Background. Despite the increasing disparity between the number of patients awaiting kidney transplants and the availability of deceased donor kidneys, a significant number of donated kidneys go unused. Early identification of organs at high risk of nonuse can facilitate effective allocation interventions, ensuring these organs are offered to patients who could potentially benefit from them. While several machine learning models have been developed to predict nonuse risk, the complexity of these models compromises their practical implementation. Methods. We propose implementable nonuse risk prediction models that consist of a minimal set of variables, including the Kidney Donor Risk Index (KDRI), along with factors selected by machine learning models or transplantation experts. Our approach takes into account the influence of Organ Procurement Organization (OPO) behavior on kidney disposition. Results. The proposed models demonstrate competitive performance compared to more complex models that involve a large number of variables. Importantly, they maintain simplicity and interpretability. Conclusions. Our results provide accurate risk predictions, offer valuable insights into key factors contributing to kidney nonuse, and underscore significant variations among OPOs in the allocation of hard-to-place kidneys. These findings can inform the design of effective organ allocation interventions, increasing the likelihood of transplantation for hard-to-place kidneys.

The authors have declared no competing interest.

This study did not receive any funding.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Pursuant to a contract with the Health Resources and Services Administration (HRSA) of the U.S. Department of Health and Human Services, through the Organ Procurement and Transplantation Network (OPTN), The United Network for Organ Sharing (UNOS) provided the authors with the patient-level, non-identifiable data extracted from the OPTN research database maintained by UNOS. While seeking to provide transplant data for research, UNOS has a great responsibility to ensure the confidentiality of organ donors and transplant recipients. They make every effort to exclude from the computer files identifying information on individual patients and facilities. Certain demographic information such as gender, race, etc. are provided for research purposes but may not be used to attempt to identify individuals or institutions. This study is based on OPTN data as of October 1, 2021.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

This study is based on OPTN data as of October 1, 2021. We comply with all the provisions specified in the "Data User Agreement" provided by the OPTN. In short, the authors can neither use nor permit others to use the Data in any way other than for statistical reporting and analysis. We can neither release nor permit others to release the Data to any person (including media and subcontractors) except with the written approval of UNOS. The data reported here have been supplied by the United Network for Organ Sharing as the contractor for the Organ Procurement and Transplantation Network. The interpretation and reporting of these data are the responsibility of the author(s) and in no way should be seen as an official policy of or interpretation by the OPTN or the U.S. Government.