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MTE 27 - CT Screening for Lung Cancer (Sign Up Required) (ID 576)
- Event: WCLC 2017
- Type: Meet the Expert
- Track: Radiology/Staging/Screening
- Presentations: 1
- Moderators:
- Coordinates: 10/18/2017, 07:00 - 08:00, Room 501
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MTE 27.01 - Who Should be Screened for Lung Cancer? (ID 8129)
07:00 - 07:30 | Presenting Author(s): Jim Jett
- Abstract
- Presentation
Abstract:
The National Lung Screening Trial (NLST) demonstrated that screening for lung cancer could reduce lung cancer (LC) mortality by 20%[1]. Screening with low-dose CT (LDCT) resulted in more early stage lung cancers and fewer late-stage cancers as compared to chest X-ray screening. It has been estimated that 12,000 lung cancer deaths could be averted each year if all eligible Americans were to undergo LDCT screening[2]. An Italian screening study with LDCT reported that stopping smoking reduces overall mortality by 39% compared with current smokers[3]. Tanner and associates also reported a 20% LC mortality reduction in the NLST in the chest X-ray arm (control arm) in the absence of smoking for 7 years[4]. The maximum mortality benefit was seen in the absence of smoking in combination with LDCT that resulted in a LC mortality reduction of 38% (HR=0.62). Accordingly, current-screening programs must include tobacco cessation counseling and treatment to current smokers[5]. The US Preventive Services Task Force has approved LDCT screening in high-risk individuals (asymptomatic persons aged 55 to 80 years who have a 30-pack-year or more smoking history and have quit within the past 15 years)[6]. However, from 2010-2015 less than 5% per year of those eligible are currently undergoing LDCT screening. Of the 6.8 million smokers eligible for LDCT screening, only 262,700 received it[7]. In the last two years a large number of centers have ramped up their screening programs in the US. Another issue is that of all lung cancers patients in the United States only 30-40% of these individuals were actually eligible for LDCT screening based on the NLST criteria for screening[8]. Tammemagi et al developed an LC-risk-prediction model based on the PLCO (Prostate, Lung, Colon, Ovarian) screening trial[9]. At a six-year LC risk of ≥1.5%, this risk prediction model detected 12% more LC and screened 8.8% fewer individuals than those using the NSLC screening criteria[10]. The number needed to screen to detect one LC was 255 with this model as compared with 320 in the NLST. None of the never-smokers in the PLCO trial had a risk of >1.5%. Do not screen never-smokers! In an effort to detect more lung cancers at an earlier stage, additional risk factors need to be included in screening programs and evaluated for their efficacy. Young and colleagues evaluated a subset of the NLST participants who had pulmonary function testing (PFT) and observed a two-fold increase in lung cancer incidence with COPD[11]. There was a linear relationship between increasing severity of airflow limitation and risk of lung cancer[12]. The heritability of lung cancer is not well explained. The OncoArray Consortium has identified 18 genetic susceptibility loci for LC across histological types[13]. Dr. Stephen Lam in Vancouver, BC is testing this 18-gene array as a risk factor in an international screening trial. The European Study of Cohorts of Air Pollution Effects (ESCAPE) identified particle matter (PM 10 and PM 2.5) as having significant association with LC risk (HR 1.22 and 1.18 respectively)[14]. The hazard ratios (HR) associated with adenocarcinoma was 1.51 and 1.55 respectively. Satellites are able to measure air pollution and have good correlation with simultaneous ground measurements ( accessed 8/4/2017). There is extensive research into biomarkers for risk of lung cancer that might be of use in screening for LC or in identifying risk of malignancy in indeterminate pulmonary nodules. Sources of biomarkers to date have included breath, sputum, urine and blood. Categories of blood biomarkers have included