Personalized Rituximab Treatment Based on Artificial Intelligence in Membranous Nephropathy (iRITUX)

Phase 3RecruitingNCT06341205

Centre Hospitalier Universitaire de Nice120 enrolled

Overview

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.

Study Type

INTERVENTIONAL

Allocation

RANDOMIZED

Purpose

TREATMENT

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

Inclusion Criteria: * Age ≥ 18 years * Ongoing episode of membranous nephropathy diagnosed by the presence of anti-PLA2R1 antibodies detected by ELISA (≥ 14 RU/ml, EUROIMMUN): the result must be validated by the Coordination team before randomization. * Nephrotic syndrome defined by proteinuria \> 3.5 g/24h (or UPCR \> 3.5 g/g) and serum albumin \< 30 g/L at diagnosis * Estimated Glomerular Filtration Rate (CKD-EPI formula) \> 30 mL/min/1,73 m2 * Indication for rituximab treatment according to the KDIGO and French guidelines * Non-immunosuppressive antiproteinuric treatment at stable dose for 2 weeks according to French guidelines, including a renin angiotensin aldosterone system inhibitor, a diuretic and a low-salt diet at maximal tolerated dose (i.e., absence of orthostatic hypotension and no increase in creatinine \> 30%) Exclusion Criteria: * Secondary Membranous nephropathy related to cancer, infection, systemic lupus, drug * Diagnosis of PLA2R1-associated Membranous nephropathy not confirmed by the Coordination team (validation mandatory for randomization) * Pregnancy or breastfeeding * Immunosuppressive treatment (including rituximab) in the 6 months preceding inclusion * Presence of anti-rituximab antibodies detected by Central Lab * Cancer under treatment * Patients with active, severe infections * Hypersensitivity to the active substance or excipients * Patients severely immunocompromised * Severe heart failure or severe, uncontrolled cardiac disease

Locations (13)

CHU de BESANCON

Besançon, France

RECRUITING

CHU de BORDEAUX - Hôpital Pellegrin

Bordeaux, France

RECRUITING

CHU de CAEN

Caen, France

RECRUITING

AP-HP - Hôpital H. Mondor

Créteil, France

RECRUITING

HCL - Hôpital E. Herriot

Lyon, France

RECRUITING

AP-HM - Hôpital de la Conception

Marseille, France

RECRUITING

CHU de NICE

Nice, France

RECRUITING

CHU de Nîmes - Hôpital CAREMEAU

Nîmes, France

RECRUITING

AP-HP - Hôpital Européen Georges Pompidou

Paris, France

NOT_YET_RECRUITING

AP-HP - Hôpital Necker

Paris, France

NOT_YET_RECRUITING

...and 3 more locations

Outcomes

Primary Outcomes

Clinical remission (complete or partial) after 6 months of rituximab initiation

Clinical remission (complete or partial) according to KDIGO and French guidelines: * Complete: urine protein/creatinine ratio (UPCR) \<0.3 g/g and serum albumin\>30 g/L and Glomerular Filtration Rate (estimated by CKD-EPI formula) \>60 ml/min/1.73m2 * Partial: UPCR \<3.5 g/g with a decrease \>50% from baseline (i.e., at first rituximab infusion) and serum albumin improvement or normalization and stable serum creatinine (or increase \<30%).

Time frame: 6 months

Secondary Outcomes

Complete clinical remission after 12 months of rituximab initiation

Complete remission: urine protein/creatinine ratio (UPCR) \<0.3 g/g and serum albumin\>30 g/L and Glomerular Filtration Rate (estimated by CKD-EPI formula) \>60 ml/min/1.73m2

Time frame: 12 months

Partial clinical remission after 12 months of rituximab initiation

Partial remission: UPCR \<3.5 g/g with a decrease \>50% from baseline (i.e., at first rituximab infusion) and serum albumin improvement or normalization and stable serum creatinine (or increase \<30%).

Time frame: 12 months

Immunological remission: anti-PLA2R1 depletion

Immunological remission: anti-PLA2R1 depletion (i.e., PLA2R1 titer \< 14 RU/mL by ELISA method) at month-3, month-6 and month-12

Time frame: 12 months

Change in urine protein/creatinine ratio (UPCR)

Percentage of change in urine albumin/creatinine ratio (mg/g) from day-0 to month-3, month-6, month-9, month-12

Time frame: 12 months

Change in serum creatinine

Percentage of change in serum creatinine (μmol/L) from day-0 to month-3, month-6, month-9, month-12

Time frame: 12 months

Change in renal function

Percentage of change in Glomerular Filtration Rate estimated by CKD-EPI formula (mL/min/1.73m²) from day-0 to month-3, month-6, month-9, month-12

Time frame: 12 months

Change in the immunological status of the disease

Percentage of change in anti-PLA2R1 titer (RU/mL) by ELISA (EUROIMMUN Kit) from day-0 to month-3, month-6, month-9, month-12

Time frame: 12 months

Appearance of anti-drug antibodies after rituximab treatment

Serum anti-rituximab antibodies (ng/mL) at month-3, month-6, month-9, month-12

Time frame: 12 months

Rituximab underdosed patients

Percentage of patients with serum rituximab (μg/mL) \>2 μg/mL 3 months after the last infusion

Time frame: 3 months

Serious adverse events

Occurence of Serious adverse events reported

Time frame: 84 months

Adaptation of symptomatic treatment

Number of dose modification of non-immunosuppressive anti-proteinuric treatment during study follow-up

Time frame: 84 months

Model improvement through machine learning

serum creatinine and serum albumin levels, weight, anti-PLA2R1 and rituximab level will be combined to report the risk of having undetectable rituximab level after 3 months (in %) at day-0, day-15, day-30, day-45, month-3, month-6

Time frame: 6 months

Effect of rituximab on immune profiles

Cytokine levels in pg/mL (IFN-γ, IFN-α, IL-12p70, IL-17A, IL-4, IL-5, IL-10, IL-1, IL-6) at day-0 and month-6

Time frame: 6 months

Personalized Rituximab Treatment Based on Artificial Intelligence in Membranous Nephropathy (iRITUX)

Overview

Conditions

Interventions

Eligibility

Locations (13)

Outcomes

Primary Outcomes

Secondary Outcomes

Central Contacts