Cancer Prevention Study Research Articles

Oral Microbiome and Subsequent Risk of Head and Neck Squamous Cell Cancer

The oral microbiota may be involved in development of head and neck squamous cell cancer (HNSCC), yet current evidence is largely limited to bacterial 16S amplicon sequencing or small retrospective case-control studies. To test whether oral bacterial and fungal microbiomes are associated with subsequent risk of HNSCC development. Prospective nested case-control study among participants providing oral samples in 3 epidemiological cohorts, the American Cancer Society Cancer Prevention Study II Nutrition Cohort, the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, and the Southern Community Cohort Study. Two hundred thirty-six patients who prospectively developed HNSCC were identified during a mean (SD) of 5.1 (3.6) years of follow-up. Control participants who remained HNSCC free were selected by 2:1 frequency matching on cohort, age, sex, race and ethnicity, and time since oral sample collection. Data analysis was conducted in 2023. Characterization of the oral bacterial microbiome using whole-genome shotgun sequencing and the oral fungal microbiome using internal transcribed spacer sequencing. Association of bacterial and fungal taxa with HNSCC was assessed by analysis of compositions of microbiomes with bias correction. Association with red and orange oral pathogen complexes was tested by logistic regression. A microbial risk score for HNSCC risk was calculated from risk-associated microbiota. The primary outcome was HNSCC incidence. The study included 236 HNSCC case participants with a mean (SD) age of 60.9 (9.5) years and 24.6% women during a mean of 5.1 (3.6) years of follow-up, and 485 matched control participants. Overall microbiome diversity at baseline was not related to subsequent HNSCC risk; however 13 oral bacterial species were found to be differentially associated with development of HNSCC. The species included the newly identified Prevotella salivae, Streptococcus sanguinis, and Leptotrichia species, as well as several species belonging to beta and gamma Proteobacteria. The red/orange periodontal pathogen complex was moderately associated with HNSCC risk (odds ratio, 1.06 per 1 SD; 95% CI, 1.00-1.12). A 1-SD increase in microbial risk score (created based on 22 bacteria) was associated with a 50% increase in HNSCC risk (multivariate odds ratio, 1.50; 95% CI, 1.21-1.85). No fungal taxa associated with HNSCC risk were identified. This case-control study yielded compelling evidence that oral bacteria are a risk factor for HNSCC development. The identified bacteria and bacterial complexes hold promise, along with other risk factors, to identify high-risk individuals for personalized prevention of HNSCC.

Excess Body Weight and the Risk of Second Primary Cancers Among Cancer Survivors

Little is known about the causes of second primary cancers among individuals with a history of cancer. Descriptive studies have suggested that lifestyle factors, including excess body weight, may be important. To investigate whether excess body weight is associated with the risk of a second primary malignant neoplasm among cancer survivors. This cohort study of adults in 21 states in the US used data from the Cancer Prevention Study II Nutrition cohort, a large prospective study that invited participants to respond to a survey in 1992 and biennial surveys starting in 1997, and who were followed-up through 2017. Eligible participants included those who received a diagnosis of a first primary nonmetastatic invasive cancer between 1992 and 2015. Data analysis occurred from September 2023 to March 2024. Body mass index (BMI), computed from self-reported height and weight at the time of the first primary cancer diagnosis (mean [SD] years to diagnosis, 1.7 [1.5] years). Main outcomes included a second primary cancer or an obesity-related second cancer. Cancer diagnoses were reported on biennial surveys and verified through medical record abstraction or linkage with state cancer registries. This cohort included 26 894 participants who received a diagnosis of a first nonmetastatic primary cancer (mean [SD] age at first cancer diagnosis, 72.2 [6.5] years; 15 920 male [59.2%]). At the time of first diagnosis, 11 497 participants (42.8%) had overweight and 4684 (17.2%) had obesity. During a median (IQR) follow-up time of 7.9 (3.4-13.6) years, 3749 (13.9%) participants received a diagnosis of a second primary cancer, of which 1243 (33.2%) were obesity-related second primary cancers. Compared with cancer survivors whose BMI was in the normal range (18.5 to <25), there was 15% increased risk of any second primary cancer for those who had overweight (25 to <30; adjusted hazard ratio [aHR], 1.15; 95% CI, 1.07-1.25) and a 34% increased risk for those who had obesity (BMI ≥30; aHR, 1.34; 95% CI, 1.21-1.48), with greater risk for obesity-related second primary cancers, including a 40% increased risk for those with overweight (aHR, 1.40; 95% CI, 1.22,-1.61) and a 78% increased risk for those with obesity (aHR, 1.78; 95% CI, 1.51-2.11). In this cohort study of older survivors of nonmetastatic cancer, those who had overweight or obesity at the time of their first cancer diagnosis were at higher risk of developing a second cancer, especially an obesity-related second cancer. Given the high prevalence of overweight and obesity among cancer survivors, it is important to promote survivorship care guidelines recommending weight management and increase awareness of second cancers among physicians and cancer survivors.

