Wang Yumin, Pitre Tyler, Wallach Joshua D, de Souza Russell J, Jassal Tanvir, Bier Dennis, Patel Chirag J, Zeraatkar Dena
Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
J Clin Epidemiol. 2024 Apr;168:111278. doi: 10.1016/j.jclinepi.2024.111278. Epub 2024 Feb 12.
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.
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.
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.
We show that the application of specification curve analysis to nutritional epidemiology is feasible and presents an innovative solution to analytic flexibility.
介绍规范曲线分析（一种涉及定义和实施所有合理且有效的分析方法以解决研究问题的新型分析方法）在营养流行病学中的应用。
我们回顾了所有关于红肉对全因死亡率影响的观察性研究，这些研究来自已发表的系统评价，并记录了分析方法的差异（例如，模型选择、协变量等）。我们列举了所有合理的分析选择组合，以生成一份关于数据合理分析方式的全面清单。我们将规范曲线分析应用于2007年至2014年美国国家健康与营养检查调查的数据，以研究未加工红肉对全因死亡率的影响。规范曲线分析使用了我们从原始研究中获取的所有合理分析规范的随机样本。
在关于红肉与全因死亡率的系统评价中所纳入的24个队列的15篇报告中，我们确定了70种独特的分析方法，每种方法都包括不同的分析模型、协变量以及红肉的操作定义（例如，连续变量与分位数）。我们将规范曲线分析应用于美国国家健康与营养检查调查，该调查包括10,661名参与者。我们的规范曲线分析包括1208种独特的分析规范，其中435种（36.0%）得出红肉对全因死亡率影响的风险比等于或大于1，773种（64.0%）小于1。规范曲线分析得出的风险比中位数为0.94（四分位间距：0.83 - 1.05）。48种规范（3.97%）具有统计学意义，其中40种表明未加工红肉可降低全因死亡率，8种表明红肉会增加死亡率。
我们表明规范曲线分析在营养流行病学中的应用是可行的，并为分析灵活性提供了一种创新解决方案。
