Risk Prediction Model for Cutaneous Squamous Cell Carcinoma in Adult Cardiac Allograft Recipients

Background: Heart transplant recipients are at higher risk of developing skin cancer than the general population due to the long-term immunosuppression treatment. Cancer has been reported as one of the major causes of morbidity and mortality for patients after heart transplantation. Among different types of skin cancers, cutaneous squamous cell carcinoma (cSCC) is the most common one, which requires timely screening and better management.

Aim: To identify risk factors and predict the incidence of cSCC for heart transplant recipients.

Methods: We retrospectively analyzed adult heart transplant recipients between 2000 and 2015 extracted from the United Network for Organ Sharing registry. The whole dataset was randomly divided into a derivation set (80%) and a validation set (20%). Uni- and multivariate Cox regression were done to identify significant risk factors associated with the development of cSCC. Receiver operating charac-teristics curves were generated and area under the curve (AUC) was calculated to assess the accuracy of the prediction model. Based on the selected risk factors, a risk scoring system was developed to stratify patients into different risk groups. A cumulative cSCC-free survival curve was generated using the Kaplan-Meier method for each group, and the log-rank test was done to compare the inter-group cSCC rates.

Results: There were 23736 heart-transplant recipients during the study period, and 1827 of them have been reported with cSCC. Significant predictors of post-transplant cSCC were older age, male sex, white race, recipient and donor human leukocyte antigen (HLA) mismatch level, malignancy at listing, diagnosis with restrictive myopathy or hypertrophic myopathy, heart re-transplant, and induction therapy with OKT3 or daclizumab. The multivariate model was used to predict the 5-, 8- and 10-year incidence of cSCC and respectively provided AUC of 0.79, 0.78 and 0.77 in the derivation set and 0.80, 0.78 and 0.77 in the validation set. The risk scoring system assigned each patient with a risk score within the range of 0-11, based on which they were stratified into 4 different risk groups. The predicted and observed 5-year probability of developing cSCC match well among different risk groups. In addition, the log-rank test indicated significantly different cSCC-free survival across different groups.

Conclusion: A risk prediction model for cSCC among heart-transplant recipients has been generated for the first time. It offers a c-statistic of ≥ 0.77 in both derivation and validation sets.