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  P2.11 - Screening and Early Detection (Not CME Accredited Session) (ID 960)

  • Event: WCLC 2018
  • Type: Poster Viewing in the Exhibit Hall
  • Track:
  • Presentations: 1
  • Moderators:
  • Coordinates: 9/25/2018, 16:45 - 18:00, Exhibit Hall

  • 27143

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    P2.11-21 - Factors Predicting Attrition in Community-Based Healthcare Network Lung Cancer Screening Programs (ID 13952)

    16:45 - 18:00  |  Author(s): Shu-Ching Chang
    • Abstract
    • Slides

    Background
    

    Since publication of the National Lung Screening Trial, the national focus has been on implementation of Lung Cancer Screening Programs (LCSPs). However, lung cancer screening (LCS) is a continuum where the benefits are derived from long-term engagement and, to date, little is known about attrition in LCS. We aimed to identify the rate of attrition within two of our healthcare network, community-based LCSPs and identify the factors predictive of attrition.

    a9ded1e5ce5d75814730bb4caaf49419 Method
    

    We reviewed 2364 individuals who underwent LCS within two of our healthcare network LCSPs from 01/01/2012-03/31/2017. One LCSP is centralized (shared decision making/evaluation/management at a single site) and the other is decentralized (shared decision making/evaluation/management occur in geographically diverse community care settings with support from a central LCSP coordinator). Attrition was defined as declining further screening or lost to follow-up. Continuous data reported as median and 25^th-75^th interquartile range, and univariate/multivariable logistic regression analyses was performed to identify predictors of attrition.

    4c3880bb027f159e801041b1021e88e8 Result
    

    We identified an attrition rate of 15% (351/2364) with median time to attrition of 15 (12-20) months. Patients who underwent attrition tended to be younger [62 (58-67) versus 65 (60-69) years, p<0.001], smoking on first visit (61% versus 55%, p=0.05), in the decentralized program (74% versus 67%, p=0.01), and less likely to have a nodule on first CT scan (48% versus 64%, p<0.001). Multivariable logistic regression demonstrated a younger age, decentralized program type, and the absence of a nodule on first CT scan to be significant predictors of attrition (p<0.05) [Table].

    Predictors of Attrition

    UNIVARIATE ANALYSIS
    Characteristic	Odds Ratio	Lower 95% C. I.	Upper 95% C. I.	P Value
    Age, years	0.95	0.93	0.97	<0.001
    Gender
    Female
    Male	0.88	0.70	1.11	0.29
    Race
    White
    Black	1.19	0.68	2.06	0.54
    Native Hawaiian/Asian	1.74	1.03	2.95	0.04
    American Indian	0.49	0.12	2.08	0.33
    Declined/Other	0.97	0.58	1.62	0.90
    Smoking Status on 1st Visit
    Former
    Current	1.28	1.01	1.61	0.04
    Distance to CT scan, miles	1.00	1.00	1.00	0.70
    Program
    Centralized
    Decentralized	1.41	1.09	1.82	0.01
    Nodule on 1st CT scan
    No
    Yes	0.53	0.42	0.67	<0.001
    Nodule Size on 1st CT scan	0.99	0.97	1.02	0.53
    MULTIVARIABLE ANALYSIS
    Characteristic	Odds Ratio	Lower 95% C. I.	Upper 95% C. I.	P value
    Age, years	0.96	0.94	0.98	<0.001
    Program
    Centralized
    Decentralized	1.37	1.04	1.79	0.02
    Nodule on 1st CT scan
    No
    Yes	0.58	0.46	0.73	<0.001

    8eea62084ca7e541d918e823422bd82e Conclusion
    

    Overall attrition is low at 15%. Factors that correlated with failure to follow-up were young age, active smoking, being in a decentralized program, and lack of nodule on first scan. Ongoing efforts are necessary to ensure that screening is a continuum, particularly in populations of individuals at high-risk of attrition.

    6f8b794f3246b0c1e1780bb4d4d5dc53

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