Investigators have developed a scoring system (DPC) to predict which kidney transplant candidates are at high risk of developing tertiary hyperparathyroidism that requires parathyroidectomy.
“Given the current uncertainty in indications and timing of parathyroidectomy for tertiary hyperparathyroidism, an accurate and clinically applicable tool to predict the risk of post-transplant parathyroidectomy during the pretransplant period may help guide individualized therapeutic approaches, including early surgical intervention,” according to Kyu Ha Huh, MD, PhD, of The Research Institute for Transplantation, Yonsei University College of Medicine in Seoul, South Korea, and colleagues.
Using machine learning-based algorithms, the investigators identified Dialysis duration, Parathyroid hormone level, and serum Calcium level at the time of admission for kidney transplantation as the top 3 predictors of tertiary hyperparathyroidism requiring parathyroidectomy. Chronic kidney disease etiology, immunosuppressive regimen, other laboratory values, age, and sex were less consequential. Clinically relevant categories of D, P, and C were scored individually and then totaled for a final score of 0 to 15. The threshold score for “high risk” was 13 or greater, the investigators reported in the Clinical Journal of the American Society of Nephrology. Serial measurements of DPC scores during the 12 months before kidney transplantation improved risk stratification compared with single-time measurements.
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Dr Huh’s team used a training set of 501 patients, a testing set of 168 patients, and an external validation cohort (KNOW-KT registry) of 542 patients to develop and test the DPC risk score for tertiary hyperparathyroidism. In these cohorts, 4.4%, 5.9%, and 2.0% of patients received posttransplant parathyroidectomy. The DPC risk score for tertiary hyperparathyroidism yielded a high area under the receiver operating curve for accuracy in both the derivation (0.94) and external (0.98) cohorts.
“The findings suggest that the DPC score has the potential to tailor clinical decision making for managing hyperparathyroidism in kidney transplant recipients,” according to investigators.
Reference
Hong N, Lee J, Woo Kim H, Ju Jeong J, Ha Huh K, Rhee Y. Machine learning-derived integer-based score and prediction of tertiary hyperparathyroidism among kidney transplant recipients. Clin J Am Soc Nephrol. Published online June 10, 2022. doi:10.2215/CJN.15921221
