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Virginia Calvo De Juan

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    MA19 - Looking at PROs in Greater Detail - What Patients Actually Want and Expect (ID 147)

    • Event: WCLC 2019
    • Type: Mini Oral Session
    • Track: Treatment in the Real World - Support, Survivorship, Systems Research
    • Presentations: 12
    • Now Available
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      MA19.01 - Empirical Identification of Distress Clusters in Lung Cancer Patients (Now Available) (ID 2085)

      11:30 - 13:00  |  Presenting Author(s): Mary Ellen Hand  |  Author(s): Teresa Lillis, Mary M. Pasquinelli, Zane Deliu, Christine Weldon, Julia Trosman, Lawrence Eric Feldman, Michael Huber

      • Abstract
      • Presentation
      • Slides

      Background

      Screening for distress from the time of diagnosis is emerging as standard cancer care. Although there is heterogeneity in patients’ experience of distress, identification of subgroups of patients with unique distress profiles may inform interventions for distressed patients. Accordingly, we aimed to identify unique subgroups of patients based on their distress screening responses from a large sample of newly diagnosed lung cancer patients across two urban academic medical centers in Chicago, IL.

      Method

      Lung cancer patients (N=596) were screened for distress at their diagnostic visit between (2/22/16 – 8/14/18) with the Coleman Foundation “Patient Screening Questions for Supportive Care” tool; a 34-item screener that identifies patient needs across psychological, physical, family/caregiver, and treatment and care concerns. A Two-Step cluster analysis was conducted to identify natural clusters of patients based on similar responses to distress screening items.

      Result

      Cluster analysis results revealed a two-cluster outcome: “High Distress” (N=332) and “Low Distress” (N=264). The items that best distinguished High Distress patients from Low Distress patients were concerns about cancer stage/diagnosis, concerns about prognosis/long-term outcome, concerns about treatment options, and having higher average number of total concerns. Cancer stage at screening was not predictive of cluster membership. Demographic characteristics, descriptive statistics, and group difference tests for survey items by cluster and for the total sample are presented in Table 1.

      Conclusion

      More than half of lung cancer patients were grouped as experiencing high distress on screening. While cancer stage was not predictive of high distress grouping, concerns about stage, treatment, and prognosis were most predictive of high distress cluster membership. An intervention to improve communication between providers and patients about these concerns may reduce distress.

      Table 1

      High Distress (N=332/55.7%)

      Low Distress (N=264/ 44.3%)

      Total Sample (N=596)

      Significance

      Tests

      Demographics

      Age

      M=65.75 (SD=9.95)

      M=66.25 (SD=9.71)

      M=65.97 (SD=9.84)

      F=.39 (p>.05)

      Female

      N=171 (51.5%)

      N=144 (54.5%)

      N=315 (52.9%)

      χ2=.55 (p>.05)

      Race/Ethnicity

      χ2=30.83 (p<.01)

      White

      N=124 (37.3%)

      N=154 (58.3%)

      N=278 (46.6%)

      p<.01

      African American

      N=161 (48.5%)

      N=72 (27.3%)

      N=233 (39.1%)

      p<.01

      Other

      N=47 (14.2%)

      N=38 (14.4%)

      N=85 (14.3%)

      p>.05

      Stage IV

      N=160 (48.2%)

      N=118 (44.7%)

      N=278 (46.6%)

      χ2=.72 (p>.05)

      Physical & Psychological Health

      Psychological Distress (PhQ-4)

      M=3.55 (SD=3.63)

      M=1.56 (SD=2.14)

      M=2.67 (SD=3.29)

      F=58.86 (p<.01)

      Pain

      M=5.13 (SD=4.76)

      M=4.76 (SD=3.45)

      M=4.99 (SD=3.66)

      F=1.04 (p>.05)

      Fatigue

      M=8.56 (SD=5.31)

      M=7.63 (SD=4.74)

      M=8.15 (SD=5.01)

      F=4.34 (p<.05)

      Physical Activity

      M=12.63 (SD=7.74)

      M=16.70 (SD=8.52)

      M=14.42 (SD=8.33)

      F=35.55 (p<.01)

      Concerns

      Practical Concerns

      Childcare

      N=8 (2.5%)

      N=2 (.8%)

      N=10 (1.7%)

      χ2=2.43 (p>.05)

      Food & Housing

      N=58 (17.8%)

      N=13 (5.0%)

      N=71 (12.2%)

      χ2=22.06 (p<.01)

      Transportation

      N=72 (22.0%)

      N=14 (5.4%)

      N=86 (14.7%)

      χ2=31.29 (p<.01)

      Work/School

      N=19 (5.9%)

      N=8 (3.1%)

      N=27 (4.7%)

      χ2=2.49 (p>.05)

      Paying for Medication

      N=79 (24.1%)

      N=35 (13.6%)

      N=114 (19.5%)

      χ2=10.19 (p<.01)

      Family/Caregiver Concerns

      Children

      N=46 (18.7%)

      N=18 (8.0%)

      N=64 (13.6%)

      χ2=11.58 (p<.01)

      Partner

      N=51 (20.9%)

      N=24 (10.6%)

      N=75 (15.9%)

      χ2=9.37 (p<.01)

      Caregiver

      N=23 (9.5%)

      N=8 (3.5%)

      N=31 (6.6%)

      χ2=6.91 (p<.01)

      Ability to have children

      N=8 (3.3%)

      N=2 (.9%)

      N=10 (2.1%)

      χ2=3.35 (p>.05)

      Family

      N=62 (25.6%)

      N=24 (10.5%)

      N=86 (N=18.3%)

      χ2=18.07 (p<.01)

      Treatment & Care Concerns

      Cancer Diagnosis & Stage

      N=303 (93.5%)

      N=8 (3.3%)

      N=311 (55.1%)

      χ2=453.34(p<.01)

      Prognosis & Long-term Outcome

      N=312 (95.7%)

      N=37 (15.4%)

      N=349 (61.6%)

      χ2=378.04 (p<.01)

      Treatment Options

      N=246 (75.7%)

      N=11 (4.6%)

      N=257 (45.4%)

      χ2=282.43 (p<.01)

      Communicating treatment wishes

      N=165 (52.1%)

      N=7 (2.9%)

      N=172 (30.8%)

      χ2=155.09 (p<.01)

      Physical Health Concerns

      Breathing

      N=160 (64.3%)

      N=78 (35.5%)

      N=238 (50.7%)

      χ2=38.77 (p<.01)

      Constipation

      N=86 (43.4%)

      N=41 (20.0%)

      N=127 (31.5%)

      χ2=25.63 (p<.01)

      Diarrhea

      N=47 (27.0%)

      N=17 (8.5%)

      N=64 (17.1%)

      χ2=22.68 (p<.01)

      Fevers

      N=22 (13.3%)

      N=4 (2.1%)

      N=26 (7.2%)

      χ2=16.72 (p<.01)

