TY  - JOUR
AU  - Gromke, Tanja
AU  - Durand, Juliane
AU  - Mueller, Tamara T
AU  - Neumaier, Felix
AU  - Liffers, Sven T
AU  - Richly, Heike
AU  - Grubert, Matthias
AU  - Haubold, Johannes
AU  - Theysohn, Jens
AU  - Kalkavan, Halime
AU  - Bechrakis, Nikolaos E
AU  - Schuler, Martin
AU  - Braren, Rickmer
AU  - Schaarschmidt, Benedikt M
AU  - Siveke, Jens T
TI  - Clinical and radiomics parameter prognostication in metastatic uveal melanoma patients treated with hepatic arterial infusion chemotherapy.
JO  - The oncologist
VL  - 31
IS  - 1
SN  - 1083-7159
CY  - Oxford
PB  - Oxford University Press
M1  - DKFZ-2025-03032
SP  - oyaf385
PY  - 2026
N1  -  Volume 31, Issue 1, January 2026, oyaf385, Published:22 December 2025
AB  - Metastatic uveal melanoma (MUM) has a poor prognosis, but hepatic arterial infusion chemotherapy (HAIC) may improve outcomes in patients with hepatic metastases. To identify reliable prognostic factors for patient stratification and treatment allocation, we analyzed the clinical and imaging data from a large single-center cohort using machine learning (ML) models.Pre- and post first treatment clinical data of 235 patients with MUM treated with HAIC between 2009 and 2019 were retrospectively analyzed using Cox regression to identify prognostic factors for overall survival (OS) and time to change treatment strategy (TTCS). Furthermore, ML models were trained on clinical and computed tomography (CT) data for endpoint prediction.Pre-treatment multivariate analysis identified elevated lactate dehydrogenase (LDH) (OS: 6.5 vs. 16.4 months, hazard ratio (HR)=1.87, p = 0.006) and gamma-glutamyl transpeptidase (GGT) (OS: 7.6 vs. 16.4 months, HR = 1.67, p = 0.012) as prognostic factors for inferior OS. Decreased albumin (TTCS: 1.3 vs. 6.1 months, HR = 6.26, p < 0.001) and elevated LDH (TTCS: 2.9 vs. 7.6 months, HR = 1.72, p = 0.011) and alanine aminotransferase (ALT) (TTCS: 3.7 vs. 6.4 months, HR = 1.65, p = 0.004) predicted shorter TTCS. Scoring enhanced the power of the prognosticators for OS and TTCS. Post first treatment multivariate analysis emphasized the importance of inflammation management and liver protection. ML models incorporating radiomics features from base line CT imaging were not superior to models based on pre-treatment clinical data alone.We identified independent but synergistic prognostic factors for outcome stratification to guide treatment decisions and optimize patient management. ML-based radiomics features did not significantly enhance prognostic performance.
KW  - hepatic arterial infusion chemotherapy (Other)
KW  - independent prognostic factors (Other)
KW  - machine learning (Other)
KW  - metastatic uveal melanoma (Other)
KW  - multivariate analysis (Other)
KW  - radiomics (Other)
LB  - PUB:(DE-HGF)16
C6  - pmid:41429572
DO  - DOI:10.1093/oncolo/oyaf385
UR  - https://inrepo02.dkfz.de/record/307433
ER  -