A Validation Study Comparing Risk Prediction Models of IgA Nephropathy

Representation of multimorbidity and frailty in the development and validation of kidney failure prognostic prediction models: a systematic review

BACKGROUND

Prognostic models that identify individuals with chronic kidney disease (CKD) at greatest risk of developing kidney failure help clinicians to make decisions and deliver precision medicine. It is recognised that people with CKD usually have multiple long-term health conditions (multimorbidity) and often experience frailty. We undertook a systematic review to evaluate the representation and consideration of multimorbidity and frailty within CKD cohorts used to develop and/or validate prognostic models assessing the risk of kidney failure.

METHODS

We identified studies that described derivation, validation or update of kidney failure prognostic models in MEDLINE, CINAHL Plus and the Cochrane Library-CENTRAL. The primary outcome was representation of multimorbidity or frailty. The secondary outcome was predictive accuracy of identified models in relation to presence of multimorbidity or frailty.

RESULTS

Ninety-seven studies reporting 121 different kidney failure prognostic models were identified. Two studies reported prevalence of multimorbidity and a single study reported prevalence of frailty. The rates of specific comorbidities were reported in a greater proportion of studies: 67.0% reported baseline data on diabetes, 54.6% reported hypertension and 39.2% reported cardiovascular disease. No studies included frailty in model development, and only one study considered multimorbidity as a predictor variable. No studies assessed model performance in populations in relation to multimorbidity. A single study assessed associations between frailty and the risks of kidney failure and death.

CONCLUSIONS

There is a paucity of kidney failure risk prediction models that consider the impact of multimorbidity and/or frailty, resulting in a lack of clear evidence-based practice for multimorbid or frail individuals. These knowledge gaps should be explored to help clinicians know whether these models can be used for CKD patients who experience multimorbidity and/or frailty.

SYSTEMATIC REVIEW REGISTRATION

This review has been registered on PROSPERO (CRD42022347295).

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.

External Validation of the Kidney Failure Risk Equation Among Urban Community-Based Chinese Patients With CKD

Rationale & Objective

The Kidney Failure Risk Equations have been proven to perform well in multinational databases, whereas validation in Asian populations is lacking. This study sought to externally validate the equations in a community-based chronic kidney disease cohort in China.

Study Design

A retrospective cohort study.

Setting & Participants

Patients with and estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2 dwelling in an industrialized coastal city of China.

Exposure

Age, sex, eGFR, and albuminuria were included in the 4-variable model, whereas serum calcium, phosphate, bicarbonate, and albumin levels were added to the previously noted variables in the 8-variable model.

Outcome

Initiation of long-term dialysis treatment.

Analytical Approach

Model discrimination, calibration, and clinical utility were evaluated by Harrell's C statistic, calibration plots, and decision curve analysis, respectively.

Results

A total of 4,587 participants were enrolled for validation of the 4-variable model, whereas 1,414 were enrolled for the 8-variable model. The median times of follow-up were 4.0 (interquartile range: 2.6-6.3) years for the 4-variable model and 3.4 (2.2-5.6) years for the 8-variable model. For the 4-variable model, the C statistics were 0.750 (95% CI: 0.615-0.885) for the 2-year model and 0.766 (0.625-0.907) for the 5-year model, whereas the values were 0.756 (0.629-0.883) and 0.774 (0.641-0.907), respectively, for the 8-variable model. Calibration was acceptable for both the 4-variable and 8-variable models. Decision curve analysis for the models at the 5-year scale performed better throughout different net benefit thresholds than the eGFR-based (<30 mL/min/1.73 m2) strategy.

Limitations

A large proportion of patients lack albuminuria measurements, and only a subset of population could provide complete data for the 8-variable equation.

Conclusions

The kidney failure risk equations showed acceptable discrimination and calibration and better clinical utility than the eGFR-based strategy for incidence of kidney failure among community-based urban Chinese patients with chronic kidney disease.

