Screening Trial Research Articles

Cancers not detected in one-view breast tomosynthesis screening-characteristics and reasons for non-detection.

Limited understanding exists regarding non-detected cancers in digital breast tomosynthesis (DBT) screening. This study aims to classify non-detected cancers into true or false negatives, compare them with true positives, and analyze reasons for non-detection. Conducted between 2010 and 2015, the prospective single-center Malmö Breast Tomosynthesis Screening Trial (MBTST) compared one-view DBT and two-view digital mammography (DM). Cancers not detected by DBT, i.e., interval cancers, those detected in the next screening round, and those only identified by DM, underwent a retrospective informed review by in total four breast radiologists. Reviewers classified cancers into true negative, false negative, or non-visible based on both DBT and DM findings and assessed radiographic appearances at screening and diagnosis, breast density, and reasons for non-detection. Statistics included the Pearson X2 test. In total, 89 cancers were not detected with DBT in the MBTST; eight cancers were solely in the DM reading mode, 59 during subsequent DM screening rounds, and 22 interval cancers. The proportion of cancers classified as false negative was 25% (22/89) based on DBT, compared with 18% (14/81) based on DM screening. The primary reason for false negatives was normal-appearing density, 50% (11/22). False negatives exhibited lower rates of high breast density, 36% (8/22), compared with true positives, 61% (78/129), p = 0.04, and spiculated densities were less frequent in false negatives, 41% (9/22) compared with true positives, 68% (88/129), p = 0.01. False negatives in one-view DBT screening commonly presented with spiculated features, but less frequently than true positives, and were missed or misinterpreted due to benign appearances. Question Cancers not detected in digital breast tomosynthesis screening, including false negatives, remain partly unexplored. Findings The most common reason behind false-negative cancers in a large screening trial was a normal-appearing density. Clinical relevance Recognizing the factors contributing to false negative findings in digital breast tomosynthesis screening is essential to further improve cancer detection.

Genetic variants of FER and SULF1 in the fibroblast-related genes are associated with non-small-cell lung cancer survival.

Fibroblasts are important components in the tumor microenvironment and can affect tumor progression and metastasis. However, the roles of genetic variants of the fibroblast-related genes (FRGs) in the prognosis of non-small-cell lung cancer (NSCLC) patients have not been reported. Therefore, we investigated the associations between 26,544 single nucleotide polymorphisms (SNPs) in 291 FRGs and survival of NSCLC patients from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. In Cox regression multivariable analysis, we found that 661 SNPs were associated with NSCLC overall survival (OS). Then we validated these SNPs in another independent replication dataset of 984 patients from the Harvard Lung Cancer Susceptibility (HLCS) Study. Finally, we identified two independent SNPs (i.e., FER rs7716388 A>G and SULF1 rs11785839 G>C) that remained significantly associated with NSCLC survival with hazards ratios (HRs) of 0.87 (95% confidence interval [CI] = 0.77-0.98, p = 0.018) and 0.88 (95% CI = 0.79-0.99, p = 0.033), respectively. Combined analysis for these two SNPs showed that the number of protective alleles was associated with better OS and disease-specific survival. Expression quantitative trait loci analysis indicated that the FER rs7716388 G allele was associated with the up-regulation of FER mRNA expression levels in lung tissue. Our results indicated that these two functional SNPs in the FRGs may be prognostic biomarkers for the prognosis of NSCLC patients, and the possible mechanism may be through modulating the expression of their corresponding genes.

Risk-based breast cancer screening: What are the challenges?

Population-based screening programs aim to detect the disease at an early stage, so less treatment will be needed as well as having better oncological outcomes when diagnosed earlier. In the majority of European countries, breast cancer screening programs are designed based on women age.Meta-analysis of randomized clinical trial data demonstrates a reduction in the relative risk of breast cancer mortality due to screening, which has been estimated to be approximately 20%.One of the controversies about the population breast screening programs is that age-based screening ignores women's individual breast cancer risk. Identification of high-risk women may intensify the screening measures and will optimize the population screening programs to align them to individual risks.Family history of breast cancer is one of the risk factors to consider along with the recently developed polygenic risk scores to stratify women into a risk group. Other factors to assess risk include: mammographic breast density; B3 lesions with atypia in breast biopsy specimens; hormonal and lyfestyle and, potentially, epigenetic markers. Still, there are some difficulties in validating these factors and reflecting the interaction between risk factors in the models.Ongoing screening trials (e.g., WISDOM and MyPebs) are currently evaluating the clinical acceptability and utility of risk-stratified screening programs in the general population, and should provide valuable information for the possible implementation of such programs.Communication of complex risk information to the women, as well as assessing ethical concerns need to be addressed before implementation of risk stratified programs.

Evaluation of primary HPV-based cervical screening among older women: Long-term follow-up of a randomized healthcare policy trial in Sweden.

Evidence on invasive cervical cancer prevention among older women is limited, especially with the introduction of human papillomavirus (HPV)-based screening and longer interval. We conducted a long-term follow-up of the first phase of a randomized healthcare policy trial in cervical screening, targeting women aged 56 to 61 years old, to investigate the effectiveness of primary HPV-based screening in preventing invasive cervical cancer (ICC) and the safety of extending screening interval. The randomized healthcare policy trial of primary HPV-based cervical screening targeted women residing in Stockholm-Gotland region during 2012 to 2016, aged 30 to 64 years. The trial aimed to investigate the detection rate of cervical intraepithelial neoplasia grade 2 or worse (CIN2+) within 24 months and long-term protection against invasive cervical cancer, comparing primary HPV-based screening to primary cytology-based screening. The initial phase of the trial, which was the focus of this study, targeted women aged 56 to 61 years old in 2012 to 2014 who were randomized to primary cytology arm (n = 7,401) or primary HPV arm (n = 7,318). We used national registries to identify the subsequent cervical tests and all histopathological diagnoses including ICC before December 31, 2022. We calculated cumulative incidence, incidence rate (IR) and IR ratio (IRR) of ICC, by baseline test result. Furthermore, we calculated longitudinal sensitivity and specificity for detecting cervical intraepithelial neoplasia grade 2 or worse (CIN2+) by receipt of primary cytology or primary HPV test for the recommended screening intervals in this age group. We found that the IR of ICC among women in the primary HPV arm was 7.2/100,000 person-years (py) and 3.0 for women who tested HPV negative, compared to 18.4/100,000 py among women in the primary cytology arm and 18.8 for women who tested cytology negative. We further found that the overall point estimate for the risk of ICC over 10 years of follow-up among women in the primary HPV arm was 0.39 compared to women in the primary cytology arm, but this was not statistically significant (IRR: 0.39; 95% confidence interval, CI [0.14, 1.09]; p = 0.0726). However, among women with a negative test result at baseline, women in the primary HPV arm had an 84% lower risk of ICC compared to women in the primary cytology arm (IRR: 0.16; 95% CI [0.04, 0.72]; p = 0.0163). Moreover, primary HPV testing had a higher sensitivity for detecting CIN2+ within a 7-year interval than primary cytology testing within a 5-year interval (89.6% versus 50.9%, p < 0.0001). We were limited by a partial imbalance of invitations during the follow-up between the 2 arms which may have led to an underestimation of the effectiveness of primary HPV-based screening. In this study, we observed that women over 55 years of age who received a primary negative HPV test result had substantially lower risk of CIN2+, and ICC, compared to women who received a primary negative cytology result. This should apply even if the screening interval were prolonged to 7 years. NCT01511328.

Testing stored control-arm specimens could dramatically increase statistical power yet reduce costs in cancer screening trials.

Testing stored control-arm specimens could dramatically increase statistical power yet reduce costs in cancer screening trials.

Prospective evaluation of lung cancer screening eligibility criteria and lung cancer detection in the Yorkshire Lung Screening Trial.

Low dose CT (LDCT) screening for lung cancer reduces lung cancer mortality, but there is a lack of international consensus regarding the optimal eligibility criteria for screening. The Yorkshire Lung Screening Trial (YLST) was designed to evaluate lung cancer screening (LCS) implementation and a primary objective was prospective evaluation of 3 pre-defined eligibility criteria. Individuals who had ever smoked, aged 55-80yrs, who responded to written invitation, underwent telephone risk assessment and if eligible by at least one criteria (PLCOM2012≥1.51%, LLPv2≥5%, USPSTF2013) were offered biennial LDCT screening. Of 44,957 individuals invited, 22,814 responded and underwent eligibility assessment, of whom a total of 7,826 were eligible according to any of the three LCS criteria. Comparing PLCOM2012≥1.51%, LLPv2≥5%, and USPSTF2013, the proportions of responders eligible for screening were 28.0%, 20.5% and 18.9% respectively (p<0.0001 for each comparison), and the proportion of all cancers detected 91.1%, 77.0%, and 62.8% respectively (p≤0.0002 for each comparison). When risk thresholds were selected to result in equivalent numbers of people eligible for screening, cancer detection proportions were higher for PLCOM2012 (74.5%) and LLPv2 (71.3%) than USPSTF2013 (62.8%) (p=0.0002 and p=0.032 respectively) but there was no significant difference between the two risk models. Reducing the LLPv2 risk threshold from 5% to 2.5% (as currently used in the English lung cancer screening programme) and reducing the pack-year requirement for the USPSTF2021 vs the USPSTF2013 criteria increased the numbers eligible for screening, but subsequent cancer yield was not measured in this study. The PLCOM2012≥1.51% criteria identified more people eligible for screening in YLST and resulted in more screen-detected lung cancers than LLPv2≥5% or USPSTF2013. When compared in equivalent populations, there was no significant difference between risk models in terms of lung cancer detection and each appeared more efficient at screening population selection than USPSTF2013.

