Sage Journals: Discover world-class research

Abstract

Migraine, particularly migraine with aura, and increased body weight are independent risk factors for cardiovascular disease (CVD). The association of weight change and clinical markers of CVD risk was evaluated in subjects participating in a randomized double-blind, parallel-group study of migraine-preventive treatment comparing 100 mg/day of topiramate and amitriptyline. Individuals from both treatment groups were pooled and stratified into three groups. The ‘major weight gain’ group gained ≥ 5% of their baseline body weight at the conclusion of the study; the ‘major weight loss’ group lost ≥ 5% of their baseline body weight. The third group had < 5% of weight change. The influence of weight change in headache outcomes, as well as in markers of CVD (blood pressure, cholesterol, C-reactive protein), was assessed using analysis of covariance. Of 331 subjects, 52 (16%) experienced major weight gain and 56 (17%) experienced major weight loss. Weight change was not associated with differential efficacy for the treatment of headache. However, contrasted with those with major weight loss, those who gained weight experienced elevations in mean diastolic blood pressure (+2.5 vs. -1.2 mmHg), heart rate (+7.6 vs. -1.3 beats per minute), glycosylated haemoglobin (+0.09% vs. -0.04%), total cholesterol (+6.4 vs. -6.3 mg/dl), low-density lipoprotein cholesterol (+7.0 vs. -4.4 mg/ dl) and triglycerides (+15.3 vs. -10.4 mg/dl) and an increase in high-sensitivity C-reactive protein (+1.8 vs. -1.9 mg/l). Both groups experienced decreases in systolic blood pressure (-4.0 vs. -1.3 mmHg) and high-density lipoprotein cholesterol (-3.7 vs. -0.8 mg/dl). Increased weight during migraine treatment is not associated with poor headache treatment outcomes, but is associated with deterioration of CVD risk markers.

Keywords

Cardiovascular disease migraine topiramate amitriptyline weight change

Introduction

Both migraine and obesity are highly prevalent in the general population. In the USA, migraine affects approximately 18% of women and 6% of men (1). It is also a global leading cause of disability (2). Results of the National Health and Nutrition Examination Survey (NHANES 2003–2004) indicate that approximately 66% of adults and 17% of children and adolescents in the USA are either overweight or obese (3). The prevalence of obesity in the USA has increased significantly during the last decade (3, 4).

Migraine, particularly migraine with aura, and greater body weight are independent risk factors for cerebrovascular and cardiovascular disease (CVD) (5–12). Increasing body weight is also associated with increases in morbidity for Type 2 diabetes mellitus, gallbladder disease, osteoarthritis, and some types of cancer (12). Migraine and obesity may also be directly linked. Migraineurs who are obese have increased frequency and severity of migraine attacks compared with those with normal body weight (13). Obesity is also considered a modifiable risk factor for transformation from episodic migraine into chronic daily headaches (14, 15). Finally, the link seems to be specific to migraine and not to headaches overall; a population study has shown that obesity is not associated with increased prevalence of episodic tension-type headache (16).

In contrast with acute treatments, most migraine-preventive medications are not weight neutral (17–19). Topiramate, a medication approved for migraine prophylaxis, and zonisamide, a medication used off-label for the preventive treatment of migraine, are typically associated with weight loss (20–23). Others, such as divalproex sodium and propranolol, approved medications for migraine prophylaxis, and amitriptyline, a medication that is not approved but has good evidence for its use as a preventive treatment of migraine, are often linked with weight gain (22, 24–26). Medication-induced weight changes may affect treatment adherence and potentially affect treatment efficacy (19). In addition, increasing body weight may be associated with an increased risk for CVD.

The association between weight change during preventive migraine treatment and clinical markers of CVD risk has not been formally investigated. We have taken advantage of the data generated by a large, double-blind study comparing topiramate and amitriptyline for the preventive treatment of migraine to examine this association and the association between weight change and response to the studied preventive medications.

Methods

Data were derived from a randomized, double-blind, multicentre parallel study (CR004666) comparing the efficacy and safety of topiramate (100 mg) and amitriptyline (100 mg) for the prevention of migraine (26). The trial was conducted using the principles of Good Clinical Practice and in accordance with the Declaration of Helsinki. An independent ethics committee or an institutional review board provided approval for the study at each site, and all subjects provided written informed consent.

Study design

The design of the clinical trial has been previously described in detail (26). In brief, eligible subjects were ≥ 18 years old and had a history of migraine, with or without aura, conforming to the International Classification of Headache Disorders, 2nd edn (27) for at least 6 months. Subjects were required to have between three and 12 headache days per month for the 3 months prior to the screening period and during the prospective baseline period, and no more than 15 headache days (migraine or non-migraine) during the prospective baseline period. Subjects were excluded from the study if they previously failed more than two adequate trials of migraine-preventive medications (i.e. recommended dose for ≥ 3 months); previously failed an adequate trial of topiramate or amitriptyline because of adverse events or lack of efficacy; or used acute abortive migraine medication on > 15 treatment days per month. Other exclusion criteria included onset of migraine past 50 years of age or having had an unstable medical condition (e.g. cardiovascular, hepatic, renal or endocrine disorder) within the past 2 years.

The study consisted of three phases: a pretreatment phase lasting up to 8 weeks, a double-blind phase lasting 26 weeks and a taper/exit phase lasting up to 2 weeks (Fig. 1). Subjects were randomized 1:1, in double-blind fashion, to receive topiramate 100 mg/day or amitriptyline 100 mg/day. Patients were initiated at a dose of 25 mg/day topiramate or amitriptyline, and the daily dose was increased weekly by 25 mg to a dose of 100 mg/day, or the maximum tolerated dose. A stable dose of ≥ 50 mg/day of topiramate or amitriptyline was required during the maintenance period.

Figure 1

Study design.

Subjects were requested to record entries in their headache records (paper diaries) to document occurrence of headaches, duration and severity of headaches(s), and headache-associated functional disability (self-reported, see below). Severity of headaches was measured on a four-point scale, as recommended by the guidelines for controlled clinical trials on migraine prevention, from the International Headache Society (28). In addition, the Migraine Disability Assessment (MIDAS) questionnaire was completed at visits 1 and 8 (final maintenance visit) to estimate headache-related disability.

Study population: weight group categorization

Individuals from both treatment groups were pooled and stratified into three groups based on percent body weight change at conclusion of the study. The ‘major weight gain’ group consisted of individuals who gained ≥ 5% of their baseline body weight; the ‘major weight loss’ group consisted of individuals who lost ≥ 5% of their baseline body weight. The third group consisted of individuals who gained or lost < 5% of their baseline body weight (no major weight change).

Study outcomes

Headache outcome measures included change in the mean monthly (28 day) headache frequency, migraine episode rate, migraine days, total headache days, migraine duration, migraine severity (self-reported on a scale of 0 to 3: 0 = no pain, 1 = mild, 2 = moderate, 3 = severe), average severity of functional disability (self-reported on a scale of 1 to 4: 1, normal activity allowed; 2, disturbance without interruption or bed rest; 3, disturbance with normal activity or bed rest; 4, emergency department visit or hospitalization), and migraine disability (assessed by MIDAS). Responses, defined as ≥ 50% reduction from baseline for each of monthly episode rate, monthly rate of migraine days, and monthly rate of total headache days, were also assessed.

CVD profile assessment

In addition to efficacy and weight measurements, the following parameters were quantified at baseline and at the termination visit: mean systolic and diastolic blood pressure (BP), mean heart rate (HR), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), levels of glycosylated haemoglobin (HbA_1c), high-sensitivity C-reactive protein (hs-CRP) and interleukin-6 (IL-6).

Statistical analyses

Analyses were performed on the pooled intent-to-treat population, which consisted of all patients who received at least one dose of study medication and provided at least one post-randomization efficacy evaluation, using the last observation carried forward method. Only subjects with both baseline and post-baseline weight measurements were included in these post hoc analyses to determine changes from the last pretreatment evaluation to the double-blind phase in mean systolic and diastolic BP, mean HR, TC, LDL-C, HDL-C, TG, levels of HbA_1c, hs-CRP and IL-6.

Subjects with major weight gain and major weight loss were compared using an analysis of covariance model (ancova) including study centre and weight gain or loss as main effects, and baseline values as covariates. Comparison of outcomes between weight change groups (e.g. the difference in changes in systolic BP between the major weight gain and major weight loss groups) is subject to biased selection of subjects in the weight change groups, since weight change is caused by treatment. Therefore, in interpreting these analyses, one must keep in mind this potential confounding by selection. To account partially for this potential bias, further analyses were conducted with additional adjustments for treatment assignment and treatment assignment by weight group interaction.

Results

Our sample consisted of 331 patients (topiramate n = 172; amitriptyline n = 159) from 347 randomized subjects (95.4%). A total of 52 (16%) individuals experienced major weight gain, 56 (17%) individuals experienced major weight loss, and 223 (67%) had no major weight change. Of the 52 subjects who experienced major weight gain, 45 (87%) received amitriptyline and seven (13%) received topiramate. In contrast, of the 56 subjects who experienced major weight loss, 51 (91%) received topiramate and five (9%) received amitriptyline. Subject demographics and baseline characteristics for the major weight gain, major weight loss, and no major weight change groups were similar, with the exception of subjects in the no major weight change group having a mean baseline weight that was 4 kg heavier than the major weight change groups (Table 1).

Table 1

Subjects' demographics and baseline characteristics

Baseline characteristic		Major weight gain group (n = 52)	No major weight change group (n = 221)	Major weight loss group (n = 56)
Age, years	Mean ±s.d.	38.2 ± 11.6	38.8 ± 11.1	39.3 ± 10.4
Gender, n (%)	Male	7 (13.5)	36 (16.3)	7 (12.5)
Gender, n (%)	Female	45 (86.5)	185 (83.7)	49 (87.5)
Race, n (%)	White	47 (90.4)	181 (81.9)	50 (89.3)
	Black	2 (3.8)	31 (14.0)	5 (8.9)
	Asian	1 (1.9)	3 (1.4)	0 (0)
	Other	2 (3.8)	6 (2.7)	1 (1.8)
Weight (kg)	Mean ±s.d.	74.5 ± 18.4	78.1 ± 21.2	74.1 ± 18.4
Weight (kg)	Median	70.1	73.9	71.2
Body mass index (kg/m²)	Mean ±s.d.	27.7 ± 6.7	28.4 ± 7.7	27.0 ± 6.0
Body mass index (kg/m²)	Median	26.5	26.6	26.1
Baseline monthly migraine episode rate	Mean ±s.d.	6.0 ± 2.6	6.3 ± 2.8	6.0 ± 2.4
Baseline monthly headache days	Mean ±s.d.	8.0 ± 3.0	8.8 ± 3.7	8.1 ± 3.2

Association of weight change with headache response to treatment

Subjects with major weight gain and major weight loss experienced similar reductions in mean monthly migraine episode rate (mean ±s.d.) (−2.7 ± 2.2 vs. −3.3 ± 3.6, P = 0.110) and mean monthly migraine days (−3.5 ± 2.5 vs. −4.0 ± 4.1, P = 0.103). Similarly, there was no significant difference between subjects who experienced major weight gain and those who experienced major weight loss in other measures of treatment efficacy, including reductions in mean monthly total headache days, mean monthly migraine duration and severity, self-reported level of disability and MIDAS scores.

Association of weight change with clinical markers of CVD risk

Blood pressure and heart rate

Changes from baseline in BP and HR differed between groups stratified by major weight change category. Subjects in the major weight gain group experienced increases in diastolic BP (2.5 ± 9.4 mmHg), whereas those in the major weight loss group experienced decreases in diastolic BP (−1.2 ± 9.0 mmHg, Fig. 2) (29). Although subjects in both major weight change groups had reductions in systolic BP, subjects experiencing major weight loss exhibited a larger decrease in systolic BP compared with subjects experiencing major weight gain (−4.0 ± 12.2 mmHg vs. −1.3 ± 9.5 mmHg, respectively, Fig. 2). HR increased by a mean 7.6 ± 11.1 beats per minute (bpm) (baseline 73.1 ± 7.4 bpm) in the major weight gain group and decreased by a mean 1.3 ± 9.7 bpm (baseline 72.6 ± 9.8 bpm) in the major weight loss group.

Figure 2

Mean change from baseline in blood pressure (BP) by weight change category. Classification of BP [systolic, diastolic (mmHg)]: normal < 120 and < 80; prehypertension 120–139 or 80–89; hypertension stage 1 140–159 or 90–99; hypertension stage 2 ≥ 160 or ≥ 100 (29).

Lipid profile

TC, LDL-C and TG increased from baseline in the major weight gain group and decreased from baseline in the major weight loss group (Fig. 3) (30). The mean changes ±s.d. mg/dl for major weight gain group vs. major weight loss group were: TC 6.4 ± 26.2 vs. −6.3 ± 28.5; LDL-C 7.0 ± 24.7 vs. −4.4 ± 25.5; TG 15.3 ± 66.6 vs. −10.4 ± 60.1. HDL-C decreased in both groups: −3.7 ± 9.6 mg/dl in the major weight gain group (baseline 55.7 ± 14.1 mg/dl); −0.8 ± 7.7 mg/dl in the major weight loss group (baseline 58.0 ± 14.3 mg/dl).

Figure 3

Mean change from baseline in (A) total cholesterol, (B) low-density lipoprotein cholesterol (LDL-C) and (C) triglycerides by weight change category. The National Cholesterol Education Program (ATP III) identifies total cholesterol < 200 mg/dl as desirable, LDL-C < 100 mg/dl as optimal, and adopts the following classification of serum triglycerides: normal < 150 mg/dl; borderline high 150–199 mg/dl; high 200–499 mg/dl; very high ≥ 500 mg/dl (30).

Other CVD risk markers

Changes from baseline in HbA_1c measurements differed in relation to weight change. In those with major weight gain, levels increased from 5.3 ± 0.4% at baseline to 5.4 ± 0.5% at follow-up. In those with weight loss, levels decreased from 5.29 ± 0.46% at baseline to 5.25 ± 0.39%. Weight was also associated with increases from baseline in hs-CRP levels of +1.8 ± 4.0 mg/l for the major weight gain group (baseline 3.6 ± 4.0 mg/l) and a decrease from baseline of −1.9 ± 13.8 mg/l for the major weight loss group (baseline 4.8 ± 10.5 mg/l; Fig. 4) (31). Levels of the cytokine IL-6 did not change from baseline (10.0 ± 0.0 pg/ml for both weight groups) in the weight gain (0.0 ± 0.0 pg/ml change from baseline) and weight loss (+0.1 ± 0.7 pg/ml change from baseline) groups.

Figure 4

Mean change in high-sensitivity C-reactive protein (hs-CRP) by weight change category. According to the Centers for Disease Control and American Heart Association, hs-CRP values of < 1 mg/l predict low cardiovascular risk, whereas values of 1−3 mg/l predict average risk, and values of > 3 mg/l predict high risk (31).

