Novel risk stratification algorithm for estimating the risk of death in patients with relapsed multiple myeloma: External validation in a retrospective chart review

Hájek, R., Gonzalez-McQuire, S., Szabo, Z., Delforge, M., DeCosta, L., Raab, M. S., Bouwmeester, W., Campioni, M. and Briggs, A. (2020) Novel risk stratification algorithm for estimating the risk of death in patients with relapsed multiple myeloma: External validation in a retrospective chart review. BMJ Open, 10(7), e034209. (doi: 10.1136/bmjopen-2019-034209) (PMID:32665382) (PMCID:PMC7365483)

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Abstract

Objectives and design: A novel risk stratification algorithm estimating risk of death in patients with relapsed multiple myeloma starting second-line treatment was recently developed using multivariable Cox regression of data from a Czech registry. It uses 16 parameters routinely collected in medical practice to stratify patients into four distinct risk groups in terms of survival expectation. To provide insight into generalisability of the risk stratification algorithm, the study aimed to validate the risk stratification algorithm using real-world data from specifically designed retrospective chart audits from three European countries. Participants and setting: Physicians collected data from 998 patients (France, 386; Germany, 344; UK, 268) and applied the risk stratification algorithm. Methods: The performance of the Cox regression model for predicting risk of death was assessed by Nagelkerke’s R2, goodness of fit and the C-index. The risk stratification algorithm’s ability to discriminate overall survival across four risk groups was evaluated using Kaplan-Meier curves and HRs. Results: Consistent with the Czech registry, the stratification performance of the risk stratification algorithm demonstrated clear differentiation in risk of death between the four groups. As risk groups increased, risk of death doubled. The C-index was 0.715 (95% CI 0.690 to 0.734). Conclusions: Validation of the novel risk stratification algorithm in an independent ‘real-world’ dataset demonstrated that it stratifies patients in four subgroups according to survival expectation.

Item Type:Articles
Keywords:Oncology, 1506, 1717, algorithm, relapsed multiple myeloma, survival, risk stratification, validation.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Briggs, Professor Andrew
Authors: Hájek, R., Gonzalez-McQuire, S., Szabo, Z., Delforge, M., DeCosta, L., Raab, M. S., Bouwmeester, W., Campioni, M., and Briggs, A.
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Health Economics and Health Technology Assessment
Journal Name:BMJ Open
Publisher:BMJ Publishing Group
ISSN:2044-6055
ISSN (Online):2044-6055
Published Online:14 July 2020
Copyright Holders:Copyright © 2020 Author(s) (or their employer(s)
First Published:First published in BMJ Open 10(7):e034209
Publisher Policy:Reproduced under a Creative Commons License

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