Standardization and advancements efforts in breast diffusion-weighted imaging.

Recent advancements in breast magnetic resonance imaging (MRI) have significantly enhanced breast cancer detection and characterization. Breast MRI offers superior sensitivity, particularly valuable for high-risk screening and assessing disease extent. Abbreviated protocols have emerged, providing efficient cancer detection while reducing scan time and cost. Diffusion-weighted imaging (DWI), a non-contrast technique, has shown promise in differentiating malignant from benign lesions. It offers shorter scanning times and eliminates contrast agent risks. Apparent diffusion coefficient (ADC) values provide quantitative measures for lesion characterization, potentially reducing unnecessary biopsies. Studies have revealed some correlations between ADC values and hormone receptor status in breast cancers, although substantial variability exists among studies. However, standardization remains challenging. Initiatives such as European Society of Breast Imaging (EUSOBI), Diffusion-Weighted Imaging Screening Trial (DWIST), Quantitative Imaging Biomarkers Alliance (QIBA) have proposed guidelines to ensure consistency in imaging protocols and equipment specifications, addressing variability in ADC measurements across different sites and vendors. Advanced techniques like Intravoxel incoherent motion (IVIM) and non-Gaussian DWI offer insights into tissue microvasculature and microstructure. Despite ongoing challenges, the integration of these advanced MRI techniques shows great promise for improving breast cancer diagnosis, characterization, and treatment planning. Continued research and standardization efforts are crucial for maximizing the potential of breast DWI in enhancing patient care and outcomes.

A Framework for Considering the Value of Race and Ethnicity in Estimating Disease Risk.

Accounting for race and ethnicity in estimating disease risk may improve the accuracy of predictions but may also encourage a racialized view of medicine. To present a decision analytic framework for considering the potential benefits of race-aware over race-unaware risk predictions, using cardiovascular disease, breast cancer, and lung cancer as case studies. Cross-sectional study. NHANES (National Health and Nutrition Examination Survey), 2011 to 2018, and NLST (National Lung Screening Trial), 2002 to 2004. U.S. adults. Starting with risk predictions from clinically recommended race-aware models, the researchers generated race-unaware predictions via statistical marginalization. They then estimated the utility gains of the race-aware over the race-unaware models, based on a simple utility function that assumes constant costs of screening and constant benefits of disease detection. The race-unaware predictions were substantially miscalibrated across racial and ethnic groups compared with the race-aware predictions as the benchmark. However, the clinical net benefit at the population level of race-aware predictions over race-unaware predictions was smaller than expected. This result stems from 2 empirical patterns: First, across all 3 diseases, 95% or more of individuals would receive the same decision regardless of whether race and ethnicity are included in risk models; second, for those who receive different decisions, the net benefit of screening or treatment is relatively small because these patients have disease risks close to the decision threshold (that is, the theoretical "point of indifference"). When used to inform rationing, race-aware models may have a more substantial net benefit. For illustrative purposes, the race-aware models were assumed to yield accurate estimates of risk given the input variables. The researchers used a simplified approach to generate race-unaware risk predictions from the race-aware models and a simple utility function to compare models. The analysis highlights the importance of foregrounding changes in decisions and utility when evaluating the potential benefit of using race and ethnicity to estimate disease risk. The Greenwall Foundation.

Moving toward Equity through Embedded ELSI Ethnography.