      Nausea/Vomiting

      N=66 (33.7%)

      N=16 (8.1%)

      N=82 (20.8%)

      χ2=39.15 (p<.01)

      Sleep

      N=137 (59.3%)

      N=58 (27.4%)

      N=195 (44.0%)

      χ2=45.79 (p<.01)

      Urination

      N=46 (26.1%)

      N=12 (6.0%)

      N=58 (15.5%)

      χ2=28.79 (p<.01)

      Chewing/Swallowing

      N=49 (27.1%)

      N=18 (9.1%)

      N=67 (17.7%)

      χ2=21.01 (p<.01)

      Mouth Sores

      N=24 (14.5%)

      N=13 (6.6%)

      N=37 (10.2%)

      χ2=6.18 (p<.05)

      Dry Mouth

      N=116 (53.2%)

      N=51 (24.5%)

      N=167 (39.2%)

      χ2=36.76 (p<.01)

      Swollen Arms or Legs

      N=76 (39.6%)

      N=21 (10.5%)

      N=97 (24.7%)

      χ2=44.49 (p<.01)

      Feeling full quickly or swollen abdomen

      N=57 (32.0%)

      N=18 (9.2%)

      N=75 (20.1%)

      χ2=30.35 (p<.01)

      Sexual Intimacy or Functioning

      N=54 (28.3%)

      N=17 (8.4%)

      N=71 (18.0%)

      χ2=23.37 (p<.01)

      Dry/Itchy or Blistered Skin

      N=94 (46.3%)

      N=43 (20.7%)

      N=137 (33.3%)

      χ2=30.37 (p<.01)

      Tingling in hands/feet

      N=84 (43.5%)

      N=33 (16.8%)

      N=117 (30.1%)

      χ2=32.93 (p<.01)

      Appearance

      N=31 (19.35)

      N=14 (7.2%)

      N=45 (12.7%)

      χ2=11.52 (p<.01)

      Use of Alcohol or Drugs

      N=3 (2.0%)

      N=1 (.5%)

      N=4 (1.2%)

      χ2=1.59 (p>.05)

      Total # of Concerns

      M=7.84 (SD=3.71)

      M=2.53 (SD=2.47)

      M=5.49(SD=4.16)

      F=400.82 (p<.01)

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      MA19.02 - Psychological Distress in Never, Ex, Current, and Passive Smokers Diagnosed with Lung Cancer - Analyses from the EnRICH Program (Now Available) (ID 461)

      11:30 - 13:00  |  Presenting Author(s): Bea Brown  |  Author(s): John Simes, Michael Boyer, Phillip Hogg, Anthony Joshua, Jane Young, Christopher Brown

      • Abstract
      • Presentation
      • Slides

      Background

      Lung cancer is associated with greater psychological distress than any other cancer. In Australia, the prevalence of anxiety and depression in those with lung cancer is nearly 30% higher than the average of other major cancers. More than 50% of patients experience distress, anxiety and/or depression, resulting in diminished quality of life (QoL), and a fourfold increase in likelihood of suicide than the general population.

      Lung cancer stigma, arising from presumption about tobacco exposure and associated smoking stigma, contributes to high levels of distress. A national survey found that more than a third (35%) of Australians believe those living with lung cancer “have only themselves to blame” and almost 40% indicated, before expressing concern, the first question they would ask someone diagnosed with lung cancer is whether they smoked. This stigma makes lung cancer patients reluctant to seek psychosocial support and reduces their sense of entitlement to care and empathy. However, approximately one fifth (21%) are life-long never-smokers.

      This study aimed to describe differences in levels of psychological distress in never-and ever-smokers enrolled in the Sydney Catalyst EnRICH Program, a prospective clinical cohort of patients with lung cancer in New South Wales, Australia.

      Method

      Measures: EnRICH incorporates patient-reported outcome measures (PROMs) that assess dimensions of anxiety, depression, emotional function, and psychological distress, namely, the: (i) EORTC QLQ-C30; and (ii) NCCN Distress Thermometer.

      Sample: All patients with newly diagnosed lung cancer presenting to study hospitals are eligible for the EnRICH cohort. Consenting patients who completed PROMs comprise the sample for the current analyses.

      Statistical Methods: Subscales of the QLQ-C30 reflecting overall QoL and emotional function, and scores on the NCCN Distress Thermometer, were compared between patient groups by smoking status. Groups were combined into never-smokers (never, passive) and ever-smokers (ex, current) for analyses. Mean differences and 95% confidence intervals were computed.

      Result

      Among 205 patients who completed PROMs (69% of consenting patients), there were 52 never-smokers, 5 passive-smokers, 161 ex-smokers and 52 current-smokers at the time of diagnosis. Emotional function was worse in never-smokers (ever=75.3, never=63.2, difference=12.1 points 95%CI 2.4-21.7). There were no differences in other subscales. Although numbers are small, passive-smokers had the lowest mean scores for emotional-, role-, and social-functioning (Figure 1). Distress thermometer scores were 1.2 points worse in never-smokers [95%CI (0.56-1.8)].

      everneverscales.png

      Conclusion

      Never-smokers had worse emotional function and higher distress than other lung cancer patients. If confirmed in larger studies, additional supportive care services may improve outcomes for these patients.

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      MA19.03 - Differences in Symptom Burden Between Responsive and Progressive Disease in Advanced Non-Small Cell Lung Cancer (aNSCLC) (Now Available) (ID 845)

      11:30 - 13:00  |  Presenting Author(s): George R Simon  |  Author(s): Loretta Ann Williams, Qiuling Shi, Belqis El Ferjani, Meita S Hirschmann, Darcy Ponce, Seyedeh S Dibaj, Sheenu Chandwani, Emily Roarty, Waree Rinsurongkawong, Jeff Lewis, Thomas Burke, Charles S Cleeland, Jack Lee, Jack Roth, Stephen Swisher, John Victor Heymach, Jianjun Zhang

      • Abstract
      • Presentation
      • Slides

      Background

      We have established a real-world Advanced Non-Small Cell Lung Holistic Registry (ANCHoR) to assess how immunotherapy impacts treatment choice, clinical outcomes, and patient-reported outcomes (PROs) of aNSCLC. Our aim in this analysis was to assess the ability of the MDASI-LC to differentiate between patients who are responding or who are progressing during treatment.

      Method

      Between May 2017 and December 2018, patients with aNSCLC at a single institution were enrolled in ANCHoR and completed the MDASI-LC prior to therapy (PTT) and at routine clinic visits. The MDASI-LC consists of 16 symptom severity and 6 interference items rated on 0-10 scales (0 = no symptom or interference, 10 = worst imaginable symptom or complete interference). MDASI-LC scores from PTT to first recorded response determination (FRD) were compared by response group using linear mixed modeling (LMM).

