Predicting survival of patients with spinal involvement in multiple myeloma using PATHFx 3.0 – a validation study of 100 patients in Germany
Julian Kylies, Elias Brauneck, Tobias M. Ballhause, Katja Weisel, Markus Schomacher, Malte Schroeder, Peter Obid, Leon-Gordian Leonhardt, Lennart Viezens

TL;DR
This study validates PATHFx 3.0 for predicting survival in multiple myeloma patients with spinal lesions, showing it performs well and can aid treatment decisions.
Contribution
The study is the first to validate PATHFx 3.0 for spinal malignant lesions in multiple myeloma patients.
Findings
PATHFx 3.0 showed good discriminatory performance with AUC values between 0.72 and 0.79 at different time points.
Calibration improved with longer prediction intervals, and Brier scores indicated best accuracy at 3 months.
Decision curve analysis showed net clinical benefit for all models except the 1-month estimate.
Abstract
Spinal malignant lesions are a common feature in multiple myeloma (MM) and often require surgical intervention. Accurate survival prediction is critical for guiding treatment decisions in these patients. While PATHFx is a widely used, machine-learning-based prognostic tool for skeletal metastases, it has not been validated for malignant bone lesions in MM so far. To evaluate the predictive performance and clinical utility of PATHFx 3.0 in a well-characterized cohort of MM patients with spinal malignant lesions. A retrospective cohort of 100 MM patients with radiologically confirmed spinal malignant lesions treated between 2009 and 2024 at a tertiary care center was analyzed. 51 patients underwent surgery for the local treatment of spinal lesions, while 49 were treated with non-operative treatment regimes. Clinical data were entered into PATHFx 3.0 to generate survival estimates at 1,…
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Taxonomy
TopicsMultiple Myeloma Research and Treatments · Management of metastatic bone disease · Medical Imaging and Analysis
