Grilling the data: application of specification curve analysis to red meat and all-cause mortality.

OBJECTIVES: To present an application of specification curve analysis-a novel analytic method that involves defining and implementing all plausible and valid analytic approaches for addressing a research question-to nutritional epidemiology. STUDY DESIGN AND SETTING: We reviewed all observational studies addressing the effect of red meat on all-cause mortality, sourced from a published systematic review, and documented variations in analytic methods (eg, choice of model, covariates, etc.). We enumerated all defensible combinations of analytic choices to produce a comprehensive list of all the ways in which the data may reasonably be analyzed. We applied specification curve analysis to data from National Health and Nutrition Examination Survey 2007 to 2014 to investigate the effect of unprocessed red meat on all-cause mortality. The specification curve analysis used a random sample of all reasonable analytic specifications we sourced from primary studies. RESULTS: Among 15 publications reporting on 24 cohorts included in the systematic review on red meat and all-cause mortality, we identified 70 unique analytic methods, each including different analytic models, covariates, and operationalizations of red meat (eg, continuous vs quantiles). We applied specification curve analysis to National Health and Nutrition Examination Survey, including 10,661 participants. Our specification curve analysis included 1208 unique analytic specifications, of which 435 (36.0%) yielded a hazard ratio equal to or more than 1 for the effect of red meat on all-cause mortality and 773 (64.0%) less than 1. The specification curve analysis yielded a median hazard ratio of 0.94 (interquartile range: 0.83-1.05). Forty-eight specifications (3.97%) were statistically significant, 40 of which indicated unprocessed red meat to reduce all-cause mortality and eight of which indicated red meat to increase mortality. CONCLUSION: We show that the application of specification curve analysis to nutritional epidemiology is feasible and presents an innovative solution to analytic flexibility.

The comparative effectiveness of migraine preventive drugs: a systematic review and network meta-analysis.

OBJECTIVE: While there are several trials that support the efficacy of various drugs for migraine prophylaxis against placebo, there is limited evidence addressing the comparative safety and efficacy of these drugs. We conducted a systematic review and network meta-analysis to facilitate comparison between drugs for migraine prophylaxis. METHODS: We searched MEDLINE, EMBASE, CENTRAL, and clinicaltrials.gov from inception to August 13, 2022, for randomized trials of pharmacological treatments for migraine prophylaxis in adults. Reviewers worked independently and in duplicate to screen references, extract data, and assess risk of bias. We performed a frequentist random-effects network meta-analysis and rated the certainty (quality) of evidence as either high, moderate, low, or very low using the GRADE approach. RESULTS: We identified 74 eligible trials, reporting on 32,990 patients. We found high certainty evidence that monoclonal antibodies acting on the calcitonin gene related peptide or its receptor (CGRP(r)mAbs), gepants, and topiramate increase the proportion of patients who experience a 50% or more reduction in monthly migraine days, compared to placebo. We found moderate certainty evidence that beta-blockers, valproate, and amitriptyline increase the proportion of patients who experience a 50% or more reduction in monthly migraine days, and low certainty evidence that gabapentin may not be different from placebo. We found high certainty evidence that, compared to placebo, valproate and amitriptyline lead to substantial adverse events leading to discontinuation, moderate certainty evidence that topiramate, beta-blockers, and gabapentin increase adverse events leading to discontinuation, and moderate to high certainty evidence that (CGRP(r)mAbs) and gepants do not increase adverse events. CONCLUSIONS: (CGRP(r)mAbs) have the best safety and efficacy profile of all drugs for migraine prophylaxis, followed closely by gepants.

European Headache Federation (EHF) critical re-appraisal and meta-analysis of oral drugs in migraine prevention-part 1: amitriptyline.

OBJECTIVE: The aim of this paper is to critically re-appraise the published trials assessing amitriptyline for migraine prophylaxis. METHODS: We report our methods and results following the Preferred Reporting Items for Systematic Reviews (PRISMA), by searching MEDLINE, EMBASE, Cochrane CENTRAL, and ClinicalTrials.gov for randomized trials of pharmacologic treatments for migraine prophylaxis. We included randomized trials that compared amitriptyline with placebo for migraine prophylaxis in adults. Our outcomes of interest were informed by the Outcome Set for preventive intervention trials in chronic and episodic migraine (COSMIG) and include the proportion of patients who experience a 50% or more reduction in migraine days per month, migraine days per month, and adverse events leading to discontinuation. We assessed risk of bias by using a modified Cochrane RoB 2.0 tool and the certainty of evidence by using the GRADE approach. RESULTS: Our search yielded 10.826 unique records, of which three trials (n = 622) were eligible for data synthesis and analysis. We found moderate certainty evidence that amitriptyline increases the proportion of patients who experience a 50% or more reduction in monthly migraine days, compared to placebo (relative risk: 1.60 (95% CI 1.17 to 2.19); absolute risk difference: 165 more per 1,000 (95% CI 47 more to 327 more). We found moderate certainty evidence that amitriptyline increases the proportion of patients who discontinue due to adverse events compared to placebo (risk difference: 0.05 (95% CI 0.01 to 0.10); absolute risk difference: 50 more per 1,000 (95% CI 10 more to 100 more). CONCLUSIONS: Our meta-analysis showed that amitriptyline may have a prophylactic role in migraine patients, however these results are far from robust. This warrants further large-scale research to evaluate the role of amitriptyline in migraine prevention.

A comparison of the effectiveness of biologic therapies for asthma: A systematic review and network meta-analysis.

BACKGROUND: Trials have not directly compared biologics for the treatment of asthma. OBJECTIVE: To compare the relative efficacy of biologics in asthma. METHODS: We searched MEDLINE, EMBASE, CENTRAL, and clinicaltrials.gov from inception to May 31, 2022 for randomized trials addressing biologic therapies for asthma. Reviewers worked independently and in duplicate to screen references, extract data, and assess risk of bias. We performed a frequentist network meta-analysis and assessed the certainty of evidence using the Grading of Recommendations, Assessment, Development, and Evaluations approach. We present dichotomous outcomes as absolute risk differences per 1000 patients and relative risk with 95% confidence intervals (95% CI) and continuous outcomes as mean difference (MD) and 95% CI. RESULTS: We identified 64 trials, including 26,630 patients. For patients with eosinophilic asthma, tezepelumab (329 fewer exacerbations per 1000 [95% CI, 272.6-366.6 fewer]) and dupilumab (319.6 fewer exacerbations per 1000 [95% CI, 272.6-357.2 fewer]) reduce exacerbations compared with placebo (high certainty). Tezepelumab (MD, 0.24 L [95% CI, 0.16-0.32]) and dupilumab (0.25 L [95% CI, 0.21-0.29]) improve lung function compared with placebo (high certainty). Both tezepelumab (110.97 fewer hospital admissions per 1000 [95% CI, 94.53-120.56 fewer]) and dupilumab (97.27 fewer hospitalizations [4.11-124.67 fewer]) probably reduce hospital admissions compared with placebo (moderate certainty). For patients with low eosinophils, biologics probably do not improve asthma outcomes. For these patients, tezepelumab (MD, 0.1 L [95% CI, 0-0.19]) and dupilumab (MD, 0.1 L [95% CI, 0-0.20]) may improve lung function (low certainty). CONCLUSION: Tezepelumab and dupilumab are effective at reducing exacerbations. For patients with low eosinophils, however, clinicians should probably be more judicious in using biologics, including tezepelumab, because they probably do not confer substantial benefit.

Reporting and interpretation of effects in non-randomized nutritional and environmental epidemiology: a methods study.

PURPOSE: The presentation of absolute effects, in addition to relative effects, is critical to the optimal interpretation of effect estimates. Failure to present and interpret absolute effects may obscure the magnitude of the effect of an intervention or exposure and mislead evidence users. OBJECTIVE: In this study, we estimate the proportion of systematic reviews and meta-analyses (SRMAs) addressing the health effects of nutritional and environmental exposures that report absolute effects. METHODS: We searched MEDLINE and EMBASE from 2019 through 2021 for SRMAs addressing the health effects of nutritional and environmental exposures and patient-important health outcomes. We included a sample of 200 SRMAs. Pairs of reviewers, working independently and in duplicate, reviewed search records for eligibility and collected data from SRMAs. RESULTS: More than two-thirds (153/200; 76.5%) of eligible systematic reviews reported on one or more dichotomous outcomes that could be translated to absolute effects. Only eight (8/153, 5.2%)5.2%), however, reported absolute effects. A similar proportion of reviews published in high-impact journals and in other journals reported absolute effects (4/131; 3.1% vs. 4/69; 5.9%). Among reviews that reported absolute effects, six reviews (6/8; 75%) reported absolute risk differences as fractions (e.g., 2 fewer cases per 1000 people) and two reviews (2/8; 25%) presented the number of cases prevented by modifying the exposure (e.g., 2000 cases prevented in United States annually). CONCLUSIONS: Reviews addressing the effects of nutritional and environmental exposures on health outcomes rarely report absolute effects, which precludes effective interpretation of magnitudes of effects and their importance. We present guidance for review authors, editors, peer reviewers, and evidence users to calculate and interpret absolute effects.