with follow-up data and case-control studies were included in this qualitative synthesis. We report methodology, analytic criteria, and results for each manuscript and for the parent study. Next, we review the strength of evidence for each of the identified risk factors using a modified version of AB Hill's criteria for causation and rank evidence as fair, moderate, or strong. We categorized risk factors as nonmodifiable, modifiable and based on putative mechanisms. We further categorized risk factors into sociodemographics, lifestyle factors and habits, headache features, comorbid and concomitant diseases and conditions and pharmacologic treatment-related. Finally, we review theories of the pathophysiology underlying the development of new onset chronic migraine or increasing attack frequency.

RESULTS

The PubMed search yielded 1870 records after duplicates were removed. Nine additional records were identified through expert consultation and other methods (eg, citations found as references in manuscripts identified in the literature review and through communication with the authors of manuscripts included in the review). The 1879 manuscripts were screened against the inclusion and exclusion criteria and 109 were found to be potentially eligible. Of 109 full-text articles, 17 studies were identified as meeting the prespecified criteria based on the consensus of all authors. Of the 17 full texts, 13 were longitudinal cohort studies and 4 were case-controlled studies. We found strength of evidence ranging from fair to strong for the identified risk factors. The strongest data were found for increased headache day frequency, depression, and medication overuse/high-frequency use. Risk factors for new onset CM and CDH in children and adolescents were similar to those identified in adults.

CONCLUSIONS

A range of risk factors for the new onset of CM/TM, CDH, or related chronic headache diseases were identified with the strongest data supporting increased headache day frequency, acute medication overuse/high-frequency use and depression, which are potentially modifiable risk factors. Modifiable risk factors may provide targets for intervention. The lack of strong evidence or any evidence does not imply that there is not a relationship between a particular risk factor and new onset CM or related disease; but may indicate little or no research or that research did not have sufficient methodological rigor. In addition, it is likely that additional risk factors exist which have not yet been identified. Putative factors include pro-inflammatory states and pro-thrombotic states. Development of central sensitization and increased activation of the trigeminal nociceptive pathways may be drivers of the new onset of CM or CDH. Future research may include the systematic testing of interventions targeting modifiable risk factors to determine if progression can be prevented as well as continued exploration of the benefits of treating these risk factors among people with CM in an effort to increase rates of remission. Future work should also consider the natural fluctuations in headache day frequency and examine progression in terms of continuous definitions rather than or in addition to a dichotomous boundary.

Analysis of Initial Nonresponders to Galcanezumab in Patients With Episodic or Chronic Migraine: Results From the EVOLVE-1, EVOLVE-2, and REGAIN Randomized, Double-Blind, Placebo-Controlled Studies

OBJECTIVE

To examine the likelihood of response with continued galcanezumab treatment in patients with episodic or chronic migraine without initial clinical improvement.

BACKGROUND

A percentage of patients with migraine may require additional time on pharmacotherapy but discontinue treatment prematurely. Additionally, recognizing when continued treatment is unlikely to provide improvement limits unnecessary exposure.

METHODS

Post hoc analysis of response after continued galcanezumab treatment was conducted in a subset of patients with episodic (N = 879) and chronic (N = 555) migraine who did not achieve "good" early improvement (episodic, ≥50% reduction in baseline migraine headache days [MHD] and chronic, ≥30% reduction) after 1 month of dosing (NR-1; episodic, n = 450 and chronic, n = 306). This subset was categorized by level of reduction in MHD during 1 month of treatment: "modest" (>30% to <50% fewer MHD for episodic and >10% to <30% fewer MHD for chronic), "limited" (episodic only; >10% to ≤30% fewer MHD), or "minimal/no" early improvement (≤10% fewer MHD to ≤10% more MHD), or "worsening" (>10% more MHD). The percentages of patients having "better" (≥75% fewer MHD for episodic and ≥50% for chronic), "good," or "little-to-no" (≤10% fewer MHD) response during the remaining treatment period were calculated for each category. Similarly, the subset of NR-1 patients who did not achieve "good" early improvement after 2 months of treatment (NR-2; episodic, n = 290 and chronic, n = 240) were categorized by level of their average monthly reduction across 1 and 2 months using similar categories.

RESULTS

Of NR-1 patients with episodic migraine having "modest" early improvement, 62% (96/155) achieved "good" and 20% (31/155) achieved "better" responses with continued treatment. A percentage of patients with "limited" (43%; 46/108) or "minimal/no" (34%; 29/85) early improvement, or "worsening" (20%; 20/102) achieved a "good" response after continued treatment. A percentage of NR-1 patients with chronic migraine having "modest" early improvement achieved "good" (38%; 44/116) and "better" (13%; 15/116) responses with continued treatment. A "good" response was achieved for a percentage of patients with "minimal/no" early improvement (17%; 23/133). Similar patterns were observed for the NR-2 subset, though percentages were lower.

CONCLUSIONS

Galcanezumab-treated patients with episodic or chronic migraine without response following 1 or 2 months of treatment appear to have a reasonable likelihood of continued improvement in months following initial treatment and this opportunity is more likely in patients showing greater early improvements. While a small percentage of patients with episodic or chronic migraine who experienced worsening in the number of MHD following initial treatment responded with continued treatment, most do not show substantial reduction in MHD. Overall benefit of therapy should be determined collaboratively between the patient and physician.

