External Validation of the International IgA Nephropathy Prediction Tool in Older Adult Patients

References

• Pattrapornpisut P, Avila-Casado C, Reich HN, et al. IgA nephropathy: core curriculum 2021. Am J Kidney Dis. 2021;78(3):429–441. doi:10.1053/j.ajkd.2021.01.024
   PubMed Web of Science ®Google Scholar
• Cheungpasitporn W, Nasr SH, Thongprayoon C, Mao MA, Qian Q. Primary IgA nephropathy in elderly patients. Nephrology. 2015;20(6):419–425. doi:10.1111/nep.12440
   PubMed Web of Science ®Google Scholar
• Lin J, Cheng Z, Qian Q. Elderly patients with glomerular diseases and IgA nephropathy. Nephrology. 2017;22(S4):20–26. doi:10.1111/nep.13144
   PubMedGoogle Scholar
• Duan Z-Y, Cai G-Y, Chen Y-Z, et al. Aging promotes progression of IgA nephropathy: a systematic review and meta-analysis. Am j Nephrol. 2013;38(3):241–252. doi:10.1159/000354646
   PubMed Web of Science ®Google Scholar
• Pesce F, Diciolla M, Binetti G, et al. Clinical decision support system for end-stage kidney disease risk estimation in IgA nephropathy patients. Nephrol Dial Transplant. 2016;31(1):80–86. doi:10.1093/ndt/gfv232
   PubMed Web of Science ®Google Scholar
• Sevillano AM, Diaz M, Caravaca-Fontán F, et al. IgA nephropathy in elderly patients. Clin J Am Soc Nephrol. 2019;14(8):1183–1192. doi:10.2215/CJN.13251118
   PubMed Web of Science ®Google Scholar
• Soleymanian T, Najafi I, Salimi BH, Broomand B. Prognostic factors and therapy assessment of IgA nephropathy: report from a single unit in Iran. Renal Failure. 2011;33(6):572–577. doi:10.3109/0886022X.2011.585001
   PubMed Web of Science ®Google Scholar
• Barbour SJ, Coppo R, Zhang H, et al. Evaluating a new international risk-prediction tool in IgA nephropathy. JAMA Intern Med. 2019;179(7):942. doi:10.1001/jamainternmed.2019.0600
   PubMed Web of Science ®Google Scholar
• Zhang J, Huang B, Liu Z, et al. External validation of the international IgA nephropathy prediction tool. Clin J Am Soc Nephrol. 2020;15(8):1112–1120. doi:10.2215/CJN.16021219
   PubMed Web of Science ®Google Scholar
• Zhang Y, Guo L, Wang Z, et al. External validation of international risk-prediction models of IgA nephropathy in an Asian-caucasian cohort. Kidney Int Rep. 2020;5(10):1753–1763. doi:10.1016/j.ekir.2020.07.036
   PubMed Web of Science ®Google Scholar
• Collins GS, Ogundimu EO, Altman DG. Sample size considerations for the external validation of a multivariable prognostic model: a resampling study. Stat Med. 2015;35(2):214–226. doi:10.1002/sim.6787
   PubMed Web of Science ®Google Scholar
• Collins GS, Reitsma JB, Altman DG, Moons KGM. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. BMJ. 2015;350(jan07 4):g7594–g7594. doi:10.1136/bmj.g7594
   PubMed Web of Science ®Google Scholar
• Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604–612. doi:10.7326/0003-4819-150-9-200905050-00006
   PubMed Web of Science ®Google Scholar
• Trimarchi H, Barratt J, Cattran DC, et al. Oxford classification of IgA nephropathy 2016: an update from the IgA nephropathy classification working group. Kidney Int. 2017;91(5):1014–1021. doi:10.1016/j.kint.2017.02.003
   PubMed Web of Science ®Google Scholar