Glomerular transcriptomics predicts long term outcome and identifies therapeutic strategies for patients with assumed benign IgA nephropathy

Some patients diagnosed with benign IgA nephropathy (IgAN) develop a progressive clinical course, not predictable by known clinical or histopathological parameters. To assess if gene expression can differentiate between progressors and non-progressors with assumed benign IgAN, we tested microdissected glomeruli from archival kidney biopsy sections from adult patients with stable clinical remission (21 non-progressors) or from 15 patients that had undergone clinical progression within a 25-year time frame. Based on 1 240 differentially expressed genes from patients with suitable sequencing results, we identified eight IgAN progressor and nine non-progressor genes using a two-component classifier. These genes, including APOL5 and ZXDC, predicted disease progression with 88% accuracy, 75% sensitivity and 100% specificity on average 21.6 years before progressive disease was clinically documented. APOL lipoproteins are associated with inflammation, autophagy and kidney disease while ZXDC is a zinc-finger transcription factor modulating adaptive immunity. Ten genes from our transcriptomics data overlapped with an external genome wide association study dataset, although the gene set enrichment test was not statistically significant. We also identified 45 drug targets in the DrugBank database, including angiotensinogen, a target of sparsentan (dual antagonist of the endothelin type A receptor and the angiotensin II type 1 receptor) currently investigated for IgAN treatment. Two validation cohorts were used for substantiating key results, one by immunohistochemistry and the other by nCounter technology. Thus, glomerular mRNA sequencing from diagnostic kidney biopsies from patients with assumed benign IgAN can differentiate between future progressors and non-progressors at the time of diagnosis.

Sequential administration of paricalcitol followed by IL-17 blockade for progressive refractory IgA nephropathy patients

There is no established treatment for progressive IgA nephropathy refractory to steroids and immunosuppressant drugs (r-IgAN). Interleukin 17 (IL-17) blockade has garnered interest in immune-mediated diseases involving the gut-kidney axis. However, single IL-17A inhibition induced paradoxical effects in patients with Crohn's disease and some cases of de novo glomerulonephritis, possibly due to the complete Th1 cell response, along with the concomitant downregulation of regulatory T cells (Tregs). Seven r-IgAN patients were treated with at least six months of oral paricalcitol, followed by the addition of subcutaneous anti-IL-17A (secukinumab). After a mean follow-up of 28 months, proteinuria decreased by 71% (95% CI: 56-87), P < 0.001. One patient started dialysis, while the annual eGFR decline in the remaining patients [mean (95% CI)] was reduced by 4.9 mL/min/1.73 m2 (95% CI: 0.1-9.7), P = 0.046. Circulating Th1, Th17, and Treg cells remained stable, but Th2 cells decreased, modifying the Th1/Th2 ratio. Intriguingly, accumulation of circulating Th17.1 cells was observed. This novel sequential therapy appears to optimize renal advantages in patients with r-IgAN and elicit alterations in potentially pathogenic T helper cells.

External validation of the pediatric International IgA Nephropathy Prediction Tool in a central China cohort

BACKGROUND

This study aimed to externally validate the pediatric International IgA Nephropathy (IgAN) Prediction Tool updated from the adult IgAN Prediction Tool.

METHODS

439 children with biopsy-confirmed idiopathic IgAN were enrolled in this external validation study. The primary outcome was a 30% decline in eGFR or end-stage kidney disease. We evaluated the discrimination using Harrell's C-index, the receiver operating characteristic (ROC) curve, and Kaplan-Meier curves for four risk groups (< 16th [low risk], ∼16 to < 50th [intermediate risk], ∼50 to < 84th [high risk], and ≥ 84th percentiles [highest risk] of linear predictor). Calibration was assessed using calibration plots.

RESULTS

The median follow-up time of the 439 patients was 4.5 (2.7-6.8) years, and 27 patients reached the primary outcome. Compared with the reported cohorts, our cohort was more contemporary, with milder proteinuria at biopsy, and had lower proportions of S1 and T1 lesions. Harrell's C-index and area under the ROC curve at 5 years were < 0.7 for both the models with and without race. The Kaplan-Meier curves of the risk groups were not well separated for the two models, only separated completely between the highest-risk group and the others for the model without race. The two models generally overestimated the risk of the primary outcome, CONCLUSION: The model without race could accurately distinguish the highest-risk patients from patients with low, intermediate, and high risk for kidney progression. Discrimination and calibration for the full model with or without race were unsatisfactory in this contemporary cohort in central China.

Ethnicity and IgA nephropathy: worldwide differences in epidemiology, timing of diagnosis, clinical manifestations, management and prognosis

Immunoglobulin A nephropathy (IgAN), the most common primary glomerulonephritis, is one of the major causes of end-stage renal disease. Significant variances in epidemiology, clinical manifestation, timing of diagnosis, management and renal prognosis of IgAN have been reported worldwide. The incidence of IgAN is the most frequent in Asia, followed by Europe, and lower in Africa. Moreover, Asian patients show more frequent acute lesions in renal histology and present poorer renal outcomes compared with Caucasians. The comorbidities also show the difference between Asians and Caucasians. Although the frequency of gross hematuria with upper respiratory tract infection is not different, comorbidities with gastrointestinal diseases are reported to be higher in Europe. Recently, genetic studies for variant ethnic patients revealed widely ranging genetic risks in each ethnicity. A genetic risk score is most elevated in Asians, intermediate in Europeans and lowest in Africans, consistent with the disease prevalence of IgAN globally. Ethnic variance might be highly affected by the difference in genetic background. However, it is also essential to mention that the different timing of diagnosis due to variant urinary screening systems and the indication for renal biopsy in different countries may also contribute to these variances. The management of IgAN also varies internationally. Currently, several novel therapies based on the pathogenesis of IgAN are being assessed and are expected to become available soon. Further understanding the ethnic variance of IgAN might help establish individualized care for this disease. Here, we review the issues of ethnic heterogeneities of IgAN.

Evaluating Progression Risk in Patients With Immunoglobulin A Nephropathy

The highly variable rate of decline in kidney function in patients with immunoglobulin A nephropathy (IgAN) provides a major clinical challenge. Predicting which patients will progress to kidney failure, and how quickly, is difficult. Multiple novel therapies are likely to be approved in the short-term, but clinicians lack the tools to identify patients most likely to benefit from specific treatments at the right time. Noninvasive and validated markers for selecting at-risk patients and longitudinal monitoring are urgently needed. This review summarizes what is known about demographic, clinical, and histopathologic prognostic markers in the clinician's toolkit, including the International IgAN Prediction Tool. We also briefly review what is known on these topics in children and adolescents with IgAN. Although helpful, currently used markers leave clinicians heavily reliant on histologic features from the diagnostic kidney biopsy and standard clinical data to guide treatment choice, and very few noninvasive markers reflect treatment efficacy over time. Novel prognostic and predictive markers are under clinical investigation, with considerable progress being made in markers of complement activation. Other areas of research are the interplay between gut microbiota and galactose-deficient IgA1 expression; microRNAs; imaging; artificial intelligence; and markers of fibrosis. Given the rate of therapeutic advancement, the remaining gaps in biomarker research need to be addressed. We finish by describing our route to clinical utility of predictive and prognostic markers in IgAN. This route will provide us with the chance to improve IgAN prognosis by using robust, clinically practical markers to inform patient care.

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.

Urinary N-Acetyl-Beta-D-Glucosaminidase levels predict immunoglobulin a nephropathy remission status

BACKGROUND

Tubulointerstitial lesions play a pivotal role in the progression of IgA nephropathy (IgAN). Elevated N-acetyl-beta-D-glucosaminidase (NAG) in urine is released from damaged proximal tubular epithelial cells (PTEC) and may serve as a biomarker of renal progression in diseases with tubulointerstitial involvement.

METHODS

We evaluated the predictive value of urinary NAG (uNAG) for disease progression in 213 biopsy-proven primary IgAN patients from January 2018 to December 2019 at Zhongshan Hospital, Fudan University. We compared the results with those of serum cystatin C (sCysC).

RESULTS

Increased uNAG and sCysC levels were associated with worse clinical and histological manifestations. Only uNAG level was independently associated with remission status after adjustment. Patients with high uNAG levels (> 22.32 U/g Cr) had a 4.32-fold greater risk of disease progression. The combination of baseline uNAG and clinical data may achieve satisfactory risk prediction in IgAN patients with relatively preserved renal function (eGFR ≥ 60 ml/min/1.73 m2, area under the curve [AUC] 0.760).

CONCLUSION

Our results suggest that uNAG is a promising biomarker for predicting IgAN remission status.

