Development of a nomogram for membranous nephropathy prediction in patients with primary Sjogren’s syndrome: a 6-year retrospective study
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PROVIDER: S-EPMC11021693 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:BackgroundPrimary membranous nephropathy (PMN) has a heterogeneous natural course. Immunosuppressive therapy is recommended for PMN patients at moderate or high risk of renal function deterioration. Prediction models for the treatment failure of PMN have rarely been reported.MethodsThis study retrospectively studied patients diagnosed as PMN by renal biopsy at Sichuan Provincial People's Hospital from January 2017 to December 2020. Information on clinical characteristics, laboratory test results, pathological examination, and treatment was collected. The outcome was treatment failure, defined as the lack of complete or partial remission at the end of 12 months. Simple logistic regression was used to identify candidate predictive variables. Forced-entry stepwise multivariable logistic regression was used to develop the prediction model, and performance was evaluated using C-statistic, calibration plot, and decision curve analysis. Internal validation was performed by bootstrapping.ResultsIn total, 310 patients were recruited for this study. 116 patients achieved the outcome. Forced-entry stepwise multivariable logistic regression indicated that PLA2Rab titer (OR = 1.002, 95% CI: 1.001-1.004, p = 0.003), inflammatory cells infiltration (OR = 2.753, 95% CI: 1.468-5.370, p = 0.002) and C3 deposition on immunofluorescence (OR = 0.217, 95% CI: 0.041-0.964, p = 0.049) were the three independent risk factors for treatment failure of PMN. The final prediction model had a C-statistic (95% CI) of 0.653 (0.590-0.717) and a net benefit of 23%-77%.ConclusionsPLA2R antibody, renal interstitial inflammation infiltration, and C3 deposition on immunofluorescence were the three independent risk factors for treatment failure in PMN. Our prediction model might help identify patients at risk of treatment failure; however, the performance awaits improvement.
| S-EPMC10557540 | biostudies-literature
Project description:BackgroundBased on the etiology, membranous nephropathy (MN) can be categorized into idiopathic membranous nephropathy (IMN) and secondary membranous nephropathy. Malignancy-associated membranous nephropathy (MMN) is a common type of secondary MN. Its incidence is only second to that of lupus nephritis. As the treatment and prognosis of MMN differ significantly from those of other MNs, the identification of MMN is crucial for clinical practice. The purpose of this study was to develop a model that could efficiently discriminate MMN, to guide more precise selection of therapeutic strategies.MethodsA total of 385 with IMN and 62 patients with MMN, who were hospitalized at the First Affiliated Hospital of Zhengzhou University between January 2017 and December 2020 were included in this study. We constructed a discriminant model based on demographic information and laboratory parameters for distinguishing MMN and IMN. To avoid an increased false positivity rate resulting from the large difference in sample numbers between the two groups, we matched MMN and IMN in a 1:3 ratio according to gender. Regression analysis was subsequently performed and a discriminant model was constructed. The calibration ability and clinical utility of the model were assessed via calibration curve and decision curve analysis.ResultsWe constructed a discriminant model based on age, CD4+ T cell counts, levels of cystatin C, albumin, free triiodothyronine and body mass index, with a diagnostic power of 0.860 and 0.870 in the training and test groups, respectively. The model was validated to demonstrate good calibration capability and clinical utility.ConclusionIn clinical practice, patients demonstrating higher scores after screening with this model should be carefully monitored for the presence of tumors in order to improve their outcome.
