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Michael Boyer
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IBS02 - Making Sense of Treatment with so Many Options: My Algoritm (Ticketed Session) (ID 33)
- Event: WCLC 2019
- Type: Interactive Breakfast Session
- Track: Advanced NSCLC
- Presentations: 1
- Now Available
- Moderators:
- Coordinates: 9/08/2019, 07:00 - 08:00, Toronto (1985)
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IBS02.03 - Making Sense of Treatment with so Many Options: My Algoritm - An Australian View (Now Available) (ID 3321)
07:00 - 08:00 | Presenting Author(s): Michael Boyer
- Abstract
- Presentation
Abstract
Section not applicable
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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: 1
- Now Available
- Moderators:Joaquim Bosch-Barrera, Virginia Calvo De Juan
- Coordinates: 9/10/2019, 11:30 - 13:00, Interlaken (1988)
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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 | Author(s): Michael Boyer
- Abstract
- Presentation
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)].
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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OA04 - Immuno Combinations and the Role of TMB (ID 126)
- Event: WCLC 2019
- Type: Oral Session
- Track: Immuno-oncology
- Presentations: 1
- Now Available
- Moderators:Solange Peters, Martin Reck
- Coordinates: 9/08/2019, 15:15 - 16:45, Copenhagen (1980)
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OA04.06 - Evaluation of TMB in KEYNOTE-189: Pembrolizumab Plus Chemotherapy vs Placebo Plus Chemotherapy for Nonsquamous NSCLC (Now Available) (ID 1936)
15:15 - 16:45 | Author(s): Michael Boyer
- Abstract
- Presentation
Background
First-line pembrolizumab plus chemotherapy with pemetrexed and platinum significantly improved OS (HR 0.49, P < .001), PFS (HR 0.52, P < .001) and ORR (47.6% vs 18.9%, P < .001) vs placebo plus chemotherapy with pemetrexed and platinum for metastatic nonsquamous NSCLC in the double-blind phase 3 KEYNOTE-189 study (NCT02578680); benefit was observed in all analyzed subgroups, including PD-L1 TPS <1%, 1-49%, and ≥50%. We explored the association of TMB with efficacy in KEYNOTE-189.
Method
616 patients were randomized 2:1 to pembrolizumab plus chemotherapy or placebo plus chemotherapy. TMB was determined by whole-exome sequencing of tumor and matched normal DNA. Association of TMB (continuous log10 transformed) with outcomes in each arm was assessed using Cox proportional hazards models (OS, PFS) and logistic regression (ORR); statistical significance was determined at the 0.05 level without multiplicity adjustment. The clinical utility of TMB on outcomes was assessed using prespecified TMB cutpoints of 175 and 150 Mut/exome (~13 and ~10 Mut/Mb by FoundationOne CDx). Data cutoff was 21 Sep 2018.
Result
293 (48.3%) treated patients had evaluable TMB data: 207 for pembrolizumab plus chemotherapy, 86 for placebo plus chemotherapy. Baseline characteristics and outcomes were generally similar in the TMB-evaluable and total populations. TMB as a continuous variable was not significantly associated with OS, PFS, or ORR for pembrolizumab plus chemotherapy (one-sided P = .174, .075 and .072, respectively) or placebo plus chemotherapy (two-sided P = .856, .055 and .434, respectively). Pembrolizumab plus chemotherapy improved OS, PFS, and ORR for TMB ≥175 and <175 (Table). Results were similar for TMB ≥150 and <150.
Conclusion
TMB was not significantly associated with efficacy of pembrolizumab plus chemotherapy or placebo plus chemotherapy as first-line therapy for metastatic nonsquamous NSCLC. Pembrolizumab plus chemotherapy had a similar OS benefit in the TMB-high and low subgroups.
