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Andrea S Ferris



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    MA24 - Initiatives to Improve Health in Lung Cancer Patients (ID 354)

    • Event: WCLC 2019
    • Type: Mini Oral Session
    • Track: Advocacy
    • Presentations: 1
    • Now Available
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      MA24.03 - Factors Impacting Patients’ Worries (Accessing Treatment, Treatment Toxicity, & Emotional Burden) Associated with Lung Cancer Treatments (Now Available) (ID 2589)

      14:30 - 16:00  |  Presenting Author(s): Andrea S Ferris

      • Abstract
      • Presentation
      • Slides

      Background

      Understanding patient experiences with lung cancer can guide research, treatment, and policy decisions. Conducted as part of a larger study (Project Transform) that aimed to quantified patient experiences, we sought to study the primary concerns of lung cancer patients and their caregivers and to determine what demographic and clinical factors impact these worries.

      Method

      Lung-cancer worries were identified from patient interviews and the literature. A novel an instrument assessing 13 potential worries on a 3-point importance scale was incorporated as part a national survey of lung cancer patients (inclusive of all types/stages of disease) and caregivers recruited through LUNGevity Foundation. Factor analyses was used to identify key constructs among the 13 worries. We then explored variation in the standardized factor scores across demographic and clinical indicators collected in the survey.

      Result

      Of the 426 participants in the survey, there were 385 patients and 41 caregivers. The average age of respondents was 58.9 years, 54% earned less than $75,000 per year, and 67.6% had completed college. Three factors were identified associated with worrying: 1) “accessing treatments” (incorporating knowledge, communication, access); 2) “treatment toxicity” (incorporating both side-effects and financial impact); and 3) “emotional burden” (including worries about dying, emotional toll, and being a burden), with Cronbach’s alphas of 0.89, 0.73, and 0.74 respectively. Worries about accessing treatment were lower among NSCLC (P=0.006), presence of MET mutations (P = 0.027) and those not currently receiving therapy (P=0.033). Worries about treatment toxicity were higher among non-white (P<0.001), non-retired (P<0.001), those earning less than $75,000 (P<0.001), younger patients (P<0.001), and those with ALK (P=0.026) or HER2 (P=0.041) mutations. Worries about treatment toxicity were lower among patients on Medicare or Medicaid during treatment (P = 0.023) and NSCLC patients (P=0.018). Worries about the emotional burden of treatment were lower among those >=60 years (P=0.002) and those who are retired (P=0.021) and higher among those having surgery (P=0.039).

      Table 1: Marginal effects of patient factors on standardized worry scores

      Factor

      Accessing Treatment

      Treatment toxicity

      Emotional burden

      Patient

      -0.052 (0.16)

      -0.144 (0.16)

      -0.224 (0.16)

      Age >= 60

      -0.1 (0.1)

      -0.336 (0.1)***

      -0.309 (0.1)**

      Female

      0.003 (0.12)

      0.239 (0.12)

      0.158 (0.12)

      Non-white

      -0.022 (0.16)

      0.56 (0.16)***

      0.048 (0.16)

      Hispanic, Latino, or Spanish

      -0.003 (0.22)

      0.233 (0.22)

      0.161 (0.21)

      Primary Language - Spanish

      0.116 (0.7)

      0.879 (0.69)

      0.423 (0.67)

      Armed Forces

      -0.103 (0.18)

      -0.134 (0.18)

      0.055 (0.18)

      Marries

      0.139 (0.11)

      -0.177 (0.11)

      0.073 (0.11)

      Has children

      0.004 (0.13)

      -0.031 (0.13)

      0.203 (0.12)

      College or professional degree

      0.208 (0.11)

      -0.096 (0.11)

      -0.104 (0.1)

      Retired

      -0.048 (0.1)

      -0.488 (0.1)***

      -0.233 (0.1)*

      Household Income < $75,000

      0.031 (0.11)

      0.376 (0.11)***

      0.025 (0.11)

      Population < 2,500

      -0.168 (0.22)

      -0.099 (0.22)

      0.193 (0.21)

      Chronic conditions as diagnosis

      -0.078 (0.12)

      -0.021 (0.12)

      0.146 (0.12)

      NSCLC

      -0.308 (0.11)**

      -0.263 (0.11)*

      -0.111 (0.11)

      Private Insurance

      0.084 (0.11)

      0.139 (0.11)

      0.057 (0.11)

      Medicare or Medicaid

      0.02 (0.1)

      -0.235 (0.1)*

      -0.079 (0.1)

      Other Insurance

      -0.092 (0.17)

      -0.144 (0.17)

      -0.128 (0.17)

      No Insurance

      0.363 (0.58)

      0.56 (0.58)

      -0.083 (0.58)

      Participated in a clinical trial

      -0.029 (0.12)

      -0.134 (0.12)

