The risk and benefit profiles of US eligible lung cancer screening attendees vs. non-attendees.

BACKGROUND: The United States Preventive Services Task Force (USPSTF) recommend lung-cancer screening for individuals aged 50-80 with ≥20 pack-years and ≤15 quit-years, but uptake is low. The risk and benefit profiles of screening attendees are unknown; consequently, the impact and lost opportunity of ongoing lung-cancer screening in the US remains unclear. METHODS: We estimated lung-cancer death risk (using the Lung Cancer Death Risk Assessment Tool) and life gained from screening (using the LYFS-CT model) for individuals 50-79 who ever-smoked in the US-representative 2022 Behavioral Risk Factor Surveillance System. We compared lung-cancer death risk and life-gained among USPSTF-eligible individuals by screening status (self-reported screened vs not screened in past year), and estimated the number of lung-cancer deaths averted and life-years gained under current screening levels and if everyone eligible was screened. RESULTS: USPSTF-eligibility was 33.7% (95%CI:33.1-34.4%), of whom 17.9% (95%CI : 17.0-18.8%) self-reported screening. Screening uptake increased with increasing lung-cancer death risk quintile (Q1 = 5.2% (95%CI : 3.0%-8.8%); Q5 = 21.8% (95%CI : 20.3%-23.3%)) and life-gain from screening quintile (Q1 = 6.2% (95%CI : 3.8%-9.9%); Q5 = 20.8% (95%CI : 19.5%-22.2%)). Screened individuals had higher lung-cancer death risk (Risk Ratio [RR]=1.35, 95%CI : 1.26-1.46) and life-years gained (RR = 1.19, 95%CI : 1.12-1.25) than unscreened individuals. Currently screening averts 19,306 lung-cancer deaths and gains 237,564 life-years; screening everyone eligible would additionally avert 56,956 lung-cancer deaths and gain 751,850 life-years. Two-thirds of USPSTF-lung-eligible women were up-to-date with breast-cancer screening, but only 17.3% attended lung screening in the past year. CONCLUSIONS: Eligible screening attendees had higher lung-cancer death risk and benefit from screening. Higher rates of screening could substantially increase the number of lung-cancer deaths prevented.

Increasing power in screening trials by testing control-arm specimens: Application to multicancer detection screening.

BACKGROUND: Cancer screening trials have required large sample-sizes and long time-horizons to demonstrate cancer mortality reductions, the primary goal of cancer screening. We examine assumptions and potential power gains from exploiting information from testing control-arm specimens, which we call the "Intended Effect" (IE) analysis that we explain in detail herein. The IE analysis is particularly suited to tests that can be conducted on stored specimens in the control-arm, such as stored blood for multicancer detection (MCD) tests. METHODS: We simulated hypothetical MCD screening trials to compare power and sample-size for the standard vs IE analysis. Under two assumptions that we detail herein, we projected the IE analysis for 3 existing screening trials (National Lung Screening Trial (NLST), Minnesota Colon Cancer Control Study (MINN-FOBT-A), and Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial-colorectal component (PLCO-CRC)). RESULTS: Compared to the standard analysis for the 3 existing trials, the IE design could have reduced cancer-specific mortality p-values 5-fold (NLST), 33-fold (MINN-FOBT-A), or 14,160-fold (PLCO-CRC), or alternately, reduced sample-size (90% power) by 26% (NLST), 48% (MINN-FOBT-A), or 59% (PLCO-CRC). For potential MCD trial designs requiring 100,000 subjects per-arm to achieve 90% power for multi-cancer mortality for the standard analysis, the IE analysis achieves 90% power for only 37,500-50,000 per arm, depending on assumptions concerning control-arm test-positives. CONCLUSIONS: Testing stored specimens in the control arm of screening trials to conduct the IE analysis could substantially increase power to reduce sample-size or accelerate trials, and provide particularly strong power gains for MCD tests.

Cancer screening with multicancer detection tests: A translational science review.

