Efird Jimmy Thomas
Epidemiologist/Chief Statistician and Director of Shared Resources, Center for Health Disparities Research, Brody School of Medicine, East Carolina University, 1800 W. 5th Street (Medical Pavilon), Greenville, NC 27834 USA.
Cancer Inform. 2010 Nov 28;9:265-79. doi: 10.4137/CIN.S6202.
Evidence of an association between survival time and date of birth would suggest an etiologic role for a seasonally variable environmental exposure occurring within a narrow perinatal time period. Risk factors that may exhibit seasonal epidemicity include diet, infectious agents, allergens, and antihistamine use. Typically data has been analyzed by simply categorizing births into months or seasons of the year and performing multiple pairwise comparisons. This paper presents a statistically robust alternative, based upon a trigonometric Cox regression model, to analyze the cyclic nature of birth dates related to patient survival. Disease birth-date results are presented using a sinusoidal plot with peak date(s) of relative risk and a single P value that indicates whether an overall statistically significant seasonal association is present. Advantages of this derivative-free method include ease of use, increased power to detect statistically significant associations, and the ability to avoid arbitrary, subjective demarcation of seasons.
生存时间与出生日期之间存在关联的证据表明，在围产期狭窄时间段内发生的季节性变化的环境暴露具有病因学作用。可能表现出季节性流行的风险因素包括饮食、传染因子、过敏原和抗组胺药的使用。通常，数据的分析方法是简单地将出生分为一年中的月份或季节，并进行多次两两比较。本文提出了一种基于三角Cox回归模型的统计稳健的替代方法，用于分析与患者生存相关的出生日期的周期性。疾病出生日期结果通过相对风险峰值日期的正弦图和一个表明是否存在总体统计学显著季节性关联的P值来呈现。这种无导数方法的优点包括易于使用、检测统计学显著关联的能力增强，以及避免季节的任意、主观划分。