• Royston P, Altman DG. External validation of a Cox prognostic model: principles and methods. BMC Med Res Methodol. 2013;13:33. doi:10.1186/1471-2288-13-33
   PubMed Web of Science ®Google Scholar
• Harrell FE, Califf RM, Pryor DB, Lee KL, Rosati RA. Evaluating the yield of medical tests. JAMA. 1982;247(18):2543–2546. doi:10.1001/jama.1982.03320430047030
   PubMed Web of Science ®Google Scholar
• Heagerty PJ, Lumley T, Pepe MS. Time-dependent ROC curves for censored survival data and a diagnostic marker. Biometrics. 2000;56(2):337–344. doi:10.1111/j.0006-341X.2000.00337.x
   PubMed Web of Science ®Google Scholar
• Rodrigues JC, Haas M, Reich HN. IgA Nephropathy. Clin J Am Soc Nephrol. 2017;12(4):677–686. doi:10.2215/CJN.07420716
   PubMed Web of Science ®Google Scholar
• Bartosik LP, Lajoie G, Sugar L, Cattran DC. Predicting progression in IgA nephropathy. Am J Kidney Dis. 2001;38(4):728–735. doi:10.1053/ajkd.2001.27689
   PubMed Web of Science ®Google Scholar
• Berthoux F, Mohey H, Laurent B, Mariat C, Afiani A, Thibaudin L. Predicting the risk for dialysis or death in IgA nephropathy. J Am Soc Nephrol. 2011;22(4):752–761. doi:10.1681/ASN.2010040355
   PubMed Web of Science ®Google Scholar
• Okonogi H, Utsunomiya Y, Miyazaki Y, et al. A predictive clinical grading system for immunoglobulin a nephropathy by combining proteinuria and estimated glomerular filtration rate. Nephron Clin Pract. 2011;118(3):c292–c300. doi:10.1159/000322613
   PubMedGoogle Scholar
• Chen T, Li X, Li Y, et al. Prediction and risk stratification of kidney outcomes in IgA nephropathy. Am J Kidney Dis. 2019;74(3):300–309. doi:10.1053/j.ajkd.2019.02.016
   PubMed Web of Science ®Google Scholar
• Moura IC, Xie J, Kiryluk K, et al. Predicting progression of iga nephropathy: new clinical progression risk score. PLoS One. 2012;7(6):1.
   Web of Science ®Google Scholar
• Chacko B, John GT, Neelakantan N, et al. Presentation, prognosis and outcome of IgA nephropathy in Indian adults. Nephrology. 2005;10(5):496–503. doi:10.1111/j.1440-1797.2005.00445.x
   PubMed Web of Science ®Google Scholar
• Gaber LW, Khan FN, Graviss EA, et al. Prevalence, characteristics, and outcomes of incidental iga glomerular deposits in donor kidneys. Kidney Int Rep. 2020;5(11):1914–1924. doi:10.1016/j.ekir.2020.08.018
   PubMed Web of Science ®Google Scholar
• Waldherr R, Rambausek M, Duncker WD, Ritz E. Frequency of mesangial IgA deposits in a non-selected autopsy series. Nephrol Dial Transplant. 1989;4(11):943–946. doi:10.1093/ndt/4.11.943
   PubMed Web of Science ®Google Scholar
• Suzuki K, Honda K, Tanabe K, Toma H, Nihei H, Yamaguchi Y. Incidence of latent mesangial IgA deposition in renal allograft donors in Japan. Kidney Int. 2003;63(6):2286–2294. doi:10.1046/j.1523-1755.63.6s.2.x
   PubMed Web of Science ®Google Scholar
• Rule AD, Amer H, Cornell LD, et al. The association between age and nephrosclerosis on renal biopsy among healthy adults. Ann Intern Med. 2010;152(9):561–567. doi:10.7326/0003-4819-152-9-201005040-00006
   PubMed Web of Science ®Google Scholar
• Denic A, Lieske JC, Chakkera HA, et al. The substantial loss of nephrons in healthy human kidneys with aging. J Am Soc Nephrol. 2017;28(1):313–320. doi:10.1681/ASN.2016020154
