Journal Article

DKFZ-2026-01383

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Machine Learning-Guided Survival Prediction and Treatment Sequencing in Advanced Soft Tissue Sarcoma Beyond Second-Line Therapy: A Retrospective Cohort Study.

Hoberger, M. ; Di Gioia, D. ; Zuber, R. L. ; Völkl, M. ; Güler, S. E. ; Jurinovic, V. ; Albertsmeier, M. ; Klein, A. ; Dürr, H. R. ; Schmidt-Hegemann, N.-S. ; Knösel, T. ; Kunz, W. G. ; von Bergwelt-Baildon, M.DKFZ* ; Lindner, L. H. ; Burkhard-Meier, A. ; Berclaz, L. M.DKFZ*

2026
Springer Healthcare [Tarporley]

Abstract: Evidence guiding the optimal sequencing of later-line systemic therapy in advanced soft tissue sarcoma (STS) remains limited. The aim of this study was to identify prognostic factors for overall survival (OS) beyond second-line treatment and to explore therapy sequencing in routine clinical practice.A total of 90 patients with advanced STS receiving third-line or later systemic therapy were retrospectively analyzed. Extreme gradient boosting (XGBoost) was used to identify clinical predictors of 1-year OS. The most influential variables were subsequently evaluated in multivariable Cox models for OS from the start of third- and fourth-line therapy. Sequencing analyses compared OS according to the line of administration of commonly used later-line agents.In the third-line cohort (n = 88), inferior OS was independently associated with progression on second-line therapy (hazard ratio [HR] 2.31, p = 0.005). In contrast, lipo-/leiomyosarcoma histology was associated with improved survival (HR 0.37, p = 0.002), as was a time to progression ≥ 12 months on first-line therapy (HR 0.43, p = 0.007). Findings were largely consistent in the fourth-line cohort (n = 57). Sequencing analyses suggested sustained activity of trabectedin in later lines (p = 0.023), greater benefit of earlier pazopanib use (p = 0.022), and no significant impact of treatment line for gemcitabine + docetaxel combination therapy (p = 0.12).Machine learning-guided variable selection identified clinically relevant predictors of survival in later-line STS. Prior treatment response and histology strongly influence outcomes, and exploratory sequencing analyses suggest differential timing effects across systemic therapy agents.

Keyword(s): Chemotherapy ; Later-line therapy ; Machine learning ; Soft tissue sarcoma ; Therapy sequencing

Note: epub

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Contributing Institute(s):

1. DKTK Koordinierungsstelle München (MU01)

Research Program(s):

1. 899 - ohne Topic (POF4-899) (POF4-899)

Appears in the scientific report 2026

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Database coverage:
; ; ; Article Processing Charges ; Clarivate Analytics Master Journal List ; DOAJ Seal ; Emerging Sources Citation Index ; Fees ; IF < 5 ; JCR ; PubMed Central ; SCOPUS ; Web of Science Core Collection

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