Colorectal Cancer Screening Trial 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.

Pooling controls from nested case-control studies with the proportional risks model.

The standard approach to regression modeling for cause-specific hazards with prospective competing risks data specifies separate models for each failure type. An alternative proposed by Lunn and McNeil (1995) assumes the cause-specific hazards are proportional across causes. This may be more efficient than the standard approach, and allows the comparison of covariate effects across causes. In this paper, we extend Lunn and McNeil (1995) to nested case-control studies, accommodating scenarios with additional matching and non-proportionality. We also consider the case where data for different causes are obtained from different studies conducted in the same cohort. It is demonstrated that while only modest gains in efficiency are possible in full cohort analyses, substantial gains may be attained in nested case-control analyses for failure types that are relatively rare. Extensive simulation studies are conducted and real data analyses are provided using the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) study.

EXPRESS: Prostate Cancer Screening: Is it Time for a New Approach? A Review Article.

Prostate cancer screening has presented a challenge to clinicians. Although the implementation of screening tests such as prostate-specific antigen (PSA) and digital rectal exam (DRE) has had a significant impact on prostate-cancer-specific mortality, these traditional screening tests have a relatively poor positive predictive value of clinically significant prostate cancer (CSPC), leading to unnecessary biopsies and treatment with a host of potential complications. Fortunately, much research regarding this topic has been done and is ongoing. This includes the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, which underwent a secondary analysis to identify an association between PSA level and CSPC, and the IP1-PROSTAGRAM Trial, which evaluated the efficacy of multiparametric magnetic resonance imaging (mpMRI) in prostate cancer screening. Studies such as these have helped tremendously in establishing appropriate PSA cutoffs, the proper use of DRE, and the promise that MRI demonstrates with the goal of maximizing CSPC diagnoses while minimizing unnecessary biopsies or treatment.

Risk-stratified screening and colorectal cancer incidence and mortality: A retrospective study from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial

ObjectiveTo determine whether risk stratification can optimize the benefits of flexible sigmoidoscopy (FSG) screening. MethodsThe Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial was conducted from 1993 to 2001 in the United States. A colorectal cancer (CRC) risk stratification tool was developed in the control arm (n = 64,207) from the PLCO cohort and validated in the UK Biobank (n = 270,726). PLCO participants (n = 130,021) were classified into low-, medium-, and high-risk groups. Cumulative incidence and mortality were estimated using the Kaplan-Meier method. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between screening and CRC incidence and mortality. ResultsThe CRC risk stratification tool was based on age, gender, body mass index, smoking status, family history of CRC, diabetes, regular use of aspirin, and CRC screening history. Compared with the control arm, FSG screening was significantly associated with a reduction in mortality in both the medium-risk (HR = 0.76, 95% CI = 0.63–0.92) and high-risk groups (0.58, 0.46–0.73), but not in the low-risk group (0.85, 0.61–1.19). FSG screening also reduced distal CRC incidence and mortality in the medium-risk and high-risk groups. Furthermore, it was associated with a reduction in incidence (0.74, 0.59–0.92) and mortality (0.59, 0.40–0.87) of proximal colon cancer in the high-risk group. ConclusionsFSG screening yielded more benefits for the high-risk group than for the low-risk and medium-risk groups, supporting the development of a risk-stratified CRC screening strategy.

Potentially functional variants of ERRFI1 in hypoxia-related genes predict survival of non-small cell lung cancer patients.

Hypoxia is often involved in tumor microenvironment, and the hypoxia-induced signaling pathways play a key role in aggressive cancer phenotypes, including angiogenesis, immune evasion, and therapy resistance. However, it is unknown what role genetic variants in the hypoxia-related genes play in survival of patients with non-small cell lung cancer (NSCLC). We evaluated the associations between 16,092 single-nucleotide polymorphisms (SNPs) in 182 hypoxia-related genes and survival outcomes of NSCLC patients. Data from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial were used as the discovery dataset, and the Harvard Lung Cancer Susceptibility (HLCS) Study served as the replication dataset. We also performed additional linkage disequilibrium analysis and a stepwise multivariable Cox proportional hazards regression analysis in the PLCO dataset. An independent SNP, ERRFI1 rs28624 A > C, was identified with an adjusted hazards ratio (HR) of 1.31 (95% CI = 1.14-1.51, p = 0.0001) for overall survival (OS). In further analyses, unfavorable genotypes AC and CC, compared with the AA genotype, were associated a worse OS (HR = 1.20, 95% CI = 1.03-1.39, p = 0.014) and disease-specific survival (HR = 1.21, 95% CI = 1.04-1.42, p = 0.016). Further expression quantitative trait loci analysis indicated that ERRFI1 rs28624C genotypes were significantly associated with higher ERRFI1 mRNA expression levels in the whole blood. Additional analysis showed that high ERRFI1 mRNA expression levels were associated with a worse OS in patients with lung adenocarcinoma. Our findings suggest that genetic variants in the hypoxia-related gene ERRFI1 may modulate NSCLC survival, potentially through their effect on the gene expression.

Effectiveness of colonoscopy, immune fecal occult blood testing, and risk-graded screening strategies in colorectal cancer screening.

Colorectal cancer (CRC) is one of the most common malignant tumors, and early screening is crucial to improving the survival rate of patients. The combination of colonoscopy and immune fecal occult blood detection has garnered significant attention as a novel method for CRC screening. Colonoscopy and fecal occult blood tests, when combined, can improve screening accuracy and early detection rates, thereby facilitating early intervention and treatment. However, certain risks and costs accompany it, making the establishment of a risk classification model crucial for accurate classification and management of screened subjects. To evaluate the feasibility and effectiveness of colonoscopy, immune fecal occult blood test (FIT), and risk-graded screening strategies in CRC screening. Based on the randomized controlled trial of CRC screening in the population conducted by our hospital May 2020 to May 2023, participants who met the requirements were randomly assigned to a colonoscopy group, an FIT group, or a graded screening group at a ratio of 1:2:2 (after risk assessment, the high-risk group received colonoscopy, the low-risk group received an FIT test, and the FIT-positive group received colonoscopy). The three groups received CRC screening with different protocols, among which the colonoscopy group only received baseline screening, and the FIT group and the graded screening group received annual follow-up screening based on baseline screening. The primary outcome was the detection rate of advanced tumors, including CRC and advanced adenoma. The population participation rate, advanced tumor detection rate, and colonoscopy load of the three screening programs were compared. A total of 19373 subjects who met the inclusion and exclusion criteria were enrolled, including 8082 males (41.7%) and 11291 females (58.3%). The mean age was 60.05 ± 6.5 years. Among them, 3883 patients were enrolled in the colonoscopy group, 7793 in the FIT group, and 7697 in the graded screening group. Two rounds of follow-up screening were completed in the FIT group and the graded screening group. The graded screening group (89.2%) and the colonoscopy group (42.3%) had the lowest overall screening participation rates, while the FIT group had the highest (99.3%). The results of the intentional analysis showed that the detection rate of advanced tumors in the colonoscopy group was greater than that of the FIT group [2.76% vs 2.17%, odds ratio (OR) = 1.30, 95% confidence interval (CI): 1.01-1.65, P = 0.037]. There was no significant difference in the detection rate of advanced tumors between the colonoscopy group and the graded screening group (2.76% vs 2.35%, OR = 1.9, 95%CI: 0.93-1.51, P = 0.156), as well as between the graded screening group and the FIT group (2.35% vs 2.17%, OR = 1.09%, 95%CI: 0.88-1.34, P = 0.440). The number of colonoscopy examinations required for each patient with advanced tumors was used as an index to evaluate the colonoscopy load during population screening. The graded screening group had the highest colonoscopy load (15.4 times), followed by the colonoscopy group (10.2 times), and the FIT group had the lowest (7.8 times). A hierarchical screening strategy based on CRC risk assessment is feasible for screening for CRC in the population. It can be used as an effective supplement to traditional colonoscopy and FIT screening programs.

Estimating sojourn time and sensitivity of screening for ovarian cancer using a Bayesian framework.

