Dataset Information

Development and validation of routine clinical laboratory data derived marker-based nomograms for the prediction of 5-year graft survival in kidney transplant recipients.

ABSTRACT:

Background

To develop and validate predictive nomograms for 5-year graft survival in kidney transplant recipients (KTRs) with easily-available laboratory data derived markers and clinical variables within the first year post-transplant.

Methods

The clinical and routine laboratory data from within the first year post-transplant of 1289 KTRs was collected to generate candidate predictors. Univariate and multivariate Cox analyses and LASSO were conducted to select final predictors. X-tile analysis was applied to identify optimal cutoff values to transform potential continuous factors into category variables and stratify patients. C-index, calibration curve, dynamic time-dependent AUC, decision curve analysis, and Kaplan-Meier curves were used to evaluate models' predictive accuracy and clinical utility.

Results

Two predictive nomograms were constructed by using 0-6- and 0-12- month laboratory data, and showed good predictive performance with C-indexes of 0.78 and 0.85, respectively, in the training cohort. Calibration curves showed that the prediction probabilities of 5-year graft survival were in concordance with actual observations. Additionally, KTRs could be successfully stratified into three risk groups by nomograms.

Conclusions

These predictive nomograms combining demographic and 0-6- or 0-12- month markers derived from post-transplant laboratory data could serve as useful tools for early identification of 5-year graft survival probability in individual KTRs.

SUBMITTER: Li Y

PROVIDER: S-EPMC8064213 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Publications

Development and validation of routine clinical laboratory data derived marker-based nomograms for the prediction of 5-year graft survival in kidney transplant recipients.

Li Yamei Y Yan Lin L Li Yi Y Wan Zhengli Z Bai Yangjuan Y Wang Xianding X Hu Shumeng S Wu Xiaojuan X Yang Cuili C Fan Jiwen J Xu Huan H Wang Lanlan L Shi Yunying Y

Aging 20210326 7

<h4>Background</h4>To develop and validate predictive nomograms for 5-year graft survival in kidney transplant recipients (KTRs) with easily-available laboratory data derived markers and clinical variables within the first year post-transplant.<h4>Methods</h4>The clinical and routine laboratory data from within the first year post-transplant of 1289 KTRs was collected to generate candidate predictors. Univariate and multivariate Cox analyses and LASSO were conducted to select final predictors. X ...[more]

PMID: 33795527

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Project description:BackgroundGraft loss is a major health concern for kidney transplant (KTx) recipients. It is of clinical interest to develop a prognostic model for both graft function, quantified by estimated glomerular filtration rate (eGFR), and the risk of graft failure. Additionally, the model should be dynamic in the sense that it adapts to accumulating longitudinal information, including time-varying at-risk population, predictor-outcome association, and clinical history. Finally, the model should also properly account for the competing risk by death with a functioning graft. A model with the features above is not yet available in the literature and is the focus of this research.MethodsWe built and internally validated a prediction model on 3,893 patients from the Wisconsin Allograft Recipient Database (WisARD) who had a functioning graft 6 months after kidney transplantation. The landmark analysis approach was used to build a proof-of-concept dynamic prediction model to address the aforementioned methodological issues: the prediction of graft failure, accounted for competing risk of death, as well as the future eGFR value, are updated at each post-transplant time. We used 21 predictors including recipient characteristics, donor characteristics, transplant-related and post-transplant factors, longitudinal eGFR, hospitalization, and rejection history. A sensitivity analysis explored a less conservative variable selection rule that resulted in a more parsimonious model with reduced predictors.ResultsFor prediction up to the next 1 to 5 years, the model achieved high accuracy in predicting graft failure, with the AUC between 0.80 and 0.95, and moderately high accuracy in predicting eGFR, with the root mean squared error between 10 and 18 mL/min/1.73m2 and 70%-90% of predicted eGFR falling within 30% of the observed eGFR. The model demonstrated substantial accuracy improvement compared to a conventional prediction model that used only baseline predictors.ConclusionThe model outperformed conventional prediction model that used only baseline predictors. It is a useful tool for patient counseling and clinical management of KTx and is currently available as a web app.

Project description:BackgroundLong-term high-dose lithium therapy in bipolar disorder is known to adversely affect kidney function. However, recent animal studies have revealed that low amounts of lithium are beneficial for the kidney when it is damaged by exposure to nephrotoxic compounds, inflammation or oxidative stress. This study aimed to investigate whether urinary lithium excretion, reflecting dietary lithium intake, is associated with adverse long-term kidney graft outcomes and patient survival.MethodsUrinary lithium concentration was measured using inductively coupled plasma mass spectrometry in 642 stable kidney transplant recipients (KTRs). Graft failure was defined as the start of dialysis or retransplantation and kidney function decline was defined as a doubling of serum creatinine.ResultsThe median urinary lithium excretion was 3.03 μmol/24 h [interquartile range (IQR) 2.31-4.01]. Urinary lithium excretion was associated with energy, plant protein and water intake. During a median follow-up of 5.3 years (IQR 4.5-6.0), 79 (12%) KTRs developed graft failure and 127 (20%) KTRs developed kidney function decline. Higher urinary lithium excretion was associated with a lower risk of graft failure {hazard ratio [HR] per doubling 0.54 [95% confidence interval (CI) 0.38-0.79]} and kidney function decline [HR per doubling 0.73 (95% CI 0.54-0.99)]. These associations remained independent of adjustment for potential confounders and in sensitivity analyses. There was a significant effect modification with the use of proliferation inhibitors (P = .05) and baseline estimated glomerular filtration rate (eGFR; P < .001), with higher urinary lithium excretion being more protective in KTRs not using proliferation inhibitors and in KTRs with lower baseline eGFR. Furthermore, higher urinary lithium excretion was associated with a reduced risk of all-cause mortality [HR 0.64 (95% CI 0.49-0.83); P = .001].ConclusionDietary lithium intake may be a potentially modifiable, yet rather overlooked, risk factor for adverse long-term kidney graft outcomes and patient survival.Trial registrationhttps://clinicaltrials.gov/ct2/show/NCT02811835.

Dataset Information

Development and validation of routine clinical laboratory data derived marker-based nomograms for the prediction of 5-year graft survival in kidney transplant recipients.

Background

Methods

Results

Conclusions

Publications

Development and validation of routine clinical laboratory data derived marker-based nomograms for the prediction of 5-year graft survival in kidney transplant recipients.

Similar Datasets

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