The International Heart Transplant Survival Algorithm (IHTSA): A New Model to Improve Organ Sharing and Survival

<div><p>Background</p><p>Heart transplantation is life saving for patients with end-stage heart disease. However, a number of factors influence how well recipients and donor organs tolerate this procedure. The main objective of this study was to develop and validate a flexible risk model for prediction of survival after heart transplantation using the largest transplant registry in the world.</p><p>Methods and Findings</p><p>We developed a flexible, non-linear artificial neural networks model (IHTSA) and classification and regression tree to comprehensively evaluate the impact of recipient-donor variables on survival over time. We analyzed 56,625 heart-transplanted adult patients, corresponding to 294,719 patient-years. We compared the discrimination power with three existing scoring models, donor risk index (DRI), risk-stratification score (RSS) and index for mortality prediction after cardiac transplantation (IMPACT). The accuracy of the model was excellent (C-index 0.600 [95% CI: 0.595–0.604]) with predicted versus actual 1-year, 5-year and 10-year survival rates of 83.7% versus 82.6%, 71.4% – 70.8%, and 54.8% – 54.3% in the derivation cohort; 83.7% versus 82.8%, 71.5% – 71.1%, and 54.9% – 53.8% in the internal validation cohort; and 84.5% versus 84.4%, 72.9% – 75.6%, and 57.5% – 57.5% in the external validation cohort. The IHTSA model showed superior or similar discrimination in all of the cohorts. The receiver operating characteristic area under the curve to predict one-year mortality was for the IHTSA: 0.650 (95% CI: 0.640–0.655), DRI 0.56 (95% CI: 0.56–0.57), RSS 0.61 (95% CI: 0.60–0.61), and IMPACT 0.61 (0.61–0.62), respectively. The decision-tree showed that recipients matched to a donor younger than 38 years had additional expected median survival time of 2.8 years. Furthermore, the number of suitable donors could be increased by up to 22%.</p><p>Conclusions</p><p>We show that the IHTSA model can be used to predict both short-term and long-term mortality with high accuracy globally. The model also estimates the expected benefit to the individual patient.</p></div

Cumulative mortality for the internal validation cohort (IVC).

<p>The black solid line shows the observed cumulative mortality and dotted lines show the 95% confidence interval (estimated with Kaplan-Meier failure function) in the IVC. The red solid line shows the predicted survival for transplanted patients in the IVC.</p

Baseline characteristics of recipients in the derivation and validation cohorts.

<p><i>a <b>b</b> c</i> represent the lower quartile <i>a</i>, the median <i><b>b</b></i>, and the upper quartile <i>c</i> for continuous variables. Numbers within parenthesis are frequencies. The numbers were calculated from patients with data available.</p><p>^#Drug or insulin treated diabetes mellitus.</p><p>^†Drug treated systemic hypertension.</p><p>^‡Infection requiring intravenous antibiotic therapy within two weeks prior to transplant.</p><p>*Previous transplant—previous kidney, liver, pancreas, pancreas islet cells, heart, lung, intestine and/or bone marrow transplant. COPD, chronic obstructive pulmonary disease; DC, derivation cohort; HLA, human leukocyte antigen; ISHLT, international society for heart and lung transplantation; IVC, internal validation cohort; NTTD, Nordic thoracic transplantation database; PRA, panel reactive antibody; PVR, pulmonary vascular resistance; SPP, systolic pulmonary pressure. TVC, temporal validation cohort. Statistical tests: Unpaired Mann-Whitney U-tests or and χ² tests.</p><p>Baseline characteristics of recipients in the derivation and validation cohorts.</p

Comparison of C-index between different risk models used to predict overall survival.

<p>*p < 0.05</p><p>^†p ≤ 0.001 compared with ITHSA. CI, confidence interval; DC, derivation cohort; DRI, donor risk index for transplantation (reported in the paper by Weiss et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0118644#pone.0118644.ref006" target="_blank">6</a>]); IMPACT, index for mortality prediction after cardiac transplantation (reported in the paper by Weiss et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0118644#pone.0118644.ref007" target="_blank">7</a>]); ITHSA, international heart transplantation survival algorithm; IVC, internal validation cohort; NTTD, Nordic thoracic transplantation database; RSS, risk-stratification score (reported in the paper by Hong et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0118644#pone.0118644.ref009" target="_blank">9</a>]); TVC, temporal validation cohort.</p><p>Comparison of C-index between different risk models used to predict overall survival.</p

Influence of age and duration of ischemia on survival.