Pair-wise comparisons including weight gain or loss group as main effects in the ancova model indicated a statistically significant association between changes from baseline in BP, HR, TC, LDL-C, TG and HbA_1c and major weight change groups (Table 2). The association between weight change during preventive migraine treatment and clinical markers of CVD risk did not reach statistical significance when additional adjustments for treatment assignment, and treatment assignment by weight change group interaction were included in the model (Table 2).

Table 2

Association of major weight change with clinical markers of cardiovascular disease (CVD)

CVD parameter	Unadjusted group effect P-value∗	Adjusted group effect P-value†
Blood pressure (BP)
Diastolic BP	< 0.001	0.533
Systolic BP	0.004	0.736
Heart rate	< 0.001	0.426
Lipid profile
TC	0.017	0.527
LDL-C	0.030	0.729
HDL-C	0.134	0.419
TG	0.025	0.764
HbA_1c	0.048	0.591
Hs-CRP	0.102	0.582
IL-6	0.140	0.387

Subjects with major weight gain and major weight loss were compared using an analysis of covariance model including study centre, weight gain or loss group, treatment assignment and treatment assignment and weight group interaction as main effects, and baseline value as covariate.

∗

Unadjusted weight group pair-wise comparison.

†

Weight group comparison adjusted for treatment assignment and treatment assignment by weight group interaction.

TC, total cholesterol: LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; TG, triglycerides; HbA_1c, glycosylated haemoglobin; hs-CRP, high-sensitivity C-reactive protein; IL-6, interleukin-6.

Discussion

In this post hoc analysis, body weight increased by ≥ 5% (major weight gain) in 16% of patients and decreased by ≥ 5% (major weight loss) in 17% of patients regardless of assigned treatment (topiramate or amitriptyline). A major change in weight in either direction was not associated with treatment response; those with major weight gain or major weight loss responded similarly to migraine prophylaxis, consistent with prior findings. In an earlier study, we showed that obesity at baseline did not account for refractoriness to preventive treatment at follow-up, after adjusting for covariates (32). Here, we have extended these findings, showing that changes in weight are also not associated with treatment response.

Published studies link weight gain and being overweight with increased levels of cholesterol, TG and CRP, whereas weight loss is reported to be associated with reduction in BP, TC and LDL-C (12, 33–36). Consistent with the literature, our data suggest that markers of CVD risk changed with body weight in the course of this study. Subjects who experienced major weight gain had significant increases in the quantitative measurements of clinical markers of CVD risk, including diastolic BP, HR, TC, LDL-C, TG and HbA_1c. In contrast, subjects who experienced major weight loss experienced decreases in these parameters. Subjects in the major weight gain group also demonstrated increased levels of hs-CRP compared with those in the major weight loss group, although the difference did not reach statistical significance. The differences between groups stratified by major weight changes were not statistically significant after additional adjustments for treatment and treatment by weight group interaction were included in the statistical model. The lack of significance after these additional adjustments is not surprising because of the causal effect of treatment on weight change. However, the magnitude of some changes in markers of CVD risk and their clinical significance warrants further discussion and analysis.

For subjects who experienced major weight gain during this study, mean values of TC, LDL-C and TG were all elevated to levels greater than current recommendations for acceptable measurements (TC < 200 mg/dl; LDL-C < 100 mg/dl; TG < 150 mg/dl) (30). The mean values of these same laboratory measurements were decreased in the subgroup of subjects who experienced major weight loss. Regardless of major weight gain or major weight loss, HDL measurements on average remained within the normal range during this study (considered low if < 40 mg/dl) (30).