| S-EPMC9329587 | biostudies-literature
Project description:BackgroundThe outcome of patients with primary membranous nephropathy (pMN) who present with nephrotic syndrome (NS) is variable and difficult to predict. The goal of this study was to develop a nomogram to predict the risk of progression for specific individuals.MethodsThis retrospective study involved biopsy-proven patients with pMN and NS treated between January 2012 and June 2018. The primary outcome of our investigation was progression, defined as a reduction of estimated glomerular filtration rate (eGFR) that was equal to or over 20% compared with baseline at the end of follow-up or the onset of end-stage renal disease (ESRD). We used backwards stepwise logistic regression analysis to create a nomogram to predict prognosis. The model was validated internally using bootstrap resampling.ResultsA total of 111 patients were enrolled. After a median follow-up of 40.0 months (range 12-92 months), 18.9% (21/111) patients showed progression. Backwards stepwise selection using the Akaike information criterion (AIC) identified the following four variables as independent risk factors for progression, which were all used in the nomogram: age ≥ 65 years [odds ratio (OR) 7.004; 95% confidence interval (CI) 1.783-27.505; p = 0.005], Ln (sPLA2R-Ab) (OR 2.150; 95% CI 1.293-3.577; p = 0.003), Ln (proteinuria) (OR 5.939; 95% CI 1.055-33.436; p = 0.043) and Ln (Uα1m/Cr) (OR 2.808; 95% CI 1.035-7.619; p = 0.043). The discriminative ability and calibration of the nomogram revealed good predictive ability, as indicated by a C-index of 0.888 (95% CI 0.814-0.940) and a bootstrap-corrected C-index of 0.869; calibration curves were also well fitted. A receiver operating characteristic (ROC) curve for the nomogram score revealed significantly better discrimination than each of the three risk factors alone, including Ln (sPLA2R-Ab) [area under the curve (AUC) 0.769], Ln (proteinuria) (AUC 0.653) and Ln (Uα1m) (AUC 0.781) in the prediction of progression (p < 0.05). The optimal cutoff value of the nomogram score was 117.8 with a positive predictive value of 44.4% and a negative predictive value of 98.5%.ConclusionThe nomogram successfully achieved good predictive ability of progression for patients with pMN who present with NS. It can therefore help clinicians to individualize treatment plans and improve the outcome of pMN.
| S-EPMC8782821 | biostudies-literature
Project description: Not available
| S-EPMC10872675 | biostudies-literature
Project description:Background Primary Sjögren syndrome (pSS) is a systemic autoimmune epithelitis, potentially affecting salivary epithelium, biliary epithelium, and hepatocytes. Common immunological mechanisms might cause clinically silent liver inflammation, and combined with non-alcoholic fatty liver disease (NAFLD), liver fibrosis (LF) may occur. No studies have explored the occurrence of LF in the context of NAFLD among pSS patients. Methods Consecutive pSS patients from the rheumatology outpatient clinic of the Department of Pathophysiology and individuals evaluated in the hepatology outpatient clinic for possible NAFLD serving as comparators underwent transient elastography (TE) to assess LF and liver steatosis (LS). All participants had no overt chronic liver disease. Clinical, demographic, and laboratory data were collected from all participants at the time of TE. Results Fifty-two pSS patients and 198 comparators were included in the study. The median age (range) of pSS and comparators was 62.5 (30–81) and 55 (19–86) years, respectively. Both groups had similar prevalence regarding type 2 diabetes mellitus, hyperlipidemia, and similar body mass index (BMI). Patients with pSS had less frequently high LS (S2, S3) (27% vs. 62%, p < 0.001) and significant LF (F2–4) [2 (3.8%) vs. 34 (17.2%), p = 0.014] than comparators. Univariable analysis showed that advanced LF was significantly associated with older age, higher LS, greater BMI, and disease status (comparators than pSS); of these, only age was identified as an independent LF risk factor in the multivariable logistic regression analysis. Conclusion Liver fibrosis among pSS patients is most likely not attributed to the disease per se.