Particulate matter of air pollution may increase risk of kidney failure in IgA nephropathy

IgA nephropathy (IgAN) is characterized by deposition of galactose-deficient IgA1 (Gd-IgA1) in glomerular mesangium associated with mucosal immune disorders. Since environmental pollution has been associated with the progression of chronic kidney disease in the general population, we specifically investigated the influence of exposure to fine particulate matter less than 2.5 μm in diameter (PM2.5) on IgAN progression. Patients with biopsy-proven primary IgAN were recruited from seven Chinese kidney centers. PM2.5 exposure from 1998 to 2016 was derived from satellite aerosol optical depth data and a total of 1,979 patients with IgAN, including 994 males were enrolled. The PM2.5 exposure levels for patients from different provinces varied but, in general, the PM2.5 exposure levels among patients from the north were higher than those among patients from the south. The severity of PM2.5 exposure in different regions was correlated with regional kidney failure burden. In addition, each 10 μg/m³ increase in annual average concentration of PM2.5 exposure before study entry (Hazard Ratio, 1.14; 95% confidence interval, 1.06-1.22) or time-varying PM2.5 exposure after study entry (1.10; 1.01-1.18) were associated with increased kidney failure risk after adjustment for age, gender, estimated glomerular filtration rate, urine protein, uric acid, hemoglobin, mean arterial pressure, Oxford classification, glucocorticoid and renin-angiotensin system blocker therapy. The associations were robust when the time period, risk factors of cardiovascular diseases or city size were further adjusted on the basis of the above model. Thus, our results suggest that PM2.5 is an independent risk factor for kidney failure in patients with IgAN, but these findings will require validation in more diverse populations and other geographic regions.

Validation of two IgA nephropathy risk-prediction tools using a cohort with a long follow-up

BACKGROUND

Recently, two immunoglobulin A nephropathy prediction tools were developed that combine clinical and histopathological parameters. The International IgAN Prediction Tool predicts the risk for 50% declines in the estimated glomerular filtration rate or end-stage renal disease up to 80 months after diagnosis. The IgA Nephropathy Clinical Decision Support System uses artificial neural networks to estimate the risk for end-stage renal disease. We aimed to externally validate both prediction tools using a Norwegian cohort with a long-term follow-up.

METHODS

We included 306 patients with biopsy-proven primary immunoglobulin A nephropathy in this study. Histopathologic samples were retrieved from the Norwegian Kidney Biopsy Registry and reclassified according to the Oxford classification. We used discrimination and calibration as principles for externally validating the prognostic models.

RESULTS

The median patient follow-up was 17.1 years. A cumulative dynamic time-dependent receiver operating characteristic analysis showed area under the curve values of ranging from 0.90 at 5 years to 0.83 at 20 years for the International IgAN Prediction Tool, while time-naive analysis showed an area under the curve value at 0.83 for the IgA Nephropathy Clinical Decision Support System. The International IgAN Prediction Tool was well calibrated, while the IgA Nephropathy Clinical Decision Support System tends to underestimate risk for patients with higher risk, and overestimates risk in the lower risk categories.

CONCLUSIONS

We have externally validated two prediction tools for IgA nephropathy. The International IgAN Prediction Tool performed well, while the IgA Nephropathy Clinical Decision Support System has some limitations.

External validation of the International Prediction Tool in Korean patients with immunoglobulin A nephropathy

Background

The International IgA Nephropathy Prediction Tool (International IgA Nephropathy Prediction Tool) has been recently developed to estimate the progression risk of immunoglobulin A nephropathy (IgAN). This study aimed to evaluate the clinical performance of this prediction tool in a large IgAN cohort in Korea.

Methods

The study cohort was comprised of 2,064 patients with biopsy-proven IgAN from four medical centers between March 2012 and September 2021. We calculated the predicted risk for each patient. The primary outcome was occurrence of a 50% decline in estimated glomerular filtration rate (eGFR) from the time of biopsy or end-stage kidney disease. The model performance was evaluated for discrimination, calibration, and reclassification. We also constructed and tested an additional model with a new coefficient for the Korean race.

Results

During a median follow-up period of 3.8 years (interquartile range, 1.8–6.6 years), 363 patients developed the primary outcome. The two prediction models exhibited good discrimination power, with a C-statistic of 0.81. The two models generally underestimated the risk of the primary outcome, with lesser underestimation for the model with race. The model with race showed better performance in reclassification compared to the model without race (net reclassification index, 0.13). The updated model with the Korean coefficient showed good agreement between predicted risk and observed outcome.

Conclusion

In Korean IgAN patients, International IgA Nephropathy Prediction Tool had good discrimination power but underestimated the risk of progression. The updated model with the Korean coefficient showed acceptable calibration and warrants external validation.