      Result

      One hundred one patients completed the MDASI-LC PTT and at FRD. Mean patient age was 63.8 years (standard deviation = 10.29) and 55% were males. Fifty percent of patients received chemotherapy (CTX), 22% immunotherapy (IM), 19% CTX+IM or angiogenesis inhibitor, and 9% targeted therapy. Median time from PTT to FRD was 105 days (lower quartile = 63, upper quartile = 224). Forty-six percent of patients had a complete or partial response (RECIST criteria CR, PR), 14% had stable disease (RECIST SD), and 41% progressed (RECIST PD). LMM showed progressing patients had significantly more fatigue (estimated effect [est] =1.39; p = 0.031), sleep disturbance (est=1.37; p = 0.046), and drowsiness (est=1.33; p = 0.037) and reported significantly more interference with work (est=1.67; p = 0.016) over time than responding patients.

      Conclusion

      The MDASI-LC differentiated the symptom burden of patients with responding disease from that of patients with progressive disease. Patients with progressive disease had more fatigue, disturbed sleep, drowsiness, and greater interference with work than those with responsive disease. Further research is needed to determine if the MDASI-LC can predict response to therapy in patients and may be useful in delineating treatment benefit.

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      MA19.04 - Discussant - MA19.01, MA19.02, MA19.03 (Now Available) (ID 3796)

      11:30 - 13:00  |  Presenting Author(s): Gilberto Castro

      • Abstract
      • Presentation
      • Slides

      Abstract not provided

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      MA19.05 - Improving Lung Cancer Outcomes and Quality in the US Community Setting with the Creation of Lung Cancer Centers of Excellence Program (Now Available) (ID 1939)

      11:30 - 13:00  |  Presenting Author(s): Amy Moore  |  Author(s): Luis Raez, Ray Osarogiagbon, Leah Fine

      • Abstract
      • Presentation
      • Slides

      Background

      The Addario Lung Cancer Foundation community hospital Centers of Excellence (COE) Program encourages community cancer centers in the US to implement ‘best practices’ across the lung cancer care continuum, including provision of coordinated, multidisciplinary care. By comparing performance metrics within and outside the network of COEs, the program seeks to ensure that lung cancer patients (pts) receive the highest quality of care in their local area whilst also enabling COE hospitals to gain insights that facilitate the rapid implementation of quality improvement cycles.

      Method

      The Impact Study was launched to conduct a comprehensive comparative analysis of COE member and non-member institutions across numerous quantitative and qualitative metrics from within the lung cancer care continuum. The 2018 analysis included 17 COE sites and 19 non-COE community hospitals representing approximately 5,000 pts in each cohort. The COE Impact study captured pts’ demographic and clinical information as well as performance metrics from early stage screening through late stage diagnosis and all aspects of pts’ care.

      Result

      Variable

      COE

      Non-COE

      P value

      # Cancer centers/hospitals

      17

      19

      Answers collected by nurse navigator

      41%

      100%

      <0.001

      Average # of hospital beds

      565

      342

      0.104

      Average # of lung cancer pts/institution

      497

      470

      0.968

      Lung cancer screening program

      94%

      42%

      0.001

      Endoscopic Bronchoscopy Ultrasound (EBUS)

      23%

      16%

      0.323

      Screening of pts for clinical trials

      81%

      35%

      <0.001

      Race: Caucasians

      81%

      37%

      <0.001

      Pathologist in tumor boards

      100%

      67%

      0.012

      ER visits the first 4 months of therapy

      14%

      32%

      0.022

      Molecular testing of pts with metastatic disease

      81%

      48%

      0.001

      Next generation sequencing

      58%

      22%

      0.009

      Conclusion

      Improved structure and processes of care delivery at COE hospitals may translate into improved quality of care, outcomes, and patient experiences. The Lung Cancer COE program, now including 38 community cancer centers encompassing 12,000 lung cancer patients, plans to conduct this study annually with prospective, longitudinal data collection for future trend analyses as a means of facilitating continuous quality improvement in community-level lung cancer care.

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      MA19.06 - Successful Development of Realtime Automatically Updated Data Warehouse in Health Care (ROOT-S) (Now Available) (ID 584)

      11:30 - 13:00  |  Presenting Author(s): Hyun Ae Jung  |  Author(s): Sunyoung Hong, JuYoun Park, MI RA Park, Jong-Mu Sun, Se-Hoon Lee, Jin Seok Ahn, Myung-Ju Ahn, Keunchil Park

      • Abstract
      • Presentation
      • Slides

      Background

      Clinical information is often not recorded in an organized way, and converting it to a structured format can be a time-consuming task that may not successfully capture all facets of the information. Clinical Data Warehouse is a real time database that consolidates data from a variety of clinical sources to present a unified view. However, the clinical data extracted from the CDW have not only structured data (SD) but also natural language (NP) generated during clinical practice, and there is a limitation that it is difficult to apply to clinical trials because it is not structured and formatted to find key-point contents. This study aims at developing a systematic and comprehensive cohort through an automatic real-time update system called CDW.

      Method

      The aim of this study was to evaluate clinical data of non-small cell lung cancer, small cell lung cancer, head and neck cancer, thymic cancer, and mesothelioma. In this study, we developed a unique algorithm that is optimized for each disease category using comprehensive natural language processing (NLP) systems and structured information from unstructured free text and structured data capture (SDC). We developed an algorithm using clinical information of patients diagnosed and treated during the past 10 years and designated validation sets of patients diagnosed and treated in 2018 for validation that these algorithms work automatically.

      Result

      We collected clinical data of 23,735 NSCLC patients, 2,077 SCLC patients, 5,032 head and neck cancer patients, 3,948 esophageal cancer patients, 747 thymic cancer patients and 138 mesothelioma patients diagnosed at Samsung Medical Center. We could demonstrate using the validation set that the program accurately extracts the data needed for the cohort of each cancer. The program is updated automatically every 24 hours, the source of each data is indicated separately, and the data that need to be integrated is transformed and systematically organized. The biggest advantage is that the scattered information is systematically integrated and automatically buildup to match the patient's cohort, so you can capture most updated survival or test results or treatment outcomes almost in real time. Data on the development of this program will be presented.

      Conclusion

      This study is the first study that successfully developed and validated real-time updated cohort using CDW. This study suggests a blueprint for constructing a big data -based cohort for clinical research and is expected to be a landmark trial. The detailed analysis of each cancer through the development of the program will be presented.

      wclc.png

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      MA19.07 - Testing an Optimal Care Coordination Model (OCCM) for Lung Cancer in a Multi-Site Study (Now Available) (ID 2659)

      11:30 - 13:00  |  Presenting Author(s): Matthew P Smeltzer  |  Author(s): Thomas Asfeldt, Nicholas Faris, Amanda Kramar, Christine Amorosi, Vikki G Nolan, Meredith Ray, Monique Dawkins, Mary Catherine Nalan, Walter Stevens, Lorna Lucas, Randall A Oyer, Christopher S Lathan, Ray Osarogiagbon

      • Abstract
      • Presentation
      • Slides

      Background

      Medicaid-insured lung cancer patients have worse outcomes than others. To address barriers to optimal care in the US Medicaid population, the Association of Community Cancer Centers (ACCC) created and tested the OCCM.

