ArticleJournal of pain and symptom management2024
AI-Generated Content in Cancer Symptom Management: A Comparative Analysis Between ChatGPT and NCCN.
Article in Journal of pain and symptom management, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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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
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence and Decision-Making in Oncology: A Review of Ethical, Legal, and Informed Consent Challenges.Current oncology reports · 2025Pooled it
- Exploring young adult cancer survivors' perspectives on generative AI chatbots for symptom support.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Article
- Benchmarking AI Chatbots for Maternal Lactation Support: A Cross-Platform Evaluation of Quality, Readability, and Clinical Accuracy.Healthcare (Basel, Switzerland) · 2025Article
- The Unmet Needs of Palliative Care Among Young and Middle-Aged Patients with Advanced Cancer: A Qualitative Study.Current oncology (Toronto, Ont.) · 2025Article
- Ethical Challenges and Opportunities of AI in End-of-Life Palliative Care: Integrative Review.Interactive journal of medical research · 2025Review
- Effectiveness of Generative Artificial Intelligence-Driven Responses to Patient Concerns in Long-Term Opioid Therapy: Cross-Model Assessment.Biomedicines · 2025Article
- Navigating the potential and pitfalls of large language models in patient-centered medication guidance and self-decision support.Frontiers in medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundArtificial intelligence-driven tools, like ChatGPT, are prevalent sources for online health information. Limited research has explored the congruity between AI-generated content and professional treatment guidelines. This study seeks to compare recommendations for cancer-related symptoms generated from ChatGPT with guidelines from the National Comprehensive Cancer Network (NCCN).
interventionWe extracted treatment recommendations for nine symptoms from NCCN, separated into four full Supportive Care sections and five subsections of the Palliative Care webpage. We entered "How can I reduce my cancer-related [symptom]" into ChatGPT- 3.5 for these same symptoms and extracted its recommendations. A comparative content analysis focused on recommendations for medications, consultations, and non-pharmacological strategies. We compared word count and Flesch-Kincaid Grade Level (FKGL) readability for each NCCN and ChatGPT section. OUTCOMES: The mean percent agreement between NCCN and ChatGPT recommendations was 37.3% (range 16.7%-81.8%). NCCN offered more specific medication recommendations. ChatGPT did recommend medications in the constipation and diarrhea sections that were not recommended by NCCN. Significant differences in word count (P=0.03) and FKGL (P<0.01) were found for NCCN Supportive Care webpages, with ChatGPT having lower word count and reading level. In the NCCN Palliative Care webpage subsections, there was no significant difference in word count (P=0.076), but FKGL was significantly lower with ChatGPT (P<0.01). CONCLUSIONS/LESSONS LEARNED: While ChatGPT provides concise, accessible supportive care advice, discrepancies with guidelines raise concerns for patient-facing symptom management recommendations. Future research should consider how AI can be used in conjunction with evidence-based guidelines to support cancer patients' supportive care needs.
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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.