A comprehensive Bayesian analysis assessing the effectiveness of lymphocyte immunotherapy for recurrent spontaneous abortion

Abstract

Recurrent spontaneous abortion (RSA) affects 2%–5% of couples worldwide and remains a subject of debate regarding the effectiveness of lymphocyte immunotherapy (LIT) due to limited retrospective studies. We conducted a comprehensive Bayesian analysis to assess the impact of LIT on RSA. Using data from the Shenzhen Maternity and Child Healthcare Hospital (2001–2020, n = 2316), a Bayesian generalized linear model with predictive projection feature selection was employed. Our analysis revealed a significant improvement in live birth rates for RSA patients undergoing LIT. Notably, LIT had a greater impact compared to the other 85 factors considered. To mitigate research bias, we conducted a Bayesian meta-analysis combining our dataset with 19 previously reported studies (1985–2021, n = 4246). Additionally, we developed an empirical model high-lighting the four key factors, which are the LIT result, age, paternal blood type, and anticardiolipin antibody. Younger age (19–27), paternal blood type B, and a positive anticardiolipin antibody (IgM) were associated with better therapeutic outcomes in LIT for RSA. These findings aid clinicians in identifying suitable candidates for LIT and improving treatment outcomes.

Keywords

recurrent spontaneous abortion / lymphocyte immunotherapy / Bayesian analysis / Bayesian meta-analysis

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The Author(s) 2023. Published by Oxford University Press on behalf of Higher Education Press.