Prediction of prognosis in immunoglobulin a nephropathy patients with focal crescent by machine learning

Prognostic factors affecting long-term outcomes in patients with concurrent IgA nephropathy and membranous nephropathy

Background

The incidence of concurrent immunoglobulin A nephropathy and membranous nephropathy (cIgAN/MN) is low and rarely reported, and the prognosis of patients with cIgAN/MN remains unclear. This study was designed to compare the clinical and prognostic characteristics of cIgAN/MN with IgAN and MN and to identify crucial factors influencing the outcomes of patients with cIgAN/MN.

Methods

We included biopsy-proven cIgAN/MN patients between December 2012 and December 2020 at Xijing Hospital. In the same period, propensity score matching was employed to select an equal number of IgAN and MN patients according to the following criteria: age, sex, and follow-up time. The primary endpoint was defined as a composite of eGFR decline ≥30 %, end-stage renal disease, or death. The patient survival rate was examined using Kaplan-Meier survival curves. Univariate and multivariate Cox regression analysis models were utilized to identify the risk factors affecting renal prognosis.

Results

A total of 135 patients were finally included in this study and 35 (25.9 %) reached the primary endpoint. The median follow-up time of cIgAN/MN was 45.9 (24.0, 72.0) months. Compared to the IgAN group, the cIgAN/MN group exhibited a lower cumulative incidence rate of composite renal endpoints (P = 0.044), while no significant difference was found between MN and cIgAN/MN patients (P = 0.211). Univariate Cox analysis revealed that mean arterial pressure, serum potassium, blood urea nitrogen, serum IgA, segmental glomerulosclerosis (S1), and MN staging were associated with an increased risk of renal composite endpoints. The multivariate Cox regression analysis of clinical variables plus histological lesion scoring demonstrated that potassium (HR = 14.350, 95 % CI 2.637-78.090, P = 0.002), serum IgA (HR = 1.870, 95 % CI 1.109-3.153, P = 0.019), and S1 (HR = 11.965, 95 % CI 2.166-66.105, P = 0.004) were independent risk factors influencing renal outcomes in cIgAN/MN patients.

Conclusion

The prognosis of cIgAN/MN patients may exhibit an intermediate pattern between IgAN and MN, leaning towards being more similar to MN in certain aspects. Within the cIgAN/MN cohort, potassium, and serum IgA may be more predictive of rapid progression of renal endpoints, and S1 may indicate a more aggressive disease course.

Validation of the international IgA nephropathy prediction tool in a French cohort beyond 10 years after diagnosis

INTRODUCTION

The International IgA Nephropathy Network developed a tool (IINN-PT) for predicting the risk of end-stage renal disease (ESRD) or a 50% decline in the estimated glomerular filtration rate (eGFR). We aimed to validate this tool in a French cohort with longer follow-up than previously published validation studies.

METHODS

The predicted survival of patients with biopsy-proven immunoglobulin A nephropathy (IgAN) from the Saint Etienne University Hospital cohort was computed with IINN-PT models with or without ethnicity. The primary outcome was the occurrence of either ESRD or a 50% decline in eGFR. The models' performances were evaluated through c-statistics, discrimination and calibration analysis.

RESULTS

There were 473 patients with biopsy-proven IgAN, with a median follow-up of 12.4 years. Models with and without ethnicity showed areas under the curve (95% confidence interval) of 0.817 (0.765; 0.869) and 0.833 (0.791; 0.875) and R2D of 0.28 and 0.29, respectively, and an excellent discrimination of groups of increasing predicted risk (P < .001). The calibration analysis was good for both models up to 15 years after diagnosis. The model without ethnicity exhibited a mathematical issue of survival function after 15 years.

DISCUSSION

The IINN-PT provided good performances even after 10 years post-biopsy as showed by our study based on a cohort with a longer follow-up than previous cohorts (12.4 versus <6 years). The model without ethnicity exhibited better performances up to 15 years but became aberrant beyond this point due to a mathematical issue affecting the survival function. Our study sheds light on the usefulness of integrating ethnicity as a covariable for prediction of IgAN course.

A noninvasive artificial neural network model to predict IgA nephropathy risk in Chinese population

Renal biopsy is the gold standard for Immunoglobulin A nephropathy (IgAN) but poses several problems. Thus, we aimed to establish a noninvasive model for predicting the risk probability of IgAN by analyzing routine and serological parameters. A total of 519 biopsy-diagnosed IgAN and 211 non-IgAN patients were recruited retrospectively. Artificial neural networks and logistic modeling were used. The receiver operating characteristic (ROC) curve and performance characteristics were determined to compare the diagnostic value between the two models. The training and validation sets did not differ significantly in terms of any variables. There were 19 significantly different parameters between the IgAN and non-IgAN groups. After multivariable logistic regression analysis, age, serum albumin, serum IgA, serum immunoglobulin G, estimated glomerular filtration rate, serum IgA/C3 ratio, and hematuria were found to be independently associated with the presence of IgAN. A backpropagation network model based on the above parameters was constructed and applied to the validation cohorts, revealing a sensitivity of 82.68% and a specificity of 84.78%. The area under the ROC curve for this model was higher than that for logistic regression model (0.881 vs. 0.839). The artificial neural network model based on routine markers can be a valuable noninvasive tool for predicting IgAN in screening practice.