AIM: To review the methodology of observational studies examining the association between glucose-lowering medications and cancer to identify the most common methodological challenges and sources of bias. METHODS: We searched PubMed systematically to identify observational studies on glucose-lowering medications and cancer published between January 2000 and January 2016. We assessed the design and analytical methods used in each study, with a focus on their ability to achieve study validity, and further evaluated the prevalence of major methodological choices over time. RESULTS: Of 155 studies evaluated, only 26% implemented a new-user design, 41% used an active comparator, 33% implemented a lag or latency period, and 51% adjusted for diabetes duration. Potential for immortal person-time bias was identified in 63% of the studies; 55% of the studies adjusted for variables measured during the follow-up without appropriate statistical methods. Aside from a decreasing trend in adjusting for variables measured during the follow-up, we observed no trends in methodological choices over time. CONCLUSIONS: The prevalence of well-known design and analysis flaws that may lead to biased results remains high among observational studies on glucose-lowering medications and cancer, limiting the conclusions that can be drawn from these studies. Avoiding known pitfalls could substantially improve the quality and validity of real-world evidence in this field.
AIM: To review the methodology of observational studies examining the association between glucose-lowering medications and cancer to identify the most common methodological challenges and sources of bias. METHODS: We searched PubMed systematically to identify observational studies on glucose-lowering medications and cancer published between January 2000 and January 2016. We assessed the design and analytical methods used in each study, with a focus on their ability to achieve study validity, and further evaluated the prevalence of major methodological choices over time. RESULTS: Of 155 studies evaluated, only 26% implemented a new-user design, 41% used an active comparator, 33% implemented a lag or latency period, and 51% adjusted for diabetes duration. Potential for immortal person-time bias was identified in 63% of the studies; 55% of the studies adjusted for variables measured during the follow-up without appropriate statistical methods. Aside from a decreasing trend in adjusting for variables measured during the follow-up, we observed no trends in methodological choices over time. CONCLUSIONS: The prevalence of well-known design and analysis flaws that may lead to biased results remains high among observational studies on glucose-lowering medications and cancer, limiting the conclusions that can be drawn from these studies. Avoiding known pitfalls could substantially improve the quality and validity of real-world evidence in this field.
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