TMB ≥175 TMB <175 Pembrolizumab plus Chemotherapy
n = 100Placebo plus Chemotherapy
n = 34Pembrolizumab plus Chemotherapy
n = 107Placebo plus Chemotherapy
n = 52Median OS (95% CI), mo 23.5
(20.2-NE)13.5
(7.0-NE)20.2
(15.8-NE)9.9
(7.4-19.1)HR (95% CI) 0.64 (0.38-1.07) 0.64 (0.42-0.97) Median PFS (95% CI), mo 9.2
(7.6-14.0)4.7
(4.0-5.5)9.0
(6.7-11.1)4.8
(4.5-6.6)HR (95% CI) 0.32 (0.21-0.51) 0.51 (0.35-0.74) ORR, % (95% CI) 50.0
(39.8-60.2)11.8
(3.3-27.5)40.2
(30.8-50.1)19.2
(9.6-32.5)Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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P1.09 - Pathology (ID 173)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Pathology
- Presentations: 1
- Moderators:
- Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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P1.09-26 - Prevalence of PD-L1 Expression Rates in Different NSCLC Specimens (ID 2125)
09:45 - 18:00 | Author(s): Michael Boyer
- Abstract
Background
Programmed death-ligand 1 (PD-L1) expression on tumor cells by immunohistochemistry (IHC) is a predictor of response to immune checkpoint inhibitors used to treat advanced non-small cell lung cancer (NSCLC). High PD-L1 expression (≥50% of tumor cells) is required for patients to receive first line pembrolizumab monotherapy. Assessing expected PD-L1 expression rates in real-world specimens is an important factor in ensuring patients are accessing the most effective treatments available. The aim of this retrospective assessment was to review the local prevalence of PD-L1 expression in NSCLC and compare different specimen types.
Method
We retrospectively reviewed cases of NSCLC stained with PD-L1 IHC Ventana SP263 assay between January 2017 and March 2019. PD-L1 expression was assessed as a tumor proportion score (TPS) of 0-<1%, 1-49% or ≥50% positive membrane staining within tumor cells. Results were compared with specimen type and mutation status.
Result
PD-L1 expression was assessed in 264 cases of NSCLC during the 51 month period. The median patient age was 70 years, 64.4% were >65 years old and 60.9% were male.
Histologically, 79.9% were adenocarcinoma, 10.6% squamous cell carcinoma and 9.5% NSCLC-NOS. Overall 29.5% of NSCLC showed high PD-L1 expression (≥50%), 43.9% low (1-49%), and 26.5% no expression (<1%). In known EGFR/ALK negative cases (n=176), high, low and negative PD-L1 was seen in 34.7%, 43.2% and 22.1% respectively.
Histology samples accounted for 80.7% of cases and 19.3% were cytology. Lung resections accounted for 27.7% with other specimen types (small biopsies, cytology and metastatic resections) accounting for 72.3%. 61.0% were primary tumors and 39.0% were from metastases.
A PD-L1 TPS of ≥50% was seen in 29.1% of histology and 31.4% of cytology specimens, with no statistically significant difference (p=0.55). Amongst lung resections, high PD-L1 expression was observed in 19.2% of cases compared to 33.5% in other specimen types (p<0.01). In primary tumors, high PD-L1 expression was seen in 27.3% compared to 33.0% in metastases (p=0.51)
Of the cases that had mutation results available, only 8.8% of NSCLC haboring EGFR mutations expressed high PD-L1 expression (≥50%) compared to 44.1% of tumors with KRAS mutations (p<0.01).
Conclusion
Our overall prevalence of PD-L1 expression in cases of NSCLC is in keeping with rates demonstrated in a large clinical trial investigating the efficacy of pembrolizumab as first line treatment in NSCLC. The same rates of high PD-L1 in cytology and histology specimens suggest cytological specimens are valid for assessment.
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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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P1.16-47 - Embedding Research (and Evidence) in Cancer Healthcare - EnRICH (ID 24)
09:45 - 18:00 | Author(s): Michael Boyer
- Abstract
Background
In Australia, as in other regions, lung cancer persists as the most common cause of cancer related death and is the leading cause of morbidity and burden of disease. Improvements in lung cancer survival rates are not comparable with improvements for other cancers.
The Sydney Catalyst flagship program ‘Embedding Research (and evidence) in Cancer Healthcare – EnRICH’, is building a program of translational research in lung cancer to develop and extend evidence of effective treatments and to increase the use of clinical care based on existing evidence.
Specifically, this prospective clinical cohort of patients with lung cancer (non-small cell and small cell, any histological type, any clinical/pathological stage) will establish a comprehensive data platform, including biological samples (FFPE diagnostic tumour tissue, and serial pre- and post-treatment blood samples) with matched demographic, clinical, biomarker, molecular profile, and outcome data (including quality of care and patient-reported outcomes) to support a range of interconnected research from across the T1 – T3 translational research spectrum, from bench to bedside (and bedside to bench) through to policy and practice. A linked implementation science program will identify methods to promote better integration of research findings and evidence.
EnRICH will build on existing collaborations within Sydney Catalyst, across NSW, Australia, and internationally to establish a multidisciplinary program of research in scientific discovery, diagnostic and therapeutic development, clinical trials and implementation science.
Method
Aim
To assemble a patient cohort to: describe the natural history of and patterns of care for lung cancer; identify current gaps in evidence and practice for clinical quality improvement; create a platform for researchers across the T1-T3 translational research spectrum to develop and initiate clinical research and intervention studies to address gaps. Initially lung cancer will be an exemplar.
