View clinical trials related to Glomerulonephritis, Membranous.
Filter by:This is an adaptive prospective, multi-center, randomized, double-blind, placebo-controlled study to evaluate the safety, efficacy, pharmacokinetics, and pharmacodynamics of WAL0921 in subjects with glomerular kidney disease and proteinuria, including diabetic nephropathy and rare glomerular kidney diseases (primary focal segmental glomerulosclerosis [FSGS], treatment-resistant minimal change disease [TR MCD], primary immunoglobulin A nephropathy [IgAN], and primary membranous nephropathy [PMN]). Subjects in this study will be randomized to receive the investigational drug WAL0921 or placebo as an intravenous infusion once every 2 weeks for 7 total infusions. All subjects will be followed for 24 weeks after their last infusion.
Membranous nephropathy is an autoimmune disease affecting the kidney, and the most common cause of nephrotic syndrome in non-diabetic Caucasian adults. The course of this disease is highly variable from one individual to another, ranging from spontaneous remission to progressive chronic kidney disease. The identification of autoantibodies - e.g., the phospholipase A2 receptor type 1 (PLA2R1) - has promoted the use of immunosuppressive drugs such as rituximab which is now a safe and effective first-line treatment for the management of membranous nephropathy. However, up to 40% of patients do not respond to a first course of rituximab treatment. In nephrotic patients, due to urinary drug loss, rituximab blood level is lower than in other autoimmune diseases treated with rituximab without proteinuria. This high urinary drug loss decreases the drug exposure, potentially explaining why rituximab regimen with low dose infusions (375 mg/m2) did not demonstrate efficacy after month-6 compared to a non-immunosuppressive antiproteinuric treatment in a previous study. In contrast, a regimen of two 1-g infusions two weeks apart was associated with a significantly greater remission rate after 6 months. Recently, the investigators have shown that after two 1-g rituximab infusions, the rituximab blood level 3 months after the first rituximab infusion, was correlated with the likelihood of remission after 6 and 12 months of the rituximab treatment. Patients with positive rituximab blood level 3 months after treatment had a higher chance of remission at month-6 and at month-12 than patients with an undetectable rituximab level at month-3. Nowadays, machine learning algorithms are increasingly used in medicine, especially in pharmacology, to predict the exposure to a drug, the initial dose to administer or the interval between two infusions. The objective of this study is to use a machine learning algorithm predicting the risk of having an undetectable residual level of rituximab 3 months after treatment, in order to propose a personalized treatment management with early additional doses of rituximab for the patients at risk.
A prospective observational study to investigate the treatment-associated changes of circulating factors associated with glomerular diseases among patients with de novo nephrotic syndrome admitted to hospital for a kidney biopsy.
This is an observational study intended to track the course of the primary membranous nephropathy disease in real-world clinical practice. The study will primarily assess the long-term outcomes of patients with primary membranous nephropathy in the context of advances in treatment options.
REMIT is an investigator-initiated, international, multi-centre, prospective, randomised, open-label, parallel-group trial. A total of 224 adult participants with Primary Membranous Nephropathy (PMN) will be recruited from renal units from Australia, New Zealand Canada, Asia, Europe, United Kingdom, and other countries. Participants will be randomised to receive either corticosteroid and cyclophosphamide or obinutuzumab. The primary outcome is a ranked, composite measure based on (a) efficacy, defined as either complete or partial remission of PMN, (b) number of adverse events, and (c) quality of life.
Membranous Nephropathy (MN) is a renal autoimmune disease mediated by autoantibodies. Current management is based on the use of immunosuppressive therapies. MN patients with a pro-inflammatory Th17 cytokine profile have a 10.5-fold increased risk of disease relapse. Interferon-based immunomodulatory therapies are effective in blocking the production of cytokines in the Th17 pathway avoiding an increased risk of infection, unlike immunosuppressive treatments. To date, these treatments have not been evaluated in the management of MN. The aims of the ALPHAGEM project are to monitor the immunological activity of the disease before and after 6 months of personalized interferon-alfa treatment in MN patients.
Investigators propose hyperspectral imaging analysis as a method to distinguish the efficacy of hormone-combined cyclophosphamide therapy for PMN, and classify sensitive and insensitive patients treated with hormone-combined cyclophosphamide regimen. A variety of machine learning models were used to prove that hyperspectral imaging technology could assist patients in selecting the optimal treatment plan, and further explore the predictive indicators of PMN treatment effect.
To observe the efficacy and safety of obinutuzumab in Chinese population with idiopathic membranous nephropathy and guide clinical management.
Morning urine samples of patients with IgA nephropathy, idiopathic membranous nephropathy, diabetic nephropathy, and minimal degenerative nephropathy confirmed by renal needle biopsy in our hospital from November 2020 to January 2022 were collected. By scanning the morning urine samples of corresponding patients with microhyperspectral imager, machine learning and deep learning were used to classify microhyperspectral images, and the classification accuracy was greater than 85%. Thus, hyperspectral imaging technology could be used as a non-invasive diagnostic means to assist the diagnosis of glomerular diseases.
We propose hyperspectral imaging analysis as a method to identify the efficacy of hormone-tacrolimus therapy for PMN, and to classify sensitive and insensitive patients treated with hormone-tacrolimus regimen. A variety of machine learning models were used to prove that hyperspectral imaging technology could assist patients in selecting the optimal treatment plan, and further explore the predictive indicators of PMN treatment effect.