The decrease in mean hs-CRP observed in the major weight loss group compared with the increase observed for subjects in the major weight gain group may be clinically meaningful, despite not reaching statistical significance. CRP has been associated with oxidative stress and vascular inflammatory mechanisms, and evidence to date supports the use of hs-CRP as an independent predictor of increased coronary risk (31). High-sensitivity CRP values of < 1 mg/l predict low CVD risk, whereas values of 1−3 mg/l predict average risk, and values > 3 mg/l predict high risk (high-risk tertile has an approximately twofold increase in relative risk compared with the low-risk tertile) (31). In the current study, mean hs-CRP levels increased by 1.8 mg/l in the major weight gain group and decreased by 1.9 mg/l in the major weight loss group. Importantly, baseline hs-CRP levels were already in an elevated risk category for subjects in both treatment groups (4.8 mg/dl for the major weight loss group; 3.6 mg/dl for the major weight gain group). This is in agreement with the results of two recent studies, which found abnormally high levels of CRP among migraine populations (37, 38), and provides further support for the role of inflammation in migraine pathophysiology (39).

In our analyses, the associations between major weight change and differences in HR and BP were less clear. For instance, although HR increased among those who experienced a major increase in weight during the study, the increase was modest and may have been confounded by the anticholinergic properties of amitriptyline, which was the assigned study medication for the majority of subjects in the major weight gain group (87%). In addition, whereas diastolic BP increased among those gaining substantial weight and decreased among those losing weight, systolic BP decreased in both groups. The anticholinergic effects of amitriptyline may also be associated with the decrease in systolic BP that was observed in the major weight gain group.

This study has several limitations. First, the clinical significance of our findings remains to be determined. Furthermore, conclusions drawn from these results are limited due to the post hoc nature of the analyses and the relatively short observation period (approximately 6 months). Long-term controlled studies investigating the relationships between weight change and clinical markers of CVD risk in migraine patients who take preventive migraine treatment are required to elucidate their association fully. However, since greater cardiovascular risks have been associated with elevated BP, high blood cholesterol, HbA_1c and hs-CRP (40), results from this study support the concept that treatment-related weight gain, including that associated with preventive migraine treatment, may be associated with a potential for harmful cardiovascular consequences. In addition, we did not have adequate power to conduct separate analyses in the different groups receiving topiramate or amitriptyline. Finally, this analysis does not separate the potential direct or indirect effect of treatment on changes in markers for CVD risk. A structural equation model is required in order to discern such associations. The strengths of this study include the prospective and systematic nature of the information obtained.

We have shown that major change in body weight happens frequently in the context of migraine-preventive treatment. Increased weight during migraine treatment is not associated with poor headache treatment outcomes, but is associated with deterioration of CVD risk markers. Given that migraine and being overweight or obese are independent risk factors for CVD, and obesity is a risk factor for the development of chronic migraine and greater disability (6–13), patients with migraine should be taught the importance of maintaining normal body weight and encouraged to exercise and eat a proper diet. In addition, healthcare professionals should carefully consider the risk of drug-related weight change when selecting a preventive migraine medication for treatment of their patients' migraines.

Competing interests

M.E.B. is a full-time employee of Merck Research Laboratories. This manuscript was written during his tenure at the Albert Einstein College of Medicine. He has received, in the past, compensation from Ortho-McNeil Pharmaceutical, AstraZeneca, GlaxoSmithKline, Merck, Allergan, MAP Pharmaceuticals, NanoMaterials Technology, and Endo Pharmaceuticals, among other pharmaceutical companies. R.B.L. has consulted for, conducted studies funded by, or received lecture honoraria from Allergan, Bristol-Myers Squibb, GlaxoSmithKline, Johnson & Johnson, Merck, Ortho-McNeil Pharmaceutical, Pfizer, and Pozen Inc., among other pharmaceutical companies. D.M.B., J.X. and J.H. are employees of Ortho-McNeil Janssen Scientific Affairs, LLC.

Acknowledgements

Editorial support was provided by Kakuri Omari, PhD (Phase Five Communications Inc., New York, NY, USA) with funding from Ortho-McNeil Janssen Scientific Affairs, LLC. Funding for this study was provided by Ortho-McNeil Janssen Scientific Affairs, LLC (Titusville, NJ, USA).

