Validation of the Toronto formula to predict progression in IgA nephropathy

Development and External Validation of a Multidimensional Deep Learning Model to Dynamically Predict Kidney Outcomes in IgA Nephropathy

Key Points

A dynamic model predicts IgA nephropathy prognosis based on deep learning. Longitudinal clinical data and deep learning improve predictive accuracy and interpretability in GN.

Background

Accurately predicting kidney outcomes in IgA nephropathy is crucial for clinical decision making. Insufficient use of longitudinal data in previous studies has limited the accuracy and interpretability of prediction models for failing to reflect the chronic nature of IgA nephropathy. The aim of this study was to establish a multivariable dynamic deep learning model using comprehensive longitudinal data for the prediction of kidney outcomes in IgA nephropathy.

Methods

In this retrospective cohort study of 2056 patients with IgA nephropathy from 18 kidney centers, a total of 28,317 data points were collected by the sliding window method. Among them, 15,462 windows in a single center were randomly assigned to training (80%) and validation (20%) sets and 8797 windows in 18 kidney centers were assigned to an independent test set. Interpretable multivariable long short-term memory, a deep learning model, was implemented to predict kidney outcomes (kidney failure or 50% decline in kidney function) based on time-invariant variables measured at biopsy and time-variant variables measured during follow-up. Risk performance was evaluated using the Kaplan–Meier analysis and C-statistic. Trajectory analysis was performed to assess the various trends of clinical variables during follow-up.

Results

The model achieved a higher C-statistic (0.93; 95% confidence interval, 0.92 to 0.95) on the test set than the machine learning prediction model that we developed in a previous study using only baseline information (C-statistic, 0.84; 95% confidence interval, 0.80 to 0.88). The Kaplan–Meier analysis showed that groups with lower predicted risks from the full model survived longer than groups with higher risks. Time-variant variables demonstrated higher importance scores than time-invariant variables. Within time-variant variables, more recent measurements showed higher importance scores. Further interpretation showed that certain trajectory groups of time-variant variables such as serum creatinine and urine protein were associated with elevated risks of adverse outcomes.

Conclusions

In IgA nephropathy, a deep learning model can be used to accurately and dynamically predict kidney prognosis based on longitudinal data, and time-variant variables show strong ability to predict kidney outcomes.

Reduction in proteinuria after immunosuppressive therapy and long-term kidney outcomes in patients with immunoglobulin A nephropathy

BACKGROUND/AIMS

Despite controversy regarding the benefits of immunosuppressive therapy in immunoglobulin A nephropathy (IgAN), clinical outcomes may vary depending on the patient's responsiveness to this therapy. This study evaluated long-term kidney outcomes according to the extent of proteinuria reduction after immunosuppression in IgAN patients.

METHODS

Among 927 patients with biopsy-proven IgAN, 127 patients underwent immunosuppression. Time-averaged urine protein-creatinine ratio before and within 1 year after start of immunosuppression were calculated, and responsiveness to immunosuppression was assessed as the reduction of proteinuria between the two periods. Patients were classified into tertiles according to the extent of proteinuria reduction. We compared the slopes of estimated glomerular filtration rate (eGFR) decline using a linear mixed model, and estimated hazard ratios (HRs) for disease progression (defined as development of a ≥ 30% decline in eGFR or end-stage renal disease) using a Cox proportional hazard model.

RESULTS

Median extent of proteinuria reduction was -2.1, -0.9, and -0.2 g/gCr in the first, second, and third tertiles, respectively. There were concomitant changes in the slopes of annual eGFR decline: -2.03, -2.44, and -4.62 mL/min/1.73 m2 among the first, second, and third tertiles, respectively. In multivariable Cox analysis, the HRs (95% confidence intervals) for disease progression were 0.30 (0.12 to 0.74) in the first tertile and 0.70 (0.34 to 1.45) in the second tertile compared with the thirdtertile.

CONCLUSION

This study showed that greater proteinuria reduction after immunosuppression was associated with a lower risk of disease progression in patients with IgAN, suggesting that responsiveness to immunosuppression may be an important determinant of kidney outcomes.