This paper describes the unique values of, challenges within, and opportunities presented by embedded ELSI ethnography. Drawing from our six-year embedded ELSI study of the WISDOM (Women Informed to Screen Depending on Measures of Risk) trial, we present three examples of the variable ways we engaged with the WISDOM trial's scientific team. WISDOM is a preference-sensitive, pragmatic, randomized controlled trial of risk-based breast cancer screening informed by genomics. Our embedded ELSI approach included multiple modes of engagement: (a) Trial investigators sought bioethics expertise; for example, we were asked to consult on traditional bioethics topics such as consent as well as more complex questions about whether to implement a specific risk-assessment approach on only one race-defined group of trial participants. (b) As the ELSI investigators, we identified ethical concerns in issues that surfaced via ethnography and considered them in the Bioethics Working Group; for example, there were concerns about the implementation processes that the WISDOM team viewed as logistical challenges. (c) Our presence in WISDOM working group conversations and our expertise on classic social science topics, including race and gender, offered opportunities to engage on the spot with topics such as how to include transgender participants in a trial initially focused on "women's health"; through such engagement, the value of social science became clear to the trial investigators. The paper elaborates on the dynamic relationship between our ethnographic observations, the Bioethics Working Group discussions, and the contributions of each to our real-time ELSI interventions in these examples. The methods and experiences we describe here suggest modes of engagement that, in combination, have the potential to expand the role of ELSI to offer real-time intervention on issues related to equity, inclusion, and justice in genetic and genomic research.

The role of artificial intelligence in drug screening, drug design, and clinical trials

The role of artificial intelligence in drug screening, drug design, and clinical trials

Association of dietary patterns derived by reduced-rank regression with colorectal cancer risk and mortality.

Unhealthy dietary patterns contribute to an increased risk of colorectal cancer (CRC). Limited prior research has used reduced rank regression (RRR) to assess dietary patterns relative to CRC risk. This study aimed to identify dietary patterns derived by RRR and assess their associations with CRC risk and mortality. We used data from the multicentre Prostate, Lung, Colorectal, and Ovarian Cancer Screening (PLCO) trial. Dietary intake was assessed using a Dietary History Questionnaire. In the RRR intake of fibre, folate, and the percentage of energy from carbohydrates, saturated and unsaturated fatty acids were used as response variables. Cox models and competing risk survival regression, with age as the time scale, were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for CRC risk and mortality, respectively. The median follow-up time for CRC risk (n = 1044) and mortality (n = 499) was 9.4 years (Interquartile Range: 8. 0, 10.1) and 16.9 years (11.9, 18.6), respectively. Two dietary patterns were identified: the first was characterised by high carbohydrate, folate and low fatty acid intake, and the second by high fibre and unsaturated fatty acid. Compared to participants in the first tertile of the high fibre and unsaturated fatty acid pattern, those in the third tertile had a lower risk of CRC (HR = 0.88; 95% CI: 0.76, 1.03), and colon cancer (HR = 0.85; 95% CI: 0.72, 1.01). Conversely, the high carbohydrate, high folate and low fatty acid pattern had no association with CRC outcomes. None of the dietary patterns showed associations with rectal cancer or CRC mortality. A diet enriched with high fibre and unsaturated fatty acids may reduce the risk of CRC. These results highlight the potential protective effect of adequate fibre intake in conjunction with high consumption of unsaturated fatty acids against CRC.

Respiratory Function as a Prognostic Factor for Lung Cancer in Screening and General Populations.

Despite advancements in screening, lung cancer remains the leading cause of cancer-related mortality globally. To investigate respiratory function as a prognostic factor for survival in the UK Biobank, a population-based cohort of over 500,000 participants, and the National Lung Screening Trial (NLST), a high-risk screening population of over 50,000 screenees. Participants with an incident lung cancer diagnosis and spirometry-assessed lung function were included. Lung cancer was measured as the ratio of forced expiratory volume in 1-second (FEV1) and forced vital capacity and percentage of predicted FEV1. Multivariable Cox proportional hazards models were fitted to estimate the impact of lung function on 5-year overall survival in populations with different baseline lung cancer risks. 2,690 and 609 patients were included in the analysis from the UK Biobank and the NLST, respectively. In the UK Biobank, a higher percentage of predicted FEV1 and ratio were associated with better survival after lung cancer diagnosis with hazard ratios of 0.97 (95% CI: 0.95 - 1.00, per 10% increase) and 0.95 (95% CI: 0.90 - 1.00, per 10% increase), respectively. No statistically significant results were found when assessing the data from the NLST study. Impaired lung function was associated with poorer survival for lung cancer patients in the general population, although this was less clear in a high risk, screening eligible population. This highlights the potential clinical importance of respiratory function as a prognostic factor in lung cancer in the general population and presents a possibility for personalized cancer management.

