Estimating the Effects of Lifestyle Interventions on Mortality Among Cancer Survivors: A Methodologic Framework

心理干预 老年学 癌症 医学 环境卫生 人口学 社会学 精神科 内科学
作者
Emma E. McGee,Miguel A. Hernán,Edward Giovannucci,Lorelei A. Mucci,Yu‐Han Chiu,A. Heather Eliassen,Barbra A. Dickerman
出处
期刊:Epidemiology [Lippincott Williams & Wilkins]
卷期号:36 (5): 705-718 被引量:1
标识
DOI:10.1097/ede.0000000000001889
摘要

Background: Many organizations recommend lifestyle modifications for cancer survivors. Effect estimates for these interventions are often based on observational data and are challenging to interpret due to vaguely defined causal questions, design-induced biases, and lack of comparability between individuals. Methods: We outlined a three-step procedure to address these challenges: target trial specification, emulation, and modification to explore lack of comparability due to unmeasured confounding or positivity violations. We illustrated this procedure by specifying the protocols of two target trials that estimate the effects of adhering to seven physical activity and dietary recommendations and abstaining from alcohol on 20-year mortality among adults with breast or prostate cancer. We emulated these target trials using data from the Nurses’ Health Study, Nurses’ Health Study II, and Health Professionals Follow-up Study. Results: In the main analysis, we included 9,107 adults (5,840 with breast cancer, 3,267 with prostate cancer) and 1,791 deaths occurred. After we modified the target trials, mortality risk differences (95% confidence intervals) comparing the physical activity and dietary intervention versus no intervention ranged from −4.8% (−7.5%, −2.3%) to −13.0% (−15.8%, −9.8%) for breast cancer and from −3.0% (−7.4%, 0.9%) to −12.8% (−17.6%, −7.6%) for prostate cancer. Risk differences comparing no alcohol consumption versus no intervention ranged from 1.3% (0.1%, 2.4%) to 3.6% (2.5%, 4.9%) for breast cancer and from −1.7% (−4.3%, 1.0%) to 6.4% (4.0%, 9.0%) for prostate cancer. Conclusions: We described a three-step procedure that improves the interpretability of observational estimates of the effects of lifestyle interventions and showed how estimates varied under different modifications.
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