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Abstract: TH-PO1114

Clinical Impact of the Predigraft/iBox System as a Clinical Decision Support for Kidney Transplant Patients' Management: Mid-Term Results of a Prospective Randomized Controlled Trial (RCT)

Session Information

  • Late-Breaking Posters
    November 02, 2023 | Location: Exhibit Hall, Pennsylvania Convention Center
    Abstract Time: 10:00 AM - 12:00 PM

Category: Transplantation

  • 2102 Transplantation: Clinical

Authors

  • Lefaucheur, Carmen, Paris Institute for Transplantation and Organ Regeneration, Paris, France
  • Loupy, Alexandre, Paris Institute for Transplantation and Organ Regeneration, Paris, France
  • Daga, Sunil, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
  • Guirado, Luis, Fundacio Puigvert, Barcelona, Catalunya, Spain
  • Dudreuilh, Caroline, Guy's & St Thomas' Hospital, London, United Kingdom
  • Grahammer, Florian, Universitatsklinikum Hamburg-Eppendorf, Hamburg, Germany
  • Weissenbacher, Annemarie, Universitätsklinikum Innsbruck, Innsbruck, Austria
Background

Computer based decision support systems are emerging tools for decision-making optimization but their clinical benefit for patient care has not been demonstrated.

Methods

We designed a European multicenter RCT with 16 centers from Europe (France, UK, Spain, Germany, Austria, Israel). Kidney recipients were randomly (1:1) assigned from 3 mos up to 10 yrs after transplant to receive either SOC or management guided by a companion software Predigraft that provides automatic iBox patient risk assessment and prognostic trajectories. The primary endpoint was the number of allograft biopsies amenable to therapeutic changes. This study presents the interim period results at 9 mos after randomization.

Results

507 total subjects were recruited, among which 252 Predigraft and 254 SOC. The mean time from transplant to inclusion was 4.4±5,7 yrs. Mean recipient and donor age were 52±14 and 52±15 yrs respectively. Other baseline characteristics were similar between groups. The mean follow-up time after randomization was 9.6±3.6 months. In Predigraft, 398 iBox alerts were recorded among which 232 (58%) were deemed clinically relevant by physicians and 133 (33%) were followed by a change in clinical management and/or therapeutics. 61 total biopsies were performed overall, 32 Predigraft and 29 SOC respectively (incidence of 12.6 vs 11.4%, p=NS). Biopsies revealed rejection (TCMR or ABMR) in 28% Predigraft vs 10% SOC respectively (p=0.08), CNI toxicity (28% vs 17%, p=0.2), and others including BKVN, AKI, IFTA, recurrent GN and Borderline lesions (50% vs 27%, p=0.07). Finally, the rate of biopsies leading to therapeutic changes (primary endpoint) was 25/32 (78.1%) in Predigraft compared with 3/29 (10.3%) in SOC (p<0.0001). Treatment modifications mostly included change in IS regimen type, dose, target in 20/32 (62.5%) in Predigraft vs 3/29 (10.3%) in SOC respectively, p<0.001).

Conclusion

These results show the ability of an automatized computer-based decision support system to screen for allograft instability and help to improve the rate of clinically relevant biopsies enabling therapeutic changes including detection of allograft rejection.

Funding

  • Commercial Support – Predict4Health