Multicancer detection (MCD) tests use a single, easily obtainable biospecimen, such as blood, to screen for more than one cancer concurrently. MCD tests can potentially be used to improve early cancer detection, including cancers that currently lack effective screening methods. However, these tests have unknown and unquantified benefits and harms. MCD tests differ from conventional cancer screening tests in that the organ responsible for a positive test is unknown, and a broad diagnostic workup may be necessary to confirm the location and type of underlying cancer. Among two prospective studies involving greater than 16,000 individuals, MCD tests identified those who had some cancers without currently recommended screening tests, including pancreas, ovary, liver, uterus, small intestine, oropharyngeal, bone, thyroid, and hematologic malignancies, at early stages. Reported MCD test sensitivities range from 27% to 95% but differ by organ and are lower for early stage cancers, for which treatment toxicity would be lowest and the potential for cure might be highest. False reassurance from a negative MCD result may reduce screening adherence, risking a loss in proven public health benefits from standard-of-care screening. Prospective clinical trials are needed to address uncertainties about MCD accuracy to detect different cancers in asymptomatic individuals, whether these tests can detect cancer sufficiently early for effective treatment and mortality reduction, the degree to which these tests may contribute to cancer overdiagnosis and overtreatment, whether MCD tests work equally well across all populations, and the appropriate diagnostic evaluation and follow-up for patients with a positive test.

Absolute lung cancer risk increases among individuals with >15 quit-years: Analyses to inform the update of the American Cancer Society lung cancer screening guidelines.

BACKGROUND: This report quantifies counteracting effects of quit-years and concomitant aging on lung cancer risk, especially on exceeding 15 quit-years, when the US Preventive Services Task Force (USPSTF) recommends curtailing lung-cancer screening. METHODS: Cox models were fitted to estimate absolute lung cancer risk among Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO) and National Lung Screening Trial (NLST) participants who ever smoked. Absolute lung cancer risk and gainable years of life from screening for individuals aged 50 to 80 in the US-representative National Health Interview Survey (NHIS) 2015-2018 who ever smoked were projected. Relaxing USPSTF recommendations to 20/25/30 quit-years versus augmenting USPSTF criteria with individuals whose estimated gain in life expectancy from screening exceeded 16.2 days according to the Life Years From Screening-CT (LYFS-CT) prediction model was compared. RESULTS: Absolute lung cancer risk increased by 8.7%/year (95% CI, 7.7%-9.7%; p < .001) as individuals aged beyond 15 quit-years in the PLCO, with similar results in NHIS and NLST. For example, mean 5-year lung cancer risk for those aged 65 years with 15 quit-years = 1.47% (95% CI, 1.35%-1.59%) versus 1.76% (95% CI, 1.62%-1.90%) for those aged 70 years with 20 quit-years in the PLCO. Removing the quit-year criterion would make 4.9 million more people eligible and increase the proportion of preventable lung cancer deaths prevented (sensitivity) from 63.7% to 74.2%. Alternatively, augmentation using LYFS-CT would make 1.7 million more people eligible while increasing the lung cancer death sensitivity to 74.0%. CONCLUSIONS: Because of aging, absolute lung cancer risk increases beyond 15 quit-years, which does not support exemption from screening or curtailing screening once it has been initiated. Compared with relaxing the USPSTF quit-year criterion, augmentation using LYFS-CT could prevent most of the deaths at substantially superior efficiency, while also preventing deaths among individuals who currently smoke with low intensity or long duration.

Inflammatory Tongue Conditions and Risk of Oral Tongue Cancer Among the US Elderly Individuals.