Survival Stacking Ensemble Model for Lung Cancer Risk Prediction.

The most well-established risk factor for lung cancer (LC) is smoking, responsible for approximately 85% of cases. The Lung Cancer Risk Assessment Tool (LCRAT) is a key advancement in this field, which predicts individual risk based on factors like smoking habits, demographic details, personal and family medical history, and environmental exposures. This paper proposes a model with fewer features that improves state of the art performance, using a simplified stacking ensemble, making it more accessible and easier to implement in routine healthcare practice. The data used in this work were derived from two cohorts in the United States: The National Lung Screening Trial (NLST) and the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Both our model and LCRAT achieve an AUC of 0.799 and 0.782 on test respectively. In terms of percentage of positives, in the 50% of the population, both detect 0.766 and 0.754 of the cases. The ensemble of different survival models enhances robustness by mitigating the weakness of individual models and directly impacts the efficiency of the model, increasing the efficiency and generalizability.

Low Dose Computed Tomography for Lung Cancer Screening in Tuberculosis Endemic Countries: A Systematic Review and Meta-Analysis

IntroductionLung cancer screening (LCS) using low-dose computed tomography (LDCT) reduces mortality. Nevertheless, in high tuberculosis-burden countries (HTBC), there are concerns about high false-positive rates due to persistent lung lesions from prior tuberculosis (TB) infections. This study aims to evaluate the screen-positive rate (SPR) of LDCT screening in HTBC. MethodsWe conducted a systematic review and meta-analysis to identify studies utilizing LDCT for LCS in HTBC and reported SPR from inception to December 6, 2023. The primary outcome was the SPR, and the secondary outcome was the lung cancer detection rate (LCDR). The summary data was pooled using a random-effects model, and factors influencing the SPR were analyzed using multivariable meta-regression analysis. ResultsA total of 44 studies with 477,424 individuals (59.3% men) were included in the systematic review. Lung Imaging Reporting and Data System (Lung-RADS) (31%, 14 studies) and National Lung Screening Trial (NLST) criteria (non-calcified nodule ≥ 4 mm; 10 studies) were the most common criteria used for assessing SPR. The pooled SPR and LCDR were 18.36% (95% confidence interval [CI]: 14.6–22.1) and 0.94% (95% confidence interval: 0.75–1.15), respectively. Although SPR was significantly higher with NLST criteria than Lung-RADS criteria (25.6% versus 10.4%, p < 0.0001), the LCDR remained similar (0.91% versus 0.95%, p = 0.92). Studies using NLST criteria had a higher SPR in multivariable meta-regression analysis. Nevertheless, the analysis is limited by significant statistical heterogeneity and publication bias. ConclusionLung cancer screening by LDCT in HTBC demonstrates comparable SPR and LCDR to regions with lower TB incidence rates. Lung-RADS criteria are preferable to NLST criteria for LCS in HTBC to mitigate false-positive rates.

Survival outcomes of population-wide colonoscopy screening: reanalysis of the NordICC data

BackgroundColonoscopy as a common screening practice to prevent colorectal cancer lacks strong evidence. NordICC, the first randomized trial of colonoscopy screening, reported no clear clinical benefit for colonoscopy in the intention-to-screen population with suggested benefit in the risk of colorectal incidence and cancer-specific mortality in the per-protocol analyses. However, although the study was designed to perform survival analysis, no survival outcomes were reported since the underlying assumption for hazard ratio was not valid. We aimed to assess whether colonoscopy screening is associated with improved survival outcomes compared with usual care.MethodsWe reconstructed patient-level data from the Kaplan-Meier estimator of the primary endpoints reported in NordICC for the intention-to-screen and adjusted per-protocol populations. The restricted-mean survival time difference (RMST-D) and restricted-mean time loss ratio (RMTL-R), which are robust alternatives to the hazard ratio without specific model assumptions, were calculated for colorectal cancer incidence and death.ResultsIn this study, no significant difference in colorectal cancer incidence over 10 years was found in the intention-to-screen population (RMST-D: -0.68 days, 95% CI -3.9–2.6; RMTL-R: 1.04, 95% CI 0.88–1.22) or in the per-protocol analysis population (RMST-D: -2.9 days, 95% CI -6.5–0.67; RMTL-R: 1.15, 95% CI 0.97–1.35). In the intention-to-screen population, inviting individuals to colonoscopy did not improve colorectal-cancer death (RMST-D: -0.29 days, 95% CI -1.6–1.0; RMTL-R: 1.07, 95% CI 0.78–1.48). Over 10 years, in the per-protocol analysis, individuals who underwent colonoscopy survived an average of 1.1 more days free of colorectal cancer, but this difference was not statistically significant (RMST-D: 95% CI -0.13–2.3; RMTL-R: 0.72, 95% CI 0.49–1.07).ConclusionsIn this reanalysis of the NordICC data, no evidence of improvement in survival outcomes for participants invited to undergo colonoscopy compared to usual care was identified, even when assuming that all invited participants did undergo colonoscopy. Thus, our results do not support the use of colonoscopy as a population-wide screening test as a mean to decrease colorectal cancer incidence or death.RegistryNot applicable.

Leveraging Deep Learning of Chest Radiograph Images to Identify Individuals at High Risk for Chronic Obstructive Pulmonary Disease.

This study assessed whether deep learning applied to routine outpatient chest X-rays (CXRs) can identify individuals at high risk for incident chronic obstructive pulmonary disease (COPD). Using cancer screening trial data, we previously developed a convolutional neural network (CXR-Lung-Risk) to predict lung-related mortality from a CXR image. In this study, we externally validated CXR-Lung-Risk to predict incident COPD from routine CXRs. We identified outpatients without lung cancer, COPD, or emphysema who had a CXR taken from 2013-2014 at a Mass General Brigham site in Boston, Massachusetts. The primary outcome was 6-year incident COPD. Discrimination was assessed using AUC compared to the TargetCOPD clinical risk score. All analyses were stratified by smoking status. A secondary analysis was conducted in the Project Baseline Health Study (PBHS) to test associations between CXR-Lung-Risk with pulmonary function and protein abundance. The primary analysis consisted of 12,550 ever-smokers (mean age 62·4±6·8 years, 48.9% male, 12.4% rate of 6-year COPD) and 15,298 never-smokers (mean age 63·0±8·1 years, 42.8% male, 3.8% rate of 6-year COPD). CXR-Lung-Risk had additive predictive value beyond the TargetCOPD score for 6-year incident COPD in both ever-smokers (CXR-Lung-Risk + TargetCOPD AUC: 0·73 [95% CI: 0·72-0·74] vs. TargetCOPD alone AUC: 0·66 [0·65-0·68], p<0·01) and never-smokers (CXR-Lung-Risk + TargetCOPD AUC: 0·70 [0·67-0·72] vs. TargetCOPD AUC: 0·60 [0·57-0·62], p<0·01). In secondary analyses of 2,097 individuals in the PBHS, CXR-Lung-Risk was associated with worse pulmonary function and with abundance of SCGB3A2 (secretoglobin family 3A member 2) and LYZ (lysozyme), proteins involved in pulmonary physiology. In external validation, a deep learning model applied to a routine CXR image identified individuals at high risk for incident COPD, beyond known risk factors. The Project Baseline Health Study and this analysis were funded by Verily Life Sciences, San Francisco, California. NCT03154346.

A generalized health index: automated thoracic CT-derived biomarkers predict life expectancy.

To identify image biomarkers associated with overall life expectancy from low-dose computed tomography and integrate them as an index for assessing an individual's health. Two categories of CT image features, body composition tissues and cardiopulmonary vasculature characteristics, were quantified from LDCT scans in the Pittsburgh Lung Screening Study cohort(n = 3,635). Cox proportional-hazards models identified significant image features which were integrated with subject demographics to predict the subject's overall hazard. Subjects were stratified using composite model predictions and feature-specific risk stratification thresholds. The model's performance was validated extensively, including 5-fold cross-validation on PLuSS baseline, PLuSS follow-up examinations, and the National Lung Screening Trial (NLST). The composite model had significantly improved prognostic ability compared to the baseline model (p < 0.01) with AUCs of 0.774 (95% CI: 0.757-0.792) on PLuSS, 0.723 (95% CI: 0.703-0.744) on PLuSS follow-up, and 0.681 (95% CI: 0.651-0.710) on the NLST cohort. The identified high-risk stratum were several times more likely to die, with mortality rates of 79.34% on PLuSS, 76.47% on PLuSS follow-up, and 46.74% on NLST. Two cardiopulmonary structures (intrapulmonary artery vein ratio, intrapulmonary vein density) and two body composition tissues (SM density, bone density) identified high-risk patients. Body composition and pulmonary vasculatures are predictive of an individual's health risk; their integrations with subject demographics facilitate the assessment of an individual's overall health status or susceptibility to disease. CT-computed body composition and vasculature biomarkers provide improved prognostic value. The integration of CT biomarkers and patient demographic information improves subject risk stratification.