      Method

      The OCCM included 13 assessment areas: Patient Access to Care, Prospective Multidisciplinary Case Planning, Financial/Transportation/Housing, Care Coordination, Electronic Health Records, Survivorship Care, Supportive Care, Tobacco Cessation, and Clinical Trials. Each area had 5 defined levels of quality care delivery. With support from the Bristol-Myers Squibb Foundation, we pilot tested the model in 7 US cancer centers. Sites selected 1-2 assessment areas to evaluate using OCCM, developing relevant data benchmarks. Sites enrolled patients on Medicaid and Non-Medicaid controls. The ACCC team worked with each site to develop quality improvement projects with bi-weekly conference calls and 2 on-site visits. Data were collected and analyzed at a centralized data coordinating center. Statistical analyses were performed with Kruskal Wallis and chi-squared tests.

      Result

      Seven sites spanning 3,081 miles evaluated 10 of the 13 OCCM areas. Total enrollment was 927 patients (257 Medicaid/ 670 Non-Medicaid). The Medicaid population had an average age of 62 years, ranging from 58-68 across sites. The clinical stage distribution was 40% stage I/II and 60% stage III/IV. Medicaid patients were 47% adenocarcinoma histology, 29% squamous cell, 14% small cell, and 10% other. Sites differed by patient age (p=0.0041), race (p<0.0001), and smoking status (p=0.028).

      Three sites evaluated models for prospective multidisciplinary case planning for Medicaid patients including: bi-weekly tumor board (BTB), virtual tumor board (VTB), and multidisciplinary team huddle (MTH). VTB and MTH allowed for presentation of higher percentages of eligible patients (BTB: 23%, VTB: 100%, MTH: 100%, p<0.0001). BTB and MTH discussed all cases prospectively, while VTB achieved 80%. Median days from diagnosis to presentation were 18 (BTB), 14 (VTB), and 9 (MTH, p=0.14).

      Two sites evaluated smoking cessation programs. One, using trained cessation counselors, had 62% (18/29) active smokers, of whom 56% (10/18) expressed readiness to quit. Another site, using the freedom from smoking initiative, had 50% (11/22) active smokers and 55% (6/11) readiness to quit. 83% of those who started the cessation program quit smoking.

      Patient access to care was evaluated with timeliness of care metrics at two sites: one found 13 days (median) from lesion discovery to diagnosis and 21 days from diagnosis to treatment in Medicaid patients, which did not differ from Non-Medicaid controls (p=0.96 and 0.38). 94% met the site goal of treatment initiation within 45 days. Another site found 16 days (median) from discovery to diagnosis and 27 days from diagnosis to treatment (did not differ from Non-Medicaid controls, p=0.68 and 0.83).

      Conclusion

      Sites successfully used the OCCM to identify areas to improve and developed meaningful data benchmarks. The OCCM is a valuable tool for cancer centers to identify specific areas to target to improve lung cancer care delivery.

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      MA19.08 - Discussant - MA19.05, MA19.06, MA19.07 (Now Available) (ID 3797)

      11:30 - 13:00  |  Presenting Author(s): Riyaz Shah

      • Abstract
      • Presentation
      • Slides

      Abstract not provided

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      MA19.09 - Assessing Clinical Frailty in Advanced Lung Cancer Patients - An Opportunity to Improve Patient Outcomes? (Now Available) (ID 2363)

      11:30 - 13:00  |  Presenting Author(s): Fabio Gomes  |  Author(s): Katie Baker, Jennifer Woods, Jonathan Bruce, Marie Eaton, Phill Higham, Laura Cove-Smith, Alex Garbett, Anthea Cree, Cassandra Ng, Fiona Blackhall, Neil Bayman

      • Abstract
      • Presentation
      • Slides

      Background

      The median age of non-small cell lung cancer (NSCLC) diagnosis in England is 73 years. At that age, 40% of the general population has some degree of clinical frailty which may impact survival, quality of life, anti-cancer treatment tolerability and access to clinical trials. However, clinical frailty is often not addressed or managed at the time of anti-cancer treatments. This project was designed to integrate frailty assessments and build frailty pathways within an advanced cancer care setting in order to better support patients and improve outcomes.

      Method

      This quality improvement project that used Plan-Do-Study-Act (PDSA) methodology. Phase one of the project focused on establishing a multidisciplinary team to integrate a frailty screening tool, the Rockwood Clinical Frailty Scale (CFS), into standard clinical practice. The primary aim was to implement and screen ≥80% of all new lung cancer patients at a high-volume tertiary cancer centre. The secondary aim was to explore the correlation of CFS with age, performance status (PS), treatment selection and systemic anti-cancer treatment (SACT) tolerability. Specialised training was provided to the clinical team and the CFS was integrated from 26/11/2018 on an electronic form routinely completed by clinicians. A digital dashboard was set-up to monitor real-time data and the frail group was defined as CFS score >3. Data cut-off for this analysis was 29-03-2019.

      Result

      335 lung cancer patients were screened using CSF by a team of 20 clinicians with a compliance rate of 89%. There was a strong correlation between PS and CFS (r= 0.77, p<0.01). The distribution of both CFS and PS correlated with ageing (r= 0.2 and r= 0.17, respectively; p<0.01). Patients ≥70 years were more likely to be frail (56% vs 40%; OR 1.4, 95%CI 1.2-1.7; p<0.01). Frailty reduced the likelihood of receiving any anti-cancer treatment by 20%. Amongst those who started SACT, patients classed as frail were less likely to go beyond the first cycle of treatment (64% vs 91%; OR 0.7, 95%CI 0.5-0.9; p<0.01).

      Conclusion

      CFS screening is feasible within a busy clinical practice when incorporated as a digital tool. CFS helps to identify patients who may potentially benefit from specialised frailty assessment and management. This could ultimately be used to better inform on treatment selection, and support requirements during treatment, to improve outcomes for patients in the future.

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      MA19.10 - Estimation of Quality-Adjusted Life Expectancy for Stage and Systemic Treatment in Non-Small Cell Lung Cancer in Rajavithi Hospital, Thailand (Now Available) (ID 585)

      11:30 - 13:00  |  Presenting Author(s): Sunatee Sa-nguansai  |  Author(s): Oranuch Kamnerdtong, Kunlatida Maneenil

      • Abstract
      • Presentation
      • Slides

      Background

      Owing to the high mortality and rapidly growing costs related to lung cancer, it is worth examining the health benefits of treatment in this cancer. This study attempts to quantify the real-life practice quality-adjusted life expectancy (QALE) of non-small cell lung cancer (NSCLC) patients with different stages and systemic treatments.

      Method

      This cross-sectional study was conducted by reviewing and collected quality of life (QoL) data from 256 eligible all stages NSCLC patients treated at Rajavithi hospital from May 1st to October 31st, 2018. The iSQoL statistical package was used to evaluate QALE compared with the reference Thai population in different stage of disease. For advanced stage, QALE was compared among treatment groups (chemotherapy and Epidermal growth factor receptor tyrosine kinase inhibitors; EGFR TKIs)

      Result

      The QALE for patients with early and advanced stage NSCLC were 4.49 ± 0.43 and 1.03 ± 0.08 QALY, with the corresponding loss-of-QALE were 14.02 ± 0.44 and 20.13 ± 0.09 QALY, respectively. The difference of QALE between early and advanced stage was 3.46 QALY (p<0.001).

      Based on systemic treatment in advanced stage, The QALE for patients who received chemotherapy and TKIs were 1.05 ± 0.08 and 2.19 ±0.28 QALY, with the corresponding loss-of-QALE were 20.48 ± 0.09 and 19.12 ± 0.29 QALY, respectively. The difference of QALE between treatment with chemotherapy and TKIs was 1.17 QALY (Figure, p=0.001).

      ca-lung_qale-results.dpi_300.jpg

      Conclusion

      The utility gained from treatment with TKIs in advanced NSCLC is substantial. Early stage had better QALE than advanced stage NSCLC patients.Future study will assess the cost-effectiveness of targeted therapy in Thailand.

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      MA19.11 - Population Based Analysis of End of Life Treatment Patterns in Thoracic Malignancies (Now Available) (ID 1154)

      11:30 - 13:00  |  Presenting Author(s): Graham Pitson  |  Author(s): Leigh Matheson, Peter Eastman, Margaret Rogers

      • Abstract
      • Presentation
      • Slides

      Background

      Active cancer treatment within the last month of life is unlikely to meaningfully benefit patients and ASCO guidelines recommend chemotherapy treatment rates be kept as low as possible. Patients with thoracic malignancies often have rapidly progressive disease and significant symptom burden and there is little population based data on patterns of care near end of life.

      Method

      The Evaluation of Cancer Outcomes Registry records clinical information on all newly diagnosed cancer patients within a region of Victoria, Australia. Core diagnostic, demographic, treatment and outcome details were extracted for all patients diagnosed from 2009-2015 with death data through to end of 2016. Patients with thoracic malignancies were further analysed for treatment patterns at end of life. Details of palliative radiotherapy (pRT) and active systemic treatment (AST – intravenous chemotherapy, targeted therapy and/or immunotherapy) were recorded for all patients. Details on oral chemotherapy and stereotactic radiotherapy were not recorded.

      Result

      The total cohort during the study period comprised 12760 patients. Of these, 1328 patients were recorded with a thoracic malignancy (TM) (non small cell lung cancer 82%, small cell lung cancer 10%, mesothelioma 7%) and 1118 of these died. At total of 39% (518) and 41% (538) of the 1328 TM patients received AST and pRT respectively at some point. Of these patients 15% (77/518) received AST and 23% (121/538) pRT within 30 days of death, compared with 7.0% (242/3436) (p<0.01) and 19% (178/965) (p=0.06) respectively for the total cohort excluding TM patients. Patients receiving AST within 30 days of death had a similar median age (66.7 vs. 67.8 years, p=NS) but shorter median survival from diagnosis (146 v. 281 days, p<0.01) than patients receiving final AST within 1-6 months. The frequency of some change in AST agents within the prior month was highest in the last month of life. The most common AST agents used in the final month of life were pemetrexed, etoposide and gemcitabine and most patients were treated with single agents. More pRT treatments were started in the last 30 days of life than in any other month near end of life. Patients receiving pRT in the last month of life also had a shorter median survival from diagnosis (113 v. 215 days, p<0.01) and the sites most commonly treated with pRT in the last month of life were chest/lung, spine and whole brain.

      Conclusion

      Patients with thoracic malignancies have higher rates of AST treatment within the last 30 days of life than other patients with cancer in the same geographic region. Those treated within 30 days of death also have shorter median overall survival and higher frequencies of changing AST agents or starting pRT, possibly suggesting aggressive, symptomatic and poorly responding disease.

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      MA19.12 - Discussant - MA19.09, MA19.10, MA19.11 (Now Available) (ID 3798)

      11:30 - 13:00  |  Presenting Author(s): Flavia Amaral Duarte

      • Abstract
      • Presentation
      • Slides

      Abstract not provided

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    EP1.14 - Targeted Therapy (ID 204)

    • Event: WCLC 2019
    • Type: E-Poster Viewing in the Exhibit Hall
    • Track: Targeted Therapy
    • Presentations: 1
    • Now Available
    • Moderators:
    • Coordinates: 9/08/2019, 08:00 - 18:00, Exhibit Hall
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      EP1.14-11 - Real-Life Data of Osimertinib in Pretreated Patients with Advanced Non-Small Cell Lung Cancer Harboring EGFR T790M Mutation (Now Available) (ID 697)

      08:00 - 18:00  |  Author(s): Virginia Calvo De Juan

      • Abstract
      • Slides

      Background

      Several clinical trials have demonstrated the efficacy and safety of osimertinib in pretreated patients with advanced non-small cell lung cancer (NSCLC) harbouring EGFR T790M resistance mutation. However, clinical real-world data on patient characteristics and efficacy of the drug is limited.

      Method

      We reviewed the medical records of T790M mutation-positive lung cancer patients treated with osimertinib between May 2016 and February 2019 in our institution. We calculated progression-free survival (PFS) and overall survival (OS) from osimertinib initiation.

      Result

      The study included 22 patients with a mean age of 59.6 years. 59% (13/22) were female and 100% had adenocarcinoma histology. We had an unusual high frequency of tobacco use in our series as 40.9% (9/22) of our patients were smokers (3/22) o former-smokers (6/22), with a mean of 35 pack-year (sd, 28.5). 45.5% (10/22) had exon 21 L858R mutations, whereas 54.5% (12/22) harboured exon 19 deletions (19del). One patient simultaneously had an exón 19 deletion and exon 20 S768I mutation. Osimertinib was used in second, third and fourth line in 50% (11/22), 27% (6/22) and 23% (5/22) of patients, respectively.

      All patients had liquid biopsy blood samples obtained prior to the start of the treatment, and T790M mutation could be detected in 86.4% (19/22), with a mean mutant-allele fraction of 4,11% (standard deviation 8.65, min 0, max 37.7). T790M was detected only in tissue in 2 patients and exclusively in cerebrospinal fluid in 1 of them.

      At the time of starting osimertinib, patients had a median of 3 metastatic sites (min 1, max 6), being the most frequent locations the lung (73%), the bone (64%), the pleura (59%), the central nervous system (23%) and the peritoneum (14%).

      Median follow-up duration was 10 months (IQR, 4.7-22.67). To the date, 63% (14/22) have experienced progression of the disease. Median PFS in our series was 8.9 (95% CI, 4.9-17.9 ) months, whereas median OS since osimertinib initiation was 18.2 (95% CI, 8.8-NE) months.