PURPOSE: The incidence of oral tongue cancers has increased since the 1980s among US men and women for unknown reasons. We investigated associations of inflammatory tongue conditions with risk of cancers of the oral tongue, other oral cavity, and oropharynx among the US elderly individuals (age 65 years or older). METHODS: We conducted a case-control study (2,534 oral tongue cancers, 6,832 other oral cavity cancers, 9,373 oropharyngeal cancers, and 200,000 controls) within the SEER-Medicare data set (1992-2013). Medicare records were used to identify patients with clinically diagnosed inflammatory tongue conditions (glossitis, benign migratory glossitis, median rhomboid glossitis, atrophic glossitis, glossodynia, other specified conditions [eg, atrophy and hypertrophy], and other unspecified conditions) and oral precancer (leukoplakia/erythroplakia). Only conditions preceding cancer/control selection by >12 months were included. RESULTS: The prevalence of inflammatory tongue conditions was significantly higher in patients with tongue cancer than controls (6.0% v 0.6%; odds ratios [ORs], adjusted for age, sex, race, Medicare utilization, and precancer, 5.8 [95% CI, 4.7 to 7.2]). This overall association primarily arose from glossitis, 5.6 (95% CI, 4.4 to 7.2); other specified conditions, 9.1 (95% CI, 5.5 to 15.2); and other unspecified conditions, 13.7 (95% CI, 8.0 to 23.7). These associations remained strongly elevated >5 years preceding tongue cancer (arguing against reverse causation), for conditions diagnosed by a specialist (arguing against misclassification), and among patients who received an oral biopsy (arguing against missed cancer). During 2013, an estimated 1 in 11 patients with oral tongue cancer had a preceding diagnosis of inflammatory tongue conditions. Associations of inflammatory tongue conditions were relatively weak for other oral cavity cancers (ORs, 1.8 [95% CI, 1.5 to 2.3]) and oropharyngeal cancer (OR, 1.3 [95% CI, 1.0 to 1.6]) and were observed only closest to cancer diagnosis. CONCLUSION: Inflammatory tongue conditions were associated with strongly increased risks of oral tongue cancers and preceded cancer diagnosis by several years, underscoring the need for increased clinical surveillance among patients with such apparently benign diagnoses.

Methods for Using Race and Ethnicity in Prediction Models for Lung Cancer Screening Eligibility.

Importance: Using race and ethnicity in clinical prediction models can reduce or inadvertently increase racial and ethnic disparities in medical decisions. Objective: To compare eligibility for lung cancer screening in a contemporary representative US population by refitting the life-years gained from screening-computed tomography (LYFS-CT) model to exclude race and ethnicity vs a counterfactual eligibility approach that recalculates life expectancy for racial and ethnic minority individuals using the same covariates but substitutes White race and uses the higher predicted life expectancy, ensuring that historically underserved groups are not penalized. Design, Setting, and Participants: The 2 submodels composing LYFS-CT NoRace were refit and externally validated without race and ethnicity: the lung cancer death submodel in participants of a large clinical trial (recruited 1993-2001; followed up until December 31, 2009) who ever smoked (n = 39 180) and the all-cause mortality submodel in the National Health Interview Survey (NHIS) 1997-2001 participants aged 40 to 80 years who ever smoked (n = 74 842, followed up until December 31, 2006). Screening eligibility was examined in NHIS 2015-2018 participants aged 50 to 80 years who ever smoked. Data were analyzed from June 2021 to September 2022. Exposure: Including and removing race and ethnicity (African American, Asian American, Hispanic American, White) in each LYFS-CT submodel. Main Outcomes and Measures: By race and ethnicity: calibration of the LYFS-CT NoRace model and the counterfactual approach (ratio of expected to observed [E/O] outcomes), US individuals eligible for screening, predicted days of life gained from screening by LYFS-CT. Results: The NHIS 2015-2018 included 25 601 individuals aged 50 to 80 years who ever smoked (2769 African American, 649 Asian American, 1855 Hispanic American, and 20 328 White individuals). Removing race and ethnicity from the submodels underestimated lung cancer death risk (expected/observed [E/O], 0.72; 95% CI, 0.52-1.00) and all-cause mortality (E/O, 0.90; 95% CI, 0.86-0.94) in African American individuals. It also overestimated mortality in Hispanic American (E/O, 1.08, 95% CI, 1.00-1.16) and Asian American individuals (E/O, 1.14, 95% CI, 1.01-1.30). Consequently, the LYFS-CT NoRace model increased Hispanic American and Asian American eligibility by 108% and 73%, respectively, while reducing African American eligibility by 39%. Using LYFS-CT with the counterfactual all-cause mortality model better maintained calibration across groups and increased African American eligibility by 13% without reducing eligibility for Hispanic American and Asian American individuals. Conclusions and Relevance: In this study, removing race and ethnicity miscalibrated LYFS-CT submodels and substantially reduced African American eligibility for lung cancer screening. Under counterfactual eligibility, no one became ineligible, and African American eligibility increased, demonstrating the potential for maintaining model accuracy while reducing disparities.

Increase in power by obtaining 10 or more controls per case when type-1 error is small in large-scale association studies.

