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Systematic review finds 96.7% of high-impact oncology journals prohibit AI authorship and mandate disclosure.

Systematic review finds 96.7% of high-impact oncology journals prohibit AI authorship and mandate di…
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Key Takeaway
Note that 96.7% of high-impact oncology journals prohibit AI authorship and mandate disclosure.

This systematic review and policy analysis examined editorial policies governing AI-assisted writing across 60 high-impact oncology journals with a 2023 Journal Impact Factor ≥5. The scope included four specific domains: authorship, disclosure, permissible uses, and enforcement. The analysis was not a clinical trial but a review of published journal policies.

The key synthesized findings reveal a high degree of consensus on authorship and transparency. Specifically, 58 of 60 journals (96.7%) prohibit AI systems from being listed as authors. Similarly, 58 of 60 journals (96.7%) mandate disclosure of AI use, and 58 of 60 journals (96.7%) recognize permissible uses of AI tools. In contrast, enforcement provisions are less common, with only 21 of 60 journals (35.0%) having such measures in place.

Publisher-level adoption of disclosure was universal for major publishers including Elsevier (17 of 17), Springer Nature (20 of 20), AACR (6 of 6), Wiley (6 of 6), and AMA (1 of 1), and was present in 8 of 10 journals in the 'Other' category. The authors highlight that incomplete standardization regarding enforcement remains a significant gap in current policy landscapes.

The authors conclude that greater harmonization is essential to ensure integrity, accountability, and equitable use of AI in oncology publishing. This review provides a snapshot of current standards rather than clinical efficacy data, as no adverse events or patient outcomes were assessed.

Study Details

Study typeMeta analysis
EvidenceLevel 1
PublishedApr 2026
View Original Abstract ↓
Generative artificial intelligence (AI) is reshaping scholarly communication, yet guidance for its responsible use remains uneven across biomedical journals. We aimed to systematically assess editorial policies governing AI-assisted writing in high-impact oncology journals. We conducted a systematic review of publicly available editorial and normative documents, operationalized as a cross-sectional policy audit. Oncology journals with a 2023 Journal Impact Factor ≥5 (JCR 2024) were included. Author instructions, editorial policies, and publisher statements issued between January 2020 and March 2025 were analyzed across four domains: authorship, disclosure, permissible uses, and enforcement. Sixty journals met inclusion criteria. Most journals prohibit AI systems as authors (58/60, 96.7%), reaffirming human accountability. Disclosure of AI use is mandated by 58/60 journals (96.7%), although reporting requirements vary in placement and specificity. Permissible uses are recognized by 58/60 journals (96.7%), generally limited to language editing and formatting under human supervision, while autonomous content generation or interpretation is discouraged. Enforcement provisions are present in 21/60 journals (35.0%), indicating incomplete standardization. At publisher level, disclosure adoption is universal in Elsevier (17/17), Springer Nature (20/20), AACR (6/6), Wiley (6/6), and AMA (1/1), and present in 8/10 journals in the “Other” category. Enforcement varies widely across publishers. Editorial policies show strong convergence on core principles but remain heterogeneous in implementation, particularly regarding enforcement. We propose a cross-publisher “AI Policy Minimum Dataset” including standardized disclosures, defined permissible uses, and proportionate enforcement mechanisms, supported by transparent and regularly updated policy frameworks. Greater harmonization is essential to ensure integrity, accountability, and equitable use of AI in oncology publishing.
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