{"doi":"10.1101/2025.09.15.25335723","title":"Bayesian Learning to Reduce Cardiac Risk for Locally Advanced NSCLC Patients Based on Personalized Radiotherapy Prescription","abstract":"Abstract Purpose Radiation-induced heart damage is a significant concern in the treatment of non-small cell lung cancer (NSCLC) that can have debilitating or life-threatening consequences. Current strategies focus on minimizing heart exposure, but individual susceptibility varies. Existing evidence also suggests that a uniform “one-size-fits-all” dosimetric constraint for the heart may not be optimal for all patients. Methods We developed a prospective study using Bayesian continuous learning and adaptation to develop a framework for personalized adaptive radiation treatment (PART) to reduce cardiovascular adverse events (CAEs) among patients with locally advanced NSCLC. The trial includes a Bayesian personalized risk prediction model to guide heart dose constraints; sequential learning to refine the model and the PART; continuous adaptation of the target risk level; and go/no-go monitoring of PART effectiveness in clinical implementation. Elevation of high-sensitivity cardiac troponin T (hs-cTnT) after radiation was used as a surrogate biomarker for grade ≥2 CAEs to allow real-time decision-making. Results As of July 31, 2025, 100 patients have been enrolled and completed radiation treatment. Standard radiation plans were implemented for cohort 1 (50 patients), and PART for cohort 2 (50 patients). The first model incorporated patient- and disease-related factors and mean heart dose (MHD) as risk factors. The average treated MHDs were 7.84 ± 6.30 Gy in cohort 1 and 6.36 ± 6.01 Gy in cohort 2. The incidence of hs-cTnT elevation was lower in cohort 2 (20.5%) than in cohort 1 (31.9%). Within cohort 2, patients who satisfied the PART dose constraint had a markedly lower incidence of hs-cTnT elevation (9.7%) compared with those who exceeded the PART dose constraint (46.2%).. Conclusion Clinical implementation of PART model to guide treatment decision within a prospective trial is feasible. The recommended mean heart dose constraints generated by the first version of PART appear reasonable and clinically relevant. PART was associated with lower incidence of hs-cTnT elevation.","journal":"medRxiv","year":2025,"id":574885,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9511,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1482517,"name":"Mei Chen","orcid":"0009-0009-2838-7677","position":1,"is_corresponding":false},{"id":426708,"name":"Xiaodong Zhang","orcid":"0000-0001-8350-0411","position":2,"is_corresponding":false},{"id":734716,"name":"Tianlin Xu","orcid":"0000-0002-5699-5540","position":3,"is_corresponding":false},{"id":1482518,"name":"Ting Xu","orcid":"0000-0002-1532-1494","position":4,"is_corresponding":false},{"id":1482919,"name":"Rachel C Maguire","orcid":null,"position":5,"is_corresponding":false},{"id":449670,"name":"Kelsey L. 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