BACKGROUND: The rule of thumb that there is little gain in statistical power by obtaining more than 4 controls per case, is based on type-1 error α = 0.05. However, association studies that evaluate thousands or millions of associations use smaller α and may have access to plentiful controls. We investigate power gains, and reductions in p-values, when increasing well beyond 4 controls per case, for small α. METHODS: We calculate the power, the median expected p-value, and the minimum detectable odds-ratio (OR), as a function of the number of controls/case, as α decreases. RESULTS: As α decreases, at each ratio of controls per case, the increase in power is larger than for α = 0.05. For α between 10-6 and 10-9 (typical for thousands or millions of associations), increasing from 4 controls per case to 10-50 controls per case increases power. For example, a study with power = 0.2 (α = 5 × 10-8) with 1 control/case has power = 0.65 with 4 controls/case, but with 10 controls/case has power = 0.78, and with 50 controls/case has power = 0.84. For situations where obtaining more than 4 controls per case provides small increases in power beyond 0.9 (at small α), the expected p-value can decrease by orders-of-magnitude below α. Increasing from 1 to 4 controls/case reduces the minimum detectable OR toward the null by 20.9%, and from 4 to 50 controls/case reduces by an additional 9.7%, a result which applies regardless of α and hence also applies to "regular" α = 0.05 epidemiology. CONCLUSIONS: At small α, versus 4 controls/case, recruiting 10 or more controls/cases can increase power, reduce the expected p-value by 1-2 orders of magnitude, and meaningfully reduce the minimum detectable OR. These benefits of increasing the controls/case ratio increase as the number of cases increases, although the amount of benefit depends on exposure frequencies and true OR. Provided that controls are comparable to cases, our findings suggest greater sharing of comparable controls in large-scale association studies.

Recalibration of a Deep Learning Model for Low-Dose Computed Tomographic Images to Inform Lung Cancer Screening Intervals.

Importance: Annual low-dose computed tomographic (LDCT) screening reduces lung cancer mortality, but harms could be reduced and cost-effectiveness improved by reusing the LDCT image in conjunction with deep learning or statistical models to identify low-risk individuals for biennial screening. Objective: To identify low-risk individuals in the National Lung Screening Trial (NLST) and estimate, had they been assigned a biennial screening, how many lung cancers would have been delayed 1 year in diagnosis. Design, Setting, and Participants: This diagnostic study included participants with a presumed nonmalignant lung nodule in the NLST between January 1, 2002, and December 31, 2004, with follow-up completed on December 31, 2009. Data were analyzed for this study from September 11, 2019, to March 15, 2022. Exposures: An externally validated deep learning algorithm that predicts malignancy in current lung nodules using LDCT images (Lung Cancer Prediction Convolutional Neural Network [LCP-CNN]; Optellum Ltd) was recalibrated to predict 1-year lung cancer detection by LDCT for presumed nonmalignant nodules. Individuals with presumed nonmalignant lung nodules were hypothetically assigned annual vs biennial screening based on the recalibrated LCP-CNN model, Lung Cancer Risk Assessment Tool (LCRAT + CT [a statistical model combining individual risk factors and LDCT image features]), and the American College of Radiology recommendations for lung nodules, version 1.1 (Lung-RADS). Main Outcomes and Measures: Primary outcomes included model prediction performance, the absolute risk of a 1-year delay in cancer diagnosis, and the proportion of people without lung cancer assigned a biennial screening interval vs the proportion of cancer diagnoses delayed. Results: The study included 10 831 LDCT images from patients with presumed nonmalignant lung nodules (58.7% men; mean [SD] age, 61.9 [5.0] years), of whom 195 were diagnosed with lung cancer from the subsequent screen. The recalibrated LCP-CNN had substantially higher area under the curve (0.87) than LCRAT + CT (0.79) or Lung-RADS (0.69) to predict 1-year lung cancer risk (P < .001). If 66% of screens with nodules were assigned to biennial screening, the absolute risk of a 1-year delay in cancer diagnosis would have been lower for recalibrated LCP-CNN (0.28%) than LCRAT + CT (0.60%; P = .001) or Lung-RADS (0.97%; P < .001). To delay only 10% of cancer diagnoses at 1 year, more people would have been safely assigned biennial screening under LCP-CNN than LCRAT + CT (66.4% vs 40.3%; P < .001). Conclusions and Relevance: In this diagnostic study evaluating models of lung cancer risk, a recalibrated deep learning algorithm was most predictive of 1-year lung cancer risk and had least risk of 1-year delay in cancer diagnosis among people assigned biennial screening. Deep learning algorithms could prioritize people for workup of suspicious nodules and decrease screening intensity for people with low-risk nodules, which may be vital for implementation in health care systems.