Design
Prospective clinical cohort of lung cancer patients including matched demographic, clinical, biomarker, molecular profile, and outcome data (including quality of care and patient-reported outcomes) for current and future research projects.
Planned sample size
At least 1000 patients. 505 patients enrolled at 31 Jan 2019.
Inclusion criteria
All patients with lung cancer presenting to defined clinical sites for diagnosis or treatment, including:
Patients with a new diagnosis of primary lung cancer (any histological type, any pathological/clinical stage including metastatic) undergoing primary treatment; curative or palliative
Patients with first progressive disease, local recurrence or new metastasis after completing previous treatment for non-metastatic disease at the time of initial diagnosis
Aged over 18 years
Data and biospecimen collection
Matched clinical and demographic data will be collected from patient medical records and hospital administrative data sets
Archival tissue, for research, will be obtained from routine biopsy specimens. Serial blood samples for research, on average 3 per patient (e.g. prior to commencement of treatment [baseline], and post-treatment [6 and 12 month follow-up])
Patient reported outcomes will be measured through questionnaires
Statistical considerations
The cohort will enable reliable estimates of outcomes both overall and within histologic and genetic sub-types.
Result
Section not applicable
Conclusion
Section not applicable
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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: 1
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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P2.16-36 - Patterns of Care in a Prospective Clinical Cohort of Patients with Lung Cancer - Preliminary Analyses from the EnRICH Program (ID 1493)
10:15 - 18:15 | Author(s): Michael Boyer
- Abstract
Background
Lung cancer accounts for 9% of all cancer diagnoses, is the most common cause of cancer related death, and is the leading cause of morbidity and burden of disease in NSW and across Australia. The outlook for patients with lung cancer remains poor with only a 15% overall five year survival rate. For patients diagnosed with advanced stage disease, five year survival is less than 5%. There is an urgent need to identify and reduce unwarranted clinical variation that may contribute to morbidity and burden of disease, and to improve quality of care, and thereby ensure best possible outcomes, for the lung cancer population.
Sydney Catalyst is addressing this need through the Embedding Research (and Evidence) in Cancer Healthcare 'EnRICH' program, a program of translational research in lung cancer which aims to: describe the natural history of and patterns of care for lung cancer; identify current gaps in evidence and practice for clinical quality improvement; and create a platform for researchers across the T1-T3 translational research spectrum to develop and initiate clinical research and intervention studies to address gaps.
The EnRICH dataset currently includes comprehensive patient, diagnostic, treatment and outcome data (including patient reported outcomes) for more than 600 consecutive patients with lung cancer (non-small cell and small cell, any histological type, any clinical/pathological stage) treated in metropolitan and regional hospitals across three Local Health Districts in NSW, Australia. By mid-2020, the EnRICH dataset will include data for more than 1000 patients.
Method
This preliminary analysis will provide descriptive data on the first 500 consecutive patients in the EnRICH cohort and, specifically, will describe patterns of care stratified by patient and disease characteristics. Patterns of care will be mapped to evidence-based quality indicators to identify clinical variation.
Result
Data collection is complete for 420 patients. Remaining data collection and analyses will be complete for 500 consecutive patients by 19 July 2019. Data presented will include:
Descriptive data
Patient characteristics: age; sex; CALD status; comorbidities, symptoms, performance status
Risk factors: smoking history; family history of lung cancer; occupational exposure; clinical history of lung disease; previous malignancy
Disease characteristics: histological type and sub-stype; pathological stage; clinical stage; genetic mutations
Quality indicators
Diagnosis - proportion with: clinical stage; pathological stage; appropriate analysis of predictive markers; time from diagnosis to treatment
Treatment - proportion: with performance status assessment; reviewed by MDT; undergoing resection, chemotherapy, targeted-therapy, immunotherapy, radiotherapy; receiving no active anti-cancer treatment
Referral - proportion: of current smokers with documented smoking cessation counselling; of stage IV patients referred to palliative care; referred to supportive care services; referred to/enrolled in clinical trials
Outcomes
Clinical outcomes: major complications (Clavien-Dindo/CTCAE grade ≥3); hospitalisations; survival
Patient reported outcomes: Global health status/QoL; social functioning; physical functioning; role functioning; emotional functioning; cognitive functioning; social functioning; symptoms; distress
Conclusion
Data from EnRICH for the first 500 consecutive patients treated for lung cancer across a wide geographical area in NSW, Australia will map routine patterns of care, and identify unwarranted clinical variation to be addressed by quality improvement interventions to achieve best possible patient outcomes.
