Methodology of a novel risk stratification algorithm for patients with multiple myeloma in the relapsed setting
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00843989%3A_____%2F19%3AE0108113" target="_blank" >RIV/00843989:_____/19:E0108113 - isvavai.cz</a>
Alternative codes found
RIV/00216224:14110/19:00111947
Result on the web
<a href="https://link.springer.com/content/pdf/10.1007%2Fs40487-019-00100-5.pdf" target="_blank" >https://link.springer.com/content/pdf/10.1007%2Fs40487-019-00100-5.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s40487-019-00100-5" target="_blank" >10.1007/s40487-019-00100-5</a>
Alternative languages
Result language
angličtina
Original language name
Methodology of a novel risk stratification algorithm for patients with multiple myeloma in the relapsed setting
Original language description
Introduction Risk stratification tools provide valuable information to inform treatment decisions. Existing algorithms for patients with multiple myeloma (MM) were based on patients with newly diagnosed disease, and these have not been validated in the relapsed setting or in routine clinical practice. We developed a risk stratification algorithm (RSA) for patients with MM at initiation of second-line (2L) treatment, based on data from the Czech Registry of Monoclonal Gammopathies. Methods Predictors of overall survival (OS) at 2L treatment were identified using Cox proportional hazards models and backward selection. Risk scores were obtained by multiplying the hazard ratios for each predictor. The K-adaptive partitioning for survival (KAPS) algorithm defined four groups of stratification based on individual risk scores. Results Performance of the RSA was assessed using Nagelkerke's R-2 test and Harrell's concordance index through Kaplan-Meier analysis of OS data. Prognostic groups were successfully defined based on real-world data. Use of a multiplicative score based on Cox modeling and KAPS to define cut-off values was effective. Conclusion Through innovative methods of risk assessment and collaboration between physicians and statisticians, the RSA was capable of stratifying patients at 2L treatment by survival expectations. This approach can be used to develop clinical decision-making tools in other disease areas to improve patient management. Funding Amgen Europe GmbH.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30205 - Hematology
Result continuities
Project
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Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Oncology and therapy
ISSN
2366-1070
e-ISSN
2366-1089
Volume of the periodical
7
Issue of the periodical within the volume
2
Country of publishing house
US - UNITED STATES
Number of pages
17
Pages from-to
141-157
UT code for WoS article
000493779800001
EID of the result in the Scopus database
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