The Accuracy of Initial U.S. Heart Transplant Candidate Rankings

Pelzer, Kenley M.; Zhang, Kevin C; Lazenby, Kevin; Narang, Nikhil; Churpek, Matthew M; Anderson, Allen S.; Parker, William F.

doi:10.1016/j.jchf.2023.02.005

Cited by 3 publications

(3 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our definition of short-term MCS included extracorporeal membrane oxygenation (ECMO), temporary surgical LVAD, and biventricular assist device without discharge, and excluded IABP and percutaneous endovascular left ventricular assist devices given the unclear association between the use of these devices and medical urgency . We then added additional laboratory results (albumin, sodium, and aspartate aminotransferase) and hemodynamic predictors (cardiac power output [CPO], aortic pulsatility index [API], and pulmonary artery pulsatility index [PAPi]) that have known associations with mortality in patients with advanced heart failure . We also included an interaction term for the model for whether the center reported N-terminal pro–B-type natriuretic peptide (NT-proBNP) or regular BNP.…”

Section: Methodsmentioning

confidence: 99%

“…Waiting candidates are assigned a priority rank for each donor organ according to distance from the donor hospital, status, and waiting time. Despite a revision in October 2018 that expanded the number of statuses, the current heart allocation system is susceptible to manipulation from overtreatment and exception requests, does not use important laboratory measures of illness severity, and has only moderate predictive ability to rank order candidates according to medical urgency . It is also unclear how the categorical 6-status system will be implemented in the forthcoming continuous distribution system, which will require a medical urgency score…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Development and Validation of a Risk Score Predicting Death Without Transplant in Adult Heart Transplant Candidates

Zhang,

Narang,

Jasseron

et al. 2024

JAMA

Self Cite

View full text Add to dashboard Cite

ImportanceThe US heart allocation system prioritizes medically urgent candidates with a high risk of dying without transplant. The current therapy-based 6-status system is susceptible to manipulation and has limited rank ordering ability.ObjectiveTo develop and validate a candidate risk score that incorporates current clinical, laboratory, and hemodynamic data.Design, Setting, and ParticipantsA registry-based observational study of adult heart transplant candidates (aged ≥18 years) from the US heart allocation system listed between January 1, 2019, and December 31, 2022, split by center into training (70%) and test (30%) datasets. Adult candidates were listed between January 1, 2019, and December 31, 2022.Main Outcomes and MeasuresA US candidate risk score (US-CRS) model was developed by adding a predefined set of predictors to the current French Candidate Risk Score (French-CRS) model. Sensitivity analyses were performed, which included intra-aortic balloon pumps (IABP) and percutaneous ventricular assist devices (VAD) in the definition of short-term mechanical circulatory support (MCS) for the US-CRS. Performance of the US-CRS model, French-CRS model, and 6-status model in the test dataset was evaluated by time-dependent area under the receiver operating characteristic curve (AUC) for death without transplant within 6 weeks and overall survival concordance (c-index) with integrated AUC.ResultsA total of 16 905 adult heart transplant candidates were listed (mean [SD] age, 53 [13] years; 73% male; 58% White); 796 patients (4.7%) died without a transplant. The final US-CRS contained time-varying short-term MCS (ventricular assist–extracorporeal membrane oxygenation or temporary surgical VAD), the log of bilirubin, estimated glomerular filtration rate, the log of B-type natriuretic peptide, albumin, sodium, and durable left ventricular assist device. In the test dataset, the AUC for death within 6 weeks of listing for the US-CRS model was 0.79 (95% CI, 0.75-0.83), for the French-CRS model was 0.72 (95% CI, 0.67-0.76), and 6-status model was 0.68 (95% CI, 0.62-0.73). Overall c-index for the US-CRS model was 0.76 (95% CI, 0.73-0.80), for the French-CRS model was 0.69 (95% CI, 0.65-0.73), and 6-status model was 0.67 (95% CI, 0.63-0.71). Classifying IABP and percutaneous VAD as short-term MCS reduced the effect size by 54%.Conclusions and RelevanceIn 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.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development and Validation of a Risk Score Predicting Death Without Transplant in Adult Heart Transplant Candidates

