Evidence map›Paper›PMID 38452323›Full record

ArticleJournal of clinical oncology : official journal of the American Society of Clinical Oncology2024

Promise and Perils of Large Language Models for Cancer Survivorship and Supportive Care.

Danielle S Bitterman, Andrea Downing, Julia Maués, Maryam Lustberg

Abstract read
In one paragraph

Article in Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Review
  5. Review
  6. Article
  7. Evidence-Based Analysis of AI Chatbots in Oncology Patient Education: Implications for Trust, Perceived Realness, and Misinformation Management.Journal of cancer education : the official journal of the American Association for Cancer Education · 2025
    Review
  8. Article
  9. Article
  10. Article
  11. Using GPT-4o to interpret patient-reported outcomes without training.Journal of the National Cancer Institute · 2025
    Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Danielle S BittermanArtificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA.ORCID 0000-0003-0345-2232
Andrea DowningThe Light Collective, Eugene, OR.
Julia MauésGRASP, Washington, DC.ORCID 0000-0002-4478-6952
Maryam LustbergDepartment of Medical Oncology, Yale School of Medicine, New Haven, CT.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Shared Resource Core 2: Clinical Artificial Intelligence CoreU54CA274516 · NCI · DANA-FARBER CANCER INST · PI Benjamin Harris Kann · 2023 to 2026
$8.1M
NCATS NIH HHS UL1 TR001863NCI NIH HHS U54 CA274516
6 · The paper itself

Abstract

A call to action to bring stakeholders together to plan for the future of LLM-enhanced cancer survivorship.

Indexed as

Cancer SurvivorsNeoplasmsHumansSurvivorship

Identifiers

PMID38452323
PMCPMC11095890

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.