Routine laboratory trajectories encode the onset of organ-level complications in cancer
Organizations: Department of Diagnostic and Interventional Radiology, School of Medicine and Health, TUM Klinikum, Rechts der Isar, Technical University of Munich, Germany. · Department of Medicine III, School of Medicine and Health, TUM Klinikum, Rechts der Isar, Technical University of Munich, Germany. · Chair of Medical Informatics, Institute of Artificial Intelligence in Medicine and Healthcare, School of Medicine and Health, TUM Klinikum, Rechts der Isar, Technical University of Munich, Germany. · Clinical Department of Gynecology, School of Medicine and Health, TUM Klinikum, Rechts der Isar, Technical University of Munich, Munich, Germany. · Department of Clinical Chemistry and Pathobiochemistry, School of Medicine and Health, TUM Klinikum, Rechts der Isar, Technical University of Munich, Germany. · Department of Radiology, Charité - Universitätsmedizin Berlin, Berlin, Germany. · Department of Cardiovascular Radiology and Nuclear Medicine, School of Medicine and Health, TUM Klinikum, German Heart Center, Technical University of Munich. · Department of Neuroradiology, School of Medicine and Health, TUM Klinikum, Rechts der Isar, Technical University of Munich, Germany. · TranslaTUM, Center for Translational Cancer Research, Technical University of Munich, Munich, Germany. · Deutsches Konsortium für Translationale Krebsforschung, Heidelberg, Germany. · Bavarian Cancer Research Center, Munich, Germany.
Abstract
Routine laboratory panels drawn during cancer treatment constitute longitudinal physiological recordings of organ function, yet their temporal structure is discarded by single-timepoint prognostic tools. A transformer trained on 2,777,595 laboratory measurements from 3,905 patients with multiple myeloma or ovarian cancer predicted the two-year onset of 162 treatment-associated complications, including therapy-related myelodysplastic syndromes, spanning eight clinical categories, achieving 1.5- to 6.1-fold enrichment above prevalence at the group level. It matched or outperformed non-sequential baselines across grouped endpoints (AUROC gains up to +0.11), demonstrating that longitudinal laboratory trajectories capture evolving complication-specific physiology inaccessible from isolated measurements. Predictions generalised across both cancers, divergence concentrating in disease-specific complications, and biomarker masking recovered signatures consistent with established pathophysiology. External validation on MIMIC-IV and MMRF CoMMpass confirmed transferability across independent healthcare systems (AUROC up to 0.85). Routine oncological laboratory data encode organ deterioration weeks to months before clinical onset, enabling complication-specific surveillance without additional testing infrastructure.