Upper age limits for US male human papillomavirus vaccination for oropharyngeal cancer prevention: a microsimulation-based modeling study.

BACKGROUND: Human papillomavirus (HVP)-positive oropharyngeal cancer is the most common HPV-associated cancer in the United States. The age at acquisition of oral HPV infections that cause oropharyngeal cancer (causal infections) is unknown; consequently, the benefit of vaccination of US men aged 27-45 years remains uncertain. METHODS: We developed a microsimulation-based, individual-level, state-transition model of oral HPV16 and HPV16-positive oropharyngeal cancer among heterosexual US men aged 15-84 years, calibrated to population-level data. We estimated the benefit of vaccination of men aged 27-45 years for prevention of oropharyngeal cancer, accounting for direct- and indirect effects (ie, herd effects) of male and female vaccination. RESULTS: In the absence of vaccination, most (70%) causal oral HPV16 infections are acquired by age 26 years, and 29% are acquired between ages 27 and 45 years. Among men aged 15-45 years in 2021 (1976-2006 birth cohorts), status quo vaccination of men through age 26 years is estimated to prevent 95% of 153 450 vaccine-preventable cancers. Assuming 100% vaccination in 2021, extending the upper age limit to 30, 35, 40, or 45 years for men aged 27-45 years (1976-1994 cohorts) is estimated to yield small benefits (3.0%, 4.2%, 5.1%, and 5.6% additional cancers prevented, respectively). Importantly, status quo vaccination of men through age 26 years is predicted to result in notable declines in HPV16-positive oropharyngeal cancer incidence in young men by 2035 (51% and 24% declines at ages 40-44 years and 45-49 years, respectively) and noticeable declines (12%) overall by 2045. CONCLUSION: Most causal oral HPV16 infections in US men are acquired by age 26 years, underscoring limited benefit from vaccination of men aged 27-45 years for prevention of HPV16-positive oropharyngeal cancers.

Study design considerations for trials to evaluate multicancer early detection assays for clinical utility.

Blood-based assays using various technologies and biomarkers are in commercial development for the purpose of detecting multiple cancer types concurrently at an early stage of disease. These multicancer early detection (MCED) assays have the potential to improve the detection of cancers, particularly those for which no current screening modality exists. However, the unknown clinical benefits and harms of using MCED assays for cancer screening necessitate the development and implementation of a randomized controlled trial (RCT) to ascertain their clinical effectiveness. This was the consensus of experts at a National Cancer Institute-hosted workshop to discuss initial design concepts for such a trial. Using these assays to screen simultaneously for multiple cancers poses novel uncertainties for patient care compared with conventional screening tests for single cancers, such as establishing the diagnostic workup to confirm the presence of cancer at any organ site; clarifying appropriate follow-up for a positive assay for which there is no definitive diagnosis; identifying potential harms such as overdiagnosis of indolent disease; determining clinically effective and efficient strategies for disseminating MCED screening in real-world practice; and understanding the ethical implications, such as potentially alleviating or exacerbating existing health disparities. These assays present new and complex challenges for designing an RCT. Issues that emerged from the meeting centered around the need for a flexibly designed, clinical utility RCT to rigorously capture the evidence required to fully understand the net benefit of this promising technology. Specific topic areas were endpoints, screening protocols, recruitment, diagnostic pathway, pilot phase, data elements, specimen collection, and ethical considerations.

Variation in Human Papillomavirus Vaccination Effectiveness in the US by Age at Vaccination.

This survey study assesses the status and timing of HPV vaccination as self-reported by female participants in the National Health and Nutrition Examination Survey from 2011 to 2018.

Decoupling blood telomere length from age in recipients of allogeneic hematopoietic cell transplant in the BMT-CTN 1202.