References

Lipton

Bigal

Diamond

Freitag

Reed

Stewart

. Migraine prevalence, disease burden, and the need for preventive therapy. Neurology 2007; 68:343−9.

Leonardi

Steiner

Scher

Lipton

. The global burden of migraine: measuring disability in headache disorders with WHO's Classification of Functioning, Disability and Health (ICF). J Headache Pain 2005; 6:429–40.

Ogden

Carroll

Curtin

McDowell

Tabak

Flegal

. Prevalence of overweight and obesity in the United States, 1999–2004. JAMA 2006; 295:1549−55.

Center for Disease Control and Prevention. State-specific prevalence of obesity among adults—United States, 2005. MMWR 2006; 55:985−88.

Kurth

Slomke

Kase

Cook

Lee

Gaziano

Migraine, headache, and the risk of stroke in women: a prospective study. Neurology 2005; 64:1020–6.

Kurth

Gaziano

Cook

Logroscino

Diener

Buring

. Migraine and risk of cardiovascular disease in women. JAMA 2006; 296:283–91. Erratum in: JAMA 2006; 296:654 and JAMA 2006; 296:1 p following 291.

Kurth

Gaziano

Cook

Bubes

Logroscino

Diener

Buring

. Migraine and risk of cardiovascular disease in men. Arch Intern Med 2007; 167:795–801.

Kurth

. Migraine and ischaemic vascular events. Cephalalgia 2007; 27:967–75.

Velentgas

Cole

Sikes

Walker

. Severe vascular events in migraine patients. Headache 2004; 44:642–51.

10.

Scher

Terwindt

Picavet

Verschuren

Ferrari

Launer

. Cardiovascular risk factors and migraine: the GEM population-based study. Neurology 2005; 64:614–20.

11.

Stang

Carson

Rose

Ephross

Shahar

Szklo

. Headache, cerebrovascular symptoms, and stroke: the Atherosclerosis Risk in Communities Study. Neurology 2005; 64:1573–7.

12.

National Institutes of Health. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults. NIH Publication No. 98-4083. 1998. [WWW document]. URL http://www.ncbi.nlm.nih.gov/books/bv.fcgi?rid=obesity (accessed November 2007).

13.

Bigal

Liberman

Lipton

. Obesity and migraine. A population study. Neurology 2006; 66:545–50.

14.

Scher

Stewart

Ricci

Lipton

. Factors associated with the onset and remission of chronic daily headache in a population-based study. Pain 2003; 106:81–9.

15.

Bigal

Lipton

. Obesity is a risk factor for transformed migraine but not chronic tension-type headache. Neurology 2006; 67:252–57.

16.

Bigal

Tsang

Loder

Serrano

Reed

Lipton

. Body mass index and episodic headaches: a population-based study. Arch Intern Med 2007; 167:1964–70.

17.

Ness-Abramof

Apovian

. Drug-induced weight gain. Drugs Today (Barc) 2005; 41:547−55.

18.

Young

Rozen

. Preventive treatment of migraine: effect on weight. Cephalalgia 2005; 25:1–11.

19.

Vanina

Podolskaya

Sedky

Shahab

Siddiqui

Munshi

Lippmann

. Body weight changes associated with psychopharmacology. Psychiatr Serv 2002; 53:842–7.

20.

Brandes

Saper

Diamond

Couch

Lewis

Schmitt

MIGR-002 Study Group . Topiramate for migraine prevention: a randomized controlled trial. JAMA 2004; 291:965–73.

21.

Silberstein

Neto

Scmitt

Jacobs

. Topiramate in migraine prevention: results from a large controlled trial. Arch Neurol 2004; 61:490–5.

22.

Diener

Tfelt-Hansen

Dahlof

Lainez

Sandrini

Wang

Topiramate in migraine prophylaxis—results from a placebo-controlled trial with propranolol as an active control. J Neurol 2004; 251:943–50.

23.

