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Validated prediction tool estimates graft failure after kidney transplant
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A risk prediction score — made up of eight prognostic factors — demonstrated accuracy in determining allograft failure after kidney transplantation.
“Although the failure of a kidney allograft represents an important cause of end-stage renal disease, robust and widely validated prognostication systems for the risk of allograft failure in individual patients are lacking,” Alexandre Loupy, MD, PhD, of the Paris Translational Research Center for Organ Transplantation, and colleagues wrote. “Accurately predicting individual patients’ risk of allograft loss would help to stratify patients into clinically meaningful risk groups, which may help to guide the monitoring of patients.”
As Loupy told Healio/Nephrology, “The iBox uses the parameters that are routinely checked on a patient, [so] we just need to enter these parameters in the algorithm to get the risk rejection score. It is a tool we can use on a daily basis to modulate immunosuppression to avoid long-term complications or rejection.”
Researchers followed 7,577 patients from academic medical centers in Europe and the United States for a median of 7.12 years after kidney transplant. During this time, 14.1% of allografts failed.
In evaluating the risk of graft failure, a variety of prognostic factors — including demographic characteristics (eg, recipient comorbidities, age, sex and transplant characteristics), biological parameters (eg, kidney allograft function, proteinuria and circulating anti-HLA antibody specificities and concentrations) and allograft pathology data (eg, elementary lesion scores and diagnoses) — were considered. Eight of these were found to be associated with allograft failure and were subsequently combined into the risk prediction score.
Researchers determined that the score showed accurate calibration and discrimination in predicting graft failure, noting that the performance of the tool was further confirmed in validation cohorts. In addition, the score was accurate when assessed at various times of evaluation and in different clinical scenarios (eg, type of immunosuppressive regimen used and response to rejection therapy). According to the researchers, it also outperformed both previous risk prediction scores and scores based only on eGFR and proteinuria. Results were confirmed in three randomized controlled trials.
Loupy said doctors face many uncertainties when treating patients in daily routine care practice, and so, a tool that enhances precision medicine — like the risk prediction score — was needed.
“[Clinical] end points developed by the Food and Drug Administration, like a biopsy-proven acute prediction or just allograft function as stand-alone, have been shown to be insufficient as prediction tools,” he continued. “With the iBox, a drug company can have a projection of long-term allograft survival at 7 or 10 years and can then decide whether to pursue the study. The iBox can thus save costs, which is very important in the current context of drug development in transplantation.”
Loupy added, “Now that the iBox risk score exists, a very important next step will be to test the added-value of the iBox in real-life settings of patient management. We will start to implement iBox in our own institutions in Paris in November 2019 and we are very excited about that.” – by Melissa J. Webb
Disclosures: Loupy reports holding shares in Cibiltech.
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