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Primary graft dysfunction (PGD) is the leading cause of early morbidity and mortality after lung transplantation. We previously developed an easy to use PGD predictive model utilizing the Lung Transplant Outcomes Group (LTOG) cohort. We therefore sought to demonstrate the net benefit of the model at an external site as a measure of model generalizability. We tested external validation in a well-phenotyped lung transplant cohort from Washington University in St. Louis (WashU) for a PGD predictive model based on lung allocation score, body mass index, pulmonary arterial pressure, recipient total lung capacity, donor and recipient age and gender, donor mode of death, and donor distance to transplant center. We primarily employed decision curve analysis (DCA) to quantify the net benefit of the predictive model and also assessed model discrimination using the c-statistic and calibration using the Hosmer-Lemeshow (H-L) test. The incidence of PGD at WashU was lower than in the LTOG cohort (7% vs 25%); the validation model accounts for the differences in PGD incidence. The model demonstrated good discrimination (c-statistic=0.67) and calibration (H-L p=0.2, where non-significant p-value is good calibration). DCA describes whether the model performs better than alternatives of classifying everyone (or no one) as high PGD risk as well as the net benefit of the model across a range of decision thresholds. The DCA (Figure 1) shows that the predictive model demonstrates significant net benefit in the PGD incidence range 2-15%, incorporating the PGD incidence seen in the WashU cohort. Our simple to implement PGD predictive model demonstrates excellent net benefit, even at centers with differing PGD incidence than the discovery cohort centers. This model can be used to identify recipients at high and low risk for PGD across a range of transplant centers, allowing treatment teams to be prepared for post-transplant complications and identify patients for potential enrollment in targeted intervention studies based on patient risk. [ABSTRACT FROM AUTHOR]

Primary graft dysfunction (PGD) is the leading cause of early morbidity and mortality after lung transplantation. Prior studies highlight the role of donor smoking in poor post-transplant outcomes. We therefore aimed to identify clinical risk factors for PGD after lung transplantation, more accurately assess the impact of donor smoking, and develop an accurate, generalizable PGD prediction model. We performed a 10-center prospective cohort study of patients in the Lung Transplant Outcomes Group from 2012-2018. PGD was defined as grade 3 PGD at 48 or 72 hours after lung reperfusion. We defined donor smoking history by clinical documentation, UNOS-reported donor smoking, or donor cotinine >9 mg/ml from urine collected at organ procurement. Building on our prior PGD prediction models, multivariable logistic regression was used to identify PGD risk factors and develop regularized predictive models with a simple user interface (R shiny). Of 1180 patients, 26% developed PGD and 633 (53%) received an organ from a previously smoking donor. The PGD predictive model included novel predictors of center and donor distance plus recipient age, lung allocation score (LAS), body mass index, pulmonary artery pressure, sex, and indication for transplant; donor age, sex, mechanism of death, and donor distance; and interaction terms for LAS and donor distance. The interface allows for real-time assessment of PGD risk for any donor/recipient combination. The predictive model offers decision making benefit in the PGD risk range of 0.15-0.5. Donor smoking was associated with increased risk of PGD but not patient mortality (Figure 1). We developed a clinically applicable PGD predictive algorithm based on modern lung transplant practices to aid in transplant decision making, post-transplant care, and to facilitate development of enriched PGD treatment trials. Donor smoking is a risk factor for PGD development but is not associated with increased mortality, potentially because of a lower risk phenotype of PGD occurring in smoking donor recipients. [ABSTRACT FROM AUTHOR]