Literature DB >> 29714570

Outdated Prescription Drug Labeling: How FDA-Approved Prescribing Information Lags Behind Real-World Clinical Practice.

Michael B Shea1, Mark Stewart1, Hugo Van Dyke2, Linda Ostermann1, Jeff Allen1, Ellen Sigal1.   

Abstract

BACKGROUND: Prescription drug labeling is an authoritative source of information that guides the safe and effective use of approved medications. In many instances, however, labeling may fail to be updated as new information about drug efficacy emerges in the postmarket setting. When labeling becomes outdated, it loses its value for prescribers and undermines a core part of the FDA's mission to communicate accurate and reliable information to patients and physicians.
METHODS: We compared the number of drug uses indicated on product labels to the number of uses contained in a leading drug compendium for 43 cancer drugs approved between 1999 and 2011. We defined a "well-accepted off-label use" of a drug as one that was not approved by the FDA and received a category 1 or 2A evidence grade.
RESULTS: Of the 43 drugs reviewed in this study, 34 (79%) had at least one well-accepted off-label use. In total, 253 off-label uses were identified; 91% were well accepted, and 65% were in cancer types not previously represented on labeling. Off-patent drugs had more well-accepted off-label uses than brand-name drugs, on average (mean 13.7 vs 3.8, P = .018).
CONCLUSIONS: The labeling for many cancer drugs, particularly for older drugs, is outdated. Although FDA-approved labeling can never be fully aligned with real-world clinical practice, steps should be taken to better align the two when high-quality data exist. Such steps, if taken, will assist patients and prescribers in discerning which uses of drugs are supported by the highest quality evidence.

Entities:  

Keywords:  FDA; compendia; labeling; off-label use; postmarket evidence

Mesh:

Substances:

Year:  2018        PMID: 29714570     DOI: 10.1177/2168479018759662

Source DB:  PubMed          Journal:  Ther Innov Regul Sci        ISSN: 2168-4790            Impact factor:   1.778


  5 in total

1.  Challenges and Opportunities to Updating Prescribing Information for Longstanding Oncology Drugs.

Authors:  Erin P Balogh; Andrew B Bindman; S Gail Eckhardt; Susan Halabi; R Donald Harvey; Ishmael Jaiyesimi; Rebecca Miksad; Harold L Moses; Sharyl J Nass; Richard L Schilsky; Steven Sun; Josephine M Torrente; Katherine E Warren
Journal:  Oncologist       Date:  2019-12-04

2.  Comparative analysis of PIM criteria and drug labels in the elderly.

Authors:  Yanwen Wang; Xiaohe Li; Shengnan Zhuo; Xinling Liu; Wei Liu
Journal:  Eur J Clin Pharmacol       Date:  2022-01-04       Impact factor: 2.953

3.  Proof-of-concept study: Homomorphically encrypted data can support real-time learning in personalized cancer medicine.

Authors:  Silvia Paddock; Hamed Abedtash; Jacqueline Zummo; Samuel Thomas
Journal:  BMC Med Inform Decis Mak       Date:  2019-12-04       Impact factor: 2.796

4.  Challenges and Opportunities to Updating Prescribing Information for Longstanding Oncology Drugs.

Authors:  Erin P Balogh; Andrew B Bindman; S Gail Eckhardt; Susan Halabi; R Donald Harvey; Ishmael Jaiyesimi; Rebecca Miksad; Harold L Moses; Sharyl J Nass; Richard L Schilsky; Steven Sun; Josephine M Torrente; Katherine E Warren
Journal:  Oncologist       Date:  2019-12-08

5.  Level of evidence used in recommendations by the National Comprehensive Cancer Network (NCCN) guidelines beyond Food and Drug Administration approvals.

Authors:  R Kurzrock; L A Gurski; R W Carlson; D S Ettinger; S M Horwitz; S K Kumar; L Million; M von Mehren; A B Benson
Journal:  Ann Oncol       Date:  2019-10-01       Impact factor: 32.976

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.