      0.077 (0.12)

      ALK

      0.143 (0.14)

      0.295 (0.13)*

      0.041 (0.12)

      BRAF

      -0.241 (0.56)

      -0.663 (0.55)

      -0.345 (0.52)

      EGFR

      -0.038 (0.13)

      -0.109 (0.13)

      0.121 (0.12)

      HER2

      0.689 (0.48)

      0.973 (0.47)*

      0.439 (0.45)

      KRAS

      -0.201 (0.21)

      -0.067 (0.21)

      -0.113 (0.2)

      MET

      -0.765 (0.34)*

      -0.389 (0.34)

      0.19 (0.32)

      NTRK

      0.767 (0.68)

      0.467 (0.67)

      0.101 (0.63)

      RET

      0.154 (0.4)

      -0.47 (0.39)

      -0.69 (0.36)

      ROS1

      0.149 (0.26)

      -0.053 (0.25)

      0.202 (0.24)

      More than 2 lines of treatment

      0.09 (0.1)

      0.026 (0.1)

      0.03 (0.1)

      Chemotherapy

      0.019 (0.16)

      0.008 (0.16)

      0.007 (0.16)

      Radiation

      0.197 (0.29)

      0.339 (0.3)

      0.101 (0.3)

      Targeted therapy

      0.143 (0.1)

      0.038 (0.1)

      0.129 (0.1)

      Immunotherapy

      0.124 (0.18)

      0.188 (0.19)

      -0.125 (0.19)

      Surgery

      0.454 (0.29)

      0.407 (0.3)

      0.612 (0.29)*

      Angiogenesis inhibitors

      0.081 (0.41)

      0.101 (0.42)

      0.268 (0.42)

      No current treatment

      -0.214 (0.1)*

      -0.192 (0.1)

      -0.163 (0.1)

      Notes: Standard errors in parentheses, * p<0.05, ** p<0.01, ***p<0.001

      Conclusion

      Conclusion:

      Patients worry to differing extents about accessing treatment, treatment toxicity, and the emotional burden of lung cancer, yet caregivers and patients (on the whole) have similar worries. Lung cancer researchers, clinicians, and policymakers should make decisions in ways that address the heterogeneous experience of patients. Patients worries vary across a confluence of demographic, disease, and treatment factors, hence greater attention to the individual needs of the patient is needed.

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    P1.16 - Treatment in the Real World - Support, Survivorship, Systems Research (ID 186)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Treatment in the Real World - Support, Survivorship, Systems Research
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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      P1.16-21 - Does Age Affect What Patients Value When Considering Lung Cancer Treatments? Evidence from a National Survey (ID 1947)

      09:45 - 18:00  |  Author(s): Andrea S Ferris

      • Abstract
      • Slides

      Background

      Few studies have explored how values vary with patients’ lung cancer treatment experience. Due to the rapidly increasing number of treatments for lung cancer, we sought to demonstrate a simple values-elicitation method and explore how values differ across age.

      Method

      The values of patients and caregivers with small cell (SCLC) and non-small cell lung cancer (NSCLC) inclusive of all stages were explored using a simple values elicitation exercise developed in partnership with diverse stakeholder advisory boards. Respondents were presented with five treatment characteristics, including progression free survival (PFS), short-term side effects (ST-SE), long-term side effects (LT-SE), and mode of administration. All characteristics and plausible outcomes were described. Values were elicited using a simple three-point Likert scale spanning not important, somewhat important, and very important, which were scored as 0, 5, and 10 respectively. Data came from a national survey completed in partnership with LUNGevity and other partners. Differences in values were explored between patients and caregivers, as well as across patients’ self-reported age with two sample t-tests.

      Result

      Among 793 eligible respondents, 556 were patients (70%) with 77% NSCLC, 11% SCLC, 12% unknown subtype and 233 were caregivers (30%). The average patient age was 58.4 years (y) (SD = 12.3), with 235 (42%) < 60y and 321 (58%) ≥60y. PFS was the most important attribute for respondents, but was undervalued by caregivers compared to patients (mean score (MS): 8.1 v 8.6, P = 0.014). Caregivers overvalued the importance of ST-SE (MS: 7.0 v 6.1, P < 0.001), LT-SE (MS: 8.4 v 7.6, P = 0.001), and mode of administration (MS: 6.9 v 6.1, P = 0.006). PFS was the most important attribute and valued similarly among younger vs. older patients (MS: 8.7 v 8.6, P = 0.76). However, ST-SE (MS: 6.4 v 5.8, P = 0.042) and LT-SE (MS: 8.0 v 7.4, P = 0.018) were more important among patients < 60y vs. ≥60y, respectively.

      Conclusion

      Among patients with lung cancer, progression free survival was highly valued regardless of patient age. Older patients value short term and long term side effects differently as compared to younger patients.

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