Retrospective Cohort Study
Copyright ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Transplant. Mar 18, 2021; 11(3): 54-69
Published online Mar 18, 2021. doi: 10.5500/wjt.v11.i3.54
Risk prediction model for cutaneous squamous cell carcinoma in adult cardiac allograft recipients
Nandini Nair, Zhiyong Hu, Dongping Du, Enrique Gongora
Nandini Nair, Division of Cardiology, Department of Internal Medicine, Texas Tech Health Sciences Center, Lubbock, TX 79430, United States
Zhiyong Hu, Dongping Du, Department of Industrial, Manufacturing and Systems Engineering, Texas Tech University, Lubbock, TX 79409, United States
Enrique Gongora, Department of Cardiothoracic Surgery, University of Alabama at Birmingham, Birmingham, AL 35233, United States
Author contributions: Nair N, Du D and Hu Z participated in the data acquisition, research design, data analysis, and the writing of the paper; Gongora E contributed to conception of the research idea.
Supported by National Science Foundation, No. CMMI-1728338.
Institutional review board statement: This is to certify that this study was done on a public database with decoded data and no patient identifiable information. The database was provided by the United Network of Organ Sharing. Hence the study is exempted from the Institutional Review Board review.
Informed consent statement: The study used a decoded database provided by the United Network of Organ sharing with no patient identifiers hence there was no requirement for informed consent. This was a retrospective database analysis.
Conflict-of-interest statement: None of the authors have any conflict of interest with respect to this research work.
Data sharing statement: No additional data are available.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Nandini Nair, MD, PhD, Professor, Division of Cardiology, Department of Internal Medicine, Texas Tech Health Sciences Center, 3601 4th Street, Lubbock, TX 79430, United States. nandini.nair@ttuhsc.edu
Received: September 6, 2020
Peer-review started: September 6, 2020
First decision: December 1, 2020
Revised: December 25, 2020
Accepted: February 19, 2021
Article in press: February 19, 2021
Published online: March 18, 2021
Processing time: 192 Days and 14.4 Hours
Abstract
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.

Keywords: Cutaneous squamous cell carcinoma; Heart transplantation; Cox proportional hazard model; Risk assessment; Squamous cell carcinoma; Mortality outcomes

Core Tip: We retrospectively analyzed 23736 heart-transplant recipients between 2010 and 2015. Eight risk factors associated with post-transplant cutaneous squamous cell carcinoma were identified, including older age, male sex, lower human leukocyte antigen mismatch level, white race, malignancy at listing, diagnosis with restrictive myopathy or hypertrophic myopathy, heart re-transplant, induction therapy with OKT3 or daclizumab. A multivariate risk prediction model was developed with c-statistics of ≥ 0.77 in both derivation and validation sets. A risk scoring system was designed to stratify patients into 4 risk groups based on their total risk scores. The predicted and observed 5-year probability of developing cutaneous squamous cell carcinoma match well among different risk groups.