Ovarian cancer is among the leading causes of gynecologic cancer-related death. Past ovarian cancer screening trials using combination of cancer antigen 125 testing and transvaginal ultrasound failed to yield statistically significant mortality reduction. Estimates of ovarian cancer sojourn time-that is, the period from when the cancer is first screen detectable until clinical detection-may inform future screening programs. We modeled ovarian cancer progression as a continuous time Markov chain and estimated screening modality-specific sojourn time and sensitivity using a Bayesian approach. Model inputs were derived from the screening arms (multimodal and ultrasound) of the UK Collaborative Trial of Ovarian Cancer Screening and the Prostate, Lung, Colorectal and Ovarian cancer screening trials. We assessed the quality of our estimates by using the posterior predictive P value. We derived histology-specific sojourn times by adjusting the overall sojourn time based on the corresponding histology-specific survival from the Surveillance, Epidemiology, and End Results Program. The overall ovarian cancer sojourn time was 2.1 years (posterior predictive P value = .469) in the Prostate, Lung, Colorectal and Ovarian studies, with 65.7% screening sensitivity. The sojourn time was 2.0 years (posterior predictive P value = .532) in the United Kingdom Collaborative Trial of Ovarian Cancer Screening's multimodal screening arm and 2.4 years (posterior predictive P value = .640) in the ultrasound screening arm, with sensitivities of 93.2% and 64.5%, respectively. Stage-specific screening sensitivities in the Prostate, Lung, Colorectal and Ovarian studies were 39.1% and 82.9% for early-stage and advanced-stage disease, respectively. The histology-specific sojourn times ranged from 0.8 to 1.8 years for type II ovarian cancer and 2.9 to 6.6 years for type I ovarian cancer. Annual screening is not effective for all ovarian cancer subtypes. Screening sensitivity for early-stage ovarian cancers is not sufficient for substantial mortality reduction.

Data-integration with pseudoweights and survey-calibration: application to developing US-representative lung cancer risk models for use in screening

Abstract Accurate cancer risk estimation is crucial to clinical decision-making, such as identifying high-risk people for screening. However, most existing cancer risk models incorporate data from epidemiologic studies, which usually cannot represent the target population. While population-based health surveys are ideal for making inference to the target population, they typically do not collect time-to-cancer incidence data. Instead, time-to-cancer specific mortality is often readily available on surveys via linkage to vital statistics. We develop calibrated pseudoweighting methods that integrate individual-level data from a cohort and a survey, and summary statistics of cancer incidence from national cancer registries. By leveraging individual-level cancer mortality data in the survey, the proposed methods impute time-to-cancer incidence for survey sample individuals and use survey calibration with auxiliary variables of influence functions generated from Cox regression to improve robustness and efficiency of the inverse-propensity pseudoweighting method in estimating pure risks. We develop a lung cancer incidence pure risk model from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial using our proposed methods by integrating data from the National Health Interview Survey and cancer registries.

Modification Role of Dietary Antioxidants in the Association of High Red Meat Intake and Lung Cancer Risk: Evidence from a Cancer Screening Trial.

Evidence on the association between red meat consumption and lung cancer risk is weak. This study examined the associations between red meat and lung cancer across levels of antioxidant intake from foods or supplements. Cox proportional hazard models were applied to assess hazard ratios (HRs) for lung cancer incidence in the Prostate, Lung, Colorectal, and Ovarian (PLCO) cancer screening trial. Baseline food frequency questionnaires measured red meat and antioxidant intake. The food-based Composite Dietary Antioxidant Index (fCDAI) evaluated the overall natural intake of vitamin A, vitamin C, vitamin E, zinc, magnesium, and selenium. During 13 years of follow-up, 95,647 participants developed 1599 lung cancer cases. Higher red meat consumption was associated with a higher risk of lung cancer (HRQ4vsQ1 1.43, 95%CI 1.20-1.71, p-trend < 0.001). We observed similar trends across groups with low or medium levels of antioxidant intake. However, no association was noticed in the group with the highest fCDAI (HRQ4vsQ1 1.24, 95%CI 0.90-1.72, p-trend = 0.08) and highest independent natural antioxidant intake. The attenuated risk was not consistently observed among groups with high supplement use. Lastly, we did not notice evidence of interactions between red meat and antioxidant intake. Our findings emphasize the importance of limiting red meat in lung cancer prevention.

A Linear Relationship between the Number of Cancers among First-Degree Relatives and the Risk of Multiple Primary Cancers.

