ArticleJTO clinical and research reports2023
Immune Checkpoint Inhibitors in Patients With Cancer and Infection by Hepatitis B or C Virus: A Perspective Through the Results of a European Survey.
Article in JTO clinical and research reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 3 citations in OpenAlex.
- Safety of Immune Checkpoint Inhibitors in Hepatitis B Virus-Positive Cancer Patients: A Multicenter Retrospective Cohort Study.Current oncology (Toronto, Ont.) · 2026Article
- Across the Social Network of the Gut: Bacterial, Fungal, and Viral Determinants of Checkpoint Inhibitor Efficacy and Toxicity.International journal of molecular sciences · 2026Review
- NetMe 2.0: a web-based platform for extracting and modeling knowledge from biomedical literature as a labeled graph.Bioinformatics (Oxford, England) · 2024Article
- Management of Hepatitis B Virus and Hepatitis C Virus Infections in Patients with Cancer Receiving Immune Checkpoint Inhibitors.Journal of immunotherapy and precision oncology · 2024Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Patients with cancer and hepatitis B virus (HBV) or hepatitis C virus (HCV) infection are underrepresented in several clinical trials testing immune checkpoint inhibitors (ICIs). Consequently, safety and efficacy of ICI therapy in this population have not been completely defined. We aimed to evaluate the attitudes of oncologists on this topic. Methods: We conducted a 14-item European anonymous online survey. Results: Physicians from 56 oncology departments (26 from Italy, 15 from France, and 15 from Spain) took part in the survey. They mainly used to prescribe ICIs for treating patients with lung cancer, melanoma, and renal cell carcinoma. Of them, 95% recognized the need for specific guidelines addressing the management of patients with cancer and HBV or HCV treated with ICIs. Just 63% of the respondents screened patients for HBV and HCV status before ICIs initiation, although the risk of immune-related hepatotoxicity or viral reactivation was a major concern for most of them. Only 9% of the surveyed oncologists considered HBV and HCV infection a major exclusion criterion for receiving ICIs. Furthermore, 29% of the respondents would start a prophylactic treatment of active infection at ICIs initiation. Conclusions: ICIs administration in patients with cancer and HBV or HCV infection is of concern for most of the surveyed European oncologists. Nonetheless, active screening and treatment of viral hepatitis should be improved. Data in this specific setting are needed for an evidence-based management and should be generated by broadening inclusion criteria of clinical trials to allow the enrollment of patients with HBV and HCV.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.