A novel risk score that incorporates recipient and donor variables to predict 1-year mortality in the current era of lung transplantation.
Grimm JC, Valero V, et al.Journal of Heart & Lung Transplantation 2015; 34(11): 1449-1454.
Aims
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.
Interventions
Patients were randomly divided into derivation (80%) and validation (20%) cohorts. Univariate analysis was performed on the derivation cohort to identify recipient and donor factors that predicted 1-year mortality.
Participants
9,185 adult (≥18 years) patients undergoing LTx
Outcomes
The primary outcomes measured were observed mortality rates and predicted mortality rates.
Follow-up
1 year
CET Conclusions
The Cardiac Surgical Division and the Division of Pulmonary and Critical Care at the Johns Hopkins Hospital have investigated the UNOS database for all adult recipients of a lung transplant between 2005 and the end of 2012 for risk factors involved with one-year patient mortality. The population, which comprised some 9,000 patients who underwent a lung transplant, were randomly allocated to a derivation group or a validation group at a ratio of 4:1. One-year mortality in the total group was 18%. A logistic regression model was used in the derivation group to identify factors that both in the donor and the recipient were associated with one-year mortality of the patient. This enabled the investigators to produce a risk score (MALT) which stood up to analysis in the validation cohort of patients. The Kaplan Meier survival rates showed a very good correlation with patients that were regarded as high risk based on the MALT score, with a somewhat lower mortality in the intermediate risk while patients defined as low risk had the lowest mortality at one year. This is the first scoring system which incorporates data from the recipient as well as the donor to predict one-year mortality. Thus this would seem to be a useful tool for predicting the risk of patient mortality at one year at the time of lung transplantation.
Quality notes
Quality Assessment not appropriate
Trial registration
None