With advances in the early detection and treatment of cancer, the incidence of multiple primary cancers (MPC) or second primary cancers has increased over time. Characterization of etiologic risk factors, including family history of cancer, within the general population is critical for assessing MPC risk in patients. We examined the association between family history of cancer among first-degree relatives and MPC risk in a prospective study of 139,958 participants from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Cox proportional hazard models were used to calculate HRs and 95% confidence intervals (95% CI), adjusting for potential confounders. Over a median follow-up of 16 years (IQR: 11-19 years), 6,170 participants were diagnosed with MPC. Having a family history of cancer increased the risk of MPC by 18% (HR, 1.18; 95% CI, 1.12-1.24). A positive linear trend was observed between the reported number of cancers in the family history and MPC risk with HRs (95% CI) of 1.13 (1.07-1.20), 1.23 (1.14-1.33), 1.29 (1.15-1.45), and 1.42 (1.20-1.70) for one, two, three, and four or more cancers among first-degree relatives, respectively (Ptrend = 2.36 × 10-13). No significant differences were observed by cancer histology or specific cancer types reported in the family history. Our study demonstrates that the family history of cancer is an important risk factor for the development of MPCs and that a comprehensive assessment of the number of cancers reported among first-degree relatives may identify those at higher risk who may benefit from targeted cancer prevention and screening strategies. Prevention Relevance: Our study makes a substantial contribution to the understanding of risk factors for MPCs in the general population. It demonstrates that individuals with a strong family history of cancer are at higher risk for MPCs and may benefit from more targeted cancer prevention and screening interventions.

Multivitamin Use and Mortality Risk in 3 Prospective US Cohorts

One in 3 US adults uses multivitamins (MV), with a primary motivation being disease prevention. In 2022, the US Preventive Services Task Force reviewed data on MV supplementation and mortality from randomized clinical trials and found insufficient evidence for determining benefits or harms owing, in part, to limited follow-up time and external validity. To estimate the association of MV use with mortality risk, accounting for confounding by healthy lifestyle and reverse causation whereby individuals in poor health initiate MV use. This cohort study used data from 3 prospective cohort studies in the US, each with baseline MV use (assessed from 1993 to 2001), and follow-up MV use (assessed from 1998 to 2004), extended duration of follow-up up to 27 years, and extensive characterization of potential confounders. Participants were adults, without a history of cancer or other chronic diseases, who participated in National Institutes of Health-AARP Diet and Health Study (327 732 participants); Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (42 732 participants); or Agricultural Health Study (19 660 participants). Data were analyzed from June 2022 to April 2024. Self-reported MV use. The main outcome was mortality. Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% CIs. Among 390 124 participants (median [IQR] age, 61.5 [56.7-66.0] years; 216 202 [55.4%] male), 164 762 deaths occurred during follow-up; 159 692 participants (40.9%) were never smokers, and 157 319 participants (40.3%) were college educated. Among daily MV users, 49.3% and 42.0% were female and college educated, compared with 39.3% and 37.9% among nonusers, respectively. In contrast, 11.0% of daily users, compared with 13.0% of nonusers, were current smokers. MV use was not associated with lower all-cause mortality risk in the first (multivariable-adjusted HR, 1.04; 95% CI, 1.02-1.07) or second (multivariable-adjusted HR, 1.04; 95% CI, 0.99-1.08) halves of follow-up. HRs were similar for major causes of death and time-varying analyses. In this cohort study of US adults, MV use was not associated with a mortality benefit. Still, many US adults report using MV to maintain or improve health.

Developing an optimal stratification model for colorectal cancer screening and reducing racial disparities in multi-center population-based studies

BackgroundEarly detection of colorectal neoplasms can reduce the colorectal cancer (CRC) burden by timely intervention for high-risk individuals. However, effective risk prediction models are lacking for personalized CRC early screening in East Asian (EAS) population. We aimed to develop, validate, and optimize a comprehensive risk prediction model across all stages of the dynamic adenoma-carcinoma sequence in EAS population.MethodsTo develop precision risk-stratification and intervention strategies, we developed three trans-ancestry PRSs targeting colorectal neoplasms: (1) using 148 previously identified CRC risk loci (PRS148); (2) SNPs selection from large-scale meta-analysis data by clumping and thresholding (PRS183); (3) PRS-CSx, a Bayesian approach for genome-wide risk prediction (PRSGenomewide). Then, the performance of each PRS was assessed and validated in two independent cross-sectional screening sets, including 4600 patients with advanced colorectal neoplasm, 4495 patients with non-advanced adenoma, and 21,199 normal individuals from the ZJCRC (Zhejiang colorectal cancer set; EAS) and PLCO (the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; European, EUR) studies. The optimal PRS was further incorporated with lifestyle factors to stratify individual risk and ultimately tested in the PLCO and UK Biobank prospective cohorts, totaling 350,013 participants.ResultsThree trans-ancestry PRSs achieved moderately improved predictive performance in EAS compared to EUR populations. Remarkably, the PRSs effectively facilitated a thorough risk assessment across all stages of the dynamic adenoma-carcinoma sequence. Among these models, PRS183 demonstrated the optimal discriminatory ability in both EAS and EUR validation datasets, particularly for individuals at risk of colorectal neoplasms. Using two large-scale and independent prospective cohorts, we further confirmed a significant dose–response effect of PRS183 on incident colorectal neoplasms. Incorporating PRS183 with lifestyle factors into a comprehensive strategy improves risk stratification and discriminatory accuracy compared to using PRS or lifestyle factors separately. This comprehensive risk-stratified model shows potential in addressing missed diagnoses in screening tests (best NPV = 0.93), while moderately reducing unnecessary screening (best PPV = 0.32).ConclusionsOur comprehensive risk-stratified model in population-based CRC screening trials represents a promising advancement in personalized risk assessment, facilitating tailored CRC screening in the EAS population. This approach enhances the transferability of PRSs across ancestries and thereby helps address health disparity.Graphical