Zhang,

Narang,

Jasseron

et al. 2024

JAMA

Self Cite

View full text Add to dashboard Cite

show abstract

“…A formal prognostic model that accurately stratifies waitlisted end-stage heart failure (HF) patients based on medical urgency is nonexistent. The need for such a model was recently highlighted by Pelzer et al, who determined the current allocation system had only a moderate ability to successfully rank transplant candidates according to medical urgency 5 .…”

Section: Introductionmentioning

confidence: 99%

The Colorado Heart Failure Acuity Risk Model (CHARM) Score: A Mortality Risk Model for Waitlisted Cardiac Transplant Patients

Murphy,

Park,

Allen

et al. 2023

Preprint

View full text Add to dashboard Cite

Although the Organ Procurement and Transplantation network provides structured policies and guidance for waitlisted cardiac transplant patients, the heart transplantation community lacks a mathematical model that can accurately estimate the short-term risk of death associated with being waitlisted. We present a multivariable, prognostic model and risk management strategy for adult waitlisted heart transplant patients (N=1,965) from the Scientific Registry of Transplant Recipients (SRTR) database that were waitlisted from January 1, 2008, to September 2, 2022. To independently validate each model, we randomly split this cohort into a discovery set (N=1,174) and validation set (N=784). Twelve independent patient attributes were selected, and three linear regression formulas were derived to estimate and rank the relative risk of dying while waitlisted. Four independent validation methods were used to measure each model's performance as a classifier and ranking system. This cohort (N=1,965) consisted of adult heart transplant candidates without missing laboratory data who were placed on the waitlist from January 1, 2008, to September 2, 2022. Patients listed for multi-organ transplantation were excluded. Patients with missing laboratory data were analyzed independently. The primary outcome of this study was the design, development, and validation of a formal risk management system for waitlisted heart transplant candidates experiencing end-stage heart failure. We derived three linear regression formulas and calibrated a seven-tiered risk index to accurately rank patients who were more likely to die on the waitlist at 30-day (30D), 90-day (90D), and 1-year (1Y) censoring periods. Four independent validation methods were used to measure each model?s classification and ranking performance. Using six interaction terms, we applied the 5-fold cross-validation procedure to the CHARM to discover an area under the ROC curve of 96.4%, 90.4.%, and 78% for the 30D, 90D, and 1Y models, respectively. The mean positive predictive values of the tiered risk system were 99.2% (30D), 94.1% (90D), and 88% (1Y). Risk indices for all three models were >99% correlated to the observed mortality rate across the seven tiers for the 30D, 90D, and 1Y models. We designed, implemented, and validated an intuitive and formal risk scoring and ranking system which is ideal for prioritizing waitlisted heart failure patients based on a well-defined medical urgency metric. The CHARM score provides extreme sensitivity in predicting short-term mortality outcomes. The CHARM score is extensible to larger patient populations experiencing end-stage heart failure.

show abstract

Equitable Access to Advanced Heart Failure Therapies in the United States: A Call to Action

CASCINO,

COGSWELL,

SHAH

et al. 2024

Journal of Cardiac Failure

View full text Add to dashboard Cite

The Accuracy of Initial U.S. Heart Transplant Candidate Rankings

Cited by 3 publications

References 22 publications

Development and Validation of a Risk Score Predicting Death Without Transplant in Adult Heart Transplant Candidates

Development and Validation of a Risk Score Predicting Death Without Transplant in Adult Heart Transplant Candidates

The Colorado Heart Failure Acuity Risk Model (CHARM) Score: A Mortality Risk Model for Waitlisted Cardiac Transplant Patients

Equitable Access to Advanced Heart Failure Therapies in the United States: A Call to Action

Contact Info

Product

Resources

About