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Diabetes Care. 2012 Dec;35(12):2665-73. doi: 10.2337/dc12-0788.

Metformin and the risk of cancer: time-related biases in observational studies.

Author information

  • 1Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, Canada. samy.suissa@mcgill.ca

Abstract

OBJECTIVE:

Time-related biases in observational studies of drug effects have been described extensively in different therapeutic areas but less so in diabetes. Immortal time bias, time-window bias, and time-lag bias all tend to greatly exaggerate the benefits observed with a drug.

RESEARCH DESIGN AND METHODS:

These time-related biases are described and shown to be prominent in observational studies that have associated metformin with impressive reductions in the incidence of and mortality from cancer. As a consequence, metformin received much attention as a potential anticancer agent; these observational studies sparked the conduction of randomized, controlled trials of metformin as cancer treatment. However, the spectacular effects reported in these studies are compatible with time-related biases.

RESULTS:

We found that 13 observational studies suffered from immortal time bias; 9 studies had not considered time-window bias, whereas other studies did not consider inherent time-lagging issues when comparing the first-line treatment metformin with second- or third-line treatments. These studies, subject to time-related biases that are avoidable with proper study design and data analysis, led to illusory extraordinarily significant effects, with reductions in cancer risk with metformin ranging from 20 to 94%. Three studies that avoided these biases reported no effect of metformin use on cancer incidence.

CONCLUSIONS:

Although observational studies are important to better understand the effects of drugs, their proper design and analysis is essential to avoid major time-related biases. With respect to metformin, the scientific evidence of its potential beneficial effects on cancer would need to be reassessed critically before embarking on further long and expensive trials.

PMID:
23173135
[PubMed - indexed for MEDLINE]
PMCID:
PMC3507580
Free PMC Article
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