Evidence map›Paper›PMID 23701064›Full record

ArticleAJR. American journal of roentgenology2013

Journal club: How radiation exposure histories influence physician imaging decisions: a multicenter radiologist survey study.

Pari V Pandharipande, Jonathan D Eisenberg, Laura L Avery, Martin L Gunn, Stella K Kang, Alec J Megibow, Ekin A Turan, H Benjamin Harvey, Chung Yin Kong, Emily C Dowling and 3 more

Abstract readMulticenter Study
In one paragraph

Article in AJR. American journal of roentgenology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Review
  3. Effects of ionizing radiation exposure during pregnancy.Abdominal radiology (New York) · 2023
    Article
  4. The cumulative radiation dose paradigm in pediatric imaging.The British journal of radiology · 2021
    Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Are Continued Efforts to Reduce Radiation Exposures from X-Rays Warranted?Dose-response : a publication of International Hormesis Society
    Article
  12. X-Ray Hesitancy: Patients' Radiophobic Concerns Over Medical X-rays.Dose-response : a publication of International Hormesis Society
    Article
  13. Death of the ALARA Radiation Protection Principle as Used in the Medical Sector.Dose-response : a publication of International Hormesis Society
    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

13 authors.

Pari V PandharipandeInstitute for Technology Assessment, Department of Radiology, Massachusetts General Hospital, 101 Merrimac St, 10th Fl, Boston, MA 02114, USA. pari@mgh-ita.org
Jonathan D Eisenberg
Laura L Avery
Martin L Gunn
Stella K Kang
Alec J Megibow
Ekin A Turan
H Benjamin Harvey
Chung Yin Kong
Emily C Dowling
Elkan F Halpern
Karen Donelan
G Scott Gazelle

Funding

Cost-Effectiveness of Radiofrequency Ablation for Small, Incidental Renal TumorsK07CA133097 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI PANDHARIPANDE, PARI VIJAY · 2009 to 2013
$891k
Applications of Multi-Criteria Optimization (AMCO) to Cancer Simulation ModelingK25CA133141 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI KONG, CHUNG YIN · 2009 to 2013
$844k
NCI NIH HHS K07 CA133097NCI NIH HHS K25 CA133141
6 · The paper itself

Abstract

objectiveThe purpose of this article is to evaluate the influence of patient radiation exposure histories on radiologists' imaging decisions. MATERIALS AND

methodsWe conducted a physician survey study in three academic medical centers. Radiologists were asked to make an imaging recommendation for a hypothetical patient with a history of multiple CT scans. We queried radiologists' decision making, evaluating whether they incorporated cancer risks from previous imaging, reported acceptance (or rejection) of the linear no-threshold model, and understood linear no-threshold model implications in this setting. Consistency between radiologists' decisions and their linear no-threshold model beliefs was evaluated; those acting in accordance with the linear no-threshold model were expected to disregard previously incurred cancer risks. A Fisher exact test was used to verify the generalizability of results across institutions and training levels (residents, fellows, and attending physicians).

resultsFifty-six percent (322/578) of radiologists completed the survey. Most (92% [295/322]) incorporated risks from the patient's exposure history during decision making. Most (61% [196/322]) also reported acceptance of the linear no-threshold model. Fewer (25% [79/322]) rejected the linear no-threshold model; 15% (47/322) could not judge. Among radiologists reporting linear no-threshold model acceptance or rejection, the minority (36% [98/275]) made decisions that were consistent with their linear no-threshold model beliefs. This finding was not statistically different across institutions (p = 0.070) or training levels (p = 0.183). Few radiologists (4% [13/322]) had an accurate understanding of linear no-threshold model implications.

conclusionMost radiologists, when faced with patient exposure histories, make decisions that contradict their self-reported acceptance of the linear no-threshold model and the linear no-threshold model itself. These findings underscore a need for educational initiatives.

Indexed as

Decision MakingPractice Patterns, Physicians'Radiation DosageTomography, X-Ray ComputedAcademic Medical CentersHumansLinear ModelsLogistic ModelsNeoplasms, Radiation-InducedRadiation ProtectionRiskSurveys and QuestionnairesUnited States

Identifiers

PMID23701064
PMCPMC3970405

What OpenQuestion holds

Textmetadata
LicenceTDM
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.