Evaluation of risk prediction models to select lung cancer screening participants in Europe: a prospective cohort consortium analysis

Lung cancer risk prediction models might efficiently identify individuals who should be offered lung cancer screening. However, their performance has not been comprehensively evaluated in Europe. We aimed to externally validate and evaluate the performance of several risk prediction models that predict lung cancer incidence or mortality in prospective European cohorts. We analysed 240 137 participants aged 45-80 years with a current or former smoking history from nine European countries in four prospective cohorts from the pooled database of the Lung Cancer Cohort Consortium: the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (Finland), the Nord-Trøndelag Health Study (Norway), CONSTANCES (France), and the European Prospective Investigation into Cancer and Nutrition (Denmark, Germany, Italy, Spain, Sweden, the Netherlands, and Norway). We evaluated ten lung cancer risk models, which comprised the Bach, the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 2012 model (PLCOm2012), the Lung Cancer Risk Assessment Tool (LCRAT), the Lung Cancer Death Risk Assessment Tool (LCDRAT), the Nord-Trøndelag Health Study (HUNT), the Optimized Early Warning Model for Lung Cancer Risk (OWL), the University College London-Death (UCLD), the University College London-Incidence (UCLI), the Liverpool Lung Project version 2 (LLP version 2), and the Liverpool Lung Project version 3 (LLP version 3) models. We quantified model calibration as the ratio of expected to observed cases or deaths and discrimination using the area under the receiver operating characteristic curve (AUC). For each model, we also identified risk thresholds that would screen the same number of individuals as each of the US Preventive Services Task Force 2021 (USPSTF-2021), the US Preventive Services Task Force 2013 (USPSTF-2013), and the Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON) criteria. Among the participants, 1734 lung cancer cases and 1072 lung cancer deaths occurred within five years of enrolment. Most models had reasonable calibration in most countries, although the LLP version 2 overpredicted risk by more than 50% in eight countries (expected to observed ≥1·50). The PLCOm2012, LCDRAT, LCRAT, Bach, HUNT, OWL, UCLD, and UCLI models showed similar discrimination in most countries, with AUCs ranging from 0·68 (95% CI 0·59-0·77) to 0·83 (0·78-0·89), whereas the LLP version 2 and LLP version 3 showed lower discrimination, with AUCs ranging from 0·64 (95% CI 0·57-0·72) to 0·78 (0·74-0·83). When pooling data from all countries (but excluding the HUNT cohort), 33·9% (73 313 of 216 387) of individuals were eligible by USPSTF-2021 criteria, which included 74·8% (1185) of lung cancers and 76·3% (730) of lung cancer deaths occurring over 5 years. Fewer individuals were selected by USPSTF-2013 and NELSON criteria. After applying thresholds to select a population of equal size to USPSTF-2021, the PLCOm2012, LCDRAT, LCRAT, Bach, HUNT, OWL, UCLD, and UCLI, models identified 77·6%-79·1% of future cases, although they selected slightly older individuals compared with USPSTF-2021 criteria. Results were similar for USPSTF-2013 and NELSON. Several lung cancer risk prediction models showed good performance in European countries and might improve the efficiency of lung cancer screening if used in place of categorical eligibility criteria. US National Cancer Institute, l'Institut National du Cancer, Cancer Research UK.

Metabolomics signatures of air pollution mixtures and lung cancer risk: Large-Scale Metabolome-Wide Association Study in the Cancer Prevention Study Cohorts

Metabolomics signatures of air pollution mixtures and lung cancer risk: Large-Scale Metabolome-Wide Association Study in the Cancer Prevention Study Cohorts

Disentangling discordant vitamin D associations with prostate cancer incidence and fatality in a large, nested case-control study.

