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Development and Validation of a Simplified Score to Predict Early Relapse in Newly Diagnosed Multiple Myeloma in a Pooled Dataset of 2,190 Patients
GM. Zaccaria, L. Bertamini, MT. Petrucci, M. Offidani, P. Corradini, A. Capra, A. Romano, AM. Liberati, D. Mannina, P. de Fabritiis, N. Cascavilla, M. Ruggeri, R. Mina, F. Patriarca, G. Benevolo, A. Belotti, G. Gaidano, A. Nagler, R. Hájek, A....
Language English Country United States
Document type Journal Article, Research Support, Non-U.S. Gov't, Validation Study
NLK
Free Medical Journals
from 1995 to 1 year ago
Freely Accessible Science Journals
from 1995
Open Access Digital Library
from 1995-01-01
Open Access Digital Library
from 1995-01-01
- MeSH
- Time Factors MeSH
- Datasets as Topic MeSH
- Middle Aged MeSH
- Humans MeSH
- Survival Rate MeSH
- Multiple Myeloma mortality therapy MeSH
- Prognosis MeSH
- Recurrence MeSH
- Aged MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Aged MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Validation Study MeSH
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 clinical 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 λ 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.
Alfred Health Monash University Melbourne Australia
Clinica di Ematologia AOU Ospedali Riuniti di Ancona Ancona Italy
Department of Emergency and Organ Transplantation Aldo Moro University School of Medicine Bari Italy
Department of Haematooncology University Hospital Ostrava Ostrava Czech Republic
Department of Hematology Erasmus MC Cancer Institute Rotterdam the Netherlands
Division of Hematology Azienda Ospedaliera Papardo Messina Italy
Divisione di Ematologia Fondazione IRCCS Istituto Nazionale dei Tumori di Milano
Ematologia Ospedale Casa Sollievo della Sofferenza IRCCS San Giovanni Rotondo Italy
Faculty of Medicine University of Ostrava Ostrava Czech Republic
Hematology and Cell Therapy Unit IRCCS Istituto Tumori 'Giovanni Paolo 2 ' Bari Italy
Hematology Division ASST Spedali Civili Brescia Brescia Italy
Hematology Division Chaim Sheba Medical Center Tel Hashomer Israel
Hematology St Eugenio Hospital ASL Roma 2 Tor Vergata University Rome Italy
SC Hematology AO Città della Salute e della Scienza Turin Italy
Unit of Hematology and Stem Cell Transplantation AOUC Policlinico Bari Italy
Università degli Studi di Milano Milano Italy
Università degli Studi di Perugia Azienda Ospedaliera Santa Maria Terni Italy
References provided by Crossref.org
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