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Objectives We sought to determine if implementation of low dose computed tomography (LDCT) screening for lung cancer in the United States had led to changes in patients being diagnosed with metastatic lung cancer over time. Materials Methods The Surveillance, Epidemiology, and End Result (SEER) database was utilized to determine the proportion of lung cancers diagnosed as stage I-III and stage IV from 2009-2018. Changes in lung cancer stage distribution were compared in the overall population and by race. Results From 2009 to 2018, the proportion of stage I-III lung cancers increased from 52% (51.3%-53.2%) in 2009 to 56% (54.0%-55.8%) in 2018 (p Conclusion Since the implementation of LDCT screening, the proportion of early-stage lung cancers increased in the general population. These changes in stage distribution were not present in black patients. Micro Abstract The SEER database was utilized to assess the impact of CT screening on lung cancer stage distribution from 2009-2018. The percentage of patients diagnosed with metastatic disease decreased overall, but there were no significant changes for black patients. These results associate CT screening to changes in lung cancer stage distribution, but potential racial disparities exist.

Background Lung cancer is the leading cause of cancer death in women in the United States. Prospective randomized lung screening trials suggest a greater lung cancer mortality benefit from screening women compared with men. Research Question Do the United States Preventative Services Task Force (USPSTF) lung screening guidelines that are based solely on age and smoking history contribute to sex disparities in eligibility, and if so, does the use of the PLCOm2012 risk prediction model that is based on 11 predictors of lung cancer reduce sex disparities? Study Design and Methods This retrospective analysis of 883 lung cancer cases in the Chicago Race Eligibility for Screening Cohort (CREST) determined the sensitivity of USPSTF vs PLCOm2012 eligibility criteria, stratified according to sex. For comparisons vs the USPSTF 2013 and the recently published USPSTF 2021 (released March 9, 2021) eligibility criteria, the PLCOm2012 model was used with risk thresholds of ≥ 1.7%/6 years (6y) and ≥ 1.0%/6y, respectively. Results The sensitivities for screening by the USPSTF 2013 were 46.7% for women and 64.6% for men (P = .003) and by the USPSTF 2021 were 56.8% and 71.8%, respectively (P = .02). In contrast, the PLCOm2012 ≥ 1.7%/6y sensitivities were 64.6% and 70.4%, and the PLCOm2012 ≥ 1.0%/6y sensitivities were 77.4% and 82.4%. The PLCOm2012 differences in sensitivity using ≥ 1.7%/6y and ≥ 1.0%/6y thresholds between women and men were nonsignificant (both, P = .07). Compared with men, women were more likely to be ineligible according to the USPSTF 2021 criteria because their smoking exposures were Interpretation Although the USPSTF 2021 eligibility criteria are more sensitive than the USPSTF 2013 guidelines, sex disparities in eligibility remain. Adding the PLCOm2012 risk prediction model to the USPSTF guidelines would improve sensitivity and attenuate sex disparities.

Background STK11 mutation (STK11m ) in patients (pts) with stage IV non-small cell lung cancer (NSCLC) is associated with inferior survival and poor response to immune checkpoint inhibitors (ICI). The significance of STK11m in stage III NSCLC pts treated with concurrent chemoradiation (CCRT) with or without consolidation ICI is unknown. Methods Stage III NSCLC patients who received CCRT and had known STK11 mutational status were included in this retrospective study. The data on the STK11m pts were collected from 4 cancer institutions. A cohort of pts with wild type STK11 (STK11w ) from the University of Iowa served as a comparison group. Patient demographics and clinical characteristics were collected. Cox regression models were used to explore the effect of STK11 mutation on survival. Results 75 pts with stage III NSCLC who had known STK11 mutational status were identified. 16/75 (21%) had STK11m . 5/16 with STK11 m did not receive CCRT so they were excluded from the analysis. The clinical and demographic characteristics for the 11 STK11m and 59 STK11w pts were not statistically different (STK11m vs. STK11w ): mean age: 57 vs. 64 yrs, non-squamous histology: 8/11 (73%) vs. 37/59 (63%), KRAS mutation: 3/11 (27%) vs. 11/59 (19%), TP53 mutation: 6/11 (55%) vs. 15/59 (25%), PD-L1 ≥50%: 1/8 (13%) vs. 10/32 (31%), and consolidation ICI 6/11 (55%) vs. 17/59 (29%). Regarding the 6 STK11m pts who received ICI (4 pembrolizumab, 2 durvalumab), the median number of ICI infusions was 8 (range, 3-17) vs. 6 (range, 1-25) in the 17 pts with STK11w who received ICI (durvalumab). After adjusting for performance status and cancer stage, multivariable analysis showed that progression free survival (PFS) for the STK11m pts was significantly worse than STK11 w pts (HR =2.25; 95% CI, 1.03-4.88, P=0.04), whereas overall survival (OS) showed no significant difference for STK11m vs. STK11w patients (HR 1.47, 95% CI, 0.49-4.38, P=0.49). Conclusions In stage III NSCLC patients who received CCRT, STK11m was associated with worse PFS compared to STK11w . Larger studies are needed to further explore the prognostic implications of STK11m in stage III NSCLC and whether ICI impacts survival for this subgroup.

