An adjustable predictive score of graft survival in kidney transplant patients and the levels of risk linked to de novo donor-specific anti-HLA antibodies

Prémaud, Aurélie; Filloux, Matthieu; Thierry, Antoine; Büchler, Matthias; E, Munteanu; Marquet, Pierre; Essig, Marie; Rousseau, Annick

doi:10.1371/journal.pone.0180236

Cited by 16 publications

(15 citation statements)

References 39 publications

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“…This risk prediction score reflects the main patterns of allograft deterioration leading to failure, represented by alloimmune processes and allograft scarring 30. Two other prognostic scores have attempted to combine several transplant diagnostic dimensions, including allograft function and pathology and alloantibodies; however, these scores were outperformed by the iBox risk prediction score 1631…”

Section: Discussionmentioning

confidence: 99%

Prediction system for risk of allograft loss in patients receiving kidney transplants: international derivation and validation study

Loupy

Aubert

Orandi

et al. 2019

BMJ

240

271

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ObjectiveTo develop and validate an integrative system to predict long term kidney allograft failure.DesignInternational cohort study.SettingThree cohorts including kidney transplant recipients from 10 academic medical centres from Europe and the United States.ParticipantsDerivation cohort: 4000 consecutive kidney recipients prospectively recruited in four French centres between 2005 and 2014. Validation cohorts: 2129 kidney recipients from three centres in Europe and 1428 from three centres in North America, recruited between 2002 and 2014. Additional validation in three randomised controlled trials (NCT01079143, EudraCT 2007-003213-13, and NCT01873157).Main outcome measureAllograft failure (return to dialysis or pre-emptive retransplantation). 32 candidate prognostic factors for kidney allograft survival were assessed.ResultsAmong the 7557 kidney transplant recipients included, 1067 (14.1%) allografts failed after a median post-transplant follow-up time of 7.12 (interquartile range 3.51-8.77) years. In the derivation cohort, eight functional, histological, and immunological prognostic factors were independently associated with allograft failure and were then combined into a risk prediction score (iBox). This score showed accurate calibration and discrimination (C index 0.81, 95% confidence interval 0.79 to 0.83). The performance of the iBox was also confirmed in the validation cohorts from Europe (C index 0.81, 0.78 to 0.84) and the US (0.80, 0.76 to 0.84). The iBox system showed accuracy when assessed at different times of evaluation post-transplant, was validated in different clinical scenarios including type of immunosuppressive regimen used and response to rejection therapy, and outperformed previous risk prediction scores as well as a risk score based solely on functional parameters including estimated glomerular filtration rate and proteinuria. Finally, the accuracy of the iBox risk score in predicting long term allograft loss was confirmed in the three randomised controlled trials.ConclusionAn integrative, accurate, and readily implementable risk prediction score for kidney allograft failure has been developed, which shows generalisability across centres worldwide and common clinical scenarios. The iBox risk prediction score may help to guide monitoring of patients and further improve the design and development of a valid and early surrogate endpoint for clinical trials.Trial registrationClinicaltrials.gov NCT03474003.

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Section: Discussionmentioning

confidence: 99%

Prediction system for risk of allograft loss in patients receiving kidney transplants: international derivation and validation study

Loupy

Aubert

Orandi

et al. 2019

BMJ

240

271

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“…Nevertheless, it should be emphasized that this score necessitates a histological evaluation of the graft, which is not always required in RCTs, in particular for interventions targeting IR or the prevention of DGF. Of note, the iBox is a time-adjusted prediction score (as it can be performed irrespective of the time point after transplantation), whereas the previously published scores comprising immunological parameters (histological findings at 1-year surveillance biopsy and/or serum donor-specific alloantibody) were based on an a priori –determined 12-month post-KT evaluation time point [ 32 , 33 ].…”

Section: Discussionmentioning

confidence: 99%

Prognostic value for long-term graft survival of estimated glomerular filtration rate and proteinuria quantified at 3 months after kidney transplantation