Remission of chronic headache: An 11-year follow-up study. Data from the Nord-Trøndelag Health Surveys 1995-1997 and 2006-2008

OBJECTIVES

To estimate remission rates of chronic headache and predictors of remission.

METHODS

In this longitudinal population-based cohort study, we used validated headache questionnaire data from the second (1995-1997, baseline; n = 51,856 aged ≥ 20 years, response rate: 55%) and third wave (2006-2008, follow-up, response rate: 42%) of the Nord-Trøndelag Health Study. Chronic headache was defined as ≥15 headache days/month during the last year. Chronic headache remission was defined as headache less than 15 days/month at follow-up. Potential predictors of remission were evaluated using logistic regression.

RESULTS

At baseline, 1266 (2.4%) participants reported chronic headache. Of these, 605 (48%) answered headache questions at follow-up. Remission was observed in 452 (74.7%), the proportion being almost identical in men and women (74.4% vs. 74.9, p = 0.92). In analyses adjusting for age, gender and education level, remission at follow-up was more than two times more likely among individuals without medication overuse headache (OR = 2.4, 95% CI 1.7-3.6) and without chronic musculoskeletal complaints (OR = 2.9, 95% CI 1.5-5.0) at baseline.

CONCLUSIONS

In this longitudinal population-based cohort study, three-quarters of chronic headache participants remitted from chronic headache. Remission was associated with no medication overuse headache and no chronic musculoskeletal complaints at baseline.

Medication overuse headache: An entrenched idea in need of scrutiny

It is a widely accepted idea that medications taken to relieve acute headache pain can paradoxically worsen headache if used too often. This type of secondary headache is referred to as medication overuse headache (MOH); previously used terms include rebound headache and drug-induced headache. In the absence of consensus about the duration of use, amount, and type of medication needed to cause MOH, the default position is conservative. A common recommendation is to limit treatment to no more than 10 or 15 days per month (depending on medication type) to prevent headache frequency progression. Medication withdrawal is often recommended as a first step in treatment of patients with very frequent headaches. Existing evidence, however, does not provide a strong basis for such causal claims about the relationship between medication use and frequent headache. Observational studies linking treatment patterns with headache frequency are by their nature confounded by indication. Medication withdrawal studies have mostly been uncontrolled and often have high dropout rates. Evaluation of this evidence suggests that only a minority of patients required to limit the use of symptomatic medication may benefit from treatment limitation. Similarly, only a minority of patients deemed to be overusing medications may benefit from withdrawal. These findings raise serious questions about the value of withholding or withdrawing symptom-relieving medications from people with frequent headaches solely to prevent or treat MOH. The benefits of doing so are smaller, and the harms larger, than currently recognized. The concept of MOH should be viewed with more skepticism. Until the evidence is better, we should avoid dogmatism about the use of symptomatic medication. Frequent use of symptom-relieving headache medications should be viewed more neutrally, as an indicator of poorly controlled headaches, and not invariably a cause.

Long-term predictors of remission in patients treated for medication-overuse headache at a specialized headache center: A prospective cohort study

Objective To evaluate long-term predictors of remission in patients with medication-overuse headache (MOH) by prospective cohort study. Background Knowledge regarding long-term predictors of MOH outcome is limited. Methods Two hundred and forty MOH patients recruited from 2000 to 2005 were included in a one-year follow-up study and then subsequently followed until 31 December 2013. The median follow-up was three years (interquartile range, three years). Predictive values of selected variables were assessed by the Cox proportional hazard regression model. Results At the end of follow-up, 102 (42.5%) patients were in remission. The most important predictors of remission were lower number of headache days per month before the one-year follow-up (HR-hazard ratio = 0.936, 95% confidence interval (CI) 0.884-0.990, p = 0.021) and efficient initial drug withdrawal (HR = 0.136, 95% CI 0.042-0.444, p = 0.001). Refractory MOH was observed in seven (2.9%) and MOH relapse in 131 patients (54.6%). Conclusions Outcome at the one-year follow-up is a reliable predictor of MOH long-term remission.

Cost-effectiveness analysis of non-invasive vagus nerve stimulation for the treatment of chronic cluster headache

Background

Cluster headache (CH) is a debilitating condition that is generally associated with substantial health care costs. Few therapies are approved for abortive or prophylactic treatment. Results from the prospective, randomised, open-label PREVA study suggested that adjunctive treatment with a novel non-invasive vagus nerve stimulation (nVNS) device led to decreased attack frequency and abortive medication use in patients with chronic CH (cCH). Herein, we evaluate whether nVNS is cost-effective compared with the current standard of care (SoC) for cCH.

