Lung Cancer Screening Trial Research Articles

Other and All-Cause Mortality among Men Diagnosed with Prostate Cancer in the PLCO Trial

Men with prostate cancer have high cause-specific survival, and most deaths are from other causes. This study aimed to investigate other and all-cause mortality in a large cancer screening cohort. From the PLCO (Prostate, Lung, Colorectal and Ovarian) Cancer Screening Trial cohort, we selected men diagnosed with prostate cancer from 1994-2014. We examined other and all-cause survival by prostate cancer risk level, defined as the D'Amico categories for localized disease (low, intermediate and high risk) plus nonlocalized disease. We developed 3 Cox proportional hazards models to assess the relationship between risk level and survival. Model I controlled for age, race, study arm and diagnosis year. Model II additionally controlled for other demographic and medical history factors. Model III additionally controlled for initial treatment. Of 76,672 men in PLCO and 10,859 prostate cancer cases, 9,248 (85.2%) had known prostate cancer risk level (mean±SD age 70.4±6.2 years). Median followup time from diagnosis was 10.8 years (IQR 6.8-15.0). Of 3,318 deaths 81% were from other causes. Compared to the low risk group, other-cause mortality HRs were 1.13 (95% CI 1.04-1.23), 1.35 (95% CI 1.21-1.50) and 1.63 (95% CI 1.35-1.97) for intermediate risk, high risk and advanced disease, respectively, in model II. Model III HRs were similar to model II except for advanced disease, where the HR decreased to 1.35. Other-cause survival was greater in lower vs higher risk disease, even after controlling for lifestyle characteristics and comorbidities. Further research is needed to identify factors contributing to this higher other-cause mortality to help mitigate the risk.

A prospective study of the associations among fine particulate matter, genetic variants, and the risk of colorectal cancer

BackgroundFine particulate matter (PM2.5) is suspected to increase the risk of colorectal cancer, but the mechanism remains unknown. We aimed to investigate the association between PM2.5 exposure, genetic variants and colorectal cancer risk in the Prostate, Lung, Colon and Ovarian (PLCO) Cancer Screening trial. MethodsWe included a prospective cohort of 139,534 cancer-free individuals from 10 United States research centers with over ten years of follow-up. We used a Cox regression model to assess the association between PM2.5 exposure and colorectal cancer incidence by calculating the hazard ratio (HR) and 95% confidence interval (CI) with adjustment for potential confounders. The polygenic risk score (PRS) and genome-wide interaction analysis (GWIA) were used to evaluate the multiplicative interaction between PM2.5 exposure and genetic variants in regard to colorectal cancer risk. ResultsAfter a median of 10.43 years of follow-up, 1,666 participants had been diagnosed with colorectal cancer. PM2.5 exposure was significantly associated with an increased risk of colorectal cancer (HR = 1.27; 95% CI = 1.17–1.37 per 5 μg/m3 increase). Five independent susceptibility loci reached statistical significance at P < 1.22 × 10−8 in the interaction analysis. Furthermore, a joint interaction was observed between PM2.5 exposure and the PRS based on these five loci with colorectal cancer risk (P = 3.11 × 10−29). The Gene Ontology analysis showed that the vascular endothelial growth factor (VEGF) receptor signaling pathway was involved in the biological process of colorectal cancer. ConclusionsOur large-scale analysis has shown for the first time that long-term PM2.5 exposure potential increases colorectal cancer risk, which might be modified by genetic variants.

Lead-Time Trajectory of CA19-9 as an Anchor Marker for Pancreatic Cancer Early Detection

