ArticleWiener klinische Wochenschrift2018
Do doctors understand the test characteristics of lung cancer screening?
Article in Wiener klinische Wochenschrift, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02542332 (Are Doctors Familiar With the Test Characteristics of Lung Cancer Screening?), which is not on this map. Cited by 4 papers.
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.
Are Doctors Familiar With the Test Characteristics of Lung Cancer Screening?
Who cites it
4 citing papers in PubMed.
- It depends on where you stand on screening: health professionals' awareness, perspectives, and approaches to overdiagnosis in cancer screening - a qualitative interview study.BMC health services research · 2026Article
- The Evidence Effect: How Fact Boxes Shift Perceptions of Lung Cancer Screening in Austrian Medical Practice.Cancer medicine · 2024Article
- Effective Educational Approaches to Training Physicians About Lung Cancer Screening.Journal of cancer education : the official journal of the American Association for Cancer Education · 2022Article
- Characterizing the Design of and Emerging Evidence for Health Care Organization-Based Lung Cancer Screening Interventions: A Systematic Review.MDM policy & practiceReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundScreening for lung cancer with a low-dose computed tomography (CT) scan is estimated to prevent 3 deaths per 1000 individuals at high risk; however, false positive results and radiation exposure are relevant harms and deserve careful consideration. Screening candidates can only make an autonomous decision if doctors correctly inform them of the pros and cons of the method; therefore, this study aimed to evaluate whether doctors understand the test characteristics of lung cancer screening.
methodsIn a randomized trial 556 doctors (members of the Austrian Respiratory Society) were invited to answer questions regarding lung cancer screening based on online case vignettes. Half of the participants were randomized to the group 'solutions provided' and received the correct solutions in advance. The group 'solutions withheld' had to rely on prior knowledge or estimates. The primary endpoint was the between-group difference in the estimated number of deaths preventable by screening. Secondary endpoints were the between-group differences in the prevalence of lung cancer, prevalence of a positive screening results, sensitivity, specificity, positive predictive value, and false negative rate. Estimations were also compared with current data from the literature.
resultsThe response rate was 29% in both groups. The reduction in the number of deaths due to screening was overestimated six-fold (95% confidence interval CI: 4-8) compared with the actual data, and there was no effect of group allocation. Providing the correct solutions to doctors had no systematic effect on their answers.
conclusionDoctors poorly understand the test characteristics of lung cancer screening. Providing the correct solutions in advance did not improve the answers. Continuing education regarding lung cancer screening and the interpretation of test characteristics may be a simple remedy. CLINICAL
trial registrationClinical trial registered with www.clinicaltrials.gov (NCT02542332).
Indexed as
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29372409What 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.