Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2019 Oct;20(10):e582-e589.
doi: 10.1016/S1470-2045(19)30335-3. Epub 2019 Sep 30.

US Food and Drug Administration review of statistical analysis of patient-reported outcomes in lung cancer clinical trials approved between January, 2008, and December, 2017

Affiliations
Review

US Food and Drug Administration review of statistical analysis of patient-reported outcomes in lung cancer clinical trials approved between January, 2008, and December, 2017

Mallorie H Fiero et al. Lancet Oncol. 2019 Oct.

Abstract

With the advent of patient-focused drug development, the US Food and Drug Administration (FDA) has redoubled its efforts to review patient-reported outcome (PRO) data in cancer trials submitted as part of a drug's marketing application. This Review aims to characterise the statistical analysis of PRO data from pivotal lung cancer trials submitted to support FDA drug approval between January, 2008, and December, 2017. For each trial and PRO instrument identified, we evaluated prespecified PRO concepts, statistical analysis, missing data and sensitivity analysis, instrument completion, and clinical relevance. Of the 37 pivotal lung cancer trials used to support FDA drug approval, 25 (68%) trials included PRO measures. The most common prespecified PRO concepts were cough, dyspnoea, and chest pain. At the trial level, the most common statistical analyses were descriptive (24 trials [96%]), followed by time-to-event analyses (19 trials [76%]), longitudinal analyses (12 trials [48%]), and basic inferential tests or general linear models (10 trials [40%]). Our findings indicate a wide variation in the analytic techniques and data presentation methods used, with very few trials reporting clear PRO research objectives and sensitivity analyses for PRO results. Our work further supports the need for focused research objectives to justify and to guide the analytic strategy of PROs to facilitate the interpretation of patient experience.

PubMed Disclaimer

LinkOut - more resources