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Characterization of a Real-World Response Variable and Comparison with RECIST-Based Response Rates from Clinical Trials in Advanced NSCLC

INTRODUCTION: Effectiveness metrics for real-word research, analogous to clinical trial ones, are needed. This study aimed to develop a real-world response (rwR) variable applicable to solid tumors and to evaluate its clinical relevance and meaningfulness. METHODS: This retrospective study used pati...

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Autores principales: Ma, Xinran, Bellomo, Lawrence, Magee, Kelly, Bennette, Caroline S., Tymejczyk, Olga, Samant, Meghna, Tucker, Melisa, Nussbaum, Nathan, Bowser, Bryan E., Kraut, Joshua S., Bourla, Ariel Bulua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Healthcare 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8004504/
https://www.ncbi.nlm.nih.gov/pubmed/33674928
http://dx.doi.org/10.1007/s12325-021-01659-0
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author Ma, Xinran
Bellomo, Lawrence
Magee, Kelly
Bennette, Caroline S.
Tymejczyk, Olga
Samant, Meghna
Tucker, Melisa
Nussbaum, Nathan
Bowser, Bryan E.
Kraut, Joshua S.
Bourla, Ariel Bulua
author_facet Ma, Xinran
Bellomo, Lawrence
Magee, Kelly
Bennette, Caroline S.
Tymejczyk, Olga
Samant, Meghna
Tucker, Melisa
Nussbaum, Nathan
Bowser, Bryan E.
Kraut, Joshua S.
Bourla, Ariel Bulua
author_sort Ma, Xinran
collection PubMed
description INTRODUCTION: Effectiveness metrics for real-word research, analogous to clinical trial ones, are needed. This study aimed to develop a real-world response (rwR) variable applicable to solid tumors and to evaluate its clinical relevance and meaningfulness. METHODS: This retrospective study used patient cohorts with advanced non-small cell lung cancer from a nationwide, de-identified electronic health record (EHR)-derived database. Disease burden information abstracted manually was classified into response categories anchored to discrete therapy lines (per patient-line). In part 1, we quantified the feasibility and reliability of data capture, and estimated the association between rwR status and real-world progression-free survival (rwPFS) and real-world overall survival (rwOS). In part 2, we investigated the correlation between published clinical trial overall response rates (ORRs) and real-world response rates (rwRRs) from corresponding real-world patient cohorts. RESULTS: In part 1, 85.4% of patients (N = 3248) had  at least one radiographic assessment documented. Median abstraction time per patient-line was 15.0 min (IQR 7.8–28.1). Inter-abstractor agreement on presence/absence of at least one assessment was 0.94 (95% CI 0.92–0.96; n = 503 patient-lines abstracted in duplicate); inter-abstractor agreement on best confirmed response category was 0.82 (95% CI 0.78–0.86; n = 384 with at least one captured assessment). Confirmed responders at a 3-month landmark showed significantly lower risk of death and progression in rwOS and rwPFS analyses across all line settings. In part 2, rwRRs (from 12 rw cohorts) showed a high correlation with trial ORRs (Spearman’s ρ = 0.99). CONCLUSIONS: We developed a rwR variable generated from clinician assessments documented in EHRs following radiographic evaluations. This variable provides clinically meaningful information and may provide a real-world measure of treatment effectiveness. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12325-021-01659-0.
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spelling pubmed-80045042021-04-16 Characterization of a Real-World Response Variable and Comparison with RECIST-Based Response Rates from Clinical Trials in Advanced NSCLC Ma, Xinran Bellomo, Lawrence Magee, Kelly Bennette, Caroline S. Tymejczyk, Olga Samant, Meghna Tucker, Melisa Nussbaum, Nathan Bowser, Bryan E. Kraut, Joshua S. Bourla, Ariel Bulua Adv Ther Original Research INTRODUCTION: Effectiveness metrics for real-word research, analogous to clinical trial ones, are needed. This study aimed to develop a real-world response (rwR) variable applicable to solid tumors and to evaluate its clinical relevance and meaningfulness. METHODS: This retrospective study used patient cohorts with advanced non-small cell lung cancer from a nationwide, de-identified electronic health record (EHR)-derived database. Disease burden information abstracted manually was classified into response categories anchored to discrete therapy lines (per patient-line). In part 1, we quantified the feasibility and reliability of data capture, and estimated the association between rwR status and real-world progression-free survival (rwPFS) and real-world overall survival (rwOS). In part 2, we investigated the correlation between published clinical trial overall response rates (ORRs) and real-world response rates (rwRRs) from corresponding real-world patient cohorts. RESULTS: In part 1, 85.4% of patients (N = 3248) had  at least one radiographic assessment documented. Median abstraction time per patient-line was 15.0 min (IQR 7.8–28.1). Inter-abstractor agreement on presence/absence of at least one assessment was 0.94 (95% CI 0.92–0.96; n = 503 patient-lines abstracted in duplicate); inter-abstractor agreement on best confirmed response category was 0.82 (95% CI 0.78–0.86; n = 384 with at least one captured assessment). Confirmed responders at a 3-month landmark showed significantly lower risk of death and progression in rwOS and rwPFS analyses across all line settings. In part 2, rwRRs (from 12 rw cohorts) showed a high correlation with trial ORRs (Spearman’s ρ = 0.99). CONCLUSIONS: We developed a rwR variable generated from clinician assessments documented in EHRs following radiographic evaluations. This variable provides clinically meaningful information and may provide a real-world measure of treatment effectiveness. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12325-021-01659-0. Springer Healthcare 2021-03-05 2021 /pmc/articles/PMC8004504/ /pubmed/33674928 http://dx.doi.org/10.1007/s12325-021-01659-0 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Original Research
Ma, Xinran
Bellomo, Lawrence
Magee, Kelly
Bennette, Caroline S.
Tymejczyk, Olga
Samant, Meghna
Tucker, Melisa
Nussbaum, Nathan
Bowser, Bryan E.
Kraut, Joshua S.
Bourla, Ariel Bulua
Characterization of a Real-World Response Variable and Comparison with RECIST-Based Response Rates from Clinical Trials in Advanced NSCLC
title Characterization of a Real-World Response Variable and Comparison with RECIST-Based Response Rates from Clinical Trials in Advanced NSCLC
title_full Characterization of a Real-World Response Variable and Comparison with RECIST-Based Response Rates from Clinical Trials in Advanced NSCLC
title_fullStr Characterization of a Real-World Response Variable and Comparison with RECIST-Based Response Rates from Clinical Trials in Advanced NSCLC
title_full_unstemmed Characterization of a Real-World Response Variable and Comparison with RECIST-Based Response Rates from Clinical Trials in Advanced NSCLC
title_short Characterization of a Real-World Response Variable and Comparison with RECIST-Based Response Rates from Clinical Trials in Advanced NSCLC
title_sort characterization of a real-world response variable and comparison with recist-based response rates from clinical trials in advanced nsclc
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8004504/
https://www.ncbi.nlm.nih.gov/pubmed/33674928
http://dx.doi.org/10.1007/s12325-021-01659-0
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