The age of allogeneic hematopoietic cell transplant (HCT) donors and their hematopoietic cell telomere length (TL) might affect recipients' outcomes. Our goals were to examine the possible effect of these donors' factors on the recipients' hematopoietic cell TL and quantify hematopoietic cell TL shortening in the critical first three-month post-HCT. We measured hematopoietic cell TL parameters in 75 recipient-donor pairs, from the Blood and Marrow Transplant Clinical Trials Network (protocol#1202), by Southern blotting (SB), the Telomeres Shortest Length Assay (TeSLA), and quantitative PCR (qPCR). Recipients' hematopoietic cell TL parameters post-HCT correlated with donors' age (p<0.001 for all methods), but not recipients' own age, and with donors' pre-HCT hematopoietic cell TL (p<0.0001 for all). Multivariate analyses showed that donors' hematopoietic cell TL pre-HCT, independent of donors' age, explained most of the variability in recipients' hematopoietic cell TL post-HCT (81% for SB, 56% for TeSLA, and 65% for qPCR; p>0.0001 for all). SB and TeSLA detected hematopoietic cell TL shortening in all recipients post-HCT (mean=0.52kb and 0.47kb, respectively; >15-fold the annual TL shortening in adults; p<0.00001 for both), but qPCR detected shortening only in 57.5% of recipients. TeSLA detected a buildup of post-HCT of telomeres <3 kb in 96% of recipients (p<0.0001). In conclusion, HCT decouples hematopoietic cell TL in the recipients from their own age to reflect the donors' age. The potential donors' age effect on outcomes of HCT might be partially mediated by short hematopoietic cell TL in older donors. qPCR-based TL measurement is suboptimal for detecting telomere shortening post-HCT.

Independent and joint associations of weightlifting and aerobic activity with all-cause, cardiovascular disease and cancer mortality in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial.

OBJECTIVES: Both aerobic moderate to vigorous physical activity (MVPA) and muscle-strengthening exercise (MSE) are recommended, but the mortality benefits of weightlifting, a specific type of MSE, are limited. METHODS: In the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial, we used Cox proportional hazards regression to calculate hazard ratios (HRs) and 95% CIs for the associations between weightlifting and mortality, adjusting for demographics, lifestyle and behavioural risk factors. The sample included 99 713 adults who completed the follow-up questionnaire that assessed weightlifting who were subsequently followed up through 2016 to determine mortality (median 9, IQR 7.6-10.6 years). RESULTS: Mean age at the follow-up questionnaire was 71.3 (IQR 66-76) years, 52.6% female, with mean body mass index of 27.8 (SD 4.9) kg/m2. Weightlifting was associated with a 9% lower risk of all-cause mortality (HR=0.91 (95% CI 0.88 to 0.94)) and CVD mortality (0.91 (95% CI 0.86 to 0.97)) after adjusting for MVPA. Joint models revealed that adults who met aerobic MVPA recommendations but did not weightlift had a 32% lower all-cause mortality risk (HR=0.68 (95% CI 0.65 to 0.70)), while those who also reported weightlifting 1-2 times/week had a 41% lower risk (HR=0.59 (95% CI 0.54 to 0.64)), both compared with adults reporting no aerobic MVPA or weightlifting. Without adjustment for MVPA, weightlifting was associated with lower cancer mortality (HR=0.85 (95% CI 0.80 to 0.91)). CONCLUSION: Weightlifting and MVPA were associated with a lower risk of all-cause and CVD mortality, but not cancer mortality. Adults who met recommended amounts of both types of exercise appeared to gain additional benefit.

Sex disparities in the incidence of 21 cancer types: Quantification of the contribution of risk factors.