Abstract PR007: Screening early detection of HPV-associated oropharynx cancers with multi-feature HPV whole genome sequencing liquid biopsy

Abstract Early detection of HPV-associated oropharyngeal cancer (HPV+OPSCC), the most common HPV cancer in the United States, could reduce disease-related morbidity, yet currently there are no screening tests. Circulating tumor HPV DNA (ctHPVDNA) is a sensitive and specific biomarker for HPV+OPSCC at diagnosis. It was previously unknown if ctHPVDNA is detectable prior to HPV+OPSCC diagnosis, and thus it’s potential as a screening test. We recently reported (2023 AACR-AHNS Head and Neck Cancer Conference) detection of ctHPVDNA with 79% overall sensitivity at 100% specificity in a case-control cohort of HPV+OPSCC patients with plasma samples collected 1-11 years prior to diagnosis (n=28) and age- and sex-matched controls (n=28) from the MassGeneralBrigham Biobank (MGBB) using a custom multi-feature HPV whole genome sequencing liquid biopsy, termed HPV-DeepSeek, demonstrating for the first time, the feasibility of blood-based screening for HPV+OPSCC. Here, we extend and validate these finding in a second independent cohort and generate combined metrics for estimating HPV+OPSCC screening accuracy by HPV-DeepSeek. We conducted a blinded case-control study nested within the NCI PLCO Screening Trial. PLCO enrolled 155,000 healthy participants from November 1993-July 2001 with plasma sample collected at multiple time points. All patients were followed for cancer outcomes. PLCO participants who were diagnosed with OPSCC &amp;gt;6 months after blood sample contribution were identified and matched 1:2 with controls based on smoking status, sex, race, year of blood collection, and year of birth. 400ul of plasma was retrieved, blinded, and transferred for testing. After quality control, the cohort included 72 OPSCC cases and 144 controls. Samples had previously underdone HPV E6 antibody testing which was used as a marker of HPV status. All samples were run on HPV- DeepSeek using pre-defined cut points and results were returned to NCI CDAS where case- control status was unblinded. 32 OPSCC cases were HPV E6 antibody positive and thus regarded as HPV16+OPSCC. 20/32 were ctHPVDNA positive and 12/32 were ctHPVDNA negative (overall sensitivity 63%). Specificity was 99%. The mean lead time of positive cases was 6.3 years, and the maximum lead time was 11.3 years. Sensitivity was highest closest to diagnosis and declined further from diagnosis (100% within 3 years of cancer diagnosis, 58% from 3-9 years, 20% from 9-12 years; p&amp;lt;0.001). Four additional samples were positive for non- HPV16 genotypes (31, 33, 33, 39) in the overall cohort. When combined with the MGBB cohort, overall screening sensitivity was 70% and specificity was 99%. Sensitivity within 3 years of cancer diagnosis was 100%. ctHPVDNA can be detected in the blood up to 11 years prior to diagnosis with HPV+OPSCC, with ≥99% specificity, and an overall screening sensitivity of 70% in a cohort of 100 OPSCC cases and 172 controls using a multi-feature HPV WGS liquid biopsy. ctHPVDNA detection alone, or in combination with previously identified serological biomarkers, may be a feasible approach to screening for HPV+OPSCC. Citation Format: Krystle Kuhs, Hilary Robbins, Dipon Das, Michael Bryan, Ling Aye, Yana Al-Inaya, Shun Hirayama, Viktor Adalsteinsson, Michael Lawrence, Tim Waterboer, Daniel L Faden. Screening early detection of HPV-associated oropharynx cancers with multi-feature HPV whole genome sequencing liquid biopsy [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr PR007.

