METHODS: We performed systematic searches using electronic databases including PubMed and EMBASE until December 2012. Key words included "metformin" AND ("ovarian cancer" OR "ovary tumor"). All human studies assessing the effects of metformin on ovarian cancer were eligible for inclusion. All articles were reviewed independently by 2 authors with a standardized approach for the purpose of study, study design, patient characteristics, exposure, and outcomes. The data were pooled using a random-effects model.
RESULTS: Of 190 studies retrieved, only 3 observational studies and 1 report of 2 randomized controlled trials were included. Among those studies, 2 reported the effects of metformin on survival outcomes of ovarian cancer, whereas the other 2 reported the effects of metformin on ovarian cancer prevention. The findings of studies reporting the effects on survival outcomes indicated that metformin may prolong overall, disease-specific, and progression-free survival in ovarian cancer patients. The results of studies reporting the effects of metformin on ovarian cancer prevention were meta-analyzed. It indicated that metformin tended to decrease occurrence of ovarian cancer among diabetic patients with the pooled odds ratio of 0.57 (95% confidence interval, 0.16-1.99).
CONCLUSIONS: Our findings showed the potential therapeutic effects of metformin on survival outcomes of ovarian cancer and ovarian cancer prevention. However, most of the evidence was observational studies. There is a call for further well-conducted controlled clinical trials to confirm the effects of metformin on ovarian cancer survival and ovarian cancer prevention.
METHODS: A retrospective database analysis at a university-affiliated hospital in Thailand was used. Diabetic patients receiving glucose-lowering medications from July 2008 to June 2011 were included. Patients were categorized into those exposed and not exposed to thiazolidinediones (TZDs). PSs were estimated by using conventional PS and CTS-PS. In the CTS-PS, PS was separately estimated for three specific calendar time periods. Patients were matched 1:1 using caliper matching. The outcomes were cardiovascular and all-cause hospitalizations. The TZD and non-TZD groups were compared with Cox proportional hazard models.
RESULTS: A total of 2165 patients were included. The average conventional PS was 0.198 (95% confidence interval [CI] 0.195-0.202), while the average PS in the CTS-PS approach was 0.212 (0.206-0.218), 0.180 (0.173-0.188), and 0.205 (0.197-0.213) for July 2008 to June 2009, July 2009 to June 2010, and July 2010 to June 2011, respectively. The average difference in PS was 0.012 (P < 0.001), -0.009 (P ≤ 0.002), and 0.000 (P = 0.950) in the three calendar time periods. The adjusted hazard ratios of the conventional PS-matched cohort were 0.97 (95% CI 0.39-2.45) and 0.97 (95% CI 0.78-1.20) for CVD-related and all-cause hospitalizations, while the adjusted hazard ratios of the CTS-PS-matched cohort were 1.11 (95% CI 0.43-2.88) and 1.12 (95% CI 0.91-1.39), respectively.
CONCLUSION: CTS-PS is different from PS estimated by using the conventional approach. CTS-PS should be considered when a pattern of medication use has changed over the study period.