New Risk Score Outperforms Current Model, Could Improve Heart Transplant Allocation


A novel risk score developed by University of Chicago investigators outperformed conventional models in predicting death in heart transplant candidates, which could help bring the field closer to optimal and equitable allocation.

William Parker, MD, MS, PhD | Credit: UChicago Medicine

William Parker, MD, MS, PhD
Credit: UChicago Medicine

A team of investigators based out of the University of Chicago have created and validated a novel risk score for predicting death in patients waiting for a heart transplant they believe could revolutionize care.

Through an assessment 46 variables, including demographic, clinical, laboratory, and hemodynamic parameters, investigators developed the US candidate risk score (US-CRS), which, when assessed in a validation study, bested the conventional 6-status model and the French-CRS.

“In this registry-based study of US heart transplant candidates, a continuous multivariable allocation score outperformed the 6-status system in rank ordering heart transplant candidates by medical urgency and may be useful for the medical urgency component of heart allocation,” investigators wrote.

Few subspecialties in cardiology have celebrated the same level of practice-changing advancement in the last decade as advanced heart failure and transplant specialists. These advancements, which have occurred in the technological and pharmacologic arenas, are not just welcomed, but necessary as the impact heart failure on public health systems is beginning to near a crisis point.

According to 2023 report from the Heart Failure Society of America, the lifetime risk of heart failure for US adults has increased to 24%, with approximately 1 in 4 developing heart failure in their lifetime. The same report suggested estimated 6.7 million US adults have heart failure and this figure is project to increase to 8.5 million by 2030.2

Citing deficiencies in the current 6-status scoring system, including the potential for manipulation, a team led by senior investigator William Parker, MD, MS, PhD, assistant professor of Medicine and assistant professor of Public Health Sciences at the University of Chicago Medicine, sought to develop and validate a candidate risk score that incorporates current clinical, laboratory, and hemodynamic data.1

US-CRC Scoring for Heart Transplant Allocation

Named the US candidate risk score (US-CRS) model, the scoring system leveraged the already existing framework of the French-CRS model to develop and validate. In total, investigators collected 46 potential predicts of death prior to transplant. This included all of the variables from the French-CRS model as well as durable left ventricular assist device.1

In the new model, investigators used the race-neutral CKD-EPI Creatinine Equation to estimate eGFR. The investigators’ definition of short-term MCS included extracorporeal membrane oxygenation, temporary surgical LVAD, and biventricular assist device without discharge, and excluded IABP and percutaneous endovascular left ventricular assist devices, citing the unclear association between the use of these devices and medical urgency.1

Investigators noted multiple additional laboratory results and hemodynamic predictors with known associations with mortality in patients with advanced heart failure were also included. The score also included an interaction term for the whether the center reported-proBNP or regular BNP. Of note, this model did not include hemodynamics based on the decision that its inclusion did not yield major improvements and measurements of hemodynamics are susceptible to manipulation.1

The final iteration of the US-CRS model was selected based on anticipated ease of implementation, coefficient significance, the area under the receiver operating characteristic curve (AUC), and the value of the Akaike information criterion in the training dataset.1

Testing the New Scoring System

The dataset used in this registry-based observational study was obtained using information from the Scientific Registry of Transplant Recipients (SRTR)—a data system including donors, wait-listed candidates, and transplant recipients in the US. The study population included all adult heart transplant waiting list candidates listed from January 1, 2019 through December 31, 2022. Investigators pointed out random sampling was used to select 97 centers (70%) for model training and 41 centers (30%) for model testing.

The primary outcomes of interest defined as the time-dependent AUC for death without transplant within 6 weeks and the overall survival concordance (c-index) with integrated AUC.1

Overall, 16,905 transplant candidates were included in the study. This cohort had a mean age of 53 (Standard Deviation, 13) years, 73% were male, and 58% were White. Among this cohort, 4.7% (n=796) died without a transplant.1

Upon analysis, results indicated the AUC for death within 6 weeks of listing for the US-CRS model was 0.79 (95% Confidence Interval [CI], 0.75-0.83). In contrast, the French-CRS model achieved an AUC for death within 6 weeks of 0.72 (95% CI, 0.67-0.76) and 6-status model achieved an AUC of 0.68 (95% CI, 0.62-0.73). Further analysis suggested the overall c-index were 0.76 (95% CI, 0.73-0.80), 0.69 (95% CI, 0.65-0.73), and 0.67 (95% CI, 0.63-0.71) for the US-CRS model, the French-CRS model, and the 6-status model, respectively.1

Investigators highlighted the US-CRS model had significantly greater sensitivity and specificity than each of the possible status system allocation thresholds. Additionally, the greatest improvements observed with the new model were a 14.2% absolute sensitivity improvement in status 2 and a 31.8% reduction in the false positive rate in status 5.1

Investigators called attention to multiple limitations within their study to consider when interpreting results. These included, but were not limited to, potential for recall or misclassification bias in SRTR variables, being limited to OPTN or Social Security Administration-verified deaths, and a large number of patients being censored by transplant.1

In a linked editorial, Michelle Kittleson, MD, PhD, director of Education in Heart Failure and Transplantation at the Smidt Heart Institute at Cedars-Sinai, called further attention to the need for reform in heart transplant allocation within the US, commended the authors for their efforts, and urged governing bodies to consider the results of the current study with urgency.3

“The current allocation system is imperfect with the potential for manipulation, however well-intentioned, to garner higher priority for some candidates without appropriate medical justification. Zhang et al report that a continuous allocation score can provide a more accurate assessment of medical urgency,” Kittleson wrote.3 “Hopefully, the UNOS/OPTN will use this elegant analysis as the framework for a continuous distribution model for heart transplant allocation.”

For more perspective on this study, check out our accompanying interview with Kittleson.


  1. Zhang KC, Narang N, Jasseron C, et al. , Kim Y, Lee DH, et al. Development and Validation of a Risk Score Predicting Death Without Transplant in Adult Heart Transplant Candidates. JAMA. doi:10.1001/jama.2023.27029
  2. Bozkurt B, Ahmad T, Alexander KM, et al. Heart Failure Epidemiology and Outcomes Statistics: A Report of the Heart Failure Society of America. J Card Fail. 2023;29(10):1412-1451. doi:10.1016/j.cardfail.2023.07.006
  3. Kittleson MM. Optimizing Beneficence and Justice in Heart Transplant Allocation. JAMA. doi:10.1001/jama.2023.27029

Related Videos
Stephanie Nahas, MD, MSEd | Credit: Jefferson Health
Kelley Branch, MD, MS | Credit: University of Washington Medicine
Alayne Markland, DO | Credit:
Timothy Wilt, MD, MPH | Credit: ACP
© 2024 MJH Life Sciences

All rights reserved.