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Identification and external validation of IgA nephropathy patients benefiting from immunosuppression therapy.
EBioMedicine ( IF 11.1 ) Pub Date : 2020-02-12 , DOI: 10.1016/j.ebiom.2020.102657 Tingyu Chen 1 , Eryu Xia 2 , Tiange Chen 3 , Caihong Zeng 1 , Shaoshan Liang 1 , Feng Xu 1 , Yong Qin 2 , Xiang Li 3 , Yuan Zhang 2 , Dandan Liang 1 , Guotong Xie 3 , Zhihong Liu 1
EBioMedicine ( IF 11.1 ) Pub Date : 2020-02-12 , DOI: 10.1016/j.ebiom.2020.102657 Tingyu Chen 1 , Eryu Xia 2 , Tiange Chen 3 , Caihong Zeng 1 , Shaoshan Liang 1 , Feng Xu 1 , Yong Qin 2 , Xiang Li 3 , Yuan Zhang 2 , Dandan Liang 1 , Guotong Xie 3 , Zhihong Liu 1
Affiliation
BACKGROUND
Although IgA nephropathy (IgAN), an immune-mediated disease with heterogeneous clinical and pathological phenotypes, is the most common glomerulonephritis worldwide, it remains unclear which IgAN patients benefit from immunosuppression (IS) therapy.
METHODS
Clinical and pathological data from 4047 biopsy-proven IgAN patients from 24 renal centres in China were included. The derivation and validation cohorts were composed of 2058 and 1989 patients, respectively. Model-based recursive partitioning, a machine learning approach, was performed to partition patients in the derivation cohort into subgroups with different IS long-term benefits, associated with time to end-stage kidney disease, measured by adjusted Kaplan-Meier estimator and adjusted hazard ratio (HR) using Cox regression.
FINDINGS
Three identified subgroups obtained a significant IS benefits with HRs ≤ 1. In patients with serum creatinine ≤ 1·437 mg/dl, the benefits of IS were observed in those with proteinuria > 1·525 g/24h (node 6; HR = 0·50; 95% CI, 0·29 to 0·89; P = 0·02), especially in those with proteinuria > 2·480 g/24h (node 8; HR = 0·23; 95% CI, 0·11 to 0·50; P <0·001). In patients with serum creatinine > 1·437 mg/dl, those with high proteinuria and crescents benefitted from IS (node 12; HR = 0·29; 95% CI, 0·09 to 0·94; P = 0·04). The treatment benefits were externally validated in the validation cohort.
INTERPRETATION
Machine learning could be employed to identify subgroups with different IS benefits. These efforts promote decision-making, assist targeted clinical trial design, and shed light on individualised treatment in IgAN patients.
FUNDING
National Key Research and Development Program of China (2016YFC0904103), National Key Technology R&D Program (2015BAI12B02).
更新日期：2020-02-20
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