      Regarding to toxicity, 12 patients referred adverse events, 82.6% of which were mild (G1), being the most frequent toxicities neutropenia (9%), diarrhoea (9%), hypertransaminasemia (9%) and asthenia (9%). Only 1 G3 event was recorded (asymptomatic hyperamilasemia).

      Conclusion

      The efficacy of osimertinib in real-world practice was similar the observed in clinical trials, with a favourable adverse effect profile. Liquid biopsy is an effective non-invasive method to assess the presence of the T790M resistance mutation prior to the start of osimertinib.

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    MA16 - Prioritizing Use of Technology to Improve Survival of Lung Cancer Subgroups and Outcomes with Chemotherapy and Surgery (ID 142)

    • Event: WCLC 2019
    • Type: Mini Oral Session
    • Track: Treatment in the Real World - Support, Survivorship, Systems Research
    • Presentations: 1
    • Now Available
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      MA16.03 - Big Data Analysis for Personalized Medicine in Lung Cancer Patients (Now Available) (ID 2532)

      15:45 - 17:15  |  Author(s): Virginia Calvo De Juan

      • Abstract
      • Presentation
      • Slides

      Background

      The use of Big Data in healthcare is in its early days, and most of the potential for value creation remains unclaimed.

      Electronic Health Records (EHR) contain a large amount of information about the patient's condition, which can potentially revolutionize the clinical practice, such information is seldom considered due to the complexity of its extraction and analysis. We report on a first integration of an NLP framework for the analysis of clinical records of lung cancer in Puerta de Hierro University Hospital (HUPHM).

      Method

      A cohort of 1000 patients diagnosed of non-small cell lung cancer (NSCLC) from 2009 to 2018 at HUPHM were included in this observational study. Unstructured clinical data were obtained from the EHR. The semantic indexing and the information analysis was performed by the Politecnica University of Madrid, using Big Data and machine learning techniques. Clinical notes were converted into usable data, and combined with genomic data, images and bibliography, such as PubMed or Drugbank.

      Result

      A total of 251.730 documents were analyzed (240.851 notes and 10.879 reports). These heterogeneous sources of information were analyzed and integrated in an interactive user interface (Figure 1). As a result, all this large amounts of data turns into actionable and exploitable information for clinicians and authorities for planning public health policies and also create new clinical trials.

      The interactive platform will allow the clinician obtain immediate and personalized information of each patient and will elaborate predictive models for long survivors, identify risk patients, reduce overtreatments, etc.

      Conclusion

      By using Big Data we will be able to exploit large amounts of clinical information and combine them with multiple databases developing interactive user interface, increasing lung cancer knowledge and directing medicine towards a more personalized one.

      This work was supported by the EU H2020 programme, under grant agreement Nº 727658 ( Project iASiS).

      captura de pantalla 2019-04-10 a las 21.07.09.png

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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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      OA13.05 - NADIM Study: Updated Clinical Research and Outcomes (Now Available) (ID 1670)

      11:30 - 13:00  |  Author(s): Virginia Calvo De Juan

      • Abstract
      • Presentation
      • Slides

      Background

      Patients with stage IIIA (N2 or T4N0) are potentially curable but median overall survival is only around 15 months

      Method

      A Phase II, single-arm, open-label multicenter study of resectable stage IIIA N2-NSCLC in adult patients with CT plus IO as neoadjuvant treatment: 3 cycles of nivolumab (NV) 360 mg IV Q3W + paclitaxel 200 mg/m2 + carboplatin AUC 6 IV Q3W followed by adjuvant NV treatment for 1 year. After completing neoadjuvant therapy, all patients underwent tumor assessment prior to surgery. Surgery was performed during the 3rd or 4th week after day 21 of the 3rd neoadjuvant treatment cycle. The study aimed to recruit 46 patients. The primary endpoint was Progression-Free Survival (PFS) at 24 months. Efficacy was explored using objective pathologic response criteria. Here we present the final data on all study patients that underwent surgical assessment.

      Result

      At the time of submission, the 46 patients had been included. None of the patients were withdrawn from the study preoperatively due to progression or toxicity. 41 patients had undergone surgery and all tumors were deemed resectable with R0 resection in all cases. Intention to treat analysis shows 35 patients (85%; 95% CI, 71; 94%) achieved major pathologic response (MPR) of which 25 (71%; 95% CI, 54; 85%) were complete pathologic responses (CPR). Downstaging was seen in 38 (93%; 95% CI, 80; 98%) of cases. The median follow-up was 13.8 months (P25; P75: 11.7; 16.6 months) for both the whole series and resected patients, and 12 month PFS was 95.7% (95% CI, 84; 99%).

      Conclusion

      This is the first multicentric study to test CT-IO in the neoadjuvant setting in stage IIIA. Neoadjuvant CT-IO with nivolumab in resectable IIIA NSCLC yields a complete pathologic response rate that is higher than ever seen previously, together with a promising PFS which may translate into increased overall survival. EudraCT Number: 2016-003732-20. Clinical trial information: NCT 03081689.

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    P1.01 - Advanced NSCLC (ID 158)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Advanced NSCLC
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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      P1.01-93 - Metastases Sites as a Prognostic Factor in a Real-World Multicenter Cohort Study of Spanish ALK-Positive NSCLC Patients (p) (ID 1377)

      09:45 - 18:00  |  Author(s): Virginia Calvo De Juan

      • Abstract

      Background

      ALK gene rearrangements are detected in 3-7% of Non-Small-Cell-Lung-Cancer (NSCLC) p. EML4-ALK translocation was first identified as an oncogene in NSCLC p in 2007. To date, published real-world data on the prognostic factors of patients with ALK-positive advanced NSCLC in Spain are limited. We aim to evaluate the effect of number of metastases (M1) organs on overall survival (OS) in a multicenter cohort of Spanish ALK-positive NSCLC p diagnosed between 2008 and 2017.

      Method

      We included p with stage IV at diagnosis since 2011 to April 2018. OS (months [m]) was estimated with the Kaplan-Meier method. Survival curves were compared between groups of p using the log-rank test. Hazard risk (HR) to death was estimated with multivariable Cox model, adjusted by site of metastases, gender, age and first line type of treatment.

      Result

      Out of the 163 p in the cohort a total of 98 p were included, with a median follow-up of 28.6 m and 45 deaths reported. Characteristics at diagnosis were median age 58 years, female 46.9%, never-smokers 59.2%, 50% with comorbidities, PS by ECOG 0-1 93%, 58.2% lung M1, 45.9% central nervous system M1, 42.9% bone M1, 22.4% liver M1 and 29.6% pleural M1.

      54.3% p and 89.4% p were treated with ALK inhibitors as first line and second line respectively. The median OS was 34.4 months, being 46.9 months in p treated with ALK inhibitors and 38.8 months in p treated with chemotherapy as first line (p= 0.9).