| S-EPMC9240196 | biostudies-literature
Project description:Membranous nephropathy (MN) is an autoimmune disease of the kidney glomerulus and one of the leading causes of nephrotic syndrome. The disease exhibits heterogenous outcomes with approximately 30% of cases progressing to end-stage renal disease. The clinical management of MN has steadily advanced owing to the identification of autoantibodies to the phospholipase A2 receptor (PLA2R) in 2009 and thrombospondin domain-containing 7A (THSD7A) in 2014 on the podocyte surface. Approximately 50-80% and 3-5% of primary MN (PMN) cases are associated with either anti-PLA2R or anti-THSD7A antibodies, respectively. The presence of these autoantibodies is used for MN diagnosis; antibody levels correlate with disease severity and possess significant biomarker values in monitoring disease progression and treatment response. Importantly, both autoantibodies are causative to MN. Additionally, evidence is emerging that NELL-1 is associated with 5-10% of PMN cases that are PLA2R- and THSD7A-negative, which moves us one step closer to mapping out the full spectrum of PMN antigens. Recent developments suggest exostosin 1 (EXT1), EXT2, NELL-1, and contactin 1 (CNTN1) are associated with MN. Genetic factors and other mechanisms are in place to regulate these factors and may contribute to MN pathogenesis. This review will discuss recent developments over the past 5 years.
| S-EPMC8065962 | biostudies-literature
Project description: Not available
| S-EPMC8591447 | biostudies-literature
Project description:BackgroundSeveral statistical models for predicting prognosis of primary membranous nephropathy (PMN) have been proposed, most of which have not been as widely accepted in clinical practice.MethodsA systematic search was performed in MEDLINE and EMBASE. English studies that developed any prediction models including two or more than two predictive variables were eligible for inclusion. The study population was limited to adult patients with pathologically confirmed PMN. The outcomes in eligible studies should be events relevant to prognosis of PMN, either disease progression or response profile after treatments. The risk of bias was assessed according to the PROBAST.ResultsIn all, eight studies with 1237 patients were included. The pooled AUC value of the seven studies with renal function deterioration and/or ESRD as the predicted outcomes was 0.88 (95% CI: 0.85 to 0.90; I2 = 77%, p = 0.006). The paired forest plots for sensitivity and specificity with corresponding 95% CIs for each of these seven studies indicated the combined sensitivity and specificity were 0.76 (95% CI: 0.64 to 0.85) and 0.84 (95% CI: 0.80 to 0.88), respectively. All seven studies included in the meta-analysis were assessed as high risk of bias according to the PROBAST tool.ConclusionsThe reported discrimination ability of included models was good; however, the insufficient calibration assessment and lack of validation studies precluded drawing a definitive conclusion on the performance of these prediction models. High-grade evidence from well-designed studies is needed in this field.
| S-EPMC9867146 | biostudies-literature
Project description:Background and objectivesThe clinical and pathological impact factors for renal function recovery in acute kidney injury (AKI) on the progression of renal function in primary membranous nephropathy (PMN) with AKI patients have not yet been reported, we sought to investigate the factors that may influence renal function recovery and develop a nomogram model for predicting renal function recovery in PMN with AKI patients.MethodsTwo PMN with AKI cohorts from the Nephrology Department, the First Affiliated Hospital of Wenzhou Medical University during 2012-2018 and 2019-2020 were included, i.e., a derivation cohort during 2012-2018 and a validation cohort during 2019-2020. Clinical characteristics and renal pathological features were obtained. The outcome measurement was the recovery of renal function within 12 months. Lasso regression was used for clinical and pathological features selection. Prediction model was built and nomogram was plotted. Model evaluations including calibration curves were performed.ResultRenal function recovery was found in 72 of 124 (58.1%) patients and 41 of 72 (56.9%) patients in the derivation and validation cohorts, respectively. The prognostic nomogram model included determinants of sex, age, the comorbidity of hypertensive nephropathy, the stage of glomerular basement membrane and diuretic treatment with a reasonable concordance index of 0.773 (95%CI,0.716-0.830) in the derivation cohort and 0.773 (95%CI, 0.693-0.853) in the validation cohort. Diuretic use was a significant impact factor with decrease of renal function recovery in PMN with AKI patients.ConclusionThe predictive nomogram model provides useful prognostic tool for renal function recovery in PMN patients with AKI.
| S-EPMC9281044 | biostudies-literature
Project description: Not available
| S-EPMC10239766 | biostudies-literature