Dataset Information

Glucose-lowering medications and the risk of cancer: A methodological review of studies based on real-world data.

ABSTRACT: 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.

SUBMITTER: Bykov K

PROVIDER: S-EPMC6684441 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Glucose-lowering medications and the risk of cancer: A methodological review of studies based on real-world data.

Bykov Katsiaryna K He Mengdong M Franklin Jessica M JM Garry Elizabeth M EM Seeger John D JD Patorno Elisabetta E

Diabetes, obesity & metabolism 20190529 9

<h4>Aim</h4>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.<h4>Methods</h4>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 ...[more]

PMID: 31062453

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Project description:Background: Big data and real-world data (RWD) have been increasingly used to measure the effectiveness and costs in cost-effectiveness analysis (CEA). However, the characteristics and methodologies of CEA based on big data and RWD remain unknown. The objectives of this study were to review the characteristics and methodologies of the CEA studies based on big data and RWD and to compare the characteristics and methodologies between the CEA studies with or without decision-analytic models. Methods: The literature search was conducted in Medline (Pubmed), Embase, Web of Science, and Cochrane Library (as of June 2020). Full CEA studies with an incremental analysis that used big data and RWD for both effectiveness and costs written in English were included. There were no restrictions regarding publication date. Results: 70 studies on CEA using RWD (37 with decision-analytic models and 33 without) were included. The majority of the studies were published between 2011 and 2020, and the number of CEA based on RWD has been increasing over the years. Few CEA studies used big data. Pharmacological interventions were the most frequently studied intervention, and they were more frequently evaluated by the studies without decision-analytic models, while those with the model focused on treatment regimen. Compared to CEA studies using decision-analytic models, both effectiveness and costs of those using the model were more likely to be obtained from literature review. All the studies using decision-analytic models included sensitivity analyses, while four studies no using the model neither used sensitivity analysis nor controlled for confounders. Conclusion: The review shows that RWD has been increasingly applied in conducting the cost-effectiveness analysis. However, few CEA studies are based on big data. In future CEA studies using big data and RWD, it is encouraged to control confounders and to discount in long-term research when decision-analytic models are not used.

Dataset Information

Glucose-lowering medications and the risk of cancer: A methodological review of studies based on real-world data.

Publications

Glucose-lowering medications and the risk of cancer: A methodological review of studies based on real-world data.

Similar Datasets

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