Prognostic value of low-density lipoprotein cholesterol in IgA nephropathy and establishment of nomogram model

Machine learning-based diagnosis and prognosis of IgAN: A systematic review and meta-analysis

Purpose

Plenty of studies have explored the diagnosis and prognosis of IgA nephropathy (IgAN) based on machine learning (ML), but the accuracy lacks the support of evidence-based medical evidence. We aim at this problem to guide the precision treatment of IgAN.

Methods

Embase, Pubmed, Cochrane Library, and Web of Science were searched systematically until February 24th, 2024, for publications on ML-based diagnosis and prognosis of IgAN. Subgroup analysis or meta-regression was conducted according to modeling method, follow-up time, endpoint definition, and variable type. Further, the rank sum test was applied to compare the discrimination ability of prognosis.

Results

A total of 47 studies involving 51,935 patients were eligible. Among the 38 diagnostic models, the pooled C-index was 0.902 (95 % CI: 0.878-0.926) in 27 diagnostic models. Of the 162 prognostic models, the C-index for model discrimination of 144 prognostic models was 0.838 (95 % CI: 0.827-0.850) in training. The overall discrimination ability of prognosis was as follows: COX regression > new ML models (e.g. ANN, DT, RF, SVM, XGBoost) > traditional ML models (logistic regression) > Naïve Bayesian network (P < 0.05). External validation of IIgAN-RPT in 19 models showed a pooled C-index of 0.801 (95 % CI: 0.784-0.817).

Conclusions

New ML models have shown application values that are as good as traditional ML models, both in diagnosis and prognosis. In addition, future models are desired to use a more sensitive prognostic endpoint (albuminuria), improve predictive ability in moderate progression risk, and ultimately translate into clinically applicable intelligent tools.

Hydroxychloroquine Induces Remission for IgA Nephropathy With Mild to Moderate Proteinuria: A Single-Centered Retrospective Analysis

BACKGROUND

Hydroxychloroquine (HCQ) influences both toll-like receptor (TLR) signaling and leukocyte activation, which are speculated to play a role in the pathogenesis of IgA nephropathy (IgAN).

METHODS

This is a single-centered retrospective study involving 426 IgAN patients diagnosed from May 2016 to August 2020. All patients were matched according to a propensity score matching (PSM) to produce three groups: renin-angiotensin-aldosterone system inhibitors (RAASi) group (RAASi only), corticosteroids group (corticosteroids only or combined with RAASi), and HCQ group (HCQ only or combined with RAASi), consisting of 63 patients for each group.

RESULTS

After PSM, the median urine protein/creatinine ratio (UPCR) of overall patients was 0.91 g/g, while their median serum creatinine was 87.00 μmol/L. After the median follow-up period of 11.03 months, the total remission rates of the RAASi group, corticosteroids group, and HCQ groups were 49.21% (n = 31), 74.60% (n = 47), and 52.38% (n = 33), respectively (p = 0.017). Thirteen (6.88%) patients experienced a decline in estimated glomerular filtration rate (eGFR) of more than 25% from baseline, including six (9.52%) patients in the RAASi group, three (4.76%) patients in the corticosteroids group, and four (6.35%) patients in HCQ group (p = 0.677). One (1.59%) patient in the HCQ group had blurred vision and continued to use HCQ after ruling out retinal lesions by ophthalmic examination.

CONCLUSION

HCQ is effective in inducing remission and well-tolerated in IgAN patients with mild to moderate proteinuria.