medwireNews: A candidate risk score (CRS) developed for US patients awaiting heart transplant significantly outperforms the current 6-status allocation system used in the USA to rank candidates by medical urgency, show data published in JAMA.
The “easy-to-implement model that captures the key clinical predictors of medical urgency” had an accuracy of 79% for predicting which patients would die without a heart transplant within 6 weeks of being registered for the procedure, report William Parker (University of Chicago, Illinois, USA) and colleagues.
This was significantly better than the accuracy of 68% achieved with the 6-status system.
Parker and co-authors explain that, at present, “the US Department of Health and Human Services mandates that the Organ Procurement and Transplantation Network (OPTN) prioritize medically urgent candidates with a high risk of death without transplant.”
This is done using a categorical 6-status system based mainly on treatment intensity, which the researchers say “is susceptible to manipulation and has limited rank ordering ability.” To address this, the OPTN is currently transitioning US deceased donor organ allocation to a point-based continuous distribution framework that will require a medical urgency score.
Parker et al therefore developed and validated a multivariable, predictive US-CRS that could be used within this framework.
They screened 46 potential predictors, which included age, diagnosis, diabetes, hemodynamics, level of inotropic support, mechanical circulatory support (MCS), and MCS complications, using data from 16,905 adult heart transplant candidates (mean age 53 years; 73% male; 58% White) who were listed in the US heart allocation system between 2019 and 2022. Of these, 4.7% died without a transplant, 71.3% received a transplant, and the remaining 24.0% were either removed from the list or were still waiting for a transplant at the time of analysis.
The final US-CRS model included the use of short-term MCS, the use of a durable left ventricular assist device, levels of bilirubin, B-type natriuretic peptide, sodium, and albumin, and estimated glomerular filtration rate.
In addition to having greater accuracy for predicting death than the 6-status system, the US-CRS had significantly higher sensitivity for predicting waiting list death and greater specificity for predicting waiting list survival than any of the thresholds within the 6-status system. The greatest improvements included a 14.3 percentage point increase in sensitivity with the US-CRS relative to status 2 of the 6-status system (76.5 vs 62.2%) and a 31.8 percentage point increase in specificity with the US-CRS relative to status 5 (47.0 vs 15.2%).
Parker and team also calculated that when they converted the predicted risk into a 50-point medical urgency score, like that used in kidney transplant allocation, 25.8% of candidates categorized at low-priority status on the 6-status system (statuses 3–6) were deemed at high risk for death on the US-CRS (>40 points).
“By assigning these high-risk candidates higher scores and less urgent candidates lower scores, an improvement in [area under the receiver operating characteristic curve] in the US-CRS model translates into clinically relevant differences in allocating a scarce resource,” the authors remark.
They conclude that their findings “suggest that the US-CRS may be useful in determining medical urgency, a major factor in the allocation of deceased donor hearts in the US.”
In an accompanying editorial, Michelle Kittleson, from Cedars-Sinai Medical Center in Los Angeles, California, USA, describes the findings as “practice changing.”
She hopes that the United Network for Organ Sharing and the OPTN “will use this elegant analysis as the framework for a continuous distribution model for heart transplant allocation.”
Kittleson continues: “This will be an important step away from subjective physician decision-making toward a system that balances beneficence and justice to optimize equitable access to transplant for all patients with advanced heart failure.”
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