Published analyses of prostate cancer nested case-control and survival data in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study cohort suggested that men with higher baseline vitamin D [25(OH)D] concentrations have both (i) increased prostate cancer risk and (ii) decreased prostate cancer-specific fatality. To investigate possible factors responsible for a spurious association with prostate cancer fatality, we reanalysed baseline serum vitamin D associations with prostate cancer risk and prostate cancer-specific fatality in case-control data nested within the ATBC Study (1000 controls and 1000 incident prostate cancer cases). Conditional logistic regression and Cox proportion hazard models were used, respectively, to estimate odds ratios for risk and hazard ratios for prostate cancer-specific fatality, overall and by disease aggressiveness. We replicated these case-control analyses using baseline serum measurements of alpha-tocopherol (vitamin E), beta-carotene and retinol (vitamin A), and used the entire ATBC Study cohort (n = 29 085) to estimate marginal associations between these baseline vitamins and prostate cancer incidence and fatality following blood collection. Vitamin D analyses agreed closely with those originally published, with opposite risk and fatality associations. By contrast, the analyses of alpha-tocopherol, beta-carotene and retinol yielded concordant associations for prostate cancer incidence and prostate cancer-specific fatality. We found evidence of neither artefacts in the nested prostate cancer case-control data set nor detection or collider biases in the fatality analyses. The present findings therefore support a valid inverse (i.e. beneficial) association between vitamin D and prostate cancer-specific survival that warrants further evaluation, including possibly in controlled trials.

Coffee Consumption and Prostate Cancer Risk in the Alpha-Tocopherol, Beta Carotene Cancer Prevention Study

Coffee Consumption and Prostate Cancer Risk in the Alpha-Tocopherol, Beta Carotene Cancer Prevention Study

Urinary Polyphenol Metabolite Signatures in a Phase I Trial of a Novel Black Raspberry Nectar and Placebo Developed for Long-Term Cancer Prevention Studies

Urinary Polyphenol Metabolite Signatures in a Phase I Trial of a Novel Black Raspberry Nectar and Placebo Developed for Long-Term Cancer Prevention Studies

The Benefits of Quitting Smoking at Different Ages

IntroductionQuantifying the impact of smoking on life expectancy and the potential benefits of smoking cessation is crucial for motivating people who smoke to quit. While previous studies have attempted to estimate these effects, they were conducted more than a decade ago and did not include a significant demographic, people over 65 years old who smoke. MethodsMortality rates by age and smoking status were calculated using mortality relative risks derived from Cancer Prevention Study II, 2018 National Health Interview Survey smoking prevalence data, 2018 US population census data, and 2018 US mortality rates. Subsequently, life tables by smoking status – never, current, and former – were constructed. Life expectancies for all three smoking statuses, including those of individuals who had quit smoking at various ages ranging from 35 to 75, were then compared. Additionally, probability distributions of years lost due to smoking and years gained by quitting smoking at different ages were generated. Analyses were conducted in 2023. ResultsCompared to people who never smoked, those who smoke currently, aged 35, 45, 55, 65 or 75 years, and who have smoked throughout adulthood until that age, will lose, on average, 9.1, 8.3, 7.3, 5.9, and 4.4 years of life, respectively, if they continue to smoke for the rest of their lives. However, if they quit smoking at each of these ages, they will avoid an average loss of 8.0, 5.6, 3.4, 1.7, and 0.7 years. The chances of gaining at least 1 year of life among those who quit at age 65 and 75 are 23.4% and 14.2%, respectively. ConclusionsQuitting smoking early will avoid most years otherwise lost due to smoking. Even those who quit at ages 65 and above can still meaningfully increase their life expectancy.

Lung cancer metabolomics: a pooled analysis in the Cancer Prevention Studies

BackgroundA better understanding of lung cancer etiology and the development of screening biomarkers have important implications for lung cancer prevention.MethodsWe included 623 matched case–control pairs from the Cancer Prevention Study (CPS) cohorts. Pre-diagnosis blood samples were collected between 1998 and 2001 in the CPS-II Nutrition cohort and 2006 and 2013 in the CPS-3 cohort and were sent for metabolomics profiling simultaneously. Cancer-free controls at the time of case diagnosis were 1:1 matched to cases on date of birth, blood draw date, sex, and race/ethnicity. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using conditional logistic regression, controlling for confounders. The Benjamini–Hochberg method was used to correct for multiple comparisons.ResultsSphingomyelin (d18:0/22:0) (OR: 1.32; 95% CI: 1.15, 1.53, FDR = 0.15) and taurodeoxycholic acid 3-sulfate (OR: 1.33; 95% CI: 1.14, 1.55, FDR = 0.15) were positively associated with lung cancer risk. Participants diagnosed within 3 years of blood draw had a 55% and 48% higher risk of lung cancer per standard deviation increase in natural log-transformed sphingomyelin (d18:0/22:0) and taurodeoxycholic acid 3-sulfate level, while 26% and 28% higher risk for those diagnosed beyond 3 years, compared to matched controls. Lipid and amino acid metabolism accounted for 47% to 80% of lung cancer-associated metabolites at P < 0.05 across all participants and subgroups. Notably, ever-smokers exhibited a higher proportion of lung cancer-associated metabolites (P < 0.05) in xenobiotic- and lipid-associated pathways, whereas never-smokers showed a more pronounced involvement of amino acid- and lipid-associated metabolic pathways.ConclusionsThis is the largest prospective study examining untargeted metabolic profiles regarding lung cancer risk. Sphingomyelin (d18:0/22:0), a sphingolipid, and taurodeoxycholic acid 3-sulfate, a bile salt, may be risk factors and potential screening biomarkers for lung cancer. Lipid and amino acid metabolism may contribute significantly to lung cancer etiology which varied by smoking status.