Validation of an international prediction model including the Oxford classification in Korean patients with IgA nephropathy

BACKGROUND

Recently, a new international risk prediction model including the Oxford classification was published which was validated in a large multi-ethnic cohort. Therefore, we aimed to validate this risk prediction model in Korean patients with IgA nephropathy.

METHODS

This retrospective cohort study was conducted with 545 patients who diagnosed IgA nephropathy with renal biopsy in three medical centers. The primary outcome was defined as a reduction in estimated glomerular filtration rate (eGFR) of >50% or incident end-stage renal disease (ESRD). Continuous net reclassification improvement (cNRI) and integrated discrimination improvement (IDI) were used to validate models.

RESULTS

During the median 3.6 years of follow-up period, 53 (9.7%) renal events occurred. In multivariable Cox regression model, M1 (hazard ratio [HR], 2.22; 95% confidence interval [CI], 1.02-4.82; p = .043), T1 (HR, 2.98; 95% CI, 1.39-6.39; p = .005) and T2 (HR, 4.80; 95% CI, 2.06-11.18; p < .001) lesions were associated with increased risk of renal outcome. When applied the international prediction model, the area under curve (AUC) for 5-year risk of renal outcome was 0.69, which was lower than previous validation and internally derived models. Moreover, cNRI and IDI analyses showed that discrimination and reclassification performance of the international model was inferior to the internally derived models.

CONCLUSION

The international risk prediction model for IgA nephropathy showed not as good performance in Korean patients as previous validation in other ethnic group. Further validation of risk prediction model is needed for Korean patients with IgA nephropathy.

Repeat renal biopsy improves the Oxford classification-based prediction of immunoglobulin A nephropathy outcome

BACKGROUND

The prognosis of IgA nephropathy (IgAN) is very heterogeneous. Predicting the nature and the rate of the disease progression is crucial for refining patient treatment. The aim of this study was to evaluate the prognostic impact of an Oxford classification-based repeat kidney tissue evaluation to predict end-stage renal disease (ESRD).

METHODS

Patients with biopsy-proven primary IgAN who underwent two renal biopsies at our centre were analyzed retrospectively. Renal biopsies were scored by two pathologists blinded to the clinical data and according to the updated Oxford classification. Cox models were generated to evaluate the prognostic impact considering the Oxford classification elementary lesions from the first (Model 1) or the second (Model 2) biopsy, adjusted on clinical data at time of reevaluation. The prognostic impacts of the dynamic evolution of each elementary lesion between biopsies were also assessed through univariate and multivariate evaluation.

RESULTS

A total of 168 adult patients were included, with a median follow-up duration of 18 (range 11-24) years. The second biopsy was performed either systematically (n = 112) of for-cause (n = 56), after a median time of 5.4 years. The prognostic performances of Model 2 (second biopsy) were significantly better than Model 1 (first biopsy, analysis of deviance P < 0.0001). The dynamic changes of C and T lesions were significantly associated with the progression toward ESRD after adjustment on variables from Model 2.

CONCLUSION

Both static and dynamic Oxford-based histological evaluation offered by a repeat biopsy improves the prediction of ESRD in patients with IgAN.

How to optimize the design and implementation of risk prediction tools: focus group with patients with IgA nephropathy

Background

IgA nephropathy (IgAN) is a common type of chronic immune-mediated kidney disease with variable risk of progression to end-stage kidney disease. Risk stratification helps clinicians weight the potential risks and benefits of immunosuppressive therapy for individual patients, and can inform patient-centred communication. No prior research examined barriers of risk predication tools (RPT) specific to IgAN. The purpose of this study was to explore determinants (facilitators, barriers) of RPT use from the patient perspective.

Methods

We conducted a single focus group with English-speaking adults aged 18 or older with biopsy-proven IgAN. We asked about how they would use an IgAN RPT, and how to improve its design and implementation. We analyzed the transcript using constant comparison to inductively derive themes, and complied with qualitative research reporting criteria.

Results

The 5 participants were Caucasian men who varied in age from 35 to 55. The glomerular filtration rate ranged from 29 to 71 mL/min/1.73m², and proteinuria ranged from 0.36 to 1.41 g/d. Participants identified both benefits and harms of the risk score. They said physicians should first ask patients for permission to use it. To make it more useful, participants offered suggestions to enhance RTP design: visual display, information on how to interpret the risk score, risk categories, health implications, modifiable risk factors, multiple scenarios, and comparison with similar patients. They offered additional suggestions to enhance RPT implementation: it should not replace patient-provider discussion, it should be accompanied by self-management education so that patients can take an active role in their health. Participants appreciated information from members of the multidisciplinary team in addition to physicians. Participants also said that physicians should monitor patient emotions or concerns on an ongoing basis.

Conclusions

Patients with IgAN identified numerous ways to enhance the design and use of an RPT. Others could use this information to design and implement RPTs for patients with other conditions, but should employ user-centred design to develop RPTs that address patient preferences.

External Validation of the International IgA Nephropathy Prediction Tool

BACKGROUND AND OBJECTIVES

The International IgA Nephropathy Network recently developed and externally validated two models to predict the risk of progression of IgA nephropathy: full models without and with race. This study sought to externally validate the International IgA Nephropathy Prediction Tool in a large, independent, and contemporary cohort in China.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

We included 1373 patients with biopsy-confirmed primary IgA nephropathy from The First Affiliated Hospital of Zhengzhou University from January 2012 to May 2018 and calculated predicted risks for each patient. The outcomes of interest were a 50% decline in eGFR or kidney failure. We assessed the performance of both models using discrimination (concordance statistics and Kaplan-Meier curves between subgroups), calibration (calibration plots), reclassification (net reclassification improvement and integrated discrimination improvement), and clinical utility (decision curve analysis).

RESULTS

The median follow-up was 29 months (interquartile range, 21-43 months; range, 1-95 months), and 186 (14%) patients reached the kidney outcomes of interest. Both models showed excellent discrimination (concordance statistics >0.85 and well separated survival curves). Overall, the full model without race generally underestimated the risk of primary outcome, whereas the full model with race was well calibrated for predicting 5-year risk. Compared with the full model without race, the full model with race had significant improvement in reclassification, as assessed by the net reclassification improvement (0.49; 95% confidence interval, 0.41 to 0.59) and integrated discrimination improvement (0.06; 95% confidence interval, 0.04 to 0.08). Decision curve analysis showed that both full models had a higher net benefit than default strategies, and the model with race performed better.

CONCLUSIONS

In this study, both full models demonstrated remarkable discrimination, acceptable calibration, and satisfactory clinical utility. The relatively short follow-up time may have limited the validation of these models.

Predictive value of mesangial C3 and C4d deposition in IgA nephropathy

We aimed to determine the relative contribution of each complement (C3 and C4d) deposition to the progression of IgA nephropathy (IgAN). We enrolled a total of 380 patients with biopsy-confirmed IgAN. Mesangial deposition of C3(<2+ vs. ≥2+) and C4d(positive vs. negative) was evaluated by immunofluorescence staining and immunohistochemistry, respectively. Study endpoint was the composite of a 30% decline in eGFR or ESRD. The risk of reaching the primary outcome was significantly higher in patients having C3 ≥ 2+ and C4d(+) than in corresponding counterparts. Adding C3 deposition to clinical data acquired at kidney biopsy modestly increased the area under the receiver-operating characteristic curve, net reclassification improvement, and integrated discrimination improvement (IDI); adding C4d increased IDI only. In conclusion, mesangial C3 and C4d deposition was an independent risk factor for progression of IgAN. C3 showed better predictability than C4d, suggesting that lectin pathway alone has limited clinical prognostic value.

Patient classification and outcome prediction in IgA nephropathy

OBJECTIVE

IgA Nephropathy (IgAN) is a common kidney disease which may entail renal failure, known as End Stage Kidney Disease (ESKD). One of the major difficulties dealing with this disease is to predict the time of the long-term prognosis for a patient at the time of diagnosis. In fact, the progression of IgAN to ESKD depends on an intricate interrelationship between clinical and laboratory findings. Therefore, the objective of this work has been the selection of the best data mining tool to build a model able to predict (I) if a patient with a biopsy proven IgAN will reach ESKD and (II) if a patient will reach the ESKD before or after 5 years.

MATERIAL AND METHODS

The largest available cohort study worldwide on IgAN has been used to design and compare several data-driven models. The complete dataset was composed of 1174 records collected from Italian, Norwegian, and Japanese IgAN patients, in the last 30 years. The data mining tools considered in this work were artificial neural networks (ANNs), neuro fuzzy systems (NFSs), support vector machines (SVMs), and decision trees (DTs). A 10-fold cross validation was used to evaluate unbiased performances for all the models.

RESULTS

An extensive model comparison based on accuracy, precision, recall, and f-measure was provided. Overall, the results indicate that ANNs can provide superior performance compared to the other models. The ANN for time-to-ESKD prediction is characterized by accuracy, precision, recall, and f-measure greater than 90%. The ANN for ESKD prediction has accuracy greater than 90% as well as precision, recall, and f-measure for the class of patients not reaching ESKD, while precision, recall, and f-measure for the class of patients reaching ESKD are slightly lower. The obtained model has been implemented in a Web-based decision support system (DSS).

CONCLUSIONS

The extraction of novel knowledge from clinical data and the definition of predictive models to support diagnosis, prognosis, and therapy is becoming an essential tool for researchers and clinical practitioners in medicine. The proposed comparative study of several data mining models for the outcome prediction in IgAN patients, using a large dataset of clinical records from three different countries, provides an insight into the relative prediction ability of the considered methods applied to such a disease.

Long-term kidney survival analyses in IgA nephropathy patients under steroids therapy: a case control study

BACKGROUND

Corticosteroids are preferred to treat patients with active IgA nephropathy (IgAN), and beneficial effects from the short-term use of corticosteroids have been confirmed. However, a large number of patients will progress to end-stage renal disease after a long time follow-up. This study aimed to evaluate kidney disease progression and risk factors on kidney survival in IgAN patients receiving steroids treatment.

METHODS

Two hundred biopsy-proven IgAN patients who received corticosteroid therapy were enrolled and followed for a median period of 63.33 months. Risk factors on kidney survival were retrospectively investigated by the Cox proportional hazards model.

RESULTS

Of the two hundred patients, twenty patients showed progression of renal impairment at the end of follow-up. The median and interquartile range values for initial serum creatinine were 89.2 and 68.08-121.35 µmol/L, respectively. Multivariate Cox regression analyses revealed that relapse, non-remission, time-averaged eGFR (TA-eGFR), and time-averaged serum albumin (TA-ALB) were independently associated with the kidney progression. Those with TA-ALB levels <35 g/L and TA-eGFR levels <60 mL/min/1.73 m(2) were less likely to recover from kidney progression. Patients were more likely to show kidney function deterioration, when they had non-remission or relapse after corticosteroids treatment.

CONCLUSION

This study demonstrated that relapse, non-remission, TA-eGFR, and TA-ALB could serve as independent predictors of long term prognosis of IgAN patients receiving corticosteroid therapy.

Clinical decision support system for end-stage kidney disease risk estimation in IgA nephropathy patients

BACKGROUND

The progression of IgA nephropathy (IgAN) to end-stage kidney disease (ESKD) depends on several factors that are not quite clear and tangle the risk assessment. We aimed at developing a clinical decision support system (CDSS) for a quantitative risk assessment of ESKD and its timing using available clinical data at the time of renal biopsy.

METHODS

We included a total of 1040 biopsy-proven IgAN patients with long-term follow-up from Italy (N = 546), Norway (N = 441) and Japan (N = 53). Of these, 241 patients reached ESKD: 104 Italian [median time to ESKD = 5 (3-9) years], 134 Norwegian [median time to ESKD = 6 (2-11) years] and 3 Japanese [median time to ESKD = 3 (2-12) years]. We independently trained and validated two cooperating artificial neural networks (ANNs) for predicting first the ESKD status and then the time to ESKD (defined as three categories: ≤ 3 years, between > 3 and 8 years and over 8 years). As inputs we used gender, age, histological grading, serum creatinine, 24-h proteinuria and hypertension at the time of renal biopsy.

RESULTS

The ANNs demonstrated high performance for both the prediction of ESKD (with an AUC of 89.9, 93.3 and 100% in the Italian, Norwegian and Japanese IgAN population, respectively) and its timing (f-measure of 90.7% in the cohort from Italy and 70.8% in the one from Norway). We embedded the two ANNs in a CDSS available online (www.igan.net). Entering the clinical parameters at the time of renal biopsy, the CDSS returns as output the estimated risk and timing of ESKD for the patient.

CONCLUSIONS

This CDSS provides useful additional information for identifying 'high-risk' IgAN patients and may help stratify them in the context of a personalized medicine approach.

Time-averaged albumin predicts the long-term prognosis of IgA nephropathy patients who achieved remission

Background

Primary IgA nephropathy (IgAN) is the most common form of idiopathic glomerulonephritis worldwide. Although most patients are able to achieve remission with the current therapy, a large number of patients will still progress to end-stage renal disease. This study aimed to evaluate kidney disease progression and the risk factors for progression in IgAN patients who achieved remission.

Methods

Patients from a prospective database with IgAN were included in this study. All the subjects had achieved a complete remission (CR) or partial remission (PR) following 6 months of therapy. Renal survival and the relationship between the clinical parameters and composite renal outcomes were assessed.

Results

The study comprised 878 IgAN patients recruited between January 2005 and December 2010. Overall, 632 patients were enrolled in this study. The data from the 369 patients who achieved remission were analyzed; the mean follow-up time was 49 months. The median serum creatinine (SCr) concentration at baseline was 91.3 μmol/L, and the time-averaged creatinine (TA-SCr) was 91.8 μmol/L. The mean serum albumin (ALB) level at baseline was 39.4 g/L, and the time-averaged serum albumin (TA-ALB) was 42.1 g/L. Multivariate Cox regression analyses revealed that the TA-ALB and TA-SCr levels were independently associated with the composite renal outcome. The patients with a TA-SCr value > 120 μmol/L and a TA-ALB level < 38 g/L were less likely to recover from renal progression.

Conclusion

The strong predictive relationship of low TA-ALB and high TA-SCr levels with progression observed in this study suggests that TA-ALB may serve as a marker of the long-term renal prognosis of IgAN patients who have achieved remission.

Progression of IgA nephropathy under current therapy regimen in a Chinese population

BACKGROUND AND OBJECTIVES

Current therapy for IgA nephropathy mainly includes renin-angiotensin system inhibitors and adding steroids for patients with persistent proteinuria. This study aimed to evaluate kidney disease progression and its risk factors in a Chinese cohort under current therapy.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Patients with IgA nephropathy followed up for at least 12 months from a prospective database were involved. Renal survival and the relationship between clinical parameters and composite kidney failure events (defined as end stage kidney failure or eGFR halving) were assessed.

RESULTS

Overall, 703 patients between 2003 and 2011 were enrolled in this study, with a mean follow-up time of 45 months. Mean eGFR was 84.0 ml/min per 1.73 m(2), systolic BP was 124 mmHg, and time-averaged mean arterial pressure was 90.0 mmHg. Median proteinuria at baseline was 1.60 g/d, and time-averaged proteinuria was 0.80 g/d. The mean rate of eGFR decline was -3.12 ml/min per 1.73 m(2) per year (95% confidence interval, -19.07 to 11.80), and annual end stage kidney failure rate was 2.3%. Multivariate Cox regression analyses revealed that baseline eGFR (hazard ratio, 0.76 per 10 ml/min per 1.73 m(2); 95% confidence interval, 0.66 to 0.91), proteinuria at 6 months (hazard ratio, 1.53 per g/d; 95% confidence interval, 1.27 to 1.84), and systolic BP control at 6 months (hazard ratio, 1.36 per 10 mmHg; 95% confidence interval, 1.05 to 1.77) were associated with composite kidney failure events. Baseline eGFR (regression coefficient, -0.06; 95% confidence interval, -0.07 to -0.04), time-averaged proteinuria (regression coefficient, -0.21; 95% confidence interval, -0.25 to -0.16), and time-averaged mean arterial pressure (regression coefficient, -0.15; 95% confidence interval, -0.21 to -0.09) were independent predictors of the slope of eGFR by linear regression.

CONCLUSION

Lower proteinuria and lower BP were associated with slower eGFR decline and lower risk of end stage kidney failure in patients currently being treated for IgA nephropathy.

Predicting progression of IgA nephropathy: new clinical progression risk score

IgA nephropathy (IgAN) is a common cause of end-stage renal disease (ESRD) in Asia. In this study, based on a large cohort of Chinese patients with IgAN, we aim to identify independent predictive factors associated with disease progression to ESRD. We collected retrospective clinical data and renal outcomes on 619 biopsy-diagnosed IgAN patients with a mean follow-up time of 41.3 months. In total, 67 individuals reached the study endpoint defined by occurrence of ESRD necessitating renal replacement therapy. In the fully adjusted Cox proportional hazards model, there were four baseline variables with a significant independent effect on the risk of ESRD. These included: eGFR [HR = 0.96(0.95-0.97)], serum albumin [HR = 0.47(0.32-0.68)], hemoglobin [HR = 0.79(0.72-0.88)], and SBP [HR = 1.02(1.00-1.03)]. Based on these observations, we developed a 4-variable equation of a clinical risk score for disease progression. Our risk score explained nearly 22% of the total variance in the primary outcome. Survival ROC curves revealed that the risk score provided improved prediction of ESRD at 24th, 60th and 120th month of follow-up compared to the three previously proposed risk scores. In summary, our data indicate that IgAN patients with higher systolic blood pressure, lower eGFR, hemoglobin, and albumin levels at baseline are at a greatest risk of progression to ESRD. The new progression risk score calculated based on these four baseline variables offers a simple clinical tool for risk stratification.

Risk stratification of patients with IgA nephropathy

In this review, we summarize recent advances in the risk stratification of patients with immunoglobulin A (IgA) nephropathy. Several clinical variables have consistent and independent associations with worse kidney prognosis, including blood pressure, proteinuria, and baseline kidney function. Although one-time cross-sectional assessments of blood pressure and proteinuria are important, a more thorough understanding of risk can be achieved when these variables are considered over a follow-up period. IgA nephropathy is unique compared with other glomerular diseases in that a much lower threshold of proteinuria (protein excretion, 1 g/d) is associated with glomerular filtration rate (GFR) loss. Controlling proteinuria and blood pressure over time is important to reduce the risk of future loss of kidney function. The recently described Oxford classification has helped standardize the pathologic characterization of IgA nephropathy using a scoring system that is readily reproducible and associated with increased risk of GFR loss independent of clinical variables. We suggest an approach to risk stratification in IgA nephropathy when considering potential treatment with immunosuppression. Despite our current understanding of risk stratification in IgA nephropathy, the ability to accurately predict individual patient-level risk currently is limited, and further research into additional biomarkers or risk prediction tools is needed to improve the care of patients with IgA nephropathy.

Hematocrit, urea and gender: the Hematocrit, Urea and GEnder formula for prognosing progressive renal failure in diabetic nephropathy

OBJECTIVE

Diabetic nephropathy is a common cause of end stage renal disease. Notwithstanding, wide inter-individual variations in the speed of progression of diabetic nephropathy are frequent. We have used the score of the HUGE formula to predict progression of kidney disease in a group of diabetic nephropathy patients.

DESIGN AND METHODS

The sample consisted of 84 type 2 diabetic patients. At treatment entry, the mean age was 62.1 ± 12.5 years and 59.5% were male. Blood pressure was measured at office at each visit. Serum creatinine, urea, hematocrit and 24h proteinuria were analyzed every 6 months. HUGE score was calculated from gender, urea and hematocrit.

RESULTS

Mean HUGE score was 0.99 ± 3.88. Using as cut off point 1.5, those patients who had a score equal or higher (n=31) showed a bigger increase in serum creatinine after one year (41.8 ± 62.1%) than those subjects with score<1.5 (n=53) (18.7 ± 38.6%, p=0.041). 5 patients with low HUGE score reached end stage renal failure (9.4%) and 10 patients in the high HUGE score group (32.3, p=0.008). When logistic regression analysis was performed only a HUGE score higher than 1.5 (p=0.003) and proteinuria higher than 2g/day (p=0.041) were independently associated to CRF progression (creatinine increment>25%).

