Predictors and Profile of Severe Infectious Complications in Multiple Myeloma Patients Treated with Daratumumab-Based Regimens: A Machine Learning Model for Pneumonia Risk
Simple clinical and laboratory assessments, including hemoglobin level and ECOG scale, can be valuable in identifying patients vulnerable to infections during Dara-based regimens, facilitating personalized prophylactic strategies.
Authors
- Paweł Robak (ORCID: https://orcid.org/0000-0002-6078-5415)
- Magdalena Pawlak (ORCID: https://orcid.org/0000-0002-1116-0603)
- Damian Mikulski (ORCID: https://orcid.org/0000-0002-2806-2583)
- Wojciech Fendler (ORCID: https://orcid.org/0000-0002-5083-9168)
- Laura J. Wozniak (ORCID: https://orcid.org/0000-0002-4473-1812)
- Michał Kośny
- Joanna Góra‐Tybor (ORCID: https://orcid.org/0000-0002-6427-4532)
- Aleksandra Gołoś (ORCID: https://orcid.org/0000-0002-7780-3587)
- Marcin Kędzior (ORCID: https://orcid.org/0000-0001-8836-7218)
- Kacper Kościelny (ORCID: https://orcid.org/0000-0002-2879-7985)
- Tadeusz Robak (ORCID: https://orcid.org/0000-0002-3411-6357)
- Grzegorz Mirocha (ORCID: https://orcid.org/0009-0006-4621-6247)
- Katarzyna Jerzmanowska-Piechota (ORCID: https://orcid.org/0000-0001-8418-0317)
- Żaneta Witas
Institutions
- Copernicus Memorial Hospital (PL)
- Medical University of Lodz (PL)
Publication Details
- Journal
- Cancers
- Published
- 2024-11-03
- DOI
- https://doi.org/10.3390/cancers16213709
- Citations
- 3
- Primary Topic
- Multiple Myeloma Research and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- Uniwersytet Łódzki