<p>Panel (A) illustrates, in matched cohorts, the influence of donor age and recipient age on survival when the duration of ischemia is fixed to 2 hours, and panels B, C, and D illustrate the influence on survival at 3, 4, and 5 hours of ischemia, respectively. The colored solid lines show the predicted survival in years (dark blue: worst; dark red: best).</p

Schematic illustration of the variable-ranking process for the derivation cohort.

<p>Panel (A). Step I: training of the survival model using fivefold cross-validation and a committee machine with 10 members. Step II: variable-ranking using the trained survival model from step I. Each variable is omitted from the model and the decrease in performance is recorded. The variable resulting in the least reduction in performance is removed. Steps I–II are repeated until only one variable is left. A ranking list is constructed using the elimination order. Panel (B). Performance as a function of number of variables included. The C-index is plotted against the number of input variables, where order is in terms of decreasing importance. Variables with a high index number are least important. Panel (C). The relative importance of 20 of the 43 top-ranked variables. The box plot for each variable is created from the series of C-index changes that was the result of removal of the variable during the ranking procedure.</p

Time-dependent hazard ratios for the 32 recipient risk variables included in the IHTSA model.

<p>The data are median hazard ratio together with 95% confidence interval for the different time points estimated from 10,000 bootstrap samples.</p><p>^#Drug or insulin treated diabetes mellitus.</p><p>^†Drug treated systemic hypertension.</p><p>^‡Infection requiring intravenous antibiotic therapy within two weeks prior to transplant.</p><p>*Previous transplant—previous kidney, liver, pancreas, pancreas islet cells, heart, lung, intestine and/or bone marrow transplant. ECMO, extracorporeal membrane oxygenation; ICU, intensive care unit; ITHSA, international heart transplantation survival algorithm; HLA, human leukocyte antigen; PRA, panel reactive antibody; PVR, pulmonary vascular resistance; SPP, systolic pulmonary pressure.</p><p>Time-dependent hazard ratios for the 32 recipient risk variables included in the IHTSA model.</p

Predicted cumulative mortality for different organ allocation models.

<p>In panel (A) the graph shows the number of transplanted patients for The IHTSA model (red lines), Clinical model (blue lines) and Control (green lines) influenced by the size of the waiting list. The internal validation cohort (IVC) is presented with solid lines, temporal validation cohort (TVC) dashed lines and external validation cohort NTTD dotted lines. In panel (B) the graph shows the difference in predicted cumulative mortality as a function of time since heart transplantation for a waiting list including 50 patients in the IVC (N = 8,569). The solid black lines present the observed mortality and the dotted lines the predicted mortality for all patients. Panel (C) shows the difference in predicted cumulative mortality for IHTSA model influenced by the number of patients on the waiting list (NW). In panel (D) the results from the sub analysis including patients from the IVC, who were not treated in the intensive care unit and were not on life support prior to transplantation, are presented (N = 4,868).</p

The International Heart Transplantation Survival Algorithm (IHTSA) as a web application.

<p>The IHTSA has been implemented as an interactive program that estimates median, 1-, 5-, and 10-year survival, and the benefit of adding (or removing) properties from an individual recipient and the potential donor (<a href="http://www.ihtsa.med.lu.se" target="_blank">http://www.ihtsa.med.lu.se</a>). ECMO, extracorporeal membrane oxygenation; HLA, human leukocyte antigen; PRA, panel reactive antibody; PVR, pulmonary vascular resistance; SPP, systolic pulmonary pressure. ^†Drug treated systemic hypertension. ‡Infection requiring intra venous antibiotic therapy within two weeks prior to transplant. *Previous transplant——previous kidney, liver, pancreas, pancreas islet cells, heart, lung, intestine and/or bone marrow transplant.</p

Influence of weight and gender match.

<p>Panel (A) illustrates, in matched cohorts, the influence of donor weight and recipient weight on survival for male-male donor-recipient pairs, and panels B, C, and D illustrate the influence on survival for female-male, female-female, and male-female donor-recipient pairs, respectively. The colored solid lines show the predicted survival in years (dark blue: worst; dark red: best).</p