Long-term benefit from high-dose ifosfamide in sarcoma depends on sustained prior control and timely intervention: a machine learning analysis.

ABSTRACT:

Purpose

High-dose ifosfamide (HD-IFO) remains an effective regimen for advanced bone and soft tissue sarcomas, but predictors of long-term benefit are poorly defined. This study evaluated clinical outcomes and prognostic factors using machine learning-assisted modeling in sarcoma patients treated with HD-IFO at a high-volume academic center.

Methods

We retrospectively analyzed 26 patients with histologically confirmed bone or soft tissue sarcoma who received HD-IFO (≥ 12 g/m² per cycle) between 2015 and 2025. Progression-free survival (PFS) and overall survival (OS) were estimated by the Kaplan-Meier method and compared across RECIST response categories using log-rank testing. Prognostic factors were identified using Least Absolute Shrinkage and Selection Operator

SUBMITTER: Hoberger M 

PROVIDER: S-EPMC12783467 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature