Metformin and cancer in type 2 diabetes: A systematic review and comprehensive bias evaluation

Ruth E. Farmer, Deborah Ford, Harriet J. Forbes, Nishi Chaturvedi, Richard Kaplan, Liam Smeeth, Krishnan Bhaskaran

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43 Scopus citations


Background: Existing observational studies provide conflicting evidence for the causal effect of metformin use on cancer risk in patients with type-2 diabetes, and there are concerns about bias affecting a number of studies. Methods: MEDLINE was used to identify observational studies investigating the association between metformin and overall or site-specific cancer in people with type-2 diabetes. A systematic data extraction and bias assessment was conducted, in which risk of eight bias domains (outcome, exposure, control selection, baseline confounding, time-dependent confounding, immortal time, missing data, censoring methods) were assessed against pre-defined criteria, and rated as unlikely, low, medium or high. Results: Of 46 studies identified, 21 assessed the effect of metformin on all cancer. Reported relative risks ranged from 0.23 to 1.22, with 12/21 reporting a statistically significant protective effect and none a harmful effect. The range of estimates was similar for site-specific cancers; 3/46 studies were rated as low or unlikely risk of bias in all domains. Two of these had results consistent with no effect of metformin; one observed a moderate protective effect overall, but presented further analyses that the authors concluded were inconsistent with causality. However, 28/46 studies were at risk from bias through exposure definition, 22 through insufficient baseline adjustment and 35 from possible time-dependent confounding. Conclusions: Observational studies on metformin and cancer varied in design, and the majority were at risk of a range of biases. The studies least likely to be affected by bias did not support a causal effect of metformin on cancer risk.

Original languageEnglish
Pages (from-to)728-744
Number of pages17
JournalInternational Journal of Epidemiology
Issue number2
StatePublished - 2017
Externally publishedYes


  • Bias
  • Cancer
  • Causality
  • Confounding
  • Diabetes
  • Pharmacoepidemiology


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