Mottola

Girerd²,

Duarte³

et al. 2020

Clinical Kidney Journal

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Background The estimated glomerular filtration rate (eGFR) measured at 1 year is the usual benchmark applied in kidney transplantation (KT). However, acting on earlier eGFR values could help in managing KT during the first post-operative year. We aimed to assess the prognostic value for long-term graft survival of the early (3 months) quantification of eGFR and proteinuria following KT. Methods The 3-, 6- and 12-month eGFR using the Modified Diet in Renal Disease equation (eGFRMDRD) was determined and proteinuria was measured in 754 patients who underwent their first KT between 2000 and 2010 (with a mean follow-up of 8.3 years) in our centre. Adjusted associations with graft survival were estimated using a multivariable Cox model. The predictive accuracy was estimated using the C-index and net reclassification index. These same analyses were measured in a multicentre validation cohort of 1936 patients. Results Both 3-month eGFRMDRD and proteinuria were independent predictors of return to dialysis (all P < 0.05) and there was a strong correlation between eGFR at 3 and 12 months (Spearman’s ρ = 0.76). The predictive accuracy of the 3-month eGFR was within a similar range and did not differ significantly from the 12-month eGFR in either the derivation cohort [C-index 62.6 (range 57.2–68.1) versus 66.0 (range 60.1–71.9), P = 0.41] or the validation cohort [C-index 69.3 (range 66.4–72.1) versus 71.7 (range 68.7–74.6), P = 0.25]. Conclusion The 3-month eGFR was a valuable predictor of the long-term return to dialysis whose predictive accuracy was not significantly less than that of the 12-month eGFR in multicentre cohorts totalling >2500 patients. Three-month outcomes may be useful in randomized controlled trials targeting early therapeutic interventions.

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“…All the grafts came from heart-beating deceased donor. More details about the patients included can be found in a previous work of our group [10].…”

Section: Methodsmentioning

confidence: 99%

“…All sera collected and tested using the Complement Dependent Cytotoxicity method prior to availability of Luminex® technology in our center (2007) were reanalyzed using Luminex® as previously described. [10] Patients in whom the Luminex® reanalysis identified presence of DSA before transplantation were excluded from the database studied.…”

Section: Methodsmentioning

confidence: 99%

A Prognostic Tool for Individualized Prediction of Graft Failure Risk within Ten Years after Kidney Transplantation

Stamenic

Rousseau

Essig

et al. 2019

Journal of Transplantation

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Identification of patients at risk of kidney graft loss relies on early individual prediction of graft failure. Data from 616 kidney transplant recipients with a follow-up of at least one year were retrospectively studied. A joint latent class model investigating the impact of serum creatinine (Scr) time-trajectories and onset of de novo donor-specific anti-HLA antibody (dnDSA) on graft survival was developed. The capacity of the model to calculate individual predicted probabilities of graft failure over time was evaluated in 80 independent patients. The model classified the patients in three latent classes with significantly different Scr time profiles and different graft survivals. Donor age contributed to explaining latent class membership. In addition to the SCr classes, the other variables retained in the survival model were proteinuria measured one-year after transplantation (HR=2.4, p=0.01), pretransplant non-donor-specific antibodies (HR=3.3, p<0.001), and dnDSA in patient who experienced acute rejection (HR=15.9, p=0.02). In the validation dataset, individual predictions of graft failure risk provided good predictive performances (sensitivity, specificity, and overall accuracy of graft failure prediction at ten years were 77.7%, 95.8%, and 85%, resp.) for the 60 patients who had not developed dnDSA. For patients with dnDSA individual risk of graft failure was not predicted with a so good performance.

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An adjustable predictive score of graft survival in kidney transplant patients and the levels of risk linked to de novo donor-specific anti-HLA antibodies

Cited by 16 publications

References 39 publications

Prediction system for risk of allograft loss in patients receiving kidney transplants: international derivation and validation study

Prediction system for risk of allograft loss in patients receiving kidney transplants: international derivation and validation study

Prognostic value for long-term graft survival of estimated glomerular filtration rate and proteinuria quantified at 3 months after kidney transplantation

A Prognostic Tool for Individualized Prediction of Graft Failure Risk within Ten Years after Kidney Transplantation

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