There is substantial interest in liquid biopsy approaches for cancer early detection among subjects at risk, using multi-marker panels. CA19-9 is an established circulating biomarker for pancreatic cancer; however, its relevance for pancreatic cancer early detection or for monitoring subjects at risk has not been established. CA19-9 levels were assessed in blinded sera from 175 subjects collected up to 5 years before diagnosis of pancreatic cancer and from 875 matched controls from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. For comparison of performance, CA19-9 was assayed in blinded independent sets of samples collected at diagnosis from 129 subjects with resectable pancreatic cancer and 275 controls (100 healthy subjects; 50 with chronic pancreatitis; and 125 with noncancerous pancreatic cysts). The complementary value of 2 additional protein markers, TIMP1 and LRG1, was determined. In the PLCO cohort, levels of CA19-9 increased exponentially starting at 2 years before diagnosis with sensitivities reaching 60% at 99% specificity within 0 to 6 months before diagnosis for all cases and 50% at 99% specificity for cases diagnosed with early-stage disease. Performance was comparable for distinguishing newly diagnosed cases with resectable pancreatic cancer from healthy controls (64% sensitivity at 99% specificity). Comparison of resectable pancreatic cancer cases to subjects with chronic pancreatitis yielded 46% sensitivity at 99% specificity and for subjects with noncancerous cysts, 30% sensitivity at 99% specificity. For prediagnostic cases below cutoff value for CA19-9, the combination with LRG1 and TIMP1 yielded an increment of 13.2% in sensitivity at 99% specificity (P= .031) in identifying cases diagnosed within 1 year of blood collection. CA19-9 can serve as an anchor marker for pancreatic cancer early detection applications.

Lung cancer screening by low-dose computed tomography: a cost-effectiveness analysis of alternative programmes in the UK using a newly developed natural history-based economic model

BackgroundA systematic review of economic evaluations for lung cancer identified no economic models of the UK setting based on disease natural history. We first sought to develop a new model of natural history for population screening, then sought to explore the cost-effectiveness of multiple alternative potential programmes.MethodsAn individual patient model (ENaBL) was constructed in MS Excel® and calibrated against data from the US National Lung Screening Trial. Costs were taken from the UK Lung Cancer Screening Trial and took the perspective of the NHS and PSS. Simulants were current or former smokers aged between 55 and 80 years and so at a higher risk of lung cancer relative to the general population. Subgroups were defined by further restricting age and risk of lung cancer as predicted by patient self-questionnaire. Programme designs were single, triple, annual and biennial arrangements of LDCT screens, thereby examining number and interval length. Forty-eight distinct screening strategies were compared to the current practice of no screening. The primary outcome was incremental cost-effectiveness of strategies (additional cost per QALY gained).ResultsLDCT screening is predicted to bring forward the stage distribution at diagnosis and reduce lung cancer mortality, with decreases versus no screening ranging from 4.2 to 7.7% depending on screen frequency. Overall healthcare costs are predicted to increase; treatment cost savings from earlier detection are outweighed by the costs of over-diagnosis. Single-screen programmes for people 55–75 or 60–75 years with ≥ 3% predicted lung cancer risk may be cost-effective at the £30,000 per QALY threshold (respective ICERs of £28,784 and £28,169 per QALY gained). Annual and biennial screening programmes were not predicted to be cost-effective at any cost-effectiveness threshold.LimitationsLDCT performance was unaffected by lung cancer type, stage or location and the impact of a national screening programme of smoking behaviour was not included.ConclusionLung cancer screening may not be cost-effective at the threshold of £20,000 per QALY commonly used in the UK but may be cost-effective at the higher threshold of £30,000 per QALY.

Abstract IA17: Lung cancer screening: a public health benefit that may deepen the divide

Abstract The National Lung Screening Trial (NLST) and most recently the Dutch–Belgian lung-cancer screening trial (NELSON) were transformative, demonstrating the efficacy of low-dose computed tomoagraphy (LDCT), and thus providing the evidence to support the implementation of screening for lung cancer, a cancer for which no efficacious screening strategy was previously available, into medical care. In a population at high risk for lung cancer as defined by age and smoking history, LDCT was associated with a 20-25% reduction on lung cancer mortality. In the absence of screening, only 16% of patients are diagnosed with a disease stage that has potential for cure by surgical resection. Lung cancer screening identifies cancer at an earlier, more treatable stage. Despite these results, a Grade B recommendation from the US Preventive Services Task Force and coverage by the Centers for Medicare and Medicaid Services, only 14.4% of those eligible underwent screening in 2017. The reasons for this reduction in access and utilization of lung cancer screening are multifactorial and include lack of provider time, limited patient and provider knowledge, and insufficient clinical and technological infrastructure. Further, there is an inverse relationship between the location of those at highest risk for lung cancer (e.g., individuals living in rural settings) and the access to lung cancer screening centers. While lung cancer screening has the potential to reduce mortality there is evidence to suggest that disparities in implementation will further widen existing gaps in lung cancer treatment and mortality among those of lower socioeconomic status, minorities, and un/underinsured populations. This presentation will highlight the challenges and suggest possible solutions. Citation Format: Nichole T. Tanner. Lung cancer screening: a public health benefit that may deepen the divide [abstract]. In: Proceedings of the AACR Virtual Conference: Thirteenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2020 Oct 2-4. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(12 Suppl):Abstract nr IA17.

