BackgroundPredicting post-transplant (PT) survival in lung allocation remains an elusive goal. We analyzed the impact of donor factors on PT survival and how these relationships vary among transplant recipients. MethodsWe studied primary bilateral lung transplant recipients (n=7,609) from the US Scientific Registry of Transplant Recipients (19 February 2015 - 1 February 2020). Main and interaction effects were evaluated and adjusted across candidate age, sex, and diagnosis. Models predicting PT survival were compared to the PT composite allocation score model (PT-CAS): 1. Cox regression donor multivariable model (COX), 2. COX + PT-CAS, 3. random forest model (RF), 4. RF + PT-CAS. Model discrimination and calibration measures were compared. ResultsInteractions between donor and recipient factors emerged by – age: lower survival for DCD organs for recipients aged 55-69 years, donor smoking for recipients aged 30-54 and 70+, Hispanic donor for recipients < 30, non-Hispanic Black (NHB) donor for recipients aged 30+; sex: CMV mismatch for males; diagnosis: higher donor recipient weight ratio for diagnosis Group C (e.g.CF), donor diabetes for diagnosis Group D (e.g. IPF). COX and RF models performed similarly to PT-CAS; however, the combined COX PT-CAS model had improved discrimination (1y AUC PT-CAS 0.609 vs. 1y AUC COX + PT-CAS 0.626) and improved calibration across a broader range of predicted risk. ConclusionThe influence of donor factors on recipient post-transplant survival differed by age, sex, and diagnosis. The addition of donor factors to existing models predicting posttransplant survival led to only modest improvement in prediction accuracy. Future efforts may focus on optimizing matching strategies to improve donor utilization.