      There were 72 p who presented M1 in more than one organ and 26 p in a single organ. The risk of death increased with greater number of organs involved at diagnosis (HR= 3.0, p=.016), and presenting liver M1 at diagnosis (HR=2.2, p=.046, with OS of 19.1 m), compared to p single site involvement (OS: 45.4 m).

      Conclusion

      OS was worse with increased metastatic sites involved at diagnosis in p with ALK positive NSCLC, being liver M1 associated with the highest risk of mortality. Brain metastases at diagnosis were not a prognostic factor for OS in our series.

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    P1.03 - Biology (ID 161)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Biology
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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      P1.03-15 - Non-Invasive Detection of Secondary Resistance Mutations in ALK-Positive NSCLC Patients by Next-Generation Sequencing (ID 1658)

      09:45 - 18:00  |  Author(s): Virginia Calvo De Juan

      • Abstract
      • Slides

      Background

      ALK inhibitors have led to important improvements in ALK-positive non-small cell lung cancer (NSCLC) patient’s survival and quality of life. However, despite the good responses, resistance mutations inevitably emerge. Several resistance mutations in ALK domain have been describe. Remarkably different mutations can confer different sensitivities to different ALK inhibitors. However, 2nd and 3rd line treatment is often prescribe empirically without knowing the molecular mechanism underlying treatment failure.

      Method

      21 samples from ALK-positive NSCLC patients were collected at disease progression. Circulating Nucleic Acids were isolated from platelets, exosomes and plasma. Libraries were prepared using 20ng of template and Oncomine™ Pan-Cancer Cell-Free Assay. Samples were sequenced on an Ion GeneStudio S5 Plus System. Sequencing data was first analyzed using Torrent Suite software. Subsequently variant calling, annotation and filtering was performed on the Ion Reporter (v5.10) platform using the Oncomine TagSeq Pan-Cancer Liquid Biopsy w2.1 workflow.

      Result

      In 14 (67%) patients a somatic mutation was identified in the plasma sample collected at disease progression. The average number of mutations detected per sample was 2.6. Noteworthy, 14 mutations were found in oncogenes that have been previously associated with ALK inhibitors resistance (5 mutations in ALK locus, 4 mutations in PIK3CA, 1 mutation in EGFR, 1 mutation in KIT, 1 mutation in KRAS, 1 mutation in MTOR and 1 mutation in MYC). The rest of mutations (N=21) were found in TP53 gene. Secondary resistance mutation in ALK locus occurred in 24% of the cases. Specifically, p.G1269A (N=2), p.G1202E (N=1), p.R1275Q (N=1) mutations were found in ALK-positive NSCLC who had progressed on crizotinib and p.G1202R mutation was found in 1 ALK-positive NSCLC who had progressed on ceritinib.

      Conclusion

      Secondary ALK-TKI resistance mutations could be detected using liquid biopsies in a high proportion of patients. Non-invasive molecular profiling of samples collected at disease progression is feasible being useful for further treatment selection in ALK-positive NSCLC patients.

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    P2.03 - Biology (ID 162)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Biology
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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      P2.03-33 - ctDNA Levels Significantly Predicts Survival in NSCLC Patients with an EGFR Activating Mutation (ID 2016)

      10:15 - 18:15  |  Author(s): Virginia Calvo De Juan

      • Abstract

      Background

      Circulating tumor DNA (ctDNA) have been shown to be useful for non-invasive biomarker testing in non-small cell lung cancer (NSCLC). In addition, there is growing evidence supporting that ctDNA levels can be useful for tumor response to treatment monitoring. Nevertheless, data from large prospective clinical longitudinal studies still limited.

      Method

      300 plasma samples from 100 advanced NSCLC patients, with tumors harboring an EGFR activating mutation and treated with a first line tyrosine Kinase inhibitor were analyzed. Samples were collected before the start of treatment, at first follow up evaluation, at 7 month and at disease progression. ctDNA was analyzed by dPCR.

      Result

      Median follow up was 11.3 months. There were not significant differences in progression free survival (PFS) or overall survival (OS) according to treatment (erlotinib, afatinib or gefitinib). Patients harboring a deletion in exon 19 or a mutation in exon 21 exhibited better survival than those with an insertion in exon 20 (P<0.001). dPCR detected EGFR sensitizing mutation in 77% of the pre-treatment samples. ctDNA levels before the start of the treatment did not significantly predict survival, although a tendency was observed, with patients with high levels of ctDNA showing poorer outcome. On the contrary, patients in which the EGFR sensitizing mutation was undetectable at first follow up had a markedly better PFS and OS (HR=2.7; 95IC= 1.4-5.5 and HR= 5.5 95IC: 1.8-17 respectively). In the same way, patients in which the EGFR sensitizing mutation remained negative at 7months had a significantly increased PFS (HR: 2.8; 95IC: 1.2-6.6). None of the patients with undetectable levels at 7 months has deceased.

      Conclusion

      ctDNA levels is of prognostic significance in EGFR positive NSCLC patients with advance disease and can be useful to monitor treatment outcome

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    P2.04 - Immuno-oncology (ID 167)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Immuno-oncology
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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      P2.04-10 - Biomarkers of Pathological Response on Neo-Adjuvant Chemo-Immunotherapy Treatment for Resectable Stage IIIA NSCLC Patients (ID 1466)

      10:15 - 18:15  |  Author(s): Virginia Calvo De Juan

      • Abstract
      • Slides

      Background

      PD1/PDL1 treatments have become the main therapy in advanced stages of NSCLC due to its significant increase in overall survival (OS), but recently, combination with chemotherapy in locally advanced stages is showing promising results. Many studies have described peripheral blood immune cells parameters as biomarkers of response to immunotherapy. In our study, we described the effect of neo-adjuvant chemo-immunotherapy treatment in Complete Blood Count (CBC) and Peripheral Blood Mononuclear Cells (PBMCs) phenotype, as well as, the association of these parameters with the degree of pathological response.

      Method

      Immune cell populations of 46 resectable stage IIIA NSCLC patients treated with neo-adjuvant chemo-immunotherapy from NADIM clinical trial were analysed. Samples were extracted before initiating the neo-adjuvant treatment with nivolumab plus carboplatin and at the third cycle before patients underwent surgery. We classified patients in 3 subgroups of pathological response assessed in the resection specimen: complete response (pCR), major response (<10% viable tumour) and incomplete response (>10% viable tumour, pIR). Wilcoxon and Mann-Whitney U statistic test were used to evaluate differences between pre and post treatment and between pathological responses groups respectively.

