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Peter J Kneuertz



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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  |  Author(s): Peter J Kneuertz

      • 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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    OA13 - Ideal Approach to Lung Resection and Novel Perioperative Therapy (ID 146)

    • Event: WCLC 2019
    • Type: Oral Session
    • Track: Treatment of Early Stage/Localized Disease
    • Presentations: 1
    • Now Available
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      OA13.07 - Neoadjuvant Atezolizumab in Resectable NSCLC Patients: Immunophenotyping Results from the Interim Analysis of the Multicenter Trial LCMC3 (Now Available) (ID 1755)

      11:30 - 13:00  |  Author(s): Peter J Kneuertz

      • Abstract
      • Presentation
      • Slides

      Background

      The immune mechanisms dictating response and resistance to PD-(L)1 blockade are not well understood in early stage non-small cell lung cancer (NSCLC). Understanding these mechanisms will be key to improve outcomes and identify the next generation of predictive biomarkers of response to these therapies. Here, we present updated immunophenotyping at time of interim analysis of LCMC3, a multicenter trial of neoadjuvant atezolizumab in resectable NSCLC (NCT02927301).

      Method

      Patients received 2 cycles of atezolizumab before resection. Tumor, LN biopsies and PB were obtained pre-atezolizumab and at surgery. Paired PB, screening and surgical LN were analyzed using IMMUNOME flow cytometry. Plasma-based cytokine arrays were performed on a subset of patients. Immunophenotypic analyses were correlated with treatment effect, major pathologic response (MPR, primary endpoint) and preoperative treatment-related adverse events (preop-TRAE).

      Result

      We report on 55 patients with paired PB samples (analyzed within 72h after collection) and completed surgery. We observed preop-TRAE in 32/55 patients (18 grade 1, 13 grade 2, 1 grade 3). CD1c+ and CD141+ myeloid cells (MC) were lower at baseline in patients developing preop-TRAEs, while monocytic M-MDSCs were higher in those patients. Senescent T cells decreased in patients with preop-TRAE and increased in patients with non-preop-TRAE. After treatment, the absolute cell counts of late activated CD4+and CD8+T cells decreased in patients achieving MPR. LN IMMUNOME data, cytokine data and 12-month follow-up (DFS, OS) will be reported.

      table 1-page-001.jpeg

      Conclusion

      Preliminary immunophenotyping data from the interim analysis showed significantly lower baseline immunosuppressive cell subsets in patients with preop-TRAE and decreased late activated CD4+and CD8+T cells from PB in patients with MPR.These results, together with additional LN IMMUNOME and cytokine analyses, may improve our understanding of immunophenotypic features associated with outcome, and changes induced by neoadjuvant atezolizumab in early stage NSCLC patients.

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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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      P1.16-03 - Incidence and Risk Factors of Metachronous Non-Pulmonary Malignancies in Resected Lung Adenocarcinoma (ID 2906)

      09:45 - 18:00  |  Presenting Author(s): Peter J Kneuertz

      • Abstract

      Background

      Patients with non-small cell lung cancers have an increased risk of developing second primary lung cancers (SPLC). However, little is known about the development of non-pulmonary cancers (NPC) in patients with long-term survival after complete resection. We analyzed our experience with resected lung adenocarcinoma patients to assess the incidence and factors associated with metachronous malignancies.

      Method

      Surveillance records of 326 patients with primary lung adenocarcinoma who underwent complete staging followed by lobectomy between 2011-2017 at a single center were reviewed. Median follow-up time was 42 months. Metachronous NPCs were distinguished from distant metastases by pathologic correlation of histology and immunohistochemistry. The association of patient/tumor factors and mutation status with NPC was assessed.

      Result

      The cohort included 275 (84.4%) smokers, and 51 (15.6%) never smokers, with a median age of 65 years. The majority of patients were pathologic stage-I (72.4%) or stage-II (19.6%). KRAS (38%) and EGFR (17.8%) were the most commonly observed mutations. Metachronous NPC were detected in 30 patients (9.2%) and SPLC in 13 patients (4%), after a median interval of 14 months [IQR: 6.8–44] and 36 months [IQR: 27–60], respectively. Highest incidence of NPCs was seen in patients having EGFR tumor mutations (EGFR+ 17.2% vs. EGFR- 7.5%, p=0.020) and former smokers (former smokers 14.8% vs. never smokers 7.8% vs. active smokers 3.8%, p=0.005). Metachronous breast and GI cancers were frequently seen in patients with EGFR+ lung cancers (Table). Controlling for age, gender, and smoking status, EGFR mutation in resected lung adenocarcinoma was associated with 2.6 times greater odds (95% CI: 1.1-6.3, p=0.028) of metachronous NPC.

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      Conclusion

      Metachronous non-pulmonary malignancies can be frequently detected in patients during active surveillance of resected lung adenocarcinoma. Besides smoking as a known risk factor, patients with EGFR mutated tumors may be at particular risk. Germline mutations of EGFR positive lung adenocarcinoma patients should be further explored.