Abstract 4135754: Prediction of Incident Atrial Fibrillation Using Handheld Single-Lead Electrocardiograms from the VITAL-AF Trial

Background: Deep learning of 12-lead electrocardiograms (ECGs) can estimate future atrial fibrillation (AF) risk. Whether these models can be applied to single-lead ECGs (1L ECGs) from wearable or handheld devices is unknown. Aim: To apply a previously published deep learning model to estimate 2-year incident AF risk using handheld 1L ECGs obtained prospectively in a large AF screening trial. Methods: In the VITAL-AF trial (NCT03515057), over 16,000 primary care patients aged ≥65 years underwent AF screening with handheld 1L ECG. We applied our published deep learning model (ECG-AI) derived using single leads of over 450,000 standard 12-lead ECGs external to the VITAL-AF study (1L ECG-AI). We compared the performance of 1L ECG-AI to the validated CHARGE-AF clinical risk score and calculated net reclassification indices. Results: Among 15,694 individuals enrolled in VITAL-AF and without prevalent AF (age 74±7 years, 9,104 [58%] women), 1L ECG-AI discriminated 2-year incident AF (area under receiver operating characteristic curve [AUROC] 0.666 [95% CI 0.603-0.721]). With addition of age and sex (1L ECG-AI AS), 2-year AF discrimination (0.695 [0.637-0.742]) was comparable to the 11-component CHARGE-AF clinical risk score (0.679 [0.625-0.729]). Two-year AF incidence was markedly higher with 1L ECG-AI AS in the top 5% (8.0% [5.7-10.2]) vs bottom 5% (0.89% [0.23-0.55]). At a threshold of ≥3% estimated 2-year AF risk, AF incidence was progressively higher among patients at high risk according to neither model (1.5% [1.2-1.8]), one model (1L ECG-AI: 3.3% [2.3-4.2]; CHARGE-AF 3.4% [2.2-4.6]), and both models (5.8% [5.0-6.5]), implying that clinical risk and ECG-AI signals are complementary ( Figure ). Compared to screening all individuals at the guideline-based threshold of ≥65 years, 1L ECG-AI AS resulted in favorable net reclassification improvement (0.27 [0.22-0.32]). Conclusion: An ECG-AI algorithm developed using single leads of a 12-lead ECG combined with age and sex can discriminate AF risk using real-world handheld 1L ECGs with comparable performance to the CHARGE-AF score. 1L ECG-AI signals complement clinical risk factors. ECG-AI applied to 1L ECG may increase the reach and efficiency of AF screening.

CTNI-60. SAFETY LEAD-IN RESULTS FOR QBS10072S IN THE INDIVIDUAL SCREENING TRIAL OF INNOVATIVE GLIOBLASTOMA THERAPY (INSIGHT) TRIAL, A RANDOMIZED ADAPTIVE PLATFORM TRIAL FOR NEWLY DIAGNOSED MGMT UNMETHYLATED GLIOBLASTOMA

Abstract BACKGROUND QBS10072S, is a L-type amino acid transporter 1 (LAT-1) targeted alkylating agent that utilizes LAT1 as both a transport and targeting mechanism. QBS10072S can cross the blood-brain barrier, exhibits potential for cytotoxicity with a mechanism distinct from temozolomide and has low off-target effects. QBS10072S is being evaluated in the Individualized Screening Trial of Innovative Glioblastoma Therapy (INSIGhT) trial (NCT02977780), a randomized phase 2 adaptive multi-arm platform trial. METHODS Adult patients with newly diagnosed MGMT-unmethylated glioblastoma are eligible for INSIGhT. Since there is no safety data available for QBS10072S in combination with radiotherapy, a safety lead-in evaluation was conducted utilizing a 3 + 3 design. Starting dose for QBS10072S was 12mg/m2 in combination with radiation therapy and adjuvantly as monotherapy in 28 day cycles. Patients were monitored for dose-limiting toxicities (DLTs) to identify the maximum tolerated dose and recommended phase 2 dose (RP2D). RESULTS Nine patients were enrolled December 2022 to October 2023 for safety lead-in testing, and median age was 57 years (41-67) with 6 (66%) males, 6 (66%) patients with gross total resection, and median KPS 90 (range 80-100). Pharmacokinetic studies indicated that drug exposure was lower than prior studies, and three patients received 12mg/m2, 15mg/m2, and 18mg/m2, respectively, per dose escalation protocol. No DLTs nor adverse events leading to study drug discontinuation were reported during the evaluation period. Four patients had possible treatment-related CTCAE grade ≥ 3 toxicity including lymphopenia (n=3) and fatigue (n=1). The RP2D was determined to be 18mg/m2. Seven patients were discontinued from study treatment due to progressive disease and two patients remain on treatment. CONCLUSION QBS10072S, concurrent and adjuvant to radiation therapy, was well-tolerated in patients with newly diagnosed unmethylated MGMT glioblastoma. QBS10072S 18mg/m2 is being evaluated as a treatment arm in phase 2 testing in the ongoing INSIGhT trial.