School of Health Sciences, Western Sydney University, Locked Bag 1797, Penrith, NSW, 2751, Australia.
Translational Health Research Institute, Western Sydney University, Locked Bag 1797, Penrith, NSW, 2751, Australia.
BMC Med Res Methodol. 2020 Apr 3;20(1):74. doi: 10.1186/s12874-020-00957-5.
Information on the associations between pre-diagnosis health behavior and post-diagnosis survival time in esophageal cancer could assist in planning health services but can be difficult to obtain using established study designs. We postulated that, with a large data set, using estimated probability for a behavior as a predictor of survival times could provide useful insight as to the impact of actual behavior.
Data from a national health survey and logistic regression were used to calculate the probability of selected health behaviors from participant's demographic characteristics for each esophageal cancer case within a large cancer registry data base. The associations between survival time and the probability of the health behaviors were investigated using Cox regression.
Observed associations include: a 0.1 increase in the probability of smoking 1 year prior to diagnosis was detrimental to survival (Hazard Ratio (HR) 1.21, 95% CI 1.19,1.23); a 0.1 increase in the probability of hazardous alcohol consumption 10 years prior to diagnosis was associated with decreased survival in squamous cell cancer (HR 1.29, 95% CI 1.07, 1.56) but not adenocarcinoma (HR 1.08, 95% CI 0.94,1.25); a 0.1 increase in the probability of physical activity outside the workplace is protective (HR 0.83, 95% CI 0.81,0.84).
We conclude that probability for health behavior estimated from demographic characteristics can provide an initial assessment of the association between pre-diagnosis health behavior and post-diagnosis health outcomes, allowing some sharing of information across otherwise unrelated data collections.
有关食管癌患者诊断前健康行为与诊断后生存时间之间关联的信息可以帮助规划卫生服务,但使用既定的研究设计可能难以获取。我们推测,通过大数据集,使用行为的估计概率作为生存时间的预测因子,可以为实际行为的影响提供有用的见解。
利用全国健康调查数据和逻辑回归,从大型癌症登记数据库中每个食管癌病例的人口统计学特征计算出特定健康行为的发生概率。使用 Cox 回归研究生存时间与健康行为概率之间的关联。
观察到的关联包括:诊断前 1 年吸烟概率增加 0.1,对生存不利(危险比(HR)1.21,95%置信区间(CI)1.19,1.23);诊断前 10 年危险饮酒概率增加 0.1,与鳞状细胞癌(HR 1.29,95% CI 1.07,1.56)而非腺癌(HR 1.08,95% CI 0.94,1.25)的生存时间减少相关;工作场所外体力活动概率增加 0.1 具有保护作用(HR 0.83,95% CI 0.81,0.84)。
我们得出结论,从人口统计学特征中估计的健康行为概率可以初步评估诊断前健康行为与诊断后健康结果之间的关联,从而允许在其他不相关的数据集中共享一些信息。