Population-Based Screening for Endometrial Cancer: Human vs. Machine Intelligence.

Incidence and mortality rates of endometrial cancer are increasing, leading to increased interest in endometrial cancer risk prediction and stratification to help in screening and prevention. Previous risk models have had moderate success with the area under the curve (AUC) ranging from 0.68 to 0.77. Here we demonstrate a population-based machine learning model for endometrial cancer screening that achieves a testing AUC of 0.96.We train seven machine learning algorithms based solely on personal health data, without any genomic, imaging, biomarkers, or invasive procedures. The data come from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO). We further compare our machine learning model with 15 gynecologic oncologists and primary care physicians in the stratification of endometrial cancer risk for 100 women.We find a random forest model that achieves a testing AUC of 0.96 and a neural network model that achieves a testing AUC of 0.91. We test both models in risk stratification against 15 practicing physicians. Our random forest model is 2.5 times better at identifying above-average risk women with a 2-fold reduction in the false positive rate. Our neural network model is 2 times better at identifying above-average risk women with a 3-fold reduction in the false positive rate.Our machine learning models provide a non-invasive and cost-effective way to identify high-risk sub-populations who may benefit from early screening of endometrial cancer, prior to disease onset. Through statistical biopsy of personal health data, we have identified a new and effective approach for early cancer detection and prevention for individual patients.

Fatherhood status in relation to prostate cancer risks in two large U.S.-based prospective cohort studies.

BackgroundDespite the high incidence and mortality of prostate cancer (PCa) in the Unites States, few risk factors have been consistently linked with these PCa outcomes. Assessing proxies of reproductive factors may offer insights into PCa pathogenesis. In this study, we examined fatherhood status as a proxy of fertility in relation to total, nonaggressive, aggressive, and fatal PCa.MethodsWe examined participants of two cohorts, the NIH‐AARP Diet and Health (NIH‐AARP) Study and Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. We used Cox proportional hazards regression to estimate hazard ratios (HRs) and 95% confidence intervals of associations between fatherhood status and number of children sired in relation to PCa incidence.ResultsFatherhood status (one or more children vs. childless) was positively associated with total PCa risk in NIH‐AARP or PLCO, but was not statistically significant (p = 0.06 and 0.55, respectively). Number of children sired indicated a slightly elevated risk of total PCa, but HRs were rarely significant and were of a fairly constant magnitude with no discernable trend relative to the childless referent group. Associations were similar for nonaggressive and aggressive PCa. The trend test for fatal PCa was statistically significant in NIH‐AARP (p trend < 0.01), despite none of the individual categorical point estimates reaching this threshold.ConclusionThis study provides tentative evidence that fathering children is associated with a slightly increased PCa risk. Future research should strive to assess better proxies of reproductive function in relation to aggressive and fatal PCa to provide more specific evidence for this putative relationship.

Abstract 313: Deep Learning to Assess Cardiovascular Age From Chest Radiographs

Introduction: Chronological age is a well-known risk factor for cardiovascular disease, but measures of vascular age may enable more personalized care. We hypothesize that a convolutional neural network (CNN) can assess vascular age from a chest radiograph image. Methods: The CNN model, CXR-Age, was developed using data from over 100,000 indviduals from publicly available cohorts and was validated in 1) a subset of the Prostate, Lung, Colorectal, and Ovarian Cancer screening trial’s chest x-ray arm (PLCO, N = 40,967) and 2) the chest radiograph arm of the National Lung Screening Trial (NLST, N = 5,414). The primary outcome was 13-year cardiovascular mortality defined by ICD9 codes for ischemic heart disease, myocardial infarction, and stroke. Results are provided for independent testing datasets only. Results: After adjusting for sex, a 5-year increase in CXR-Age was a better predictor of cardiovascular mortality than a 5-year increase in chronological age in PLCO (CXR-Age aHR 2.69 per 5 years [95% CI 2.55-2.84] vs. chronological age aHR 1.84 per 5 years [95% CI 1.75-1.93], p &lt; 0.001) and NLST (CXR-Age aHR 2.06 per 5-years [95% CI, 1.78-2.39] vs. chronological age aHR 1.64 per 5 years [95% CI, 1.44-1.86], p = 0.06). This association with cardiovascular mortality was robust to adjustment for baseline cardiovascular risk factors (chronological age, sex, diabetes, hypertension, smoking) in PLCO (CXR-Age aHR 1.58 per 5 years [95% CI, 1.54-1.63], p &lt; 0.001) and NLST (CXR-Age aHR 1.48 per 5 years [95% CI, 1.36-1.61], p &lt; 0.001). Kaplan-Meier curves (Figure 1) stratified by chronological age groups show CXR-Age has a graded association with cardiovascular mortality in individuals with similar baseline chronological age. Conclusions: A CNN model, CXR-Age, can assess vascular age from a chest radiograph image, and this CXR-Age predicts cardiovascular mortality better than chronological age.

Psychological outcomes of low-dose CT lung cancer screening in a multisite demonstration screening pilot: the Lung Screen Uptake Trial (LSUT)

BackgroundPrevious studies of psychological burden in low-dose CT (LDCT) lung cancer screening trials may lack generalisability due to participation bias and control arms having elevated distress.MethodsCurrent and former smokers (n=787,...

Unexpected detection of SARS-CoV-2 antibodies in the prepandemic period in Italy.

There are no robust data on the real onset of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and spread in the prepandemic period worldwide. We investigated the presence of SARS-CoV-2 receptor-binding domain (RBD)–specific antibodies in blood samples of 959 asymptomatic individuals enrolled in a prospective lung cancer screening trial between September 2019 and March 2020 to track the date of onset, frequency, and temporal and geographic variations across the Italian regions. SARS-CoV-2 RBD-specific antibodies were detected in 111 of 959 (11.6%) individuals, starting from September 2019 (14%), with a cluster of positive cases (>30%) in the second week of February 2020 and the highest number (53.2%) in Lombardy. This study shows an unexpected very early circulation of SARS-CoV-2 among asymptomatic individuals in Italy several months before the first patient was identified, and clarifies the onset and spread of the coronavirus disease 2019 (COVID-19) pandemic. Finding SARS-CoV-2 antibodies in asymptomatic people before the COVID-19 outbreak in Italy may reshape the history of pandemic.

Blunted PTH response to vitamin D insufficiency/deficiency and colorectal neoplasia risk

In contrast to many observational studies, large-scale randomized trials do not support the protective role of vitamin D for the prevention of colorectal neoplasia. However, in previous studies, individuals with blunted parathyroid hormone (PTH) response to vitamin D insufficiency/deficiency (BPRVID), were not differentiated from those with high PTH response to vitamin D insufficiency/deficiency (HPRVID). Individuals with BPRVID are responsive to magnesium treatment, particularly treatment of magnesium plus vitamin D while those with HPRVID are responsive to vitamin D treatment. We prospectively compared these two distinct groups (i.e. BPRVID and HPRVID) for risk of incident adenoma, metachronous adenoma, and incident colorectal cancer (CRC) METHODS: Three nested case-control studies in the Prostate, Lung, Colorectal and Ovarian Cancer (PLCO) Screening Trial. We found optimal 25(OH)D levels were associated with a significantly reduced risk of CRC, primarily among women. The associations between 25(OH)D and CRC risk significantly differed by PTH levels, particularly among women. Compared to individuals with optimal levels for both 25(OH)D and PTH, all others were at an elevated risk of incident CRC, primarily in women. We found those with BPRVID had 2.56-fold significantly increased risk of CRC compared to 1.65-fold non-significantly increased risk for those with HPRVID. Among women, we observed those with BPRVID had 4.79-6.25-fold significantly increased risks of incident CRC and adenoma whereas those with HPRVID had 3.65-fold significantly increased risk of CRC. Individuals with BPRVID are at higher risks of incident adenoma and CRC compared to those with HPRVID, particularly among women.

Cancer-Specific Mortality, All-Cause Mortality, and Overdiagnosis in Lung Cancer Screening Trials: A Meta-Analysis.

Benefit of lung cancer screening using low-dose computed tomography (LDCT) in reducing lung cancer-specific and all-cause mortality is unclear. We undertook a meta-analysis to assess its associations with outcomes. We searched the literature and previous systematic reviews to identify randomized controlled trials comparing LDCT screening with usual care or chest radiography. We performed meta-analysis using a random effects model. The primary outcomes were lung cancer-specific mortality, all-cause mortality, and the cumulative incidence ratio of lung cancer between screened and unscreened groups as a measure of overdiagnosis. Meta-analysis was based on 8 trials with 90,475 patients that had a low risk of bias. There was a significant reduction in lung cancer-specific mortality with LDCT screening (relative risk = 0.81; 95% CI, 0.74-0.89); the estimated absolute risk reduction was 0.4% (number needed to screen = 250). The reduction in all-cause mortality was not statistically significant (relative risk = 0.96; 95% CI, 0.92-1.01), but the absolute reduction was consistent with that for lung cancer-specific mortality (0.34%; number needed to screen = 294). In the studies with the longest duration of follow-up, the incidence of lung cancer was 25% higher in the screened group, corresponding to a 20% rate of overdiagnosis. This meta-analysis showing a significant reduction in lung cancer-specific mortality, albeit with a tradeoff of likely overdiagnosis, supports recommendations to screen individuals at elevated risk for lung cancer with LDCT.

Variability in interpretation of low-dose chest CT using computerized assessment in a nationwide lung cancer screening program: comparison of prospective reading at individual institutions and retrospective central reading.

To evaluate the degree of variability in computer-assisted interpretation of low-dose chest CTs (LDCTs) among radiologists in a nationwide lung cancer screening (LCS) program, through comparison with a retrospective interpretation from a central laboratory. Consecutive baseline LDCTs (n = 3353) from a nationwide LCS program were investigated. In the institutional reading, 20 radiologists in 14 institutions interpreted LDCTs using computer-aided detection and semi-automated segmentation systems for lung nodules. In the retrospective central review, a single radiologist re-interpreted all LDCTs using the same system, recording any non-calcified nodules ≥ 3mm without arbitrary rejection of semi-automated segmentation to minimize the intervention of radiologist's discretion. Positive results (requiring additional follow-up LDCTs or diagnostic procedures) were initially classified by the lung CT screening reporting and data system (Lung-RADS) during the interpretation, while the classifications based on the volumetric criteria from the Dutch-Belgian lung cancer screening trial (NELSON) were retrospectively applied. Variabilities in positive rates were assessed with coefficients of variation (CVs). In the institutional reading, positive rates by the Lung-RADS ranged from 7.5 to 43.3%, and those by the NELSON ranged from 11.4 to 45.0% across radiologists. The central review exhibited higher positive rates by Lung-RADS (20.0% vs. 27.3%; p < .001) and the NELSON (23.1% vs. 37.0%; p < .001), and lower inter-institution variability (CV, 0.30 vs. 0.12, p = .003 by Lung-RADS; CV, 0.25 vs. 0.12, p = .014 by the NELSON) compared to the institutional reading. Considerable inter-institution variability in the interpretation of LCS results is caused by different usage of the computer-assisted system. • Considerable variability existed in the interpretation of screening LDCT among radiologists partly from the different usage of the computerized system. • A retrospective reading of low-dose chest CTs in the central laboratory resulted in reduced variability but an increased positive rate.

Associations between daily aspirin use and cancer risk across strata of major cancer risk factors in two large U.S. cohorts.

Daily aspirin use has been shown to reduce risk of colorectal, and possibly other, cancers, but it is unknown if these benefits are consistent across subgroups of people with differing cancer risk factors. We investigated whether age, body mass index (BMI), smoking status, physical inactivity, and family history of cancer modify the effect of daily aspirin use on colorectal, ovarian, breast, endometrial and aggressive prostate cancer risk. We pooled 423,495 individuals from two prospective, U.S.-based studies: the NIH-AARP Diet and Health Study (1995-2011) and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (1993-2009). Using Cox proportional hazards regression, we examined associations between daily aspirin use (≥ 5days/week) and risk of colorectal, ovarian, breast, endometrial, and aggressive prostate cancer, overall and across strata of risk factors. Daily aspirin use was associated with a 15% reduction in colorectal cancer risk (hazard ratio [HR]: 0.85, 95% confidence interval [CI] 0.80-0.89). Risk reductions were generally consistent across strata of risk factors but attenuated with increasing BMI (p-interaction = 0.16). For ovarian cancer, there was no significant association overall (HR: 0.93, 95% CI 0.80-1.08) but reduced risk among obese women (HR: 0.73, 95% CI 0.52-0.98, p-interaction = 0.12). Weak or null associations were observed for breast, endometrial, and aggressive prostate cancer, with no strong effect modification observed. Daily aspirin use appears to reduce colorectal cancer risk regardless of other risk factors, though the potential modifying effect of BMI warrants further investigation and may need to be considered in risk-benefit calculations for aspirin use.

Serum concentrations of per- and polyfluoroalkyl substances and risk of renal cell carcinoma: A nested case-control study in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial

Background: Per- and polyfluoroalkyl substances (PFAS) are a diverse class of industrial chemicals used in non-stick cookware, firefighting foams, and textiles. Exposure to PFAS is widespread in the general population, with detectable serum levels in 98% of U.S. adults. The International Agency for Research on Cancer has classified perfluorooctanoic acid (PFOA) as a possible kidney carcinogen; other PFAS have not yet been evaluated. The purpose of this study was to assess whether pre-diagnostic serum concentrations of PFOA and seven additional PFAS are associated with risk of renal cell carcinoma (RCC) in a large population-based cohort. Methods: We conducted a nested case-control study within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial that included 324 histologically-confirmed RCC cases and 324 individually matched controls. Serum concentrations of eight PFAS were quantified using on-line solid phase extraction liquid chromatography isotope dilution tandem mass spectrometry. Multivariable conditional logistic regression analysis was used to estimate RCC risk in relation to each individual PFAS modeled both continuously (Log2-transformed) and categorically. All models were implicitly conditioned on matching factors (e.g., age, sex, race, study center) and further adjusted for kidney function (i.e., estimated glomerular filtration rate) and other potential confounders. Results: In preliminary analyses, we observed positive exposure-response associations with RCC risk for several PFAS including PFOA, perfluorooctane sulfonic acid, and perfluorohexane sulfonic acid. However, only the association with PFOA remained apparent after adjustment for all three chemicals. Conclusions: This is, to our knowledge, the first study to investigate the associations between serum concentrations of individual PFAS and risk of RCC in a prospective cohort with PFAS concentrations comparable to the general population. Our findings may have important public health implications for the many individuals exposed to these ubiquitous and highly persistent chemicals.

Association study between genetic variants in retinol metabolism pathway genes and prostate cancer risk

BackgroundEvidence suggests that serum retinol level is associated with prostate cancer risk, but the association between genetic variants in the retinol metabolism pathway genes and prostate cancer risk remains unclarified.MethodsSingle‐nucleotide polymorphisms (SNPs) in 31 genes in the retinol metabolism pathway were genotyped to evaluate the association with prostate cancer risk in 4,662 cases and 3,114 controls from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. The gene expression analysis was evaluated using data from the Gene Expression Omnibus (GEO) datasets and the Cancer Genome Atlas (TCGA) database. Data from the Genotype‐Tissue Expression (GTEx) project dataset were utilized to perform the expression quantitative trait loci (eQTL) analysis.ResultsTwo SNPs were significantly associated with prostate cancer risk [rs1330286 in ALDH1A1: odds ratio (OR) = 0.88, 95% confidence interval (CI) = 0.83‐0.94, p = 2.45 × 10−4; rs4646653 in ALDH1A3: OR = 1.17, 95% CI =1.07‐1.27, p = 4.33 × 10−4]. Moreover, the mRNA level of ALDH1A3 was significantly higher in prostate cancer tissues than in normal tissues in both TCGA datasets and GEO datasets (p = 1.63 × 10−12 and p = 4.33 × 10−2, respectively). rs1330286 was an eQTL of ALDH1A1 (P = 2.90 × 10−3).ConclusionOur findings highlight that genetic variants in retinol metabolism pathway genes are associated with prostate cancer risk.

Lung cancer LDCT screening and mortality reduction - evidence, pitfalls and future perspectives.

In the past decade, the introduction of molecularly targeted agents and immune-checkpoint inhibitors has led to improved survival outcomes for patients with advanced-stage lung cancer; however, this disease remains the leading cause of cancer-related mortality worldwide. Two large randomized controlled trials of low-dose CT (LDCT)-based lung cancer screening in high-risk populations - the US National Lung Screening Trial (NLST) and NELSON - have provided evidence of a statistically significant mortality reduction in patients. LDCT-based screening programmes for individuals at a high risk of lung cancer have already been implemented in the USA. Furthermore, implementation programmes are currently underway in the UK following the success of the UK Lung Cancer Screening (UKLS) trial, which included the Liverpool Health Lung Project, Manchester Lung Health Check, the Lung Screen Uptake Trial, the West LondonLung Cancer Screening pilot and the Yorkshire Lung Screening trial. In this Review, we focus on the current evidence on LDCT-based lung cancer screening and discuss the clinical developments in high-risk populations worldwide; additionally, we address aspects such as cost-effectiveness. We present a framework to define the scope of future implementation research on lung cancer screening programmes referred to as Screening Planning and Implementation RAtionale for Lung cancer (SPIRAL).

Closing the gap in health care disparities by improving the rate of lung cancer screening in an intercity hospital.

195 Background: The National Lung Cancer Screening Trial showed reduced lung cancer mortality with low-dose computed tomography (LDCT) screening. Although LDCT is generally covered by private and government insurance, the rate of LDCT screening has been reported to be very low (2-3%) in previous studies. One of the main barriers in adequate screening was assessment of smoking history to identify eligible populations. Purpose: To increase the rate of lung cancer screening in Medstar Washington Hospital Center Internal Medicine (WHCIM) clinics from a baseline rate of 2.88% by 50% over a 3-month period. Methods: Retrospective baseline data was collected over a 2-week period 01/06/2020–01/17/2020 from patients visits at WHCIM to assess the rate of lung cancer screening. A session was held with physicians and nursing staff to find the barriers in identifying eligible patients for lung cancer screening and to create a fishbone diagram. The first plan-do-study act cycle (PDSA) was initiated from 02/24/2020–03/13/2020 where we piloted a clinical reminder in the form of a print-out filled out by the medical assistants at check in and then given to physicians. The form included the patient's age and simple smoking questionnaire according to the lung cancer screening guidelines. Data was collected during this time period which included documentation of patient’s smoking history, lung cancer screening eligibility and referral to LDCT. Results: By retrospective analysis from the time period of 01/06/2020-01/17/2020 providers documented a smoking history in only 16% of patients seen and only 2.88% of all patients seen over the age of 55 were referred for lung cancer screening. Post intervention for the time period of 02/24/2020-03/13/2020 increased the amount of documented smoking history by providers to 26% and number of patients sent for lung cancer screening to 6.0%. Of patients who met the criteria for lung cancer screening, prior to the intervention only 42% of patients were referred. However, after the clinical reminder has been initiated, 86% of patients who did meet the criteria were sent for screening. Conclusions: The clinical reminder has increased documentation of smoking history by 62% and lung cancer screening for those who meet the criteria according to the guidelines by a relative increase of 105%. We are currently working on PDSA cycle 2 to incorporate education materials in the encounter room and PDSA cycle 3 to incorporate this clinical reminder into the electronic medical record and to implement hospital wide.

