Biased effects of pre-diagnostic physical activity on breast cancer survival: Systematic review and meta-analysis.

Ziyu Wang, Frances Em Albers,Sabrina E Wang,Dallas R English,Brigid M Lynch

Cancer epidemiology(2024)

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摘要
BACKGROUND:Pre-diagnostic physical activity is reported to improve survival for women with breast cancer. However, studies of pre-diagnostic exposures and cancer survival are susceptible to bias, made clear when applying a target trial framework. We investigated the impact of selection bias, immortal time bias, confounding and bias due to inappropriate adjustment for post-exposure variables in a systematic review and meta-analysis of pre-diagnostic physical activity and survival after breast cancer. METHODS:Medline, Embase and Emcare were searched from inception to November 2021 for studies examining pre-diagnostic physical activity and overall or breast cancer-specific survival for women with breast cancer. Random-effects meta-analysis was used to estimate pooled hazard ratios (HRs) and 95% confidence intervals (CIs) comparing highest versus lowest pre-diagnostic physical activity. Subgroup meta-analyses were used to compare HRs of studies with and without different biases. ROBINS-E was used to assess risk of bias. RESULTS:We included 22 studies. Women with highest versus lowest pre-diagnostic physical activity had higher overall and breast cancer-specific survival across most analyses. The overall risk of bias was high. We observed marked differences in estimated HRs between studies that did and did not adjust for post-exposure variables or have immortal time bias. All studies were at risk of selection bias due to participants becoming eligible for study when they have survived to post-exposure events (e.g., breast cancer diagnosis). Insufficient studies were available to investigate confounding. CONCLUSION:Biases can substantially change effect estimates. Due to misalignment of treatment assignment (before diagnosis), eligibility (survival to post-exposure events) and start of follow-up, bias is difficult to avoid. It is difficult to lend a causal interpretation to effect estimates from studies of pre-diagnostic physical activity and survival after cancer. Biased effect estimates that are difficult to interpret may be less useful for clinical or public health policy applications.
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