Methods

A pharmacoeconomic model from the German statutory health insurance perspective was developed to estimate the 1-year cost-effectiveness of nVNS + SoC (versus SoC alone) using data from PREVA. Short-term treatment response data were taken from the clinical trial; longer-term response was modelled under scenarios of response maintenance, constant rate of response loss, and diminishing rate of response loss. Health-related quality of life was estimated by modelling EQ-5D™ data from PREVA; benefits were defined as quality-adjusted life-years (QALY). Abortive medication use data from PREVA, along with costs for the nVNS device and abortive therapies (i.e. intranasal zolmitriptan, subcutaneous sumatriptan, and inhaled oxygen), were used to assess health care costs in the German setting.

Results

The analysis resulted in mean expected yearly costs of €7096.69 for nVNS + SoC and €7511.35 for SoC alone and mean QALY of 0.607 for nVNS + SoC and 0.522 for SoC alone, suggesting that nVNS generates greater health benefits for lower overall cost. Abortive medication costs were 23 % lower with nVNS + SoC than with SoC alone. In the alternative scenarios (i.e. constant rate of response loss and diminishing rate of response loss), nVNS + SoC was more effective and cost saving than SoC alone.

Conclusions

In all scenarios modelled from a German perspective, nVNS was cost-effective compared with current SoC, which suggests that adjunctive nVNS therapy provides economic benefits in the treatment of cCH. Notably, the current analysis included only costs associated with abortive treatments. Treatment with nVNS will likely promote further economic benefit when other potential sources of cost savings (e.g. reduced frequency of clinic visits) are considered.

Trial registration

Clinicaltrials.gov identifier NCT01701245, 03OCT2012.

Rounding behavior in the reporting of headache frequency complicates headache chronification research

OBJECTIVES

To characterize the extent of measurement error arising from rounding in headache frequency reporting (days per month) in a population sample of headache sufferers.

BACKGROUND

When reporting numerical health information, individuals tend to round their estimates. The tendency to round to the nearest 5 days when reporting headache frequency can distort distributions and engender unreliability in frequency estimates in both clinical and research contexts.

METHODS

This secondary analysis of the 2005 American Migraine Prevalence and Prevention study survey characterized the population distribution of 30-day headache frequency among community headache sufferers and determined the extent of numerical rounding ("heaping") in self-reported data. Headache frequency distributions (days per month) were examined using a simplified version of Wang and Heitjan's approach to heaping to estimate the probability that headache sufferers round to a multiple of 5 when providing frequency reports. Multiple imputation was used to estimate a theoretical "true" headache frequency.

RESULTS

Of the 24,000 surveys, headache frequency data were available for 15,976 respondents diagnosed with migraine (68.6%), probable migraine (8.3%), or episodic tension-type headache (10.0%); the remainder had other headache types. The mean number of headaches days/month was 3.7 (standard deviation = 5.6). Examination of the distribution of headache frequency reports revealed a disproportionate number of responses centered on multiples of 5 days. The odds that headache frequency was rounded to 5 increased by 24% with each 1-day increase in headache frequency (odds ratio: 1.24, 95% confidence interval: 1.23 to 1.25), indicating that heaping occurs most commonly at higher headache frequencies. Women were more likely to round than men, and rounding decreased with increasing age and increased with symptoms of depression.

CONCLUSIONS

Because of the coarsening induced by rounding, caution should be used when distinguishing between episodic and chronic headache sufferers using self-reported estimates of headache frequency. Unreliability in frequency estimates is of particular concern among individuals with high-frequency (chronic) headache. Employing shorter recall intervals when assessing headache frequency, preferably using daily diaries, may improve accuracy and allow more precise estimation of chronic migraine onset and remission.

Influence of random measurement error on estimated rates of headache chronification and remission

OBJECTIVE

To examine the potential influence of random measurement error on estimated rates of chronification and remission.

BACKGROUND

Studies of headache chronification and remission examine the proportion of headache sufferers that move across a boundary of 15 headache days per month between 2 points in time. At least part of that apparent movement may represent measurement error or random variation in headache activity over time.

METHODS

A mathematical simulation was conducted to examine the influence of varying degrees of measurement error on rates of chronic migraine onset and remission. Using data from the American Migraine Prevalence and Prevention Study, we estimated a starting distribution of headache days from 0 to 30 in the migraine population. Assuming various levels of measurement error, we then simulated 2 sets of data for Time 1 and Time 2. The "individuals" in this study were assumed to have no real change in headache frequency from Time 1 to Time 2. The observed variations in headache frequency were those influenced by imputed random variance to resemble typical measurement error or natural variability. Using this simulation approach, we estimated the amount of chronification and remission rates that might be attributed simply to statistical artifacts such as unreliability or regression to the mean.

RESULTS

As the degree of measurement error increased, the amounts of illusory chronification and remission increased substantially. For example, if the headache frequency of sufferers randomly varies by only 2 headache days each month due to chance alone, a substantial degree of illusory chronification (0.6% to 1.3%) and illusory remission (10.3% to 23.5%) rates are expected simply due to random variation.

CONCLUSIONS

Random variation, without real change, has the potential to influence estimated rates of progression and remission in longitudinal migraine studies. The magnitude of random variation needed to fully reproduce observed rates of progression and remission are implausibly large. Recommendations are offered to improve estimation of rates of progression and remission, reducing the influence of random variation.