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KMDATA: a curated database of reconstructed individual patient-level data from 153 oncology clinical trials
Author(s) -
Geoffrey Fell,
Robert Redd,
Alyssa M. Vanderbeek,
Rifaquat Rahman,
Bill Louv,
Jon McDunn,
Andrea Arfé,
Brian M. Alexander,
Steffen Ventz,
Lorenzo Trippa
Publication year - 2021
Publication title -
database
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.406
H-Index - 62
ISSN - 1758-0463
DOI - 10.1093/database/baab037
Subject(s) - clinical trial , medicine , event data , event (particle physics) , computer science , medical physics , oncology , database , data modeling , physics , quantum mechanics
We created a database of reconstructed patient-level data from published clinical trials that includes multiple time-to-event outcomes such as overall survival and progression-free survival. Outcomes were extracted from Kaplan-Meier (KM) curves reported in 153 oncology Phase III clinical trial publications identified through a PubMed search of clinical trials in breast, lung, prostate and colorectal cancer, published between 2014 and 2016. For each trial that met our search criteria, we curated study-level information and digitized all reported KM curves with the software Digitizelt. We then used the digitized KM survival curves to estimate (possibly censored) patient-level time-to-event outcomes. Collections of time-to-event datasets from completed trials can be used to support the choice of appropriate trial designs for future clinical studies. Patient-level data allow investigators to tailor clinical trial designs to diseases and classes of treatments. Patient-level data also allow investigators to estimate the operating characteristics (e.g. power and type I error rate) of candidate statistical designs and methods. Database URL: https://10.6084/m9.figshare.14642247.v1.

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