Skip to main navigation Skip to search Skip to main content

Risk Prediction of Post-Transplant Lymphoproliferative Disease in Heart Transplant Patients

Research output: Contribution to journalArticlepeer-review

Abstract

Post-transplant lymphoproliferative disease (PTLD) represents the second most frequent malignancy in cardiac allograft recipients and constitutes up to 10% of de novo cancers. This study attempts to determine risk factors in adult heart transplant patients to develop a risk prediction model using the Scientific Registry of Transplant Recipients database and the lasso regression model. Data on 55, 150 adult heart transplant patients (1987–2021) were extracted. The χ2/Wilcoxon tests were performed to identify significant variables (p < 0.05). The dataset was divided into two. One set was used for model development/validation, and the other for simulating external validation. Lasso logistic regression models were developed to predict disease at 1, 3, and 5 years post-transplant. Cyclosporine, positive donor Epstein–Barr Virus (EBV) IgG, induction with OKT3, and the donor’s human leukocyte antigen (HLA) B38 antigen had a higher risk at 3 and 5 years post-transplant. African American recipients have a lower risk of developing PTLD as compared with other ethnic groups. This is the first report of a lasso regression model with good discriminatory power (c statistic of >0.7) in testing and validation cohorts. Future studies need to explore advanced modeling technologies and artificial intelligence systems capable of capturing patient diversity.

Original languageEnglish (US)
Pages (from-to)924-931
Number of pages8
JournalASAIO Journal
Volume71
Issue number11
DOIs
StatePublished - Nov 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Bioengineering
  • General Medicine
  • Biomaterials
  • Biomedical Engineering

Fingerprint

Dive into the research topics of 'Risk Prediction of Post-Transplant Lymphoproliferative Disease in Heart Transplant Patients'. Together they form a unique fingerprint.

Cite this