Drake

Jr Renner

Greathouse

Armentbright

. Open-label zonisamide for refractory migraine. Clin Neuropharmacol 2004; 27:278–80.

24.

Silberstein

Collins

. Safety of divalproex sodium in migraine prophylaxis: an open-label, long-term study. Long-term Safety of Depakote in Headache Prophylaxis Study Group. Headache 1999; 39:633–43.

25.

Maggioni

Ruffatti

Dainese

Mainardi

Zanchin

. Weight variations in the prophylactic therapy of primary headaches: 6-month follow-up. J Headache Pain 2005; 6:322–4.

26.

Dodick

Silberstein

Freitag

Ruoff

Banks

Saper

Topiramate versus amitriptyline for migraine prophylaxis: a multicenter, randomized, double-blind, parallel treatment group trial. Presented at the 59th American Academy of Neurology Annual Meeting; April 28–May 5, 2007; Boston, MA. Poster P08.001.

27.

Headache Classification Subcommittee of the International Headache Society. The International Classification of Headache Disorders, 2nd edn. Cephalagia 2004; 24 (Suppl. 1):1–160.

28.

Tfelt-Hansen

Block

Dahlof

Diener

Ferrari

Goadsby

Guidelines for controlled trials of drugs in migraine: second edition. Cephalalgia 2000; 20:765−86.

29.

US Department of Health and Human Services. National high blood pressure education program. NIH Publication No. 03-5231. May 2003.

30.

Third Report of the National Cholesterol Education Program (NCEP). Expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III). NIH. [WWW document]. URL http://www.nhlbi.nih.gov/guidelines/cholesterol/index.htm (accessed 28 August, 2007).

31.

Pearson

Mensah

Alexander

Anderson

Cannon

3rd Criqui

Markers of inflammation and cardiovascular disease: application to clinical and public health practice: a statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation 2003; 107:499–511.

32.

Bigal

Gironda

Tepper

Feleppa

Rapoport

Sheftell

Lipton

. Headache prevention outcome and body mass index. Cephalalgia 2006; 26:445–50.

33.

Ashley

Jr Kannel

. Relation of weight change to changes in atherogenic traits: the Framingham Study. J Chronic Dis 1974; 27:103–14.

34.

Denke

Sempos

Grundy

. Excess body weight. An underrecognized contributor to high blood cholesterol levels in white American men. Arch Intern Med 1993; 153:1093–103.

35.

Hershcopf

Elahi

Andres

Baldwin

Raizes

Schocken

Tobin

. Longitudinal changes in serum cholesterol in man: an epidemiologic search for an etiology. J Chronic Dis 1982; 35:101–14.

36.

Lee

Pratley

. The evolving role of inflammation in obesity and the metabolic syndrome. Curr Diab Rep 2005; 5:70–5.

37.

Welch

KMA

Brandes

Salerno

Brandes

. C-reactive protein may be increased in migraine patients who present with complex clinical features. Headache 2006; 46:197–9.

38.

Vanmolkot

de Hoon

. Increased C-reactive protein in young adult patients with migraine. Cephalalgia 2007; 27:843–6.

39.

Waeber

Moskowitz

. Migraine as an inflammatory disorder. Neurology 2005; 64 (Suppl. 2): S9−15.

40.

World Health Organization. Cardiovascular diseases prevention and control. 2003. [WWW document]. URL http://www.who.int/dietphysicalactivity/publications/facts/cvd/en/print.html (accessed 28 August 2007).

Weight Change and Clinical Markers of Cardiovascular Disease Risk During Preventive Treatment of Migraine

Abstract

Keywords

Introduction

Methods

Study design

Study population: weight group categorization

Study outcomes

CVD profile assessment

Statistical analyses

Results

Association of weight change with headache response to treatment

Association of weight change with clinical markers of CVD risk

Blood pressure and heart rate

Lipid profile

Other CVD risk markers

Discussion

Competing interests

Acknowledgements

References