Blinded Independent Central Review (BICR) in New Therapeutic Lung Cancer Trials

Autor: Antoine Iannessi, Yi Wang, Hubert Beaumont, Yan Liu, Charles M. Voyton, Jennifer Cillario
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Cancers
Volume 13
Issue 18
Cancers, Vol 13, Iss 4533, p 4533 (2021)
ISSN: 2072-6694
Popis: Simple Summary Lung cancer treatment has dramatically evolved in the past decade, but some pitfalls of image interpretation have been introduced in parallel, such as pseudo-progressions. These challenges could be made more evident with blinded independent central reviews, as readers are often blinded to patient clinical symptoms and outcomes. The aim of this study was to analyze a pool of lung trials that used RECIST 1.1, document the proportion of reader discrepancies and the reader performance through monitoring procedures, and provide suggestions for the reduction of read inconsistency. This study provides benchmarks for the reader discordance rate in novel lung cancer therapeutic trials that will help to trigger corrective actions such as initial reader training and follow-up re-training. Abstract Background: Double reads in blinded independent central reviews (BICRs) are recommended to control the quality of trials but they are prone to discordances. We analyzed inter-reader discordances in a pool of lung cancer trials using RECIST 1.1. Methods: We analyzed six lung cancer BICR trials that included 1833 patients (10,684 time points) involving 17 radiologists. We analyzed the rate of discrepancy of each trial at the time-point and patient levels as well as testing inter-trial differences. The analysis of adjudication made it possible to compute the readers’ endorsement rates, the root causes of adjudications, and the proportions of “errors” versus “medically justifiable differences”. Results: The trials had significantly different discrepancy rates both at the time-point (average = 34.3%) and patient (average = 59.2%) levels. When considering only discrepancies for progressive disease, homogeneous discrepancy rates were found with an average of 32.9%, while readers’ endorsement rates ranged between 27.7% and 77.8%. Major causes of adjudication were different per trial, with medically justifiable differences being the most common, triggering 74.2% of total adjudications. Conclusions: We provide baseline performances for monitoring reader performance in trials with double reads. Intelligent reading system implementation along with appropriate reader training and monitoring are solutions that could mitigate a large portion of the commonly encountered reading errors.
Databáze: OpenAIRE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje