Safety and Efficacy of Rechallenge With Immune Checkpoint Inhibitors in Advanced Solid Tumor: A Systematic Review and Meta‐Analysis Article Swipe
Huijun Xu
,
Yang Yang
,
Ying Yan
,
Mengge Li
,
Shusheng Wu
,
Lulu Cao
,
Wenju Chen
,
Huiqin Luo
,
Yifu He
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1002/cam4.70324
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1002/cam4.70324
Background Immune checkpoint inhibitors (ICIs) have drastically shifted the current landscape toward a wide variety of malignancies. However, ICIs are interrupted owing immune‐related adverse events (irAEs), therapy completion, and disease progression. The risk–benefit of rechallenged ICIs remains inconclusive. Herein, a systematic review and meta‐analysis were conducted to evaluate the safety and efficacy of ICI rechallenge in the treatment of advanced solid tumor. Methods PubMed, Web of Science, Embase, and Cochrane Library were searched to analyze the efficacy and safety of ICI rechallenge. The study protocol was approved by the PROSPERO International Register of Systematic Reviews (CRD42022372222). The last updated search date was March 2, 2024. Objective response rate (ORR), disease control rate (DCR), overall survival (OS), and incidence rates of all‐ and high‐grade irAEs were evaluated. Results A total of 41 retrospective studies comprising 2343 patients were ultimately enrolled for qualitative and quantitative assessments. A total of 1200 (51.2%) individuals were male and the median age was 66 years (range 18–97 years). The majority of the tumors was lung cancer ( n = 898, 38.3%). The occurrence rates of all‐grade and high‐grade (grade 3 or 4) irAEs between initial and readministration ICIs were not significantly different (all‐grade: OR, 0.75, 95% CI: 0.39–1.45, p = 0.40; I 2 = 87%; high‐grade: OR, 0.96, 95% CI: 0.62–1.49, p = 0.87, I 2 = 65%). ICIs restart presented a decreased ORR and DCR compared to initial ICI administration (ORR: OR, 0.36, 95% CI: 0.23–0.56, p < 0.00001; I 2 = 67%; DCR: OR, 0.62, 95% CI: 0.43–0.89, p = 0.010; I 2 = 53%). Seven studies with 513 patients for survival analysis revealed a nonsignificant difference in OS between the ICIs rechallenge and discontinuation cohorts (hazard ratio [HR]: 0.68, 95% confidence interval (CI): 0.35 to 1.35, p = 0.27). Conclusion Rechallenging immunotherapy is feasible, and patients should be carefully evaluated by a multidisciplinary team prior to initial therapy for close monitoring and assessment of the risk–benefit ratio. Therefore, prospective trials are essential to guide clinicians in the decision‐making process. PROSPERO Registration: CRD42022372222.
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Metadata
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.1002/cam4.70324
- OA Status
- gold
- Cited By
- 8
- References
- 54
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4403846512
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4403846512Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1002/cam4.70324Digital Object Identifier
- Title
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Safety and Efficacy of Rechallenge With Immune Checkpoint Inhibitors in Advanced Solid Tumor: A Systematic Review and Meta‐AnalysisWork title
- Type
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reviewOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-10-01Full publication date if available
- Authors
-
Huijun Xu, Yang Yang, Ying Yan, Mengge Li, Shusheng Wu, Lulu Cao, Wenju Chen, Huiqin Luo, Yifu HeList of authors in order
- Landing page
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https://doi.org/10.1002/cam4.70324Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://doi.org/10.1002/cam4.70324Direct OA link when available
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Medicine, Cochrane Library, Internal medicine, Adverse effect, Incidence (geometry), Meta-analysis, Systematic review, Oncology, Lung cancer, MEDLINE, Political science, Physics, Optics, LawTop concepts (fields/topics) attached by OpenAlex
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8Total citation count in OpenAlex
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2025: 8Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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