Objectives Adjuvant chemotherapy is routinely offered post-surgical resection for early stage non-small-cell lung cancer (NSCLC) ≥4 cm; however, its role following definitive stereotactic body radiotherapy (SBRT) has not been well defined. We investigated the association between receipt of adjuvant chemotherapy post-SBRT and overall survival (OS) for patients with T1-T3N0M0 NSCLC in the National Cancer Database (NCDB). Materials and Methods The NCDB was queried for patients with T1-T3N0M0 NSCLC treated with definitive SBRT from 2004 to 2014. The association between non-randomized receipt of adjuvant chemotherapy and OS was analyzed for all patients (n = 24,011) and a propensity-matched cohort (n = 608) using Kaplan-Meier methods and Cox proportional hazard models. A subset analysis was performed for patients with tumors ≥4 cm (n = 2,323). Results There were 24,011 patients in the cohort with a median follow-up of 32.5 months. Of these, 322 (1.3%) received adjuvant chemotherapy. Three-year OS was 41.3% with adjuvant chemotherapy compared to 50.6% without adjuvant chemotherapy (p = 0.001). On multivariate analysis, adjuvant chemotherapy was independently associated with higher overall mortality (hazard ratio:1.22, 95% confidence interval:1.06–1.40, p = 0.005). For tumors ≥4 cm, 3-year OS was 38.2% with adjuvant chemotherapy (n = 80) compared to 33.0% without adjuvant chemotherapy (p = 0.81). After propensity-score matching, there was a persistent association between lower OS and adjuvant chemotherapy with those receiving adjuvant chemotherapy (n = 322) having 3-year OS of 41.3% compared to 60.9% without adjuvant chemotherapy (p Conclusion Adjuvant chemotherapy following definitive SBRT for T1-3N0M0 NSCLC is associated with lower OS and is not associated with a survival benefit for patients with tumors ≥4 cm.

Purpose: Low-dose CT screening can reduce lung cancer–related mortality. However, CT screening has an FDR of nearly 96%. We sought to assess whether urine samples can be a source for DNA methylation–based detection of non–small cell lung cancer (NSCLC). Experimental Design: This nested case–control study of subjects with suspicious nodules on CT imaging obtained plasma and urine samples preoperatively. Cases (n = 74) had pathologic confirmation of NSCLC. Controls (n = 27) had a noncancer diagnosis. We detected promoter methylation in plasma and urine samples using methylation on beads and quantitative methylation–specific real-time PCR for cancer-specific genes (CDO1, TAC1, HOXA7, HOXA9, SOX17, and ZFP42). Results: DNA methylation at cancer-specific loci was detected in both plasma and urine, and was more frequent in patients with cancer compared with controls for all six genes in plasma and in CDO1, TAC1, HOXA9, and SOX17 in urine. Univariate and multivariate logistic regression analysis showed that methylation detection in each one of six genes in plasma and CDO1, TAC1, HOXA9, and SOX17 in urine were significantly associated with the diagnosis of NSCLC, independent of age, race, and smoking pack-years. When methylation was detected for three or more genes in both plasma and urine, the sensitivity and specificity for lung cancer diagnosis were 73% and 92%, respectively. Conclusions: DNA methylation–based biomarkers in plasma and urine could be useful as an adjunct to CT screening to guide decision-making regarding further invasive procedures in patients with pulmonary nodules.

Tyrosine kinase inhibitor therapy is an established standard of care for patients with NSCLC with EGFR mutations, but a worse prognosis has been observed in patients with specific EGFR exon-20 insertion mutations. Mobocertinib (TAK-788) is a novel tyrosine kinase inhibitor developed to target EGFR exon-20 insertion and has exhibited promising response rates and acceptable safety in phase 1 and 2 trials. We report a case of a 59-year-old woman with metastatic NSCLC and EGFR exon-20 mutation responsive to mobocertinib therapy, who developed severe depression and catatonia approximately 4 months after mobocertinib initiation, ultimately necessitating its permanent discontinuation. Given the observed severe depression in this case report, we recommend that, for patients on mobocertinib who develop neuropsychiatric adverse effects, strong consideration should be given for dose interruption or discontinuation.

9033 Background: STK11 mutation ( STK11m) in patients with stage IV NSCLC is associated with inferior survival and poor response to immune check point inhibitors (ICI). The significance of STK11m in patients (pts) with stage III NSCLC treated with concurrent chemoradiation (CCRT) with and without consolidation ICI is unknown. Methods: Patient demographics, disease characteristics, treatment received and outcomes in pts with stage III NSCLC that harbor STK11m were retrospectively reviewed from 4 cancer centers. A cohort of pts with stage III NSCLC and wild type STK11 (STK11w) from the University of Iowa served as a comparison group. SPSS version 25 was used for data analysis. Results: 75 pts with stage III NSCLC who had gene sequencing were included. 16/75 (21%) had STK11m. The clinical characteristics for the 16 STK11m and 59 STK11w pts showed ( STK11m vs. STK11w): mean age: 58 vs. 64 yrs, non-squamous histology: 11/16 (69%) vs. 37/59 (63%), KRAS co-mutation: 6/16 (38%) vs. 11/59 (19%), TP53 co-mutation: 9/16 (56%) vs. 15/59 (25%), PD-L1 ≥ 50%: 2/16 (13%) vs. 10/59 (17%), received CCRT 11/16 (69%) vs. 59/59 (100%) and consolidation ICI 6/16 (38%) vs. 17/59 (29%). Regarding the 6 STK11m pts who received ICI (4 pembrolizumab, 2 durvalumab), the median number of ICI infusions was 8 (range, 3-17) vs. 7 (range, 1-25) in the 17 pts with STK11w who received ICI (durvalumab). Progression free survival (PFS) for the STK11m vs. STK11w pts who received CCRT but not ICI was (4.2 vs. 34.3 months, respectively. P = 0.168), for the STK11m vs. STK11w pts who received CCRT and ICI was (11.3 vs. 17.5 months, respectively. P = 0.174), and for the STK11m vs. STK11w pts who received CCRT regardless of receiving ICI (11.3 vs. 32.9 months, respectively. P = 0.021). The median overall survival for STK11m pts (16 pts) was 25.5 months (95% CI, 13.7 to 37.2) while not yet reached for the STK11w group. Conclusions: In stage III NSCLC, STK11m was associated with inferior clinical outcomes. Larger studies are needed to identify the prognostic implications of STK11m in stage III NSCLC and whether ICI impacts survival for this subgroup.

33 Background: The Institute of Medicine and Commission on Cancer recommend systematic delivery of supportive oncology care for cancer patients. The CSOC is focused on quality improvement (QI) of supportive care across Chicago cancer centers (Weldon ASCO ’17). Supportive oncology includes distress, practical, family, physical, nutrition, pain, fatigue and care concerns. To support QI, cross-institution teams developed unique, relevant tools, methods, care delivery processes, patient handouts and online training. Methods: Ten centers (5 academic, 1 VA, 1 public, 2 safety net, 1 community) implemented supportive oncology screening and care delivery quality improvements. Centers collected data for relevant Quality Oncology Practice Initiative (QOPI) metrics. Analyses used simple frequencies and Fishers exact test. Results: Five of six QOPI measures were improved at statistically significant levels from 2014 to 2017, p < .00001. Improvements are more modest in 2016 & 2017 as 4 of the centers started this QI in 2017. Conclusions: The CSOC achieved significant improvements in supportive oncology screening and identifying and addressing patients’ needs and concerns. Additional work is needed to improve these measures to achieve the best quality of cancer care possible for every patient based on their needs and concerns. [Table: see text]

59 Background: A challenge in supportive oncology is training the HCP workforce. The Coleman Supportive Oncology Collaborative clinicians (faculty) from 25 institutions (academic, community & safety net) developed a unique and easily accessible supportive oncology training curriculum (Trosman JR JNCCN 2017). Methods: Using data provided by The National Comprehensive Cancer Network (NCCN) Continuing Education team, we evaluated completion rates of survivorship and supportive oncology education courses using simple frequencies. Results: Over 4748 on-line courses were completed (pretest, course, post-test, evaluation) of 7184 accessed. Of 4748 courses, nurses completed 45%, physicians 17%, advance practice clinicians 16%, and others 22% (social workers, chaplains, MAs). Course completion improved from 65% to 69% after articles describing collaborative work were published in Cure and Oncology Nursing News, p = 0.0014. Conclusions: A variety of HCPs successfully completed supportive oncology guideline education via the NCCN’s education portal. These on-line courses are an efficient way to train HCPs in supportive oncology. Curriculum advertising improves course completion.[Table: see text]

e18909Background: The goal of incorporating lung cancer screening programs into health systems is to identify cases of early stage lung cancer and thereby reduce mortality. However, there is limite...

19 Background: A challenge in supportive oncology, integral to patient care, is training the health professional workforce. A collaborative funded by The Coleman Foundation of 30+ clinicians (faculty) from 25 institutions (academic, community & safety net) developed a unique fundamental survivorship care (Weldon JCO 2017) and supportive oncology training curriculum (Trosman JNCCN 2017). Methods: Using data from The National Comprehensive Cancer Network Continuing Education team, we analyzed utilization of survivorship and supportive oncology education courses using simple frequencies. Results: Over 3200 courses were completed (pretest, course, post-test, evaluation) and 4850 accessed. Nurses completed 56%, physicians 15%, social workers/psychologists/support staff 14%, advance practice clinicians 8%, and various roles for the rest. Courses in table. Conclusions: NCCN’s education portal achieved strong utilization from a variety of healthcare professionals in these courses. The Coleman Supportive Oncology Collaborative supports improvement in supportive care with tools, processes and training and will continue to update/offer courses through this portal.[Table: see text]

61 Background: The Institute of Medicine (IOM) 2013 Report recommends that supportive oncology care start at cancer diagnosis; the Commission on Cancer (CoC) Standard 3.2 requires distress screening and indicated action. Screening tools are not standardized and often address only a portion of patients’ supportive oncology needs. Methods: A collaborative of 100+ clinicians, funded by The Coleman Foundation, developed a patient-centric screening tool adapted from NCCN Distress Problem List, IOM report and CoC standards, with validated sub-tools: PHQ-4 for anxiety and depression and PROMIS short forms for pain, fatigue and physical function. Novel treatment/care and other concerns were included. The screening tool was implemented at 4 cancer centers (2 academic, 1 public & 1 safety-net). End points included correlation of PHQ-4 score with other supportive oncology needs. Descriptive statistics, Fisher’s exact test were used. Results: 2805 patients were screened. Average scores were: PHQ4 – Anxiety and Depression 1.8 (mild > 3), Pain 4.5 (mild > 4), Fatigue 8.8 (mild > 6), Physical Function 20.2 (mild < 20), see table for additional items. Higher scores on the PHQ-4 were significantly associated with each of the following: greater pain, fatigue, , nutritional and specific treatment/care concerns, and lower physical function (p

e18071Background: While lung cancer is the leading cause of cancer death in the United States for both men and women its incidence and mortality rate differs depending on race, ethnicity, and gende...