Development and Validation of a Simplified Score to Predict Early Relapse in Newly Diagnosed Multiple Myeloma in a Pooled Dataset of 2,190 Patients

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17110%2F21%3AA2202CSX" target="_blank" >RIV/61988987:17110/21:A2202CSX - isvavai.cz</a>

Alternative codes found

RIV/00843989:_____/21:E0109148

Result on the web

<a href="https://www.webofscience.com/wos/woscc/full-record/WOS:000670550600024" target="_blank" >https://www.webofscience.com/wos/woscc/full-record/WOS:000670550600024</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1158/1078-0432.CCR-21-0134" target="_blank" >10.1158/1078-0432.CCR-21-0134</a>

Result language

angličtina

Original language name

Development and Validation of a Simplified Score to Predict Early Relapse in Newly Diagnosed Multiple Myeloma in a Pooled Dataset of 2,190 Patients

Original language description

Purpose: Despite the improvement of therapeutic regimens, several patients with multiple myeloma (MM) still experience early relapse (ER). This subset of patients currently represents an unmet medical need. Experimental Design: We pooled data from seven European multicenter phase II/III dinical trials enrolling 2,190 patients with newly diagnosed MM from 2003 to 2017. Baseline patient evaluation included 14 clinically relevant features. Patients with complete data (n = 1,218) were split into training (n = 844) and validation sets (n = 374). In the training set, a univariate analysis and a multivariate logistic regression model on ER within 18 months (ER18) were made. The most accurate model was selected on the validation set. We also developed a dynamic version of the score by including response to treatment. Results: The Simplified Early Relapse in Multiple Myeloma (S-ERMM) score was modeled on six features weighted by a score: 5 points for high lactate dehydrogenase or t(4;14); 3 for del17p, abnormal albumin, or bone marrow plasma cells >60%; and 2 for lambda free light chain. The S-ERMM identified three patient groups with different risks of ER18: Intermediate (Int) versus Low (OR = 2.39, P < 0.001) and High versus Low (OR = 5.59, P < 0.001). S-ERMM High/Int patients had significantly shorter overall survival (High vs. Low: HR 3.24, P < 0.001; Int vs. Low: HR = 1.86, P < 0.001) and progression-free survival-2 (High vs. Low: HR = 2.89, P < 0.001; Int vs. Low: HR = 1.76, P < 0.001) than S-ERMM Low. The Dynamic S-ERMM (DS-ERMM) modulated the prognostic power of the S-ERMM. Conclusions: On the basis of simple, widely available baseline features, the S-ERMM and DS-ERMM properly identified patients with different risks of ER and survival outcomes.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

30204 - Oncology

Project

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Continuities

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Clinical Cancer Research

ISSN

1078-0432

e-ISSN

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Volume of the periodical

27

Issue of the periodical within the volume

13

Country of publishing house

US - UNITED STATES

Number of pages

9

Pages from-to

3695-3703

UT code for WoS article

000670550600024

EID of the result in the Scopus database

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