| アブストラクト | Observational drug safety studies may be susceptible to confounding or protopathic bias. This bias may cause a spurious relationship between drug exposure and adverse side effect when none exists and may lead to unwarranted safety alerts. The spurious relationship may manifest itself through substantially different risk levels between exposure groups at the start of follow-up when exposure is deemed too short to have any plausible biological effect of the drug. The restrictive proportional hazards assumption with its arbitrary choice of baseline hazard function renders the commonly used Cox proportional hazards model of limited use for revealing such potential bias. We demonstrate a fully parametric approach using accelerated failure time models with an illustrative safety study of glucose-lowering therapies and show that its results are comparable against other methods that allow time-varying exposure effects. Our approach includes a wide variety of models that are based on the flexible generalized gamma distribution and allows direct comparisons of estimated hazard functions following different exposure-specific distributions of survival times. This approach lends itself to two alternative metrics, namely relative times and difference in times to event, allowing physicians more ways to communicate patient's prognosis without invoking the concept of risks, which some may find hard to grasp. In our illustrative case study, substantial differences in cancer risks at drug initiation followed by a gradual reduction towards null were found. This evidence is compatible with the presence of protopathic bias, in which undiagnosed symptoms of cancer lead to switches in diabetes medication. |
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| 組織名 | Director's Office, London School of Hygiene and Tropical Medicine, UK.;Clinical Practice Research Datalink (CPRD), Medicines and Healthcare Products;Regulatory Agency, UK.;Department of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute;for Pharmaceutical Sciences, University of Utrecht, Utrecht, P.O. Box 80082,;3508, TB, The Netherlands.;Julius Center for Health Sciences and Primary Care, University Medical Center;Utrecht, Utrecht, the Netherlands.;Faculty of Epidemiology and Public Health, London School of Hygiene and Tropical;Medicine, UK.;Health eResearch Centre, Farr Institute for Health Informatics Research,;University of Manchester, UK. |
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