Body mass index and the risk of subsequent cancers among older cancer survivors.

12043 Background: Little is known about the etiology of second primary cancers among survivors of older adult-onset cancers. Descriptive studies have suggested that lifestyle factors, including body mass index (BMI), may be important. Here we investigated whether BMI is associated with the risk of a subsequent malignancy among older adult cancer survivors. Methods: This analysis was conducted among men and women enrolled in the Cancer Prevention Study II Nutrition cohort who were diagnosed with a first non-metastatic incident cancer between 1992 and 2015. Survivors were followed-up until 2017 for the diagnosis of a subsequent primary malignancy at a different organ to avoid the inclusion of recurrences, as their etiology may differ. Analyses were restricted to those who were younger than 85 years at their initial diagnosis. Subsequent malignancies were included if they were diagnosed at least 60 days after the first cancer. Outcomes of interest were second cancers and obesity-related second cancer as defined by the IARC. BMI at the time or before their first cancer was self-reported (median: 1.3 years from BMI report to diagnosis). Participants who were underweight (BMI&lt;18.5 kg/m2) were excluded. Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (CI) to estimate the risk of second cancers associated with BMI. Models were adjusted for age, sex, race, diagnosis year, and stage of the first cancer. Results: This cohort included 26,894 participants diagnosed with a first cancer. The median age at diagnosis of the first cancer was 72.5 years (interquartile range (IQR): 67.7, 77.0). Most participants were women (59%), overweight or obese (60%) and diagnosed with localized disease (71%). During a median of follow-up of 7.5 years (IQR: 3.2, 13.1), 3,748 participants were diagnosed with a second cancer, including 1,140 obesity-related second cancers. Approximately 90% of second malignancies were diagnosed at least 1 year, and 70% at least 5 years after the first cancer. Compared with cancer survivors whose BMI was in the normal range (18.5≤BMI&lt;25), those who were overweight or obese were at an increased risk of any second cancer (25≤BMI&lt;30: HR=1.12, 95% CI: 1.05, 1.21; BMI≥30: HR=1.29, 95% CI: 1.18, 1.42) and BMI-related cancers (25≤BMI&lt;30: HR=1.37, 95% CI: 1.20, 1.57; BMI≥30: HR=1.60, 95% CI: 1.36, 1.88). In particular, obesity was associated with increased risks of breast (HR=1.43, 95% CI: 1.03, 1.98) and colorectal (HR=1.91, 95% CI: 1.42, 1.56) second cancers. Conclusions: Older adult cancer survivors who were overweight or obese at the time of their first cancer diagnosis were at higher risk of developing a second cancer, especially a BMI-related cancer. These findings have important public health implications given the high prevalence of overweight and obesity in this population. Weight loss strategies should be considered and heightened awareness of second cancers among physicians of older cancer survivors.

Metabolomics signatures of air pollution mixtures and lung cancer risk: A large-scale metabolome-wide association study in the Cancer Prevention Study cohorts.

10571 Background: Despite the well-established link between air pollution exposure and lung carcinogenesis, the underlying mechanism remains underexplored. While metabolomics has provided valuable molecular insights, existing air pollution metabolomics studies only assess biological changes to single air pollutants, without examining the join effects of air pollutant mixtures. We sought to identify metabolic signatures mediating the association between ambient air pollution mixtures and lung cancer risk. Methods: A total of 603 matched lung cancer case-control pairs were selected from the Cancer Prevention Study cohorts. Controls were matched to cases on age at blood draw, sex, race/ethnicity, and blood draw date. Plasma metabolomics was conducted using ultrahigh-performance liquid chromatography-tandem mass spectrometry. Air pollution mixtures include carbon monoxide, nitrogen dioxide, particulate matter, sulfur dioxide, and ozone, matched to subjects’ residential address at blood draw. We conducted an untargeted metabolome-wide association study with multivariable-adjusted linear and conditional logistic regression models to assess associations between metabolites and individual air pollutants and lung cancer risk, respectively, adjusting for individual and lifestyle-related covariates. We used a meet-in-the-middle (MITM) approach to identify potential mediators. Quantile g-computation was used to examine the effects of air pollution mixtures on metabolome perturbations to analyze the collective effects of multiple air pollutants concurrently. Results: Among 1,138 extracted metabolic features, 162 were significantly associated with the combined mixture (false discovery rate &lt; 0.2). Using MITM, no metabolites were associated with both air pollution mixture and lung cancer risk at FDR &lt; 0.2. At raw p &lt; 0.05, 16 metabolites were identified as potential mediators of the air pollution mixture and lung cancer risk. These metabolites, including 4-hydroxyphenylacetylglutamine, glutamate, and 3-aminoisobutyrate, were also significantly associated with the mixture at FDR &lt; 0.2. Conclusions: Findings from this analysis demonstrate the feasibility of considering multiple air pollutants as mixtures when conducting air pollution-related metabolomics investigations. Future exploration of the underlying biological mechanisms will be critical for validating pathways that participate in air pollution carcinogenicity. As lung cancer cases in never smokers continue to increase, it is pertinent to study air pollution and other environmental risk factors on cancer incidence.

