Methodology of a Novel Risk Stratification Algorithm for Patients with Multiple Myeloma in the Relapsed Setting
Autor: | Ben van Hout, Lucy DeCosta, Walter Bouwmeester, Marco Campioni, Sebastian Gonzalez-McQuire, Roman Hájek, Lucie Brozova, Andrew Briggs |
---|---|
Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: |
Risk
Survival business.industry Proportional hazards model Hazard ratio Disease lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens medicine.disease Individual risk lcsh:RC254-282 Patient management Algorithm Oncology Multiple myeloma Risk stratification medicine business Risk assessment Prognostic model Original Research |
Zdroj: | Oncology and Therapy Oncology and Therapy, Vol 7, Iss 2, Pp 141-157 (2019) |
ISSN: | 2366-1089 2366-1070 |
Popis: | 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 R2 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. Electronic supplementary material The online version of this article (10.1007/s40487-019-00100-5) contains supplementary material, which is available to authorized users. |
Databáze: | OpenAIRE |
Externí odkaz: |