BACKGROUND: Cancer incidence is higher in men than in women at most shared anatomic sites for currently unknown reasons. The authors quantified the extent to which behaviors (smoking and alcohol use), anthropometrics (body mass index and height), lifestyles (physical activity, diet, medications), and medical history collectively explain the male predominance of risk at 21 shared cancer sites. METHODS: Prospective cohort analyses (n = 171,274 male and n = 122,826 female participants; age range, 50-71 years) in the National Institutes of Health-AARP Diet and Health Study (1995-2011). Cancer-specific Cox regression models were used to estimate male-to-female hazard ratios (HRs). The degree to which risk factors explained the observed male-female risk disparity was quantified using the Peters-Belson method. RESULTS: There were 26,693 incident cancers (17,951 in men and 8742 in women). Incidence was significantly lower in men than in women only for thyroid and gallbladder cancers. At most other anatomic sites, the risks were higher in men than in women (adjusted HR range, 1.3-10.8), with the strongest increases for bladder cancer (HR, 3.33; 95% confidence interval [CI], 2.93-3.79), gastric cardia cancer (HR, 3.49; 95% CI, 2.26-5.37), larynx cancer (HR, 3.53; 95% CI, 2.46-5.06), and esophageal adenocarcinoma (HR, 10.80; 95% CI, 7.33-15.90). Risk factors explained a statistically significant (nonzero) proportion of the observed male excess for esophageal adenocarcinoma and cancers of liver, other biliary tract, bladder, skin, colon, rectum, and lung. However, only a modest proportion of the male excess was explained by risk factors (ranging from 50% for lung cancer to 11% for esophageal adenocarcinoma). CONCLUSIONS: Men have a higher risk of cancer than women at most shared anatomic sites. Such male predominance is largely unexplained by risk factors, underscoring a role for sex-related biologic factors.

Inaccuracies in electronic health records smoking data and a potential approach to address resulting underestimation in determining lung cancer screening eligibility.

OBJECTIVE: The US Preventive Services Task Force (USPSTF) requires the estimation of lifetime pack-years to determine lung cancer screening eligibility. Leading electronic health record (EHR) vendors calculate pack-years using only the most recently recorded smoking data. The objective was to characterize EHR smoking data issues and to propose an approach to addressing these issues using longitudinal smoking data. MATERIALS AND METHODS: In this cross-sectional study, we evaluated 16 874 current or former smokers who met USPSTF age criteria for screening (50-80 years old), had no prior lung cancer diagnosis, and were seen in 2020 at an academic health system using the Epic® EHR. We described and quantified issues in the smoking data. We then estimated how many additional potentially eligible patients could be identified using longitudinal data. The approach was verified through manual review of records from 100 subjects. RESULTS: Over 80% of evaluated records had inaccuracies, including missing packs-per-day or years-smoked (42.7%), outdated data (25.1%), missing years-quit (17.4%), and a recent change in packs-per-day resulting in inaccurate lifetime pack-years estimation (16.9%). Addressing these issues by using longitudinal data enabled the identification of 49.4% more patients potentially eligible for lung cancer screening (P < .001). DISCUSSION: Missing, outdated, and inaccurate smoking data in the EHR are important barriers to effective lung cancer screening. Data collection and analysis strategies that reflect changes in smoking habits over time could improve the identification of patients eligible for screening. CONCLUSION: The use of longitudinal EHR smoking data could improve lung cancer screening.

Patient Perspectives on the Risk-Based NLST Outcomes Tool for Lung Cancer Screening.

Researchers at the NCI have developed the Risk-Based NLST Outcomes Tool (RNOT), an online tool that calculates risk of lung cancer diagnosis and death with and without lung cancer screening, and false-positive risk estimates. This tool has the potential to facilitate shared decision making for screening. The objective of this study was to examine how current heavy and former smokers understand and respond to personalized risk estimates from the RNOT. Individuals who were eligible for lung cancer screening and were visiting Walter Reed National Military Medical Center were invited to participate in a semi-structured interview to assess their experiences with and perceptions of the RNOT. Results were analyzed using template analysis. Participants found their risk of lung cancer death to be lower than anticipated and were confused by changes in risk for lung cancer diagnosis with and without screening. Most participants indicated that the RNOT would be helpful in making screening decisions, despite reporting that there was no maximum risk for a false positive that would lead them to forgo lung cancer screening. Participants provided actionable needs and recommendations to optimize this tool. Risk-based screening tools may enhance shared decision making. The RNOT is being updated to incorporate these findings.

A Quantitative Framework to Study Potential Benefits and Harms of Multi-Cancer Early Detection Testing.