Abstract PO5-11-07: Short- and long-term treatment-related effects on physical health in breast cancer survivors

Abstract Background. Breast cancer (BC) survivors experience greater physical health declines compared to cancer-free women of the same age, which is thought to be caused by their cancer and its treatment. However, the short- and long-term effects of different types of treatment on physical health are not well understood, especially for hormone therapy. Moreover, whether specific aspects of physical health, such as activities of daily living (ADL), are affected by treatment is unknown. Methods. This analysis was conducted in the Cancer Prevention Study 3 (CPS-3), a prospective cohort study with approximately 300,000 participants enrolled between 2006-2013. Participants returned a baseline survey and triennial follow-up surveys beginning in 2015. Incident, non-metastatic, female BC patients were included in this analysis if they returned a survey at least 90 days after their diagnosis through June 30, 2020, the end of follow-up for this analysis. All 2,551 BC patients included in this study had pre- and post-diagnostic surveys and underwent breast surgery if they were diagnosed with invasive disease. They were matched to up to five cancer-free women on age and year of survey returns (N=12,704). Self-reported physical health and ADL were assessed using the Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health Scale instrument. Treatment information was obtained from cancer registries and self-report and included surgery, chemotherapy, radiation and hormonal therapy. Odds Ratios (OR) and 95% confidence intervals (CI) between treatment received and self-reported physical function were estimated using multivariable ordinal logistic regression models at three time points relative to the case’s diagnosis date: before diagnosis, within 90 days to 5 years after diagnosis, and more than 5 years after diagnosis. Results. Median age at diagnosis was 56 years (interquartile range (IQR): 50-62). Approximately 82% of the tumors were hormone-receptor positive. The median times from the three physical health measurements to diagnoses were 1.7 years before diagnosis (IQR: 0.9 – 2.7), 1.7 years (IQR: 0.9 – 2.5) from 90 days to 5 years post-diagnosis and 6.6 years (IQR: 5.5-7.0) for more than 5 years post-diagnosis. There was a significant risk of physical decline within 5 years of diagnosis for women who received chemotherapy or hormonal therapy compared to cancer-free women (Table 1). However, more than 5 years after diagnosis, the risk of physical decline was only observed among those who received chemotherapy. Treatment combinations that included chemotherapy were also associated with a decline in the ability to carry out ADL during the first 5 years. Patients who received hormonal therapy without chemotherapy were comparable to cancer-free women in their ability to carry out ADL during the post-diagnosis period. BC patients who received surgery only or surgery and radiation reported physical health and ADLs similar to cancer-free women within 5 and &amp;gt;5 years after diagnosis. Conclusions. Post-diagnosis physical health decline is time and treatment dependent. Patients receiving chemotherapy have the greatest overall physical health decline and it is long-lasting. Beyond five years from diagnosis, physical health of breast cancer patients who did not receive chemotherapy were similar to cancer-free women. Strategies are needed to help BC patients receiving chemotherapy overcome the long-term physical function limitations of their cancer treatment. Table. Associations between treatment received and physical health and ability to carry out activities of daily living. OR: Odds Ratio; CI: confidence interval; chemo: chemotherapy; radio: radiation therapy; horm: hormonal therapy. *Associations were adjusted for matching factors, which included age and time from diagnosis to measurement of physical health. Citation Format: Clara Bodelon, Matthew Masters, Lauren McCullough, Alpa Patel, Lauren Teras. Short- and long-term treatment-related effects on physical health in breast cancer survivors [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-11-07.

