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A most stubborn bias: no adjustment method fully resolves confounding by indication in observational studies
Jaclyn L F Bosco1, Rebecca A Silliman, Soe Soe Thwin
1Department of Medicine, Geriatrics Section, Boston University School of Medicine, Boston, MA 02118, USA. jfong@bu.edu
Journal of Clinical Epidemiology
|May 22, 2009
Summary
Confounding by indication can distort results. This study found that common statistical methods, including propensity scores and instrumental variables, failed to fully control for unmeasured factors in breast cancer chemotherapy analysis.
Area of Science:
- Oncology
- Biostatistics
- Epidemiology
Background:
- Confounding by indication is a significant challenge in observational studies, particularly when evaluating the effectiveness of treatments like adjuvant chemotherapy for breast cancer.
- Crude analyses may suggest misleading associations due to unmeasured factors influencing treatment decisions.
Purpose of the Study:
- To assess the efficacy of various statistical methods in controlling for confounding by indication when analyzing breast cancer recurrence rates.
- To compare breast cancer recurrence in women receiving adjuvant chemotherapy versus those not receiving it, while accounting for confounding factors.
Main Methods:
- A medical record review of 1798 older women diagnosed with breast cancer between 1990-1994.
- Application of crude analysis, restriction, multivariable regression, propensity score (PS) adjustment, and instrumental variable (IV) methods to adjust for confounding by indication.
Main Results:
- Initial crude analysis showed an association between chemotherapy and increased recurrence (HR=2.6).
- After adjustment using restriction, multivariable regression, and PS methods, no significant association between chemotherapy and recurrence was found (HRs ranging from 1.1 to 1.3).
- An IV-like method suggested a protective effect (HR=0.9), but residual confounding was suspected due to imbalances in measured factors.
Conclusions:
- Standard statistical methods, including propensity scores and instrumental variables, may not adequately control for unmeasured confounding by indication in breast cancer research.
- Addressing confounding by indication requires careful consideration of unmeasured factors, and specialized methods may be useful but have limitations.
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