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A novel learning algorithm to predict individual survival after liver transplantation for primary sclerosing cholangitis.

ABSTRACT: Deciding who should receive a liver transplant (LT) depends on both urgency and utility. Most survival scores are validated through discriminative tests, which compare predicted outcomes between patients. Assessing post-transplant survival utility is not discriminate, but should be "calibrated" to be effective. There are currently no such calibrated models. We developed and validated a novel calibrated model to predict individual survival after LT for Primary Sclerosing Cholangitis (PSC). We applied a software tool, PSSP, to adult patients in the Scientific Registry of Transplant Recipients (n = 2769) who received a LT for PSC between 2002 and 2013; this produced a model for predicting individual survival distributions for novel patients. We also developed an appropriate evaluation measure, D-calibration, to validate this model. The learned PSSP model showed an excellent D-calibration (p = 1.0), and passed the single-time calibration test (Hosmer-Lemeshow p-value of over 0.05) at 0.25, 1, 5 and 10 years. In contrast, the model based on traditional Cox regression showed worse calibration on long-term survival and failed at 10 years (Hosmer-Lemeshow p value = 0.027). The calculator and visualizer are available at: http://pssp.srv.ualberta.ca/calculator/liver_transplant_2002. In conclusion we present a new tool that accurately estimates individual post liver transplantation survival.

SUBMITTER: Andres A

PROVIDER: S-EPMC5854273 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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A novel learning algorithm to predict individual survival after liver transplantation for primary sclerosing cholangitis.

Andres Axel A Montano-Loza Aldo A Greiner Russell R Uhlich Max M Jin Ping P Hoehn Bret B Bigam David D Shapiro James Andrew Mark JAM Kneteman Norman Mark NM

PloS one 20180315 3

Deciding who should receive a liver transplant (LT) depends on both urgency and utility. Most survival scores are validated through discriminative tests, which compare predicted outcomes between patients. Assessing post-transplant survival utility is not discriminate, but should be "calibrated" to be effective. There are currently no such calibrated models. We developed and validated a novel calibrated model to predict individual survival after LT for Primary Sclerosing Cholangitis (PSC). We app ...[more]

PMID: 29543895

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Project description:BackgroundThe course of inflammatory bowel disease (IBD) after liver transplantation (LT) for primary sclerosing cholangitis (PSC) is poorly understood. We describe the natural history of established IBD after LT (including risk of disease progression, colectomy, and neoplasia) and de novo IBD.MethodsIn a retrospective cohort, we identified all patients with PSC who underwent LT for advanced PSC at Mayo Clinic, Rochester, Minnesota. Risk factors were identified using multivariate Cox proportional hazard analysis.ResultsThree hundred seventy-three patients were identified (mean age, 47.5 ± 11.7 years; 64.9% male). Over a median (range) of 10 (5.5-17.1) years, 151 patients with PSC-IBD with an intact colon at the time of LT were studied. Post-LT, despite transplant-related immunosuppression, 56/151 (37.1%) required escalation of therapy, whereas 87 had a stable course (57.6%) and 8 patients (5.3%) improved. The 1-, 5-, and 10-year risks of progression of IBD were 4.0%, 18.5%, and 25.5%, respectively. On multivariate analysis, tacrolimus-based immunosuppression post-LT were associated with unfavorable course, and azathioprine use after LT was associated with improved course post-LT. Of 84 patients with no evidence of IBD at the time of LT, 22 (26.2%) developed de novo IBD post-LT. The 1-, 5-, and 10-year cumulative incidences of de novo IBD were 5.5%, 20.0%, and 25.4%, respectively. On univariate analysis, mycophenolate mofetil use after LT was associated with increased risk of de novo IBD, but azathioprine use after LT seemed to be protective.ConclusionsThe 10-year cumulative probability of IBD flare requiring escalation of therapy after LT for PSC was 25.5%, despite immunosuppression for LT. The 10-year cumulative risk of de novo IBD after LT for PSC was 25.4%. Transplant-related immunosuppression may modify the risk of de novo IBD, with an increased risk with mycophenolate and a decreased risk with azathioprine. 10.1093/ibd/izx096_video1izx096.video15746673864001.

Dataset Information

A novel learning algorithm to predict individual survival after liver transplantation for primary sclerosing cholangitis.

Publications

A novel learning algorithm to predict individual survival after liver transplantation for primary sclerosing cholangitis.

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