ArticleBMJ open2020
Novel risk stratification algorithm for estimating the risk of death in patients with relapsed multiple myeloma: external validation in a retrospective chart review.
Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- A mortality model for relapsed or refractory multiple myeloma: emulation of subjective life expectancy criteria from a clinical trial in real-world data.Annals of hematology · 2026Article
- Establishment and Validation for Predicting the Death of Multiple Myeloma among Whites.Evidence-based complementary and alternative medicine : eCAM · 2022Article
- Efficacy and safety profile of deep responders to carfilzomib-based therapy: a subgroup analysis from ASPIRE and ENDEAVOR.Leukemia · 2021Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
OBJECTIVES AND
designA 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
settingPhysicians collected data from 998 patients (France, 386; Germany, 344; UK, 268) and applied the risk stratification algorithm.
methodsThe performance of the Cox regression model for predicting risk of death was assessed by Nagelkerke's R
resultsConsistent 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).
conclusionsValidation of the novel risk stratification algorithm in an independent 'real-world' dataset demonstrated that it stratifies patients in four subgroups according to survival expectation.
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