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Yvonne Leung



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    P2.10 - Prevention and Tobacco Control (ID 176)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Prevention and Tobacco Control
    • Presentations: 1
    • Now Available
    • Moderators:
    • Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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      P2.10-04 - Predicting Non-Compliance in Routine Lung Cancer Screening for High-Risk Adults (Now Available) (ID 2664)

      10:15 - 18:15  |  Presenting Author(s): Yvonne Leung

      • Abstract
      • Slides

      Background

      Lung cancer is the most common cause of cancer-related deaths, which can be effectively reduced by routine screening. To detect lung cancer early, annual screening in high-risk adults aged 55-74 years using low-dose computed tomography (LDCT) is recommended by the Canadian Medical Association guidelines. High-risk adults are recommended an annual screen within 11-15 months of their baseline scan. However, screening compliance is a challenging area influenced by a series of complex biopsychosocial, behavioral and cognitive processes. This study aims to describe the participants and identify predictors of noncompliance in the Lung Cancer Screening Pilot for People at High Risk Program (HR LCSP) conducted in Ontario, Canada.

      Method

      During 2017-18, HR LCSP has recruited over 5,999 high-risk adults from 3 sites in Ontario, with 5,502 adults undergone risk assessment for screening eligibility, and 2,997 baseline scans conducted. Baseline and follow-up participant experience surveys assess satisfaction especially around test result communication. During risk assessment, all individuals who identify as current smokers are referred to smoking cessation services irrespective of their eligibility. The clinical data are collected using an internationally accepted standard, the Resident Assessment Instrument Minimum Data Set at each site. We hypothesize that participant compliance is predicted by the satisfaction of their first screening experience in additional to socio-demographic and clinical factors. A multivariable logistic regression model will be conducted to predict non-compliance, which is defined by a return interval >15 months or missing. The model will contain individual level factors including age, sex, aboriginal status, education, income estimates, geographic distance; system level factor includes physician-referral/ self-referral status; clinical factors include the risk prediction by PLCOm2012, which assesses smoking status including intensity and duration; other clinical factors include personal and family history of cancer, history of lung disease, body mass index; psychosocial/behavioral factors include smoking cessation program participation, baseline screening results including the presence of actionable incidental findings and appropriate follow-up of the abnormal results. Data linkage is under way and results will be presented at the conference.

      Result

      This study will provide a granular view on the predictors of routine screening compliance among high-risk adults, which will be used to improve the program recruitment and retention especially when designing targeted messages. Findings will have implications for health care professionals when communicating with high-risk individuals about routine screening for lung cancer.

      Conclusion

      Section not applicable.

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