Association of a polygenic risk score with risk of abnormal ultrasound findings and ovarian cancer in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial.

10542 Background: Several susceptibility loci have been identified in genome-wide association studies (GWAS) of single nucleotide polymorphisms (SNPs) that are associated with ovarian cancers. Polygenic risk scores (PRS) combining certain loci have shown limited performance at predicting ovarian cancer risk. However, the utilization of PRS with ovarian cancer screening tests, like transvaginal ultrasound (TVU), warrants further evaluation. This study investigated the association between a polygenic risk score and ovarian cancer risk and abnormal TVU screening in a large-scale randomized controlled ovarian cancer screening trial. Methods: A polygenic risk score was constructed using weighted sums of risk alleles of 15 ovarian cancer SNPs identified in previous GWAS to evaluate the association with abnormal TVU screening results and ovarian cancer outcomes in female participants of the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Complete genotyping information, TVU results, and ovarian cancer outcomes were available for 15722 females (mean age 62.2 years +/- 5.3) with European ancestry, including 116 ovarian cancer cases. Abnormal TVU was defined as ovarian volume or cyst volume &gt; 10 cm3, any solid/cystic component within a cystic ovarian tumor, or any solid area or papillary projection extending into the cavity of a cystic ovarian tumor. Polygenic risk scores were categorized as quartiles and odds ratios (OR) were calculated to assess risk of ovarian cancer or abnormal TVU result using the lowest PRS quartile as reference category. Results: TVU screening results were abnormal for 732 (732/15722, 4.66%) participants and normal for 14990 (14990/15722, 95.3%) participants at trial baseline. PRS within the fourth quartile demonstrated increased risk of ovarian cancer with reference to the lowest quartile (OR 1.77, 95% confidence interval: 1.04-3.08). Similarly, women in the highest quartile of the PRS had increased odds of an abnormal TVU screening result (OR 1.46, 95% confidence interval: 1.17-1.83) compared to women in the lowest PRS quartile. Conclusions: A polygenic risk score including 15 loci previously shown to be associated with ovarian cancer risk showed an association with increased ovarian cancer risk in the PLCO trial. Furthermore, the PRS was also associated with abnormal ultrasound results. Our findings support further evaluation of polygenic risk scores and transvaginal ultrasound for ovarian cancer risk stratification and screening approaches.

Deep Survival Models Can Improve Long-Term Mortality Risk Estimates from Chest Radiographs

Deep learning has recently demonstrated the ability to predict long-term patient risk and its stratification when trained on imaging data such as chest radiographs. However, existing methods formulate estimating patient risk as a binary classification, typically ignoring or limiting the use of temporal information, and not accounting for the loss of patient follow-up, which reduces the fidelity of estimation and limits the prediction to a certain time horizon. In this paper, we demonstrate that deep survival and time-to-event prediction models can outperform binary classifiers at predicting mortality and risk of adverse health events. In our study, deep survival models were trained to predict risk scores from chest radiographs and patient demographic information in the Prostate, Lung, Colorectal, and Ovarian (PLCO) cancer screening trial (25,433 patient data points used in this paper) for 2-, 5-, and 10-year time horizons. Binary classification models that predict mortality at these time horizons were built as baselines. Compared to the considered alternative, deep survival models improve the Brier score (5-year: 0.0455 [95% CI, 0.0427–0.0482] vs. 0.0555 [95% CI, (0.0535–0.0575)], p &lt; 0.05) and expected calibration error (ECE) (5-year: 0.0110 [95% CI, 0.0080–0.0141] vs. 0.0747 [95% CI, 0.0718–0.0776], p &lt; 0.05) for those fixed time horizons and are able to generate predictions for any time horizon, without the need to retrain the models. Our study suggests that deep survival analysis tools can outperform binary classification in terms of both discriminative performance and calibration, offering a potentially plausible solution for forecasting risk in clinical practice.

Association between coffee and tea consumption and ovarian cancer incidence: A prospective analysis in the PLCO dataset.

Epidemiological evidence regarding the relationship between coffee and tea consumption and the risk of ovarian cancer (OC) is inconsistent. Therefore, we aimed to quantitatively investigate this topic in a large prospective cohort study. This cohort study included 24,715 individuals recruited from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trials between 1993 and 2001. The data used for our analysis included the latest follow-up information collected up to 2015. Coffee intake of ≥4 cups/day (hazard ratio [HR], 0.586; 95% confidence interval [CI]: 0.356-0.966) or caffeine intake of 458.787 mg/day (HR, 0.607; 95% CI: 0.411-0.895) were associated with the lowest HR of incident OC in the fully adjusted model. Participants who consumed varying amounts of tea did not exhibit a statistically significant reduction in the risk of OC. Our findings suggest that a higher consumption of coffee or caffeine is associated with a reduced risk of OC. However, no statistically significant association was observed between tea consumption and the risk of OC.

Adherence to the low-fat diet pattern reduces the risk of lung cancer in American adults aged 55 years and above: a prospective cohort study

ObjectivesThere is little evidence on the association between low-fat dietary patterns and lung cancer risk among middle-aged and older adults. To fill this gap, we comprehensively investigated the association of adherence to a low-fat diet (LFD) and intake of different fat components including saturated, monounsaturated, and polyunsaturated fatty acids with incidence of lung cancer and its subtypes [non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC)] among adults aged 55 years and older. DesignA prospective cohort study with a mean follow-up time of 8.8 years. Setting and participantsThis study used data from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. The study population included 98,459 PLCO participants age 55 and over at baseline who completed food frequency questionnaires providing detailed dietary information and had no history of cancer. MethodsDietary intake was assessed using a validated food frequency questionnaire at baseline. A LFD score was calculated based on fat, protein, and carbohydrate intake as a percentage of total calories. Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between LFD score and intake of fat components (in quartiles) and incident lung cancer and its subtypes over follow-up. Restricted cubic spline analyses were conducted to examine possible nonlinear relationships. Subgroup analyses were performed to evaluate potential effect modifiers, and several sensitivity analyses were conducted to assess the stability of the findings. ResultsDuring a follow-up of 869,807.9 person-years, 1,642 cases of lung cancer were observed, consisting of 1,408 (85.75%) cases of NSCLC and 234 (14.25%) cases of SCLC. The highest versus the lowest quartiles of the LFD score were found to be associated with a reduced risk of lung cancer (HR, 0.76; 95% CI, 0.66−0.89), NSCLC (HR, 0.79; 95% CI, 0.67−0.93), and SCLC (HR, 0.59; 95% CI, 0.38−0.92). The restricted cubic spline plots demonstrated a linear dose-response relationship between the LFD score and the risk of lung cancer as well as its subtypes. This risk reduction association for overall lung cancer was more pronounced in smokers (HR, 0.71; 95% CI, 0.60−0.84; P for interaction = 0.003). For fat components, high consumption of saturated fatty acids was associated with an increased lung cancer risk (HR, 1.35; 95% CI, 1.10–1.66), especially for SCLC (HR, 2.05; 95% CI, 1.20–3.53). No significant association was found between consumption of monounsaturated or polyunsaturated fatty acids and incident lung cancer and its subtypes. ConclusionsOur findings suggest that adherence to LFD may reduce the lung cancer risk, particularly in smokers; while high saturated fatty acids consumption may increase lung cancer risk, especially for SCLC, among middle-aged and older adults in the US population.

Exploration and validation of optimal cut-off values for tPSA and fPSA/tPSA screening of prostate cancer at different ages

Objective: To determine the total and age-specific cut-off values of total prostate specific antigen (tPSA) and the ratio of free PSA divided total PSA (fPSA/tPSA) for screening prostate cancer in China. Methods: Based on the Chinese Colorectal, Breast, Lung, Liver, and Stomach cancer Screening Trial (C-BLAST) and the Tianjin Common Cancer Case Cohort (TJ4C), males who were not diagnosed with any cancers at baseline since 2017 and received both tPSA and fPSA testes were selected. Based on Cox regression, the overall and age-specific (＜60, 60-＜70, and ≥70 years) accuracy and optimal cut-off values of tPSA and fPSA/tPSA ratio for screening prostate cancer were evaluated with time-dependent receiver operating characteristic curve (tdROC) and area under curve (AUC). Bootstrap resampling was used to internally validate the stability of the optimal cut-off value, and the PLCO study was used to externally validate the accuracy under different cut-off values. Results: A total of 5 180 participants were included in the study, and after a median follow-up of 1.48 years, a total of 332 prostate cancer patients were included. In the total population, the tdAUC of tPSA and fPSA/tPSA screening for prostate cancer were 0.852 and 0.748, respectively, with the optimal cut-off values of 5.08 ng/ml and 0.173, respectively. After age stratification, the age specific cut-off values of tPSA in the <60, 60-<70, and ≥70 age groups were 3.13, 4.82, and 11.54 ng/ml, respectively, while the age-specific cut-off values of fPSA/tPSA were 0.153, 0.135, and 0.130, respectively. Under the age-specific cut-off values, the sensitivities of tPSA screening for prostate cancer in males <60, 60-70, and ≥70 years old were 92.3%, 82.0%, and 77.6%, respectively, while the specificities were 84.7%, 81.3%, and 75.4%, respectively. The age-specific sensitivities of fPSA/tPSA for screening prostate cancer were 74.4%, 53.3%, and 55.9%, respectively, while the specificities were 83.8%, 83.7%, and 83.7%, respectively. Both bootstrap's internal validation and PLCO external validation provided similar results. The combination of tPSA and fPSA/tPSA could further improve the accuracy of screening. Conclusion: To improve the screening effects, it is recommended that age-specific cut-off values of tPSA and fPSA/tPSA should be used to screen for prostate cancer in the general risk population.

Circulating microRNAs in association with pancreatic cancer risk within 5 years.

Early detection is critical for improving pancreatic cancer prognosis. Our study aims to identify circulating microRNAs (miRNAs) associated with pancreatic cancer risk. The two-stage study used plasma samples collected ≤5 years prior to cancer diagnosis, from case-control studies nested in five prospective cohort studies. The discovery stage included 185 case-control pairs from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Replication stage samples comprised 277 pairs from Shanghai Women's Health Study/Shanghai Men's Health Study, Southern Community Cohort Study, and Multiethnic Cohort Study. Seven hundred and ninety-eight miRNAs were measured using the NanoString nCounter Analysis System. Odds ratios (OR) and 95% confidence intervals (CI) for per 10% change in miRNAs in association with pancreatic cancer risk were derived from conditional logistic regression analysis in discovery and replication studies, separately, and then meta-analyzed. Stratified analysis was conducted by age at diagnosis (<65/≥65 years) and time interval between sample collection and diagnosis (≤2/>2 years). In the discovery stage, 120 risk associated miRNAs were identified at p < .05. Three were validated in the replication stage: hsa-miR-199a-3p/hsa-miR-199b-3p, hsa-miR-767-5p, and hsa-miR-191-5p, with respective ORs (95% CI) being 0.89 (0.84-0.95), 1.08 (1.02-1.13), and 0.90 (0.85-0.95). Five additional miRNAs, hsa-miR-640, hsa-miR-874-5p, hsa-miR-1299, hsa-miR-22-3p, and hsa-miR-449b-5p, were validated among patients diagnosed at ≥65 years, with OR (95% CI) of 1.23 (1.09-1.39), 1.33 (1.16-1.52), 1.25 (1.09-1.43), 1.28 (1.12-1.46), 0.76 (0.65-0.89), and 1.22 (1.07-1.39), respectively. The miRNA targets were enriched in pancreatic carcinogenesis/progression-related pathways. Our study suggests that circulating miRNAs may identify individuals at high risk for pancreatic cancer ≤5 years prior to diagnosis, indicating its potential utility in cancer screening and surveillance.

Safety net hospital risk model demonstrates stronger, population-specific applicability in characterizing lung cancer risk.

Determining lung cancer (LC) risk using personalized risk stratification may improve screening effectiveness. While the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) is a well-established stratification model for LC screening, it was derived from a predominantly Caucasian population and its effectiveness in a safety net hospital (SNH) population is unknown. We have developed a model more tailored to the SNH population and compared its performance to the PLCO model in a SNH setting. Retrospective dataset was compiled from patients screened for LC at SNH from 2015 to 2019. Descriptive statistics were calculated using the following variables: age, sex, race, education, body mass index (BMI), smoking history, personal cancer history, family LC history, chronic obstructive pulmonary disease (COPD), and emphysema. Variables distribution was compared using t- and chi-square tests. LC risk scores were calculated using SNH and PLCO models and categorized as low (scores <0.65%), moderate (0.65-1.49%), and high (>1.5%). Linear regression was applied to evaluate the relationship between models and covariates. Of 896 individuals, 38 were diagnosed with LC. Data reflected the SNH patient demographics, which predominantly were African American (53.5%), current smokers (69.9%), and with emphysema (70.1%). Among the non-LC cohort, SNH model most frequently categorized patients as low risk, while PLCO model most frequently classified patients as moderate risk. Among the LC cohort, there was no significant difference between mean scores or risk stratification. SNH model showed 92.1% sensitivity and 96.8% specificity while PLCO model showed 89.4% sensitivity and 26.1% specificity. Emphysema demonstrated a strong association in SNH model (P<0.001) while race showed no relation. SNH model demonstrated greater specificity for characterizing LC risk in a SNH population. The results demonstrated the importance of study sample representation when identifying risk factors in a stratification model.

Abstract 468: Associations of circulating miRNAs with pancreatic cancer risk differ by years between blood collection &amp; and cancer diagnosis

Abstract Pancreatic adenocarcinoma (PDAC) is one of the most fatal cancers and currently used biomarkers for PDAC diagnosis are not adequate for early detection. Therefore, new biomarkers for PDAC early detection are urgently needed. We conducted a large-scale study to prospectively evaluate the association of circulating miRNAs with PDAC risk. Specially, we aimed to examine whether the associations of miRNAs expression levels and changes of those levels from blood collection to cancer diagnosis (BCCD) with PDAC risk. We used pre-diagnostic plasma samples of 1307 PDAC cases from 5 cohort studies (290 from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, 395 from the Shanghai Women’s and Men’s Health Studies, 154 from the Southern Community Cohort Study, and 468 from the Multiethnic Cohort). Cancer free controls (n=1307) were selected and individually matched to index cases in each cohort. All miRNAs were measured by the NanoString nCounter Analysis System using the Human v3 miRNA Expression panel (798 miRNAs total). Data were pooled and quantile normalized prior to analysis. Associations of circulating miRNAs with PDAC risk were assessed by odds ratio per decile change in miRNA levels using conditional logistic regression. Fold-change of miRNA for cases versus controls by BCCD was analyzed via linear regression. Median time of BCCD was 7.13 years (range: 0.03-19.61 years). We first conducted the association analysis stratified by BCCD: &amp;lt; 5 years, 5-10 years, and &amp;gt;10 years. We found 20 miRNAs were significantly associated with PDAC risk in the &amp;lt;5 years after FDR correction. In the analysis of regressing fold-change of these 20 miRNAs on BCCD, we found the fold change of miR-155-5p was inversely associated with BCCD (β=-0.04, P&amp;lt;0.01), i.e., the case-control difference was larger when blood was drawn closer to PDAC diagnosis, suggesting its potential utility as disease biomarkers for early detection. Conversely, the fold-change of miR-93-5p (β=0.04, P=0.01), miR-223-3p (β=0.03, P=0.02), let-7i-5p (β=0.03, P&amp;lt;0.01), and miR-191-5p (β=0.05, P&amp;lt;0.01) were positively associated with BCCD, i.e., the case-control difference increased with an increasing the time interval of BCCD, indicating they are more likely biomarkers for PDAC risk. Ingenuity pathway analyses of these five significant miRNAs revealed that they were significantly enriched in ribonucleotide reductase signaling pathways at p&amp;lt;0.05. Notably, the silencing of ribonucleotide reductase M2 subunit suppresses tumorigenesis in pancreatic cancer by deactivating the PI3K/AKT/mTOR pathway, further supporting our findings. Findings of this large-scale multiethnic study suggest that changes in circulating levels of let-7i-5p, miR-155-5p, miR-93-5p, miR-191-5p, and miR-223-3p may help identify individuals at an elevated risk of developing PDAC, allowing for screening tests and close surveillance. Citation Format: Hui Cai, Veronica Wendy Setiawan, Xingyi Guo, Jie Wu, Rachael Z Stolzenberg-Solomon, Claire Zhu, Yu-Tang Gao, Jordan Berlin, Fei Ye, Qiuyin Cai, Wei Zheng, Xiao-ou Shu. Associations of circulating miRNAs with pancreