Dataset Information

Risk indices predicting graft use, graft and patient survival in solid pancreas transplantation: a systematic review.

ABSTRACT:

Background

Risk indices such as the pancreas donor risk index (PDRI) and pre-procurement pancreas allocation suitability score (P-PASS) are utilised in solid pancreas transplantation however no review has compared all derived and validated indices in this field. We systematically reviewed all risk indices in solid pancreas transplantation to compare their predictive ability for transplant outcomes.

Methods

Medline Plus, Embase and the Cochrane Library were searched for studies deriving and externally validating risk indices in solid pancreas transplantation for the outcomes of pancreas and patient survival and donor pancreas acceptance for transplantation. Results were analysed descriptively due to limited reporting of discrimination and calibration metrics required to assess model performance.

Results

From 25 included studies, discrimination and calibration metrics were only reported in 88% and 38% of derivation studies (n?=?8) and in 25% and 25% of external validation studies (n?=?12) respectively. 21 risk indices were derived with mild to moderate ability to predict risk (C-statistics 0.52-0.78). Donor age, donor body mass index (BMI) and donor gender were the commonest covariates within derived risk indices. Only PDRI and P-PASS were subsequently externally validated, with variable association with post-transplant outcomes. P-PASS was not associated with pancreas graft survival.

Conclusion

Most of the risk indices derived for use in solid pancreas transplantation were not externally validated (90%). PDRI and P-PASS are the only risk indices externally validated for solid pancreas transplantation, and when validated without reclassification measures, are associated with 1-year pancreas graft survival and donor pancreas acceptance respectively. Future risk indices incorporating recipient and other covariates alongside donor risk factors may have improved predictive ability for solid pancreas transplant outcomes.

SUBMITTER: Ling JEH

PROVIDER: S-EPMC7901078 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Risk indices predicting graft use, graft and patient survival in solid pancreas transplantation: a systematic review.

Ling Jonathan E H JEH Coughlan Timothy T Polkinghorne Kevan R KR Kanellis John J

BMC gastroenterology 20210223 1

<h4>Background</h4>Risk indices such as the pancreas donor risk index (PDRI) and pre-procurement pancreas allocation suitability score (P-PASS) are utilised in solid pancreas transplantation however no review has compared all derived and validated indices in this field. We systematically reviewed all risk indices in solid pancreas transplantation to compare their predictive ability for transplant outcomes.<h4>Methods</h4>Medline Plus, Embase and the Cochrane Library were searched for studies der ...[more]

PMID: 33622257

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Project description:BackgroundThe variations in outcome and frequent occurrence of kidney allograft failure continue to pose important clinical and research challenges despite recent advances in kidney transplantation. The aim of this systematic review was to examine the current application of machine learning models in kidney transplantation and perform a meta-analysis of these models in the prediction of graft survival.MethodsThis review was registered with the PROSPERO database (CRD42021247469) and all peer-reviewed original articles that reported machine learning model-based prediction of graft survival were included. Quality assessment was performed by the criteria defined by Qiao and risk-of-bias assessment was performed using the PROBAST tool. The diagnostic performance of the meta-analysis was assessed by a meta-analysis of the area under the receiver operating characteristic curve and a hierarchical summary receiver operating characteristic plot.ResultsA total of 31 studies met the inclusion criteria for the review and 27 studies were included in the meta-analysis. Twenty-nine different machine learning models were used to predict graft survival in the included studies. Nine studies compared the predictive performance of machine learning models with traditional regression methods. Five studies had a high risk of bias and three studies had an unclear risk of bias. The area under the hierarchical summary receiver operating characteristic curve was 0.82 and the summary sensitivity and specificity of machine learning-based models were 0.81 (95 per cent c.i. 0.76 to 0.86) and 0.81 (95 per cent c.i. 0.74 to 0.86) respectively for the overall model. The diagnostic odds ratio for the overall model was 18.24 (95 per cent c.i. 11.00 to 30.16) and 29.27 (95 per cent c.i. 13.22 to 44.46) based on the sensitivity analyses.ConclusionPrediction models using machine learning methods may improve the prediction of outcomes after kidney transplantation by the integration of the vast amounts of non-linear data.

Project description:BackgroundMyosteatosis is associated with perioperative outcomes in orthotopic liver transplantation (OLT). Here, we investigated the effects of body composition and myosteatosis on long-term graft and patient survival following OLT.MethodsClinical data from 225 consecutive OLT recipients from a prospective database were retrospectively analysed (May 2010 to December 2017). Computed tomography-based lumbar skeletal muscle index (SMI) (muscle mass) and mean skeletal muscle radiation attenuation (SM-RA) (myosteatosis) were calculated using a segmentation tool (3D Slicer). Patients with low skeletal muscle mass (low SMI) and myosteatosis (low SM-RA) were identified using predefined and validated cut-off values.ResultsThe mean donor and recipient age was 55 ± 16 and 54 ± 12 years, respectively. Some 67% of the recipients were male. The probability of graft and patient survival was significantly lower in patients with myosteatosis compared with patients with higher SM-RA values (P = 0.011 and P = 0.001, respectively). Low skeletal muscle mass alone was not associated with graft and patient survival (P = 0.273 and P = 0.278, respectively). Dividing the cohort into quartiles, based on the values of SMI and SM-RA, resulted in significant differences in patient but not in graft survival (P = 0.011). Even though multivariable analysis identified low SM-RA as an important prognostic marker (hazard ratio: 2.260, 95% confidence interval: 1.177-4.340, P = 0.014), myosteatosis lost its significance when early mortality (90 days) was excluded from the final multivariable model. Patients with myosteatosis showed significantly higher all-cause mortality and in particular higher rates of deaths due to respiratory and septic complication (P = 0.002, P = 0.022, and P = 0.049, respectively).ConclusionsPreoperative myosteatosis may be an important prognostic marker in patients undergoing deceased donor liver transplantation. The prognostic value of myosteatosis seems to be particularly important in the early post-operative phase. Validation in prospective clinical trials is warranted.

Dataset Information

Risk indices predicting graft use, graft and patient survival in solid pancreas transplantation: a systematic review.

Background

Methods

Results

Conclusion

Publications

Risk indices predicting graft use, graft and patient survival in solid pancreas transplantation: a systematic review.

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