Metformin Treatment Among Men With Diabetes and the Risk of Prostate Cancer: A Population-Based Historical Cohort Study

Laurence S. Freedman, Nirit Agay, Ruth Farmer, Havi Murad, Liraz Olmer, Rachel Dankner

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


There is conflicting evidence regarding the association between metformin treatment and prostate cancer risk in diabetic men. We investigated this association in a population-based Israeli cohort of 145,617 men aged 21-89 years with incident diabetes who were followed over the period 2002-2012. We implemented a time-dependent covariate Cox model, using weighted cumulative exposure to relate metformin history to prostate cancer risk, adjusting for use of other glucose-lowering medications, age, ethnicity, and socioeconomic status. To adjust for time-varying glucose control variables, we used inverse probability weighting of a marginal structural model. With 666,553 person-years of follow-up, 1,592 men were diagnosed with prostate cancer. Metformin exposure in the previous year was positively associated with prostate cancer risk (per defined daily dose; without adjustment for glucose control, hazard ratio (HR) = 1.53 (95% confidence interval (CI): 1.19, 1.96); with adjustment, HR = 1.42 (95% CI: 1.04, 1.94)). However, exposure during the previous 2-7 years was negatively associated with risk (without adjustment for glucose control, HR = 0.58 (95% CI: 0.37, 0.93); with adjustment, HR = 0.60 (95% CI: 0.33, 1.09)). These positive and negative associations with previous-year and earlier metformin exposure, respectively, need to be confirmed and better understood.

Original languageEnglish
Pages (from-to)626-635
Number of pages10
JournalAmerican Journal of Epidemiology
Issue number4
StatePublished - 24 Mar 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022 The Author(s) 2021. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.


  • glucose-lowering medications
  • inverse probability weighting
  • marginal structural models
  • metformin
  • prostate cancer
  • time-dependent confounding
  • type 2 diabetes


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