micro-RNA, proteins, circulating tumor DNA and autoantibodies. A randomized prospective trial (RCT) in Scotland is evaluating an autoantibody panel against tumor antigens for early detection of LC[15]. The trial randomized 12,000 high-risk participants to the blood test alone or routine care (no screening). Those with a positive blood test undergo a CT chest scan. Results of this RTC should be available in late 2018. If we (IASLC) are going to decrease the mortality of lung cancer then we must promote tobacco use intervention and implement LC screening so that more LCs are detected in an early and more curable stage. The optimal paradigm for screening has yet to be developed and is likely to vary in different countries. The NLST was a starting point and reveals that is can be accomplished. Continued innovations and research are required. References 1) The National Lung Cancer Screening Trial Research Team. NEJM (2011); 365:395-409 2) Ma et al. Cancer (2013); 119:1381-5 3) Pastorino et al. J Thorac Oncol (2016); 11:693-699 4) Tanner et al. Amer J Resp Crit Care Med (2016); 193:534-541 5) Tammemagi et al. JNCI (2014); 106:doi.1043/jnci/dju168 6) Moyer et al. Ann Int Med (2014); 160:330-338 7) Jemal and Fedewa. JAMA Oncol, published online February 2, 2017 8) Wang et al. JAMA (2015); 313:853-855 9) Tammemagi et al. NEJM (2013); 368:728-736 10) Tammemagi et al. PLOS (2014); 11e 1001764 11) Young et al. Amer J Resp Crit Care Med (2015); 192:1060-1067 12) Hopkins et al. Annals Amer Thorac Society, published online January 11, 2017. 13) McKay et al. Nature Genetics (2017); 49:1126-1132 14) Raaschou-Nielsen et al. Lancet Oncol (2013); 14:813-822 15) Sullivan et al. BMC Cancer (2017); 17:187-196
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P1.07 - Immunology and Immunotherapy (ID 693)
- Event: WCLC 2017
- Type: Poster Session with Presenters Present
- Track: Immunology and Immunotherapy
- Presentations: 1
- Moderators:
- Coordinates: 10/16/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)
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P1.07-016 - Comparison of PD-L1 Immunohistochemical Staining between EBUS-TBNA and Resected Non-Small Cell Lung Cancer Specimens (ID 8964)
09:30 - 09:30 | Author(s): Jim Jett
- Abstract
Background:
PD-L1 can be detected by immunohistochemical (IHC) analysis and has emerged as a biomarker that predicts which patients are more likely to respond to anti-PD-L1/PD-1 immunotherapies in non-small cell lung cancer (NSCLC)(1, 2). To date, there is no evidence to support or refute PD-L1 IHC staining on endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) samples. Our study aimed to establish the sensitivity, specificity, positive predictive value, and negative predictive value of PD-L1 IHC staining reliability on EBUS-TBNA samples, when compared to resected tumor specimens.
Method:
A retrospective review was performed on all patients who underwent an EBUS-TBNA of either a lymph node(s) or the tumor itself, who subsequently had surgical resection of their tumor between July 2006 through September 2016. Patients who had a concordant NSCLC EBUS-TBNA diagnosis with their resected tumor were included. Patients with small cell lung cancer were excluded. All EBUS-TBNA samples were obtained using Olympus EBUS bronchoscopes and a 22-gauge ViziShot needle (Olympus Medical Systems Corp., Tokyo, Japan). The Dako PD-L1 IHC 22C3 (Agilent Pathology Solutions) assay was used. A positive PD-L1 stain was defined as ≥1% of tumor cell positivity. EBUS-TBNA aspirates were compared with the surgically resected specimen to calculate the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).
Result:
We performed 5448 EBUS-TBNA procedures for lung cancer. Seventy patients were included in our analysis. To date, 23 cases have been stained and reviewed (Table). The sensitivity and specificity was 71% and 100%, respectively. The PPV and NPV were 100% and 69%, respectively. We expect to complete our analysis of all patients prior to the IASLC World Conference.Comparison of PD-L1 IHC stain between EBUS-TBNA samples and resected tumor specimen.
Resected tumor PD-L1 positive Resected tumor PD-L1 negative EBUS-TBNA PD-L1 positive 10 0 EBUS-TBNA PD-L1 negative 4 9
Conclusion:
Positive PD-L1 IHC staining on EBUS-TBNA aspirates appears to have a strong correlation with resected tumor specimen. When EBUS-TBNA aspirates are negative for PD-L1 staining, additional tumor specimens are required to confirm the PD-L1 status.
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P2.13 - Radiology/Staging/Screening (ID 714)
- Event: WCLC 2017
- Type: Poster Session with Presenters Present
- Track: Radiology/Staging/Screening
- Presentations: 1
- Moderators:
- Coordinates: 10/17/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)
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P2.13-013 - Determination of the Detection Lead Time for Autoantibody Biomarkers in Early Stage Lung Cancer Using the UKCTOCS Cohort (ID 9999)
09:30 - 09:30 | Presenting Author(s): Jim Jett
- Abstract
Background:
Tumor associated (TA) autoantibodies are present during early stage lung cancer and have been detected up to five years before diagnosis. However the detection lead time provided by their measurement has never been accurately determined due to a lack of suitable patient samples. The United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) recruited 202,638 postmenopausal women. Annual blood samples were collected for over 10 years during which time a number of lung cancer cases were diagnosed. The primary aim of this study was to determine the detection lead time of tumor associated autoantibody assays for a subset of the UKCTOCS cohort.
Method:
A set of 142 primary lung cancer cases (NSCLC 83%, SCLC 12%) with 7 serial samples over a pre-diagnosis period of 10 years were randomly split into Training (n=100) and Validation (n=42) cohorts and matched to healthy controls by age-at-diagnosis, age-at-first sample and smoking history. TA autoantibody profiles were produced for each patient by measuring autoantibody levels against a panel of tumour associated antigens ( p53, SOX2, CAGE, NY-ESO-1, GBU4-5, MAGE A4, HuD, CK8, CK20, LMYC, SSX1, p53-95, p16 and p62) using ELISA. The profiles for each patient were compared to those for the preceding time point using a multivariate distance measure to determine if a statistically significant positive change had occurred. Comparison against a population based cut-off for the earliest time point sample for each patient was used to determine initial positivity. An optimised algorithm was developed on the Training cohort and then applied to the Validation cohort.
Result:
There were 49 positive patients in the training cohort: 11 at the earliest time point and 38 during serial sampling. For the Validation cohort there were 14: 3 at the earliest and 11 during serial sampling. The median detection lead time for the Training cohort was 4.0 years (0.3 to 9.4 range) and for the Validation cohort 4.3 years (0.1 to 9.0 range) before clinical diagnosis. The median was 4.1 years (0.1 to 9.4 range) for the entire cohort.
Conclusion:
This is the first time statistically sound estimates of detection lead time have been reported for tumor assoicated autoantibody tests run on such a large cohort of pre-diagnostic serial samples. These cancer biomarkers can be detected on average 4 years before diagnosis. Monitoring autoantibody profiles could be hugely beneficial by enabling earlier detection and stratification of screening populations for cancer. This could lower mortality rates and reduce healthcare costs.
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YI 01 - Young Investigator and First Time Attendee Session (ID 588)
- Event: WCLC 2017
- Type: Young Investigator
- Track: Education/Publication/Career Development
- Presentations: 1
- Moderators:Peter Goldstraw, Giorgio Vittorio Scagliotti
- Coordinates: 10/15/2017, 08:00 - 11:30, F201 + F202 (Annex Hall)
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YI 01.08 - Why Should I Publish? An Overview of the Manuscript Cycle: From Submission to Publication (ID 7851)
09:55 - 10:10 | Presenting Author(s): Jim Jett
- Abstract
- Presentation
Abstract not provided
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.
