Screening Of Predictors And Establishment Of Early Prognostic Model For Idiopathic Membranous Nephropathy

Background:Membranous nephropathy(MN)with the characteristics of massive proteinuria and hypoalbuminemia is a common cause of nephrotic syndrome in adults.The special pathological feature of MN is the formation of immune complexes in the epithelial side of the capillary loop of the glomerulus.The incidence of membranous nephropathy in our country is increasing gradually,which has attracted extensive attention from nephrologists.The membranous nephropathy was classed by the cause of the disease named secondary and idiopathic membranous nephropathy.Secondary membranous nephropathy,which accounts for about 20%of total membranous nephropathy,is caused by systemic disease or exposure to certain factors.Idiopathic membranous nephropathy(IMN),also known as primary membranous nephropathy,accounts for about 80%of total membranous nephropathy and is limited to the kidney.Against the secondary MN,the treatment of IMN is more complicated.Although IMN is often considered a"benign disease",30%-40%of IMN patients,especially those with persistent proteinuria and impaired kidney function,may develop the end-stage renal disease within 5-15 years.At present,the treatment of IMN is still controversial.The treatment of IMN is still contentious.Even though immunosuppressive therapies can be selected for IMN,KDIGO guidelines give the indications and contraindications for immunosuppressive treatment.For the significant side effects of immunosuppressive therapies,it should be selected cautiously.The KDIGO guidelines also pointed out that it is necessary to find appropriate clinical,pathological,and biological markers to predict the prognosis of IMN to screen suitable patients and give active treatment for improving the prognosis of IMN and reducing the side effects of immunosuppressive therapy.However,early prediction of the renal prognosis of IMN is still very challenging and requires more extensive and in-depth research and verification.Part I.Risk factors of renal prognosis in idiopathic membranous nephropathyPurpose:The distribution characteristics of age,24-hour urinary protein level,renal function level,serum anti-PLA2R antibody titer,and serum uric acid(UA)level at the time of renal biopsy in IMN patients were analyzed,and their relationship with renal prognosis was analyzed so as to screen for early predictors of poor renal prognosis in IMN patients.Methods:We identified patients with a renal biopsy-confirmed diagnosis of IMN from2009 to 2017 in Wenzhou medical university's first affiliate.The demographic,clinical data and renal histopathological reports were collected at the renal biopsy.Cases were filtered by the including and exclusion criteria.The receiver operating characteristic(ROC)analysis was used for evaluating the identification power of risk factors,including serum UA for the poor renal outcomes.The time-event analysis was used to assess the impact of risk factors for poor renal outcomes in patients with IMN.The primary endpoint was the poor renal outcome,which was defined as a decrease in the estimated glomerular filtration rate to 50%of the baseline level or progression to end-stage renal disease during the follow-up.R(version 3.5.2,R Core Team)and it?s packages were used to perform the statistical analyses and plot the figures.Results:Selected 989 cases of MN from 8000 renal biopsy cases,and 572 eligible patients were included.During a median of 18 months of follow-up,45(7.9%)patients progressed to the primary endpoint.Although the age at biopsy,24-hour proteinuria and estimated glomerular clearance(e GFR)at biopsy were associated with poor renal outcomes in IMN patients,multivariate Cox regression showed these three clinical indicators were not independent risk factors for IMN patients.Both baseline serum UA and time-averaged UA levels could be used for discrimination of renal outcomes,but the difference was not significant(p-value=0.6).Our multivariate Cox regression analysis further demonstrated that baseline serum UA was an independent predictor of poor renal outcome in IMN patients,and subgroup analysis revealed a gender difference in the predictive effect of serum UA.Conclusions:Our study demonstrated that age 24-hour urinary protein level,EGFR level,and serum UA at the time of renal biopsy were associated with poor renal outcomes in IMN patients.Furthermore,our multivariate Cox regression analysis indicated that serum UA was an independent predictor for poor renal outcomes in patients with IMN.Part II.Establishment of an early prognostic model for idiopathic membranous nephropathyPurpose:The first part showed that the clinical indicators of renal biopsy in IMN patients were closely related to adverse renal outcomes.Still,the single factor prediction of poor renal outcomes in IMN patients was not robust.Therefore,this study intends to combine the mature prognosis prediction model of IMN with robust statistical methods to construct a multi-factor prediction model for early prediction of poor renal prognosis.Methods:Patients with a renal biopsy-confirmed diagnosis of IMN between 2009 and2017 in our department were identified.The demographic,clinical data,and renal pathology recorded at the time of renal biopsy as well as follow-up data were collected.The data set of this study was used to verify the performance of a risk score model for evaluating the renal outcomes among IMN patients constructed by Cattran et al.,which is called the Toronto Risk Score model.A new IMN prognostic model based on clinical and pathological data at the time of renal biopsy was established by using a multivariate Cox regression model.A variable optimization model was selected by the AIC principle.Then,all variables in the model were diagnosed by the Therneau-Grambsch method,and variables that did not fit the model hypothesis were excluded.Finally,net reclassification improvement(NRI)was used to evaluate the classification performance difference between the newly constructed early prediction model in this study and the Toronto Risk Score model.Poor renal outcomes included primary endpoint events defined as a decrease of the estimated glomerular filtration rate(e GFR)by 30%of the baseline level or e GFR<30ml/min/1.73m~2,and secondary endpoint events defined as progression to CRI(chronic renal insufficiency),which means e GFR<60 ml/min/1.73m~2 during the follow-up.Finally,we carried out an internal validation of the model with our data set.R(version 3.5.2,R Core Team)and it?s packages were used to perform the statistical analyses and create the figures.Result:A total of 572 eligible patients were included,including 118(20.6%)patients who progressed to primary endpoint events and 98(17.1%)patients who progressed to secondary endpoint events.There were significant differences in the parameters at the time of renal biopsy between patients with or without primary endpoint events,especially in the age,gender,serum albumin levels,e GFR,serum creatinine levels,serum fibrinogen levels,24-hour urinary protein quantification,and systolic blood pressure.Data from this study showed that the Toronto Risk Score model had a sensitivity and specificity of 28%and 96.4%for predicting primary endpoint events,respectively.In the newly constructed multivariate Cox regression model,only age,serum albumin,serum uric acid,blood triglyceride,and tubulointerstitial injury were retained after screening by the AIC principle,suggesting that these variables were closely related to long-term renal prognosis at renal biopsy.However,the Therneau-Grambsch analysis showed that serum albumin levels did not conform to the proportional risk hypothesis and were eliminated from the model.The final model included age,blood uric acid level,blood triglyceride level,and renal tubular damage.The model's sensitivity and specificity for predicting poor renal outcomes were 68.8%and 71.5%,respectively.Compared with the Toronto Risk Score model,the NRI was 0.174(P=0.003),indicating that this study's early prediction model has significantly improved in the classification performance.Conclusion:In this study,an evaluation model based on the multivariate Cox regression model for early prediction of renal prognosis of IMN was established.The classification performance of the model has been significantly improved compared with the Toronto Risk Score model.However,due to data limitations,the results of this study still need to be verified by external data.