Predicting progression events in multiple myeloma from routine blood work Journal Article
| Authors: | Ferle, M.; Grieb, N.; Kreuz, M.; Ader, J.; Goldschmidt, H.; Mai, E. K.; Bertsch, U.; Platzbecker, U.; Neumuth, T.; Reiche, K.; Oeser, A.; Merz, M. |
| Article Title: | Predicting progression events in multiple myeloma from routine blood work |
| Abstract: | This study introduces a system for predicting disease progression events in multiple myeloma patients from the CoMMpass study (N = 1186). Utilizing a hybrid neural network architecture, our model predicts future blood work from historical lab results with high accuracy, significantly outperforming baseline estimators for key disease parameters. Disease progression events are annotated in the forecasted data, predicting these events with significant reliability. We externally validated our model using the GMMG-MM5 study dataset (N = 504), and could reproduce the main results of our study. Our approach enables early detection and personalized monitoring of patients at risk of impeding progression. Designed modularly, our system enhances interpretability, facilitates integration of additional modules, and uses routine blood work measurements to ensure accessibility in clinical settings. With this, we contribute to the development of a scalable, cost-effective virtual human twin system for optimized healthcare resource utilization and improved outcomes in multiple myeloma patient care. © The Author(s) 2025. |
| Keywords: | adult; controlled study; treatment outcome; aged; major clinical study; doxorubicin; cancer combination chemotherapy; cancer growth; comparative study; bortezomib; multiple myeloma; cohort analysis; calcium; creatinine; cyclophosphamide; dexamethasone; hemoglobin; calcium blood level; creatinine blood level; hemoglobin blood level; patient monitoring; prediction; patient care; albumin; disease progression; blood analysis; forecasting; lactate dehydrogenase; beta 2 microglobulin; m protein; monte carlo method; personalized medicine; albumin blood level; electrotherapeutics; interpretability; clinical settings; predictive model; human; male; female; article; mean squared error; restricted boltzmann machine; cost effective; long short term memory network; prediction error; high-accuracy; hybrid neural networks; neural network architecture; virtual humans; work measurement |
| Journal Title: | npj Digital Medicine |
| Volume: | 8 |
| ISSN: | 2398-6352 |
| Publisher: | Nature Publishing Group |
| Date Published: | 2025-04-30 |
| Start Page: | 231 |
| Language: | English |
| DOI: | 10.1038/s41746-025-01636-9 |
| PROVIDER: | scopus |
| PMCID: | PMC12043975 |
| PUBMED: | 40307417 |
| DOI/URL: | |
| Notes: | Article -- Erratum issued, see DOI: 10.1038/s41746-025-01719-7 -- Source: Scopus |
