Quantitative integrative survival prediction in multiple myeloma patients treated with bortezomib-based induction, high-dose therapy and autologous stem cell transplantation

• Verfasst von: Hummel, Manuela [VerfasserIn]
• Verfasst von: Hielscher, Thomas [VerfasserIn]
• Verfasst von: Emde-Rajaratnam, Martina [VerfasserIn]
• Verfasst von: Salwender, Hans [VerfasserIn]
• Verfasst von: Beck, Susanne [VerfasserIn]
• Verfasst von: Scheid, Christoph [VerfasserIn]
• Verfasst von: Bertsch, Uta [VerfasserIn]
• Verfasst von: Goldschmidt, Hartmut [VerfasserIn]
• Verfasst von: Jauch, Anna [VerfasserIn]
• Verfasst von: Moreaux, Jérôme [VerfasserIn]
• Verfasst von: Seckinger, Anja [VerfasserIn]
• Verfasst von: Hose, Dirk [VerfasserIn]
• Titel: Quantitative integrative survival prediction in multiple myeloma patients treated with bortezomib-based induction, high-dose therapy and autologous stem cell transplantation
• Verf.angabe: Manuela Hummel; Thomas Hielscher; Martina Emde-Rajaratnam; Hans Salwender; Susanne Beck; Christof Scheid; Uta Bertsch; Hartmut Goldschmidt; Anna Jauch; Jérôme Moreaux; Anja Seckinger; and Dirk Hose
• E-Jahr: 2024
• Jahr: July 10, 2024
• Umfang: 12 S.
• Illustrationen: Illustrationen
• Fussnoten: Gesehen am 07.08.2024
• Titel Quelle: Enthalten in: JCO precision oncology
• Ort Quelle: Alexandria, VA : American Society of Clinical Oncology, 2017
• Jahr Quelle: 2024
• Band/Heft Quelle: 8(2024), Artikel-ID e2300613, Seite 1-12
• ISSN Quelle: 2473-4284
• DOI: doi:10.1200/PO.23.00613
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1898041288

Abstract

Purpose - Given the high heterogeneity in survival for patients with multiple myeloma, it would be clinically useful to quantitatively predict the individual survival instead of attributing patients to two to four risk groups as in current models, for example, revised International Staging System (R-ISS), R2-ISS, or Mayo-2022-score. - Patients and Methods - Our aim was to develop a quantitative prediction tool for individual patient's 3-/5-year overall survival (OS) probability. We integrated established clinical and molecular risk factors into a comprehensive prognostic model and evaluated and validated its risk discrimination capabilities versus R-ISS, R2-ISS, and Mayo-2022-score. - Results - A nomogram for estimating OS probabilities was built on the basis of a Cox regression model. It allows one to translate the individual risk profile of a patient into 3-/5-year OS probabilities by attributing points to each prognostic factor and summing up all points. The nomogram was externally validated regarding discrimination and calibration. There was no obvious bias or overfitting of the prognostic index on the validation cohort. Resampling-based and external evaluation showed good calibration. The c-index of the model was similar on the training (0.76) and validation cohort (0.75) and significantly higher than for the R-ISS (P < .001) or R2-ISS (P < .01). - Conclusion - In summary, we developed and validated individual quantitative nomogram-based OS prediction. Continuous risk assessment integrating molecular prognostic factors is superior to R-ISS, R2-ISS, or Mayo-2022-score alone.