      Result

      From 46 patients, 5 patients did not undergo surgery, so they were excluded from the analysis. Absolute numbers of Leucocytes, Eosinophil, Monocytes, Neutrophils, Haemoglobin and Platelets from hemograms were significantly reduced after neo-adjuvant treatment. However, no changes were observed for Lymphocytes, Basophils, LDH levels or the Lung Immune Prognostic Index (LIPI). Additionally, post-treatment Neutrophil-to-Lymphocyte (NLR), Myeloid-to-Lymphoid lineage (M:L) and Platelets-to-Lymphocytes (PLR) ratios were decreased. Remarkably, from all the CBC absolute numbers and ratios, only PLR variation showed differences between pCR and pIR.

      On the other hand, percentages of PBMCs (T cells, B cells, NK cells and macrophages) did not vary after neo-adjuvant treatment, however activation of CD4 T cells and NK cells as well as PD-1 receptor expression on immune cells were downregulated after neo-adjuvant chemo-immunotherapy. Interestingly, these variations correlate with pCR.

      Conclusion

      In our study, PLR, PD-1 expression, CD4 T cells and NK cells activation are predictive biomarkers of response to treatment. Thus, a higher decrease on PLR post neo-adjuvant treatment is associated to pCR. Moreover, a decrease of PD-1 expression in CD4, CD8 and NK cells, as well as, a reduction of CD4 T cells and NK cells activation after neo-adjuvant treatment, are associated to pCR.

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    P2.05 - Interventional Diagnostic/Pulmonology (ID 168)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Interventional Diagnostics/Pulmonology
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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      P2.05-10 - Liquid Biopsy: Association Between the Burden of Disease in Patients with EGFR-Mutated NSCLC and the Frequency of Its Detection in Blood (ID 2384)

      10:15 - 18:15  |  Author(s): Virginia Calvo De Juan

      • Abstract
      • Slides

      Background

      In the management of patient’s whit non small cell lung cancer (NSCLC) with EGFR mutations after progression to first and second generation tyrosine kinasa inhibitors (TKI), the mechanism of resistance is very important. Our objective is to analyse the appearance kinetics of the T790M by means of digital PCR techniques in liquid biopsy.

      Method

      We conducted a multicenter study with 100 patients with EGFR-mutated NSCLC, treated with first-line TKI therapy. We analyze the ctDNA by dPCR before the start of treatment, at first follow up evaluation, at 6 months and at disease progression.

      Result

      We included a total of 100 patients from July 2016 to December of 2017. Seven patients with Exon 20 insertion in EGFR were excluded (final sample 93). The median of follow-up was 12 months. There were not significant differences in progression free survival (PFS) or overall survival (OS) according to treatment (erlotinib, gefitinib or afatinib). dPCR detected EGFR sensitizing mutation in 77% of the pre-treatment samples. Of these cases, EGFR sensitizing mutation was detected in 75% of the patients with stage IVA and 85% in stage IVB respectively, p=0,075. The resistance mutation p.T790M was detected in 52% of the samples collected at disease progression. The probability to detect the resistance mutation p.T790M by liquid biopsy, is greater if the pre-treatment sample was positive for EGFR sensitizing mutation (11% vs 62%) p 0,009. In cases with progression of the disease the percent of detection of p.T790M was 52% and 54% in patients with Exon 19 deletion and L858R mutation respectively. The OS in patients with progression of the disease and p.T790M negative was 85% at 12 months (95%CI: 60%-94%) and 75% with p.T790M positive (95%CI: 49%-88%), p=0,01.

      Conclusion

      The burden of disease in patients with NSCLC mutated with EGFR is related to the appearance of sensitivity and resistance mutations in liquid biopsy. The probability to detect the resistance mutation p.T790M in blood, is greater if the pre-treatment sample was positive for EGFR sensitizing mutation.

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    P2.16 - Treatment in the Real World - Support, Survivorship, Systems Research (ID 187)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Treatment in the Real World - Support, Survivorship, Systems Research
    • Presentations: 2
    • Now Available
    • Moderators:
    • Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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      P2.16-20 - Big Data and Survival Predictors in Lung Cancer Patients (ID 1943)

      10:15 - 18:15  |  Author(s): Virginia Calvo De Juan

      • Abstract
      • Slides

      Background

      Lung cancer is the most common and fatal one (18% of all cancer deaths). Parameters which imply better survival are still unknown.

      The objective of this project is to turn the large amount of data from each patient into exploitable information.

      Method

      Between 2008-2019, 935 non-small cell lung cancer patients from our hospital were enrolled in an observational study.

      Unstructured data was obtained from the patient Electronic Health Records.

      Politecnica University from Madrid made the information analysis using Big Data and machine learning techniques.

      Result

      A total of 251.730 documents have been analyzed from 935 patients, 54% in stage IV.

      EGFR/ALK mutation was found in 9%, showing better OS than non-mutated (23.5 months vs 12 months, log-rank p=0.016). Survival curves are shown in figure 1.

      In a multivariate analysis (table 1), independent predictors of mortality were male sex, squamous histology and PS status. Additionally, independent predictors of survival were receiving immunotherapy, surgery treatment or developing endocrine toxicities.

      Conclusion

      Big data is a very useful tool to exploit a large amount of lung cancer data, increasing knowledge about these disease and allowing the development of survival predictive models.


      This work was supported by the EU H2020 programme, under grant agreement Nº 727658 (Project iASiS).

      captura de pantalla 2019-04-10 a las 17.32.38.png

      captura de pantalla 2019-04-10 a las 17.png

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      P2.16-34 - Is Prophylactic Cranial Irradiation Useful in Real World? (Now Available) (ID 1398)

      10:15 - 18:15  |  Author(s): Virginia Calvo De Juan

      • Abstract
      • Slides

      Background

      Small cell lung cancer (SCLC) is the most aggressive lung cancer subtype. Just one third of patients are diagnosed as limited stage (LS), in which the goal is to perform a radical treatment. However, the majority will develop metastasis, being in central nervous system (CNS) one of the most frequent. In patients with LS, after systemic treatment, prophylactic cranial irradiation (PCI) should be considered. Nevertheless, the effectiveness of PCI has been a controversial issue in terms of overall survival (OS).

      Method

      A cohort of 81 patients diagnosed of localized SCLC were retrospectively analyzed in our center over a 10-year period (January 2008-December 2017). Brain imagen was done before chemo-radiotherapy (CRT) and repeated before PCI. Baseline demographics characteristics and brain metastases rate incidence were described.

      Result

      From 81 patients, 48 received PCI and 33 did not. Complete baseline characteristics from both groups are shown in table 1. No differences were found in performance status at diagnosis between groups . From those who did not receive PCI, 8 (26%) had developed brain metastases after CRT and before PCI. Brain metastases incidence rate in PCI subgroup was 9/100 people per year vs 35/100 people per year in those who did not receive PCI, in whom 54.5% had brain or systemic progression before PCI planning. Progression free survival in both subgroups was 13.5 months and OS was 21.2 months.

      imagen 1.png

      Conclusion

      In our series, PCI had a significant effect in decreasing brain metastases. This study also confirms the requirement of brain imaging to confirm lack of brain metastases after initial CRT and before PCI.

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