Authors
Hiroyuki Tamaki, Masahiro Eriguchi, Kohei Ohori, Takayuki Uemura, Hikari Tasaki, Riri Furuyama, Masatoshi Nishimoto, Kaori Tanabe, Katsuhiko Morimoto, Keisuke Okamoto, Masaru Matsui, Ken-Ichi Samejima, Kazuhiko Tsuruya
Published in
Diabetes, obesity & metabolism. Jul 13, 2026. Epub Jul 13, 2026.
Abstract
Proteinuria is a standard predictor for kidney prognosis in patients with diabetic nephropathy (DN). Even among patients with similar levels of proteinuria, the protein load per functioning nephron can vary substantially depending on the total number of functioning nephrons. We examined whether fractional excretion of total protein (FETP), which reflects the protein load per single functioning nephron, provides superior prognostic value for kidney outcomes compared with conventional proteinuria in DN.
This observational study included patients with biopsy-proven DN at our institution between June 1981 and December 2014. The primary focus was the incremental prognostic value of adding FETP, compared with proteinuria, to a baseline clinical model for predicting kidney failure requiring replacement therapy (KFRT). Improvements in model discrimination and risk reclassification were quantified using the concordance index (C-index), net reclassification improvement (NRI), and integrated discrimination improvement (IDI).
This study included 376 patients with biopsy-proven DN (median age: 59 years; 62.5% male; median estimated glomerular filtration rate, 58.1 mL/min/1.73 m2). Over a median follow-up period of 6.7 years, 97 patients developed KFRT. Compared with the proteinuria-based model, the FETP-based model showed a significantly higher discrimination ability (ΔC-index: 0.021 [95% confidence interval (CI): 0.002-0.039]) and improved IDI (0.089 [95% CI: 0.001-0.207]). In contrast, the continuous NRI was not statistically significant.
FETP was independently associated with KFRT in patients with DN and may provide additional prognostic information beyond conventional proteinuria for risk stratification.
UMIN000031121 (University Hospital Medical Information Network).
PMID:
42443597
Bibliographic data and abstract were imported from PubMed on 14 Jul 2026.
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