COVID-19 vaccine effectiveness in people on immunosuppressive therapies: a systematic review and meta-analysis
- Journal
- The Lancet. Microbe (Q1)
- Published
- 15 September 2026
- Study design
- Systematic review / meta-analysis of RCTs
- Evidence level
- Level 1, High (CEBM 1a)
- Authors
- Eva Stadler, Shanchita R Khan, Karen M Elias, Ece Egilmezer, Chansavath Phetsouphanh, Priyanka Hastak, et al.
- PMID
- 42743943
- DOI
- 10.1016/j.lanmic.2026.101424
Why clinicians should know about it
- Picked for Transplantation (top studies of the week, 20 September 2026): Recent Transplantation research from a high-quartile journal
- Picked for Microbiology (medical) (top studies of the week, 20 September 2026): High-quality evidence in a top journal
Abstract
BACKGROUND: People on immunosuppressive therapies are at increased risk of severe COVID-19, yet vaccine efficacy in these individuals has been inadequately assessed in randomised controlled trials. This systematic review and meta-analysis aims to examine vaccine effectiveness in people with medical conditions commonly treated with conventional synthetic or targeted immunosuppressive therapies. METHODS: We searched PubMed and Scopus from database inception and Embase from Jan 1, 2020, until Dec 5, 2025. We included randomised controlled trials, cohort studies, and case-control studies of COVID-19 vaccines in adults with haematological malignancies or autoimmune and immune-mediated inflammatory disorders. Studies were eligible if they were published in English and reported vaccine effectiveness or a relative risk (RR) measure for preventing SARS-CoV-2 infection, hospitalisation, severe disease, or death. We excluded studies of organ transplant recipients and patients with other conditions (eg, HIV or non-haematologic cancers). Data were extracted by one author (SRK or ES) and verified by another author (SRK, KME, ES, CP, PH, RVH, RVJ, or SCS). Risk of bias was assessed independently by two authors (KME and EE) using the Newcastle-Ottawa Scale. Effect measures were pooled using random-effects meta-analysis with inverse variance weighting. I2 with 95% CIs were reported as measures of between-study heterogeneity. This review was registered with PROSPERO (CRD42023434975). FINDINGS: Our database search identified 3316 studies, and one additional study was identified from citation searching. 35 studies were eligible for inclusion in the review, of which 34 were included in the meta-analysis (one study was excluded due to no cases in all arms). Of the 34 included studies, 17 reported vaccine effectiveness against COVID-19 outcomes in people on immunosuppressive therapies compared with unvaccinated individuals, 16 reported RR measures in vaccinated individuals on immunosuppressive therapies compared with vaccinated healthy controls, and one reported both. Of the 34 included studies, risk of bias was rated as good in 21 (62%) studies, as fair in four (12%), and as poor in nine (26%). Clinical outcomes reported across the studies were: infection in 28 (82%), hospitalisation or severe disease in 16 (47%), and death in eight (24%). Vaccine effectiveness was 82·3% (95% CI 72·4-88·7, I2=96·8%) against SARS-CoV-2 infection with pre-omicron variants after three vaccinations and 88·4% (82·8-92·3, 73·9%) against hospitalisation. Among vaccinated individuals on immunosuppressive therapies, the RR compared with that in vaccinated healthy individuals was 1·57 (1·25-1·96, I2=89·7%) for SARS-CoV-2 infection, 3·72 (1·63-8·47, 85·5%) for hospitalisation, and 3·14 (1·51-6·54, 75·2%) for death. INTERPRETATION: This analysis shows a substantial benefit of vaccination for people on immunosuppressive therapy, particularly after three vaccine doses and against severe outcomes. It also highlights a significantly higher risk of hospitalisation and death in this group than in vaccinated healthy individuals. Assessing booster vaccine effectiveness in these populations against current circulating variants and with updated vaccines remains a priority. FUNDING: National Health and Medical Research Council (Australia).
Abstract as published, via PubMed.
For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.