IMPROVING RATE OF LUNG CANCER SCREENING IN PRIMARY CARE CLINIC

SESSION TITLE: Lung Cancer Posters SESSION TYPE: Original Investigation Posters PRESENTED ON: October 18-21, 2020 PURPOSE: The National Lung Cancer Screening Trial showed reduced lung cancer mortality with low-dose computed tomography (LDCT) screening. Although LDCT is generally covered by private and government insurance, the rate of LDCT screening is reported to be about 2-3% in previous studies. One of the main barrier in adequate screening was assessment of smoking history to identify eligible populations. Our study aims to address this barrier and improve the rate of lung cancer screening in Medstar Washington Hospital Center Internal Medicine (WHCIM) clinics. We aim to achieve an improvement from a baseline rate of 2.88% by 50% over a 3-month period. METHODS: Data from cumulative patient visits at WHCIM clinic was collected over a 2 week period to assess the baseline rate of LDCT screening. After multidisciplinary team meeting to assess the barriers in adequate screening, we piloted a clinical reminder in the form of print-out form given to physicians from the medical assistants. This served to remind physicians to take detailed smoking histories and included the current lung cancer screening guidelines. This reminder is being given to providers for each patient seen in the clinic and the results will be followed for the next 3 months. For this study post-intervention data was collected over a 2 week period. RESULTS: Preceding the intervention, providers documented a smoking history in 16% of patients seen where post-intervention was 26%. Prior to the clinical reminder 2.88% of all patients seen over the age of 55 were referred for lung cancer screening which has now increased to 6.0%. Of patients who met the criteria for lung cancer screening, prior to the intervention only 42% of patients were referred for LDCT. However, after the clinical reminder has been initiated, 86% of patients who did meet the criteria were sent for screening. CONCLUSIONS: Our intervention has increased documentation of smoking history by 62% and lung cancer screening, for those who meet the criteria according to the guidelines, by a relative increase of 105%. We are currently working on further interventions to incorporate this clinical reminder into the electronic medical record and to implement this across the Medstar Health Hospitals. CLINICAL IMPLICATIONS: Lung cancer is the leading cause of death not only in the United States, but throughout the world. Improving the rate of lung cancer screening by addressing barriers is a simple and cost-effective method that would go a long way in lowering lung cancer mortality. Furthermore, multidisciplinary team involvement helps address gaps in patient care in a holistic manner. DISCLOSURES: No relevant relationships by Anika Bhargava, source=Web Response No relevant relationships by Akshay Kohli, source=Web Response no disclosure on file for Irina Veytsman

Assessing Different Approaches to Leveraging Historical Smoking Exposure Data to Better Select Lung Cancer Screening Candidates: A Retrospective Validation Study

There is mounting interest in the use of risk prediction models to guide lung cancer screening. Electronic health records (EHRs) could facilitate such an approach, but smoking exposure documentation is notoriously inaccurate. While the negative impact of inaccurate EHR data on screening practices reliant on dichotomized age and smoking exposure-based criteria has been demonstrated, less is known regarding its impact on the performance of model-based screening. Data were collected from a cohort of 37 422 ever-smokers between the ages of 55 and 74, seen at an academic safety-net healthcare system between 1999 and 2018. The National Lung Cancer Screening Trial (NLST) criteria, PLCOM2012 and LCRAT lung cancer risk prediction models were validated against time to lung cancer diagnosis. Discrimination (area under the receiver operator curve [AUC]) and calibration were assessed. The effect of substituting the last documented smoking variables with differentially retrieved "history conscious" measures was also determined. The PLCOM2012 and LCRAT models had AUCs of 0.71 (95% CI, 0.69 to 0.73) and 0.72 (95% CI, 0.70 to 0.74), respectively. Compared with the NLST criteria, PLCOM2012 had a significantly greater time-dependent sensitivity (69.9% vs. 64.5%, p < .01) and specificity (58.3% vs. 56.4%, p < .001). Unlike the NLST criteria, the performances of the PLCOM2012 and LCRAT models were not prone to historical variability in smoking exposure documentation. Despite the inaccuracies of EHR-documented smoking histories, leveraging model-based lung cancer risk estimation may be a reasonable strategy for screening, and is of greater value compared with using NLST criteria in the same setting. EHRs are potentially well suited to aid in the risk-based selection of lung cancer screening candidates, but healthcare providers and systems may elect not to leverage EHR data due to prior work that has shown limitations in structured smoking exposure data quality. Our findings suggest that despite potential inaccuracies in the underlying EHR data, screening approaches that use multivariable models may perform significantly better than approaches that rely on simpler age and exposure-based criteria. These results should encourage providers to consider using pre-existing smoking exposure data with a model-based approach to guide lung cancer screening practices.