CONCLUSIONS

In diabetic nephropathy patients the HUGE equation may be useful to detect the subjects prone to progressive renal failure. Wider samples will be needed to confirm this finding and, most important, its applicability to other kinds of nephropathy.

Predicting the risk for dialysis or death in IgA nephropathy

For the individual patient with primary IgA nephropathy (IgAN), it remains a challenge to predict long-term outcomes for patients receiving standard treatment. We studied a prospective cohort of 332 patients with biopsy-proven IgAN patients followed over an average of 13 years. We calculated an absolute renal risk (ARR) of dialysis or death by counting the number of risk factors present at diagnosis: hypertension, proteinuria ≥1 g/d, and severe pathologic lesions (global optical score, ≥8). Overall, the ARR score allowed significant risk stratification (P < 0.0001). The cumulative incidence of death or dialysis at 10 and 20 years was 2 and 4%, respectively, for ARR=0; 2 and 9% for ARR=1; 7 and 18% for ARR=2; and 29 and 64% for ARR=3, in adequately treated patients. When achieved, control of hypertension and reduction of proteinuria reduced the risk for death or dialysis. In conclusion, the absolute renal risk score, determined at diagnosis, associates with risk for dialysis or death.

alpha- and beta-Adducin polymorphisms affect podocyte proteins and proteinuria in rodents and decline of renal function in human IgA nephropathy

Adducins are cytoskeletal actin-binding proteins (α, β, γ) that function as heterodimers and heterotetramers and are encoded by distinct genes. Experimental and clinical evidence implicates α- and β-adducin variants in hypertension and renal dysfunction. Here, we have addressed the role of α- and β-adducin on glomerular function and disease using β-adducin null mice, congenic substrains for α- and β-adducin from the Milan hypertensive (MHS) and Milan normotensive (MNS) rats and patients with IgA nephropathy. Targeted deletion of β-adducin in mice reduced urinary protein excretion, preceded by an increase of podocyte protein expression (phospho-nephrin, synaptopodin, α-actinin, ZO-1, Fyn). The introgression of polymorphic MHS β-adducin locus into MNS (Add2, 529R) rats was associated with an early reduction of podocyte protein expression (nephrin, synaptopodin, α-actinin, ZO-1, podocin, Fyn), followed by severe glomerular and interstitial lesions and increased urinary protein excretion. These alterations were markedly attenuated when the polymorphic MHS α-adducin locus was also present (Add1, 316Y). In patients with IgA nephropathy, the rate of decline of renal function over time was associated to polymorphic β-adducin (ADD2, 1797T, rs4984) with a significant interaction with α-adducin (ADD1, 460W, rs4961). These findings suggest that adducin genetic variants participate in the development of glomerular lesions by modulating the expression of specific podocyte proteins.

Pathological predictors of prognosis in immunoglobulin A nephropathy: a review

PURPOSE OF REVIEW

To provide a review and discussion of histological prognostic indicators in immunoglobulin A (IgA) nephropathy (IgAN).

RECENT FINDINGS

A variety of histological parameters and classifications have been used to attempt to predict prognosis in patients with IgAN. Grading systems used thus far do not consistently provide a useful adjunct to clinical prognostic parameters. This may be due to the variety of grading systems used, to inconsistent patient recruitment processes, and to the use of actuarial renal survival as an end point. This has led to the development of a new IgAN classification proposal by the International IgA Nephropathy Network in conjunction with the Renal Pathological Society. Additional potential markers of disease progression currently under investigation include glomerular parameters such as number and size, markers of podocyte function and of complement activation, inflammatory infiltrates and mediators of tubulointerstitial fibrosis.

SUMMARY

There is a need for an internationally accepted, reproducible and clinically meaningful pathological classification of IgAN. Such a classification is currently being developed. By using only reproducible, single parameters and validating them on a large group of cases from all over the world, it is hoped that a useful clinically predictive tool will be developed.