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      External Validation of International Risk-Prediction Models of IgA Nephropathy in an Asian-Caucasian Cohort

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          Abstract

          Introduction

          Two prediction models for IgA nephropathy (IgAN) using clinical variables and the Oxford MEST scores were developed and validated in 2 multiethnic cohorts. Additional external validation is required.

          Methods

          Biopsy-proven Chinese and Argentinian patients with IgAN were included. The primary outcome was defined as a 50% decline in estimated glomerular filtration rate (eGFR) or end-stage renal disease. C-statistics and stratified analyses were used for model discrimination, coefficient of determination (R 2 D) for model fit, and calibration plots for model calibration. Baseline survival function was also evaluated.

          Results

          A total of 1275 patients were enrolled, with a mean age of 34 (interquartile range: 27–42) years, 50% of whom (638 of 1275) were men. Use of renin-angiotensin system blockers was higher than in previously reported cohorts, whereas other variables were comparable. The C-statistic of the models was 0.81, and R 2 D was higher than reported. Survival curves in the subgroups (<16th, ∼16th to <50th, ∼50th to <84th, and ≥84th percentiles of linear predictor) were well separated. Most of the predictor variables, including hazard ratio, predicted 5-year risk, and eGFR decline slope, were worse with risk increasing. The baseline survival function was comparable in our cohort and the reported cohorts. The calibration was acceptable for the full model without race. However, the risk probability over 3 years was overestimated in the full model with race included.

          Conclusion

          The prediction models showed good performance on personalized risk assessment, which may be used as drug-specific, precision-medicine approaches to treatment decisionmaking.

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          Most cited references34

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          A new equation to estimate glomerular filtration rate.

          Equations to estimate glomerular filtration rate (GFR) are routinely used to assess kidney function. Current equations have limited precision and systematically underestimate measured GFR at higher values. To develop a new estimating equation for GFR: the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. Cross-sectional analysis with separate pooled data sets for equation development and validation and a representative sample of the U.S. population for prevalence estimates. Research studies and clinical populations ("studies") with measured GFR and NHANES (National Health and Nutrition Examination Survey), 1999 to 2006. 8254 participants in 10 studies (equation development data set) and 3896 participants in 16 studies (validation data set). Prevalence estimates were based on 16,032 participants in NHANES. GFR, measured as the clearance of exogenous filtration markers (iothalamate in the development data set; iothalamate and other markers in the validation data set), and linear regression to estimate the logarithm of measured GFR from standardized creatinine levels, sex, race, and age. In the validation data set, the CKD-EPI equation performed better than the Modification of Diet in Renal Disease Study equation, especially at higher GFR (P < 0.001 for all subsequent comparisons), with less bias (median difference between measured and estimated GFR, 2.5 vs. 5.5 mL/min per 1.73 m(2)), improved precision (interquartile range [IQR] of the differences, 16.6 vs. 18.3 mL/min per 1.73 m(2)), and greater accuracy (percentage of estimated GFR within 30% of measured GFR, 84.1% vs. 80.6%). In NHANES, the median estimated GFR was 94.5 mL/min per 1.73 m(2) (IQR, 79.7 to 108.1) vs. 85.0 (IQR, 72.9 to 98.5) mL/min per 1.73 m(2), and the prevalence of chronic kidney disease was 11.5% (95% CI, 10.6% to 12.4%) versus 13.1% (CI, 12.1% to 14.0%). The sample contained a limited number of elderly people and racial and ethnic minorities with measured GFR. The CKD-EPI creatinine equation is more accurate than the Modification of Diet in Renal Disease Study equation and could replace it for routine clinical use. National Institute of Diabetes and Digestive and Kidney Diseases.
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            Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration

            The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. This explanation and elaboration document describes the rationale; clarifies the meaning of each item; and discusses why transparent reporting is important, with a view to assessing risk of bias and clinical usefulness of the prediction model. Each checklist item of the TRIPOD Statement is explained in detail and accompanied by published examples of good reporting. The document also provides a valuable reference of issues to consider when designing, conducting, and analyzing prediction model studies. To aid the editorial process and help peer reviewers and, ultimately, readers and systematic reviewers of prediction model studies, it is recommended that authors include a completed checklist in their submission. The TRIPOD checklist can also be downloaded from www.tripod-statement.org.
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              Oxford Classification of IgA nephropathy 2016: an update from the IgA Nephropathy Classification Working Group.

              Since the Oxford Classification of IgA nephropathy (IgAN) was published in 2009, MEST scores have been increasingly used in clinical practice. Further retrospective cohort studies have confirmed that in biopsy specimens with a minimum of 8 glomeruli, mesangial hypercellularity (M), segmental sclerosis (S), and interstitial fibrosis/tubular atrophy (T) lesions predict clinical outcome. In a larger, more broadly based cohort than in the original Oxford study, crescents (C) are predictive of outcome, and we now recommend that C be added to the MEST score, and biopsy reporting should provide a MEST-C score. Inconsistencies in the reporting of M and endocapillary cellularity (E) lesions have been reported, so a web-based educational tool to assist pathologists has been developed. A large study showed E lesions are predictive of outcome in children and adults, but only in those without immunosuppression. A review of S lesions suggests there may be clinical utility in the subclassification of segmental sclerosis, identifying those cases with evidence of podocyte damage. It has now been shown that combining the MEST score with clinical data at biopsy provides the same predictive power as monitoring clinical data for 2 years; this requires further evaluation to assess earlier effective treatment intervention. The IgAN Classification Working Group has established a well-characterized dataset from a large cohort of adults and children with IgAN that will provide a substrate for further studies to refine risk prediction and clinical utility, including the MEST-C score and other factors.
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                Author and article information

                Contributors
                Journal
                Kidney Int Rep
                Kidney Int Rep
                Kidney International Reports
                Elsevier
                2468-0249
                07 August 2020
                October 2020
                07 August 2020
                : 5
                : 10
                : 1753-1763
                Affiliations
                [1 ]Renal Division, Department of Medicine, Peking University First Hospital, Beijing China; Institute of Nephrology, Peking University, Beijing, China
                [2 ]Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
                [3 ]Key Laboratory of Chronic Kidney Disease Prevention and Treatment of Peking University, Ministry of Education, Beijing, China
                [4 ]Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
                [5 ]BC Renal, Vancouver, British Columbia, Canada
                [6 ]Division of Nephrology, University of British Columbia, Vancouver, British Columbia, Canada
                [7 ]Nephrology Service, Hospital Británico de Buenos Aires, Argentina
                Author notes
                [] Correspondence: Jicheng Lv, Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, No. 8, Xishiku Street, Xicheng District, Beijing 100034, China. jichenglv75@ 123456gmail.com
                [∗∗ ]Hernan Trimarchi, Nephrology Service, Hospital Británico de Buenos Aires, Perdriel 74 (1280), Buenos Aires, Argentina. htrimarchi@ 123456hotmail.com
                [8]

                YMZ and LG contributed equally to this research.

                Article
                S2468-0249(20)31435-2
                10.1016/j.ekir.2020.07.036
                7572322
                33102968
                1b1647cc-d071-4bc2-ae9f-6886659d423c
                © 2020 International Society of Nephrology. Published by Elsevier Inc.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 7 July 2020
                : 28 July 2020
                Categories
                Clinical Research

                calibration,discrimination,external validation,iga nephropathy,prediction models

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