Brief ReportEvaluation of a Personalized, Web-Based Decision Aid for Lung Cancer Screening
Introduction
Lung cancer screening (LCS) programs are being implemented across the U.S. following evidence that low-dose computed tomographic screening can significantly reduce lung cancer mortality.1 Population-wide screening is most efficient if high-risk individuals, who are most likely to benefit, are identified and encouraged to screen, whereas those who are less likely to develop lung cancer are discouraged.
Decision aids (DAs) improve decision quality by helping users understand the pros and cons of available options, decrease decisional conflicts, and potentially prevent underuse or overuse of screening services.2, 3, 4, 5 The Centers for Medicare and Medicaid Services made shared decision making a requirement for LCS reimbursement, recommending the use of one or more DAs to facilitate the shared decision-making process.6 The authors’ DA complies with Centers for Medicare and Medicaid Services requirements in terms of content: benefits and harms of screening, follow-up diagnostic testing, overdiagnosis, false positive rate, and total radiation exposure.6 However, with LCS being a relatively new screening procedure, there is a paucity of DAs available. To the authors’ knowledge, only one DA has been peer-reviewed to date.7 Moreover, current DAs7, 8, 9, 10, 11 do not consider individual characteristics and only provide average risks and benefits of LCS. Precise risk prediction should be a critical part of LCS because clinically important differences in benefit exist even among screen-eligible individuals.12
The authors developed a web-based DA that provides individual estimates of lung cancer risk, and screening benefits and harms. They then tested its efficacy with current and former smokers aged 45–80 years.
Section snippets
Study Sample
An uncontrolled, before-and-after study was conducted with 60 participants to assess the efficacy of the DA (August through December 2014). A sample size of ≥52 was calculated to detect a 20% improvement in knowledge assuming an initial mean of 7.8 (score of 60%), with power of 0.8. Participants were a convenience sample of volunteers who were current/former smokers, aged 45–80 years, with no previous history of lung cancer and no chest computed tomographic scan in the previous year at the time
Results
The average participant was aged 60.6 years, half were male, 27% were current smokers, and 18% fulfilled the USPSTF’s eligibility criteria for screening (Table 1). The average 6-year lung cancer risk was 0.012 (PLCOm2012 model22). Average time spent on the study website/DA was 10 minutes.
Table 2 provides before/after changes for knowledge, decisional conflict, and concordance. Knowledge for all questions improved significantly after viewing the DA (p<0.001). Most people were not aware that the
Discussion
This web-based DA was highly accepted, improved LCS knowledge, decreased decisional conflict, and raised concordance between USPSTF recommendations and the screening option preferred by the participants.
After receiving personalized estimates of lung cancer risk, screening benefit–harm comparisons, and current guideline recommendations, there were significant reductions in the number of individuals ineligible for screening who stated their preferred option was to get screened, and in those who
Acknowledgments
This work has been supported by the Elizabeth A. Crary Fund of the University of Michigan Comprehensive Cancer Center. The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, and approval of the manuscript.
No financial disclosures were reported by the authors of this paper.
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