BACKGROUND: Multi-cancer tests offer screening for multiple cancers with one blood draw, but the potential population impact is poorly understood. METHODS: We formulate mathematical expressions for expected numbers of: (i) individuals exposed to unnecessary confirmation tests (EUC), (ii) cancers detected (CD), and (iii) lives saved (LS) given test performance, disease incidence and mortality, and mortality reduction. We add colorectal, liver, lung, ovary, and pancreatic cancer to a test for breast cancer, approximating prevalence at ages 50, 60, or 70 using incidence over the next 5 years and mortality using corresponding probabilities of cancer death over 15 years in the Surveillance, Epidemiology, and End Results registry. RESULTS: EUC is overwhelmingly determined by specificity. For a given specificity, EUC/CD is most favorable for higher prevalence cancers. Under 99% specificity and sensitivities as published for a 50-cancer test, EUC/CD is 1.1 for breast + lung versus 1.3 for breast + liver at age 50. Under a common mortality reduction associated with screening, EUC/LS> is most favorable when the test includes higher mortality cancers (e.g., 19.9 for breast + lung vs. 30.4 for breast + liver at age 50 assuming a common 10% mortality reduction). CONCLUSIONS: Published multi-cancer test performance suggests a favorable tradeoff of EUC to CD, yet the full burden of unnecessary confirmations will depend on the posttest work-up protocol. Harm-benefit tradeoffs will be improved if tests prioritize more prevalent and/or lethal cancers for which curative treatments exist. IMPACT: The population impact of multi-cancer testing will depend not only on test performance but also on disease characteristics and efficacy of early treatment.See related commentary by Duffy and Sasieni, p. 3.

Management of Lung Cancer Screening Results Based on Individual Prediction of Current and Future Lung Cancer Risks.

OBJECTIVES: We propose a risk-tailored approach for management of lung cancer screening results. This approach incorporates individual risk factors and low-dose computed tomography (LDCT) image features into calculations of immediate and next-screen (1-y) risks of lung cancer detection, which in turn can recommend short-interval imaging or 1-year or 2-year screening intervals. METHODS: We first extended the "LCRAT+CT" individualized risk calculator to predict lung cancer risk after either a negative or abnormal LDCT screen result. To develop the abnormal screen portion, we analyzed 18,129 abnormal LDCT results in the National Lung Screening Trial (NLST), including lung cancers detected immediately (n = 649) or at the next screen (n = 235). We estimated the potential impact of this approach among NLST participants with any screen result (negative or abnormal). RESULTS: Applying the draft National Health Service (NHS) England protocol for lung screening to NLST participants referred 76% of participants to a 2-year interval, but delayed diagnosis for 40% of detectable cancers. The Lung Cancer Risk Assessment Tool+Computed Tomography (LCRAT+CT) risk model, with a threshold of less than 0.95% cumulative lung cancer risk, would also refer 76% of participants to a 2-year interval, but would delay diagnosis for only 30% of cancers, a 25% reduction versus the NHS protocol. Alternatively, LCRAT+CT, with a threshold of less than 1.7% cumulative lung cancer risk, would also delay diagnosis for 40% of cancers, but would refer 85% of participants for a 2-year interval, a 38% further reduction in the number of required 1-year screens beyond the NHS protocol. CONCLUSIONS: Using individualized risk models to determine management in lung cancer screening could substantially reduce the number of screens or increase early detection.

Inflammatory markers in women with reported benign gynecologic pathology: an analysis of the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial.

BACKGROUND: Associations between benign gynecologic pathologies and circulating inflammatory markers are unknown. Our goal was to evaluate self-reported history of benign gynecologic pathology and subsequent alterations in systemic inflammation. METHODS: Using nested case-control studies from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial, study-specific associations between self-reported history of benign ovarian cysts, uterine fibroids, and endometriosis with inflammatory marker concentrations were evaluated using logistic regression and combined using meta-analysis. Inflammatory markers associated with individual benign pathologies were mutually adjusted for one another to evaluate independent associations. RESULTS: Compared to women without a self-reported history of the pathology evaluated, benign ovarian cysts were associated with increased PAI-1 (OR [95% CI] 6.24 [2.53-15.39], P <.001) and TGF-ß1 (3.79 [1.62-8.86], P =.002) and decreased BCA-1 (0.38 [0.19-0.73], P =.004). Uterine fibroids were associated with decreased CXCL11 (0.37 [0.22-0.63], P <.001) and VEGFR3 (0.40 [0.24-0.65], P <.001). Endometriosis was associated with increased SIL-4R (4.75 [1.84-12.26], P =.001). CONCLUSIONS: Self-reported history of benign gynecologic pathologies were associated with alterations in inflammatory markers that have been previously linked to cancer risk. Understanding interactions between benign gynecologic pathologies and the systemic immune system may help inform disease risk later in life.