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Depression and the Risk of Breast Cancer: A Meta-Analysis of Cohort Studies

  • Sun, Hui-Lian (School of Public Health, Tongji Medical College, Huazhong University of Science and Technology) ;
  • Dong, Xiao-Xin (School of Public Health, Tongji Medical College, Huazhong University of Science and Technology) ;
  • Cong, Ying-Jie (School of Public Health, Tongji Medical College, Huazhong University of Science and Technology) ;
  • Gan, Yong (School of Public Health, Tongji Medical College, Huazhong University of Science and Technology) ;
  • Deng, Jian (School of Public Health, Tongji Medical College, Huazhong University of Science and Technology) ;
  • Cao, Shi-Yi (School of Public Health, Tongji Medical College, Huazhong University of Science and Technology) ;
  • Lu, Zu-Xun (School of Public Health, Tongji Medical College, Huazhong University of Science and Technology)
  • Published : 2015.04.29

Abstract

Background: Whether depression causes increased risk of the development of breast cancer has long been debated. We conducted an updated meta-analysis of cohort studies to assess the association between depression and risk of breast cancer. Materials and Methods: Relevant literature was searched from Medline, Embase, Web of Science (up to April 2014) as well as manual searches of reference lists of selected publications. Cohort studies on the association between depression and breast cancer were included. Data abstraction and quality assessment were conducted independently by two authors. Random-effect model was used to compute the pooled risk estimate. Visual inspection of a funnel plot, Begg rank correlation test and Egger linear regression test were used to evaluate the publication bias. Results: We identified eleven cohort studies (182,241 participants, 2,353 cases) with a follow-up duration ranging from 5 to 38 years. The pooled adjusted RR was 1.13(95% CI: 0.94 to 1.36; $I^2=67.2%$, p=0.001). The association between the risk of breast cancer and depression was consistent across subgroups. Visual inspection of funnel plot and Begg's and Egger's tests indicated no evidence of publication bias. Regarding limitations, a one-time assessment of depression with no measure of duration weakens the test of hypothesis. In addition, 8 different scales were used for the measurement of depression, potentially adding to the multiple conceptual problems concerned with the definition of depression. Conclusions: Available epidemiological evidence is insufficient to support a positive association between depression and breast cancer.

Keywords

Depression;breast cancer;meta-analysis

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