0756 Validity of Self-reported Sleep in the Cancer Prevention Study – 3

0756 Validity of Self-reported Sleep in the Cancer Prevention Study – 3

A prospective study of smoking-related white blood cell DNA methylation markers and risk of bladder cancer

Bladder cancer, a common neoplasm, is primarily caused by tobacco smoking. Epigenetic alterations including DNA methylation have the potential to be used as prospective markers of increased risk, particularly in at-risk populations such as smokers. We aimed to investigate the potential of smoking-related white blood cell (WBC) methylation markers to contribute to an increase in bladder cancer risk prediction over classical questionnaire-based smoking metrics (i.e., duration, intensity, packyears) in a nested case–control study within the prospective prostate, lung, colorectal, and ovarian (PLCO) Cancer Screening Trial and the alpha-tocopherol, beta-carotene cancer (ATBC) Prevention Study (789 cases; 849 controls). We identified 200 differentially methylated sites associated with smoking status and 28 significantly associated (after correction for multiple testing) with bladder cancer risk among 2670 previously reported smoking-related cytosine–phosphate–guanines sites (CpGs). Similar patterns were observed across cohorts. Receiver operating characteristic (ROC) analyses indicated that cg05575921 (AHHR), the strongest smoking-related association we identified for bladder cancer risk, alone yielded similar predictive performance (AUC: 0.60) than classical smoking metrics (AUC: 0.59–0.62). Best prediction was achieved by including the first principal component (PC1) from the 200 smoking-related CpGs alongside smoking metrics (AUC: 0.63–0.65). Further, PC1 remained significantly associated with elevated bladder cancer risk after adjusting for smoking metrics. These findings suggest DNA methylation profiles reflect aspects of tobacco smoke exposure in addition to those captured by smoking duration, intensity and packyears, and/or individual susceptibility relevant to bladder cancer etiology, warranting further investigation.

Prevalence and predictors of colon and prostate cancer screening among volunteer firefighters: The United States Firefighter Cancer Assessment and Prevention Study.

Although firefighters have increased risk for colon and prostate cancer, limited information exists on screening practices for these cancers in volunteer firefighters who compose two-thirds of the US fire service. We estimated the prevalence of colon and prostate cancer screening among volunteer firefighters using eligibility criteria from 4 evidence-based screening recommendations and evaluated factors influencing screening. We evaluated colon (n = 569) and prostate (n = 498) cancer screening prevalence in a sample of US volunteer firefighters using eligibility criteria from the US Preventive Services Taskforce (USPSTF), National Fire Protection Association, American Cancer Society, and National Comprehensive Cancer Network. We assessed associations with fire service experience, demographics, and cancer risk perception based on USPSTF guidelines. For those eligible based on USPSTF guidelines, colon and prostate cancer screening prevalence was 51.7% (95% CI: 45.7, 57.8) and 48.8% (95% CI: 40.0, 57.6), respectively. Higher odds of colon and prostate cancer screening were observed with older age and with some college education compared to those with less education. Fire service experience and cancer risk perception were not associated with screening practices. This is the first large study to assess colon and prostate cancer screening among US volunteer firefighters based on different screening guidelines. Our findings suggest gaps in cancer prevention efforts in the US volunteer fire service. Promoting cancer screening education and opportunities for volunteer firefighters by their fire departments, healthcare professionals, and public health practitioners, may help to address the gaps.

Abstract 3427: Serum metabolites and pancreatic ductal adenocarcinoma in two prospective cohorts

Abstract Objective: Metabolomics may provide insight to understand the etiology and potential mechanisms for pancreatic ductal adenocarcinoma (PDAC) development beyond established risk factors of smoking, diabetes, and adiposity. We extended our previous metabolomic study by including additional participants from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) with the aim to examine prospective associations between serum metabolites and incident PDAC. Method: We measured 1483 known metabolites in pre-diagnostic serum (up to 24 years) in two PDAC nested case-control studies within the PLCO (360 cases-control pairs) of mostly non-smoker men and women and Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (ATBC, 372 cases-control pairs) male smokers using liquid chromatography, high resolution/accurate mass spectrometry. Controls were incidence-density sampled and matched to cases by age, blood draw date, sex, race/ethnicity, and cohort. We used conditional logistic regression to calculate odds ratios and 95% confidence intervals for PDAC per standard deviation increase in log10-metabolite levels in each cohort and combined using fixed-effect meta-analyses and stratified by follow-up time. We also performed ElasticNet regression in each cohort to identify metabolites. We assessed associations of 72 predefined metabolic pathways with PDAC by comparing Fisher’s statistic of metabolite p-values per pathway with a null distribution based on 500,000 permutations. Results: Sixty-six metabolites were associated with PDAC at a false discovery rate (FDR)&amp;lt;0.05 with 26 below the Bonferroni threshold (P&amp;lt;3.4 × 10−5). Among the 66 metabolites, 14 and 15 were selected in ElasticNet regressions in ATBC and PLCO, respectively, with two in both cohorts. Notable findings include: fibrinopeptide B(1-9); seven modified, di- or poly-peptides; eight xenobiotics related to tobacco smoke; amino acids, carbohydrates, and TCA cycle metabolites known to be regulated by mutant KRAS (aspartate, glutamate, lactate, pyruvate, and α-ketoglutarate); four secondary bile acids and three aromatic amino acids (tryptophan, phenylalanine, and tyrosine) that were positively, while four fibrinogen cleavage peptides were inversely associated with PDAC. Among the top identified metabolites, aspartate, α-glutamyltyrosine, pyroglutamylglutamine, and Glu-Gly-Asn-Val showed time-varying associations overall (P≤0.05) with greater magnitudes within the first 5 years after blood draw. Thirteen metabolic pathways were associated with PDAC (Bonferroni P≤0.05). Conclusion: Our study suggests pre-diagnostic circulating metabolites, particularly those potentially related to subclinical disease, microbiome, and tobacco metabolism are associated with PDAC. The identified metabolites along with other known risk factors might be useful in algorithms to model disease risk and progression. Citation Format: Ting Zhang, Steven C. Moore, Sheng Fu, Kevin Wang, Demetrius Albanes, Stephanie J. Weinstein, Kai Yu, Rachael Z. Stolzenberg-Solomon. Serum metabolites and pancreatic ductal adenocarcinoma in two prospective cohorts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3427.

Abstract 3425: Genetic predisposition to obesity and survival in women with breast cancer

Abstract Background. Higher body mass index (BMI) is associated with poor survival after breast cancer diagnosis. BMI is a heritable trait. A polygenic risk score (PRS) for BMI has been associated with cardiometabolic traits and found to modify weight loss interventions. Whether BMI genetic scores affect survival in women with breast cancer is unknown. Methods. This analysis was conducted in the Cancer Prevention Study II Nutrition cohort. Women diagnosed with non-metastatic breast cancer between 1992 and 2017 were included in the analysis if they had genotype data. Analyses were restricted to unrelated, postmenopausal women at the time of diagnosis who were of European ancestry (N=3,566). Deaths through 2020 were identified through linkage with the National Death Index. Primary cause of death was based on the International Classification of Disease codes. Pre-diagnosis BMI was self-reported (median 1.3 years from BMI measurement to diagnosis, interquartile range (IQR): 0.6, 1.9). We constructed a PRS using findings from a published meta-analysis of BMI genome wide association studies (GWAS) that included ~700,000 individuals and the PRSice tool.Hazard ratios (HR) and 95% confidence intervals (CI) between the PRS and all-cause mortality were estimated using Cox proportional hazards regression and Fine and Gray models for cause-specific mortality to account for competing risks. Models were adjusted for age and GWAS-specific statistically significant (P&amp;lt;0.05) principal components for population stratification. Mediation was estimated using the mediation R package. Results. The median age at diagnosis was 71.5 years (IQR: 66.3, 76.8). Most women were overweight (33.5%) or obese (18.4%) and were diagnosed with localized stage (63%) and estrogen receptor positive (65%) breast cancer. During a median follow-up of 14.5 years (IQR: 9.7-19.8), there were 1,825 (51.2%) deaths, including 301 breast cancer and 337 cardiovascular disease (CVD) specific deaths. In multivariable models, a 5 Kg/m2 increase in BMI was associated with increased risks of all-cause mortality (HR=1.09, 95% CI: 1.04, 1.15), breast cancer-specific mortality (HR=1.27, 95% CI: 1.13, 1.42), and CVD-specific mortality (HR=1.25, 95% CI: 1.11, 1.41). The PRS was highly predictive of pre-diagnostic BMI (P&amp;lt;0.001). A 1-standard deviation increase in the PRS was associated with statistically increased risk of all-cause mortality (HR=1.06, 95% CI: 1.02, 1.11). Risks of breast cancer (HR=1.07, 95% CI: 0.96, 1.19) or CVD (HR=1.01, 95% CI: 0.90, 1.12) specific mortality did not reach statistical significance. We estimated that 27% of the PRS and all-cause mortality association was mediated by BMI (95% CI: 12%, 91%; P=0.004). Conclusions. Women with breast cancer predisposed to higher BMI were at increased risk of all-cause mortality. A BMI-related PRS may be a useful tool to identify women with breast cancer in need of additional interventions and/or surveillance. Citation Format: Clara Bodelon, Adriana Lori, Mariah Landry, James Hodge, Parichoy Pal Choudhury, Ying Wang, Lauren E. McCullough, Alpa V. Patel, Lauren R. Teras. Genetic predisposition to obesity and survival in women with breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3425.

Fiber and whole grain intakes in relation to liver cancer risk: An analysis in 2 prospective cohorts and systematic review and meta-analysis of prospective studies.

The association between fiber or whole grain intakes and the risk of liver cancer remains unclear. We assessed the associations between fiber or whole grain intakes and liver cancer risk among 2 prospective studies, and systematically reviewed and meta-analyzed these results with published prospective studies. A total of 111,396 participants from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) and 26,085 men from the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study were included. Intakes of total fiber and whole grains were estimated from validated food frequency questionnaires. Study-specific HRs and 95% CI with liver cancer risk were estimated using multivariable-adjusted Cox regression. We systematically reviewed existing literature, and studies were combined in a dose-response meta-analysis. A total of 277 (median follow-up = 15.6 y) and 165 (median follow-up = 16.0 y) cases of liver cancer were observed in Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial and Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study, respectively. Dietary fiber was inversely associated with liver cancer risk in Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (HR 10g/day : 0.69; 95% CI: 0.55-0.86). No significant associations were observed between whole grain intakes and liver cancer risk in either study. Our meta-analysis included 2383 incident liver cancer cases (7 prospective cohorts) for fiber intake and 1523 cases (5 prospective cohorts) for whole grain intake; combined HRs for liver cancer risk were 0.83 (0.76-0.91) per 10 g/day of fiber and 0.92 (0.85-0.99) per 16 g/day (1 serving) of whole grains. Dietary fiber and whole grains were inversely associated with liver cancer risk. Further research exploring potential mechanisms and different fiber types is needed.

Physical activity and pain in people with and without cancer.

Performing physical activity may provide analgesic benefit, although this effect is more established for noncancer pain rather than cancer pain. The relationship between physical activity and pain outcomes in adults with and without a history of cancer was examined. Totals of 51,439 adults without a cancer history and 10,651 adults with a cancer history from the Cancer Prevention Study II Nutrition Cohort were included. Exposures included self-reported moderate to vigorous physical activity (MVPA) as well as 2-year change in MVPA. Pain outcomes included pain intensity (primary outcome) and analgesic use (secondary outcome). MVPA was inversely associated with pain intensity for adults with (odds ratio [OR], 0.84 [≥15 metabolic equivalent of task (MET) h/week vs.<7.5 MET h/week]; 95% confidence interval [CI], 0.76-0.93) and without (OR, 0.79; 95% CI, 0.75-0.82) a history of cancer. Compared to remaining inactive, participants who became sufficiently active (cancer: OR, 0.76; 95% CI, 0.68-0.86; no cancer: OR, 0.73; 95% CI, 0.69-0.77), became inactive (cancer: OR, 0.79; 95% CI, 0.71-0.88; no cancer: OR, 0.84; 95% CI, 0.80-0.89), or remained sufficiently active (cancer: OR, 0.66; 95% CI, 0.60-0.72; no cancer: OR, 0.62; 95% CI, 0.60-0.65) also reported less pain. Physical activity was not related to analgesic use. The relationship between physical activity and pain intensity was not substantially different between people with and without a history of cancer. Cancer survivors who perform more activity, or who increase their activity, may experience less pain than cancer survivors who consistently perform less. People who have had cancer often experience ongoing pain. Being physically active may help reduce the intensity of the pain they experience.

Determination of correlations in multivariate count data with informative observation times.

We consider there are various types of recurrent events and the total number of occurrences are collected at the random observation times. It has concerned that the observation process may not be independent to the multivariate event processes, hence the total counts and observation times may be correlated and the dependence may exist among different types of the event processes as well. Many methods have developed nonparametric models to accommodate such unknown structures; however, it is difficult to assess and directly quantify their correlation relationships. A multivariate frailty model is proposed to this study, in which the event and observation processes are linked by frailty variables whose joint distribution can be implicitly specified through the multivariate normal distribution with some unknown covariance matrix. The Bayesian inference method is conducted to obtain the estimates of the regression coefficients and correlation parameters. We use a form of trigonometric functions to represent the covariance matrix, so that it meets the positive-definiteness condition efficiently during the estimation schemes. The simulation studies demonstrate the utility of the proposed models. We apply the model to a skin cancer prevention study, and aim to determine the covariate and association effects. We found treatment is significant in determining the duration of examination times; prior-counts, age and gender are significant variables on the occurrence rates of tumor counts. Using the covariance matrix to access the underlying dependent structure, the mutual correlations among them are all positive, and the basal cell counts are more related to the examination times.