Clinicopathological predictors for progression of chronic kidney disease in nephrosclerosis: a biopsy-based cohort study

Author:

Yamanouchi Masayuki1234,Hoshino Junichi24,Ubara Yoshifumi34,Takaichi Kenmei24,Kinowaki Keiichi5,Fujii Takeshi5,Ohashi Kenichi56,Mise Koki7,Toyama Tadashi8,Hara Akinori8,Shimizu Miho8,Furuichi Kengo8,Wada Takashi18

Affiliation:

1. Department of Nephrology and Laboratory Medicine, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Graduate School of Medical Sciences, Kanazawa University, Kanazawa, Japan

2. Nephrology Center, Toranomon Hospital, Tokyo, Japan

3. Nephrology Center, Toranomon Hospital Kajigaya, Kanagawa, Japan

4. Okinaka Memorial Institute for Medical Research, Tokyo, Japan

5. Department of Pathology, Toranomon Hospital, Tokyo, Japan

6. Department of Pathology, Yokohama City University Graduate School of Medicine, Kanagawa, Japan

7. Department of Nephrology, Rheumatology, Endocrinology and Metabolism, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan

8. Division of Nephrology, Kanazawa University Hospital, Kanazawa, Japan

Abstract

Abstract Background Biopsy-based studies on nephrosclerosis are lacking and the clinicopathological predictors for progression of chronic kidney disease (CKD) are not well established. Methods We retrospectively assessed 401 patients with biopsy-proven nephrosclerosis in Japan. Progression of CKD was defined as new-onset end-stage renal disease, decrease of estimated glomerular filtration rate (eGFR) by  ≥50% or doubling of serum creatinine, and the sub-distribution hazard ratio (SHR) with 95% confidence interval (CI) for CKD progression was determined for various clinical and histological characteristics in competing risks analysis. The incremental value of pathological information for predicting CKD progression was assessed by calculating Harrell’s C-statistics, the Akaike information criterion (AIC), net reclassification improvement and integrated discrimination improvement. Results During a median follow-up period of 5.3 years, 117 patients showed progression of CKD and 10 patients died before the defined kidney event. Multivariable sub-distribution hazards model identified serum albumin (SHR 0.48; 95% CI 0.35–0.67), hemoglobin A1c (SHR 0.71; 95% CI 0.54–0.94), eGFR (SHR 0.98; 95% CI 0.97–0.99), urinary albumin/creatinine ratio (UACR) (SHR 1.18; 95% CI 1.08–1.29), percentage of segmental/global glomerulosclerosis (%GS) (SHR 1.01; 95% CI 1.00–1.02) and interstitial fibrosis and tubular atrophy (IFTA) (SHR 1.52; 95% CI 1.20–1.92) as risk factors for CKD progression. The C-statistic of a model with only clinical variables was improved by adding %GS (0.790 versus 0.796, P < 0.01) and IFTA (0.790 versus 0.811, P < 0.01). The reclassification statistic was also improved after adding the biopsy data to the clinical data. The model including IFTA was superior, with the lowest AIC. Conclusions The study implies that in addition to the traditional markers of eGFR and UACR, we may explore the markers of serum albumin and hemoglobin A1c, which are widely available but not routinely measured in patients with nephrosclerosis, and the biopsy data, especially the data on the severity of interstitial damage, for the better prediction of CKD progression in patients with nephrosclerosis.

Funder

Grant-in-Aid for Practical Research Projects for Renal Diseases

Japan Agency for Medical Research and Development

Publisher

Oxford University Press (OUP)

Subject

Transplantation,Nephrology

Reference38 articles.

1. Chronic kidney disease: global dimension and perspectives;Jha;Lancet,2013

2. Annual report 2014;Ren Replace Ther,2014

3. Benign nephrosclerosis: incidence, morphology and prognosis;Takebayashi;Clin Nephrol,2001

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3