A novel risk score that incorporates recipient and donor variables to predict 1-year mortality in the current era of lung transplantation

Joshua C. Grimm, Vicente Valero, J. Trent Magruder, Arman Kilic, Samuel P. Dungan, Leann L. Silhan, Pali D. Shah, Bo S. Kim, Christian A. Merlo, Christopher M. Sciortino, Ashish S. Shah

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


Background In this study we sought to construct a novel scoring system to pre-operatively stratify a patient's risk of 1-year mortality after lung transplantation (LTx) based on recipient- and donor-specific characteristics. Methods The UNOS database was queried for adult (≥18 years) patients undergoing LTx between May 1, 2005 and December 31, 2012. The population was randomly divided in a 4:1 fashion into derivation and validation cohorts. A multivariable logistic regression model for 1-year mortality was constructed within the derivation cohort. Points were then assigned to independent predictors (p < 0.05) based on relative odds ratios. Risk groups were established based on score ranges. Results During the study period, 9,185 patients underwent LTx and the 1-year mortality was 18.0% (n = 1,654). There was a similar distribution of variables between the derivation (n = 7,336) and validation (n = 1,849) cohorts. Of the 14 covariates included in the final model, 9 were ultimately allotted point values (maximum score = 70). The model exhibited good predictive strength (c = 0.65) in the derivation cohort and demonstrated a strong correlation between the observed and expected rates of 1-year mortality in the validation cohort (r = 0.87). The low-risk (score 0 to 11), intermediate-risk (score 12 to 21) and high-risk (score ≥22) groups had a 10.8%, 17.1% and 32.0% risk of mortality (p < 0.001), respectively. Conclusions This is the first scoring system that incorporates both recipient- and donor-related factors to predict 1-year mortality after LTx. Its use could assist providers in the identification of patients at highest risk for poor post-transplant outcomes.

Original languageEnglish (US)
Pages (from-to)1449-1454
Number of pages6
JournalJournal of Heart and Lung Transplantation
Issue number11
StatePublished - Nov 2015


  • lung transplantation
  • mortality
  • multivariable regression
  • risk stratification

ASJC Scopus subject areas

  • Surgery
  • Pulmonary and Respiratory Medicine
  • Cardiology and Cardiovascular Medicine
  • Transplantation


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