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SYSTEMATIC REVIEW article

Front. Immunol.
Sec. Autoimmune and Autoinflammatory Disorders : Autoimmune Disorders
Volume 15 - 2024 | doi: 10.3389/fimmu.2024.1445814
This article is part of the Research Topic How Underappreciated Autoinflammatory Mechanisms (Innate Immunity) Dominate Disparate Autoimmune Disorders View all articles

Biologicals for the Treatment of Lupus Nephritis: A Bayesian network meta-regression analysis

Provisionally accepted
Xi Liu Xi Liu 1*Xiaoli Chen Xiaoli Chen 1Xiaoli Chen Xiaoli Chen 1Ruixue Li Ruixue Li 1Xi Chen Xi Chen 2Qiaoli Li Qiaoli Li 3
  • 1 Yubei District People’s Hospital, Chongqing, China
  • 2 Department of Epidemiology and Health Statistics, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, China
  • 3 Thirteenth People's Hospital of Chongqing, Chongqing, Chongqing Municipality, China

The final, formatted version of the article will be published soon.

    Background: Previous studies comparing the efficacy and safety of different treatment regimens for lupus nephritis are scarce. Moreover, confounding factors such as the duration of follow-up were hardly adjusted in those studies, potentially compromising the results and their extents to clinical settings.Objective: To rigorously investigate the efficacy and safety of biologics in patients with lupus nephritis using Bayesian network meta-regression analyses that adjust for the follow-up period, in order to provide more robust evidence for clinicians.Methods: Databases comprising PubMed, Embase, MedlinePlus, Cochrane Library, Google Scholars, and Scopus were retrieved for eligible articles from inception to February 29, 2024. The primary endpoint was the complete response rate, the secondary endpoint was the partial response rate, the tertiary endpoints were the adverse events, and infection-related adverse events. Napierian Logarithm of hazard ratio (lnHR) and the standard error of lnHR (selnHR) were generated for dichotomous variants by STATA 18.0 MP and then put into Rstudio 4.3.2 to conduct Bayesian network metaanalysis as well as network meta-regression analysis to yield hazard ratio (HR) as pairwise effect size.Results: Ten studies involving 2138 patients and 11 treatment regimens were ultimately included. In the original analysis, for the primary endpoint, compared to the control group, obinutuzumab (22.6 months), abatacept-30mg (20.5 months), abatacept-10mg (17.8 months), and belimumab (23.3 months) demonstrated significant superiority (HR ranged from 1.6 to 2.5), more ever, their significance regarding relative efficacy was correlated with follow up period, namely "time window" (shown in parentheses above). For the secondary endpoint, compared to the control group, obinutuzumab and abatacept-30mg showed conspicuous preponderance (HR ranged from 1.6 to 2.4), "time window" was also detected in abatacept-30mg (20.5 months), whereas obinutuzumab remained consistently obviously effective regardless of the follow-up period (shown in parentheses above). For the tertiary endpoint, there were no differences among active regimens and control. Conclusions: Considering the efficacy and safety and "time window" phenomenon, we recommend obinutuzumab as the preferred treatment for LN. Certainly, more rigorous head-to-head clinical trials are warranted to validate those findings.

    Keywords: Biological Agents1, Lupus nephritis2, Follow-Up Period3, Bayesian Network Meta-Regression Analysis4, Complete Response Rate5

    Received: 08 Jun 2024; Accepted: 12 Aug 2024.

    Copyright: © 2024 Liu, Chen, Chen, Li, Chen and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Xi Liu, Yubei District People’s Hospital, Chongqing, China

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