   PubMed Web of Science ®Google Scholar
• Mancilla E, Avila-Casado C, Uribe-Uribe N, et al. Time-zero renal biopsy in living kidney transplantation: a valuable opportunity to correlate predonation clinical data with histological abnormalities. Transplantation. 2008;86(12):1684–1688. doi:10.1097/TP.0b013e3181906150
   PubMed Web of Science ®Google Scholar
• Poggio ED, Rule AD, Tanchanco R, et al. Demographic and clinical characteristics associated with glomerular filtration rates in living kidney donors. Kidney Int. 2009;75(10):1079–1087. doi:10.1038/ki.2009.11
   PubMed Web of Science ®Google Scholar
• Wetzels JF, Kiemeney LA, Swinkels DW, Willems HL, den Heijer M. Age- and gender-specific reference values of estimated GFR in caucasians: the Nijmegen biomedical study. Kidney Int. 2007;72(5):632–637. doi:10.1038/sj.ki.5002374
   PubMed Web of Science ®Google Scholar
• Pottel H, Delanaye P, Weekers L, et al. Age-dependent reference intervals for estimated and measured glomerular filtration rate. Clin Kidney J. 2017;10(4):545–551. doi:10.1093/ckj/sfx026
   PubMed Web of Science ®Google Scholar
• Eriksen BO, Palsson R, Ebert N, et al. GFR in healthy aging: an individual participant data meta-analysis of iohexol clearance in European population-based cohorts. J Am Soc Nephrol. 2020;31(7):1602–1615. doi:10.1681/ASN.2020020151
   PubMed Web of Science ®Google Scholar
• Chakkera HA, Denic A, Kremers WK, et al. Comparison of high glomerular filtration rate thresholds for identifying hyperfiltration. Nephrol Dial Transplant. 2020;35(6):1017–1026. doi:10.1093/ndt/gfy332
   PubMed Web of Science ®Google Scholar
• Praga M, Gutiérrez E, González E, Morales E, Hernández E. Treatment of IgA nephropathy with ACE inhibitors: a randomized and controlled trial. J Am Soc Nephrol. 2003;14(6):1578–1583. doi:10.1097/01.ASN.0000068460.37369.DC
   PubMed Web of Science ®Google Scholar
• Li PK, Leung CB, Chow KM, et al. Hong Kong study using valsartan in IgA nephropathy (HKVIN): a double-blind, randomized, placebo-controlled study. Am J Kidney Dis. 2006;47(5):751–760. doi:10.1053/j.ajkd.2006.01.017
   PubMed Web of Science ®Google Scholar
• Coppo R, Peruzzi L, Amore A, et al. IgACE: a placebo-controlled, randomized trial of angiotensin-converting enzyme inhibitors in children and young people with IgA nephropathy and moderate proteinuria. J Am Soc Nephrol. 2007;18(6):1880–1888. doi:10.1681/ASN.2006040347
   PubMed Web of Science ®Google Scholar
• Radford MG, Donadio JV, Bergstralh EJ, Grande JP. Predicting renal outcome in IgA nephropathy. J Am Soc Nephrol. 1997;8(2):199–207. doi:10.1681/ASN.V82199
   PubMed Web of Science ®Google Scholar
• Jakobsen JC, Gluud C, Wetterslev J, Winkel P. When and how should multiple imputation be used for handling missing data in randomised clinical trials - a practical guide with flowcharts. BMC Med Res Methodol. 2017;17(1):162. doi:10.1186/s12874-017-0442-1
   PubMed Web of Science ®Google Scholar
• Toll DB, Janssen KJ, Vergouwe Y, Moons KG. Validation, updating and impact of clinical prediction rules: a review. J Clin Epidemiol. 2008;61(11):1085–1094. doi:10.1016/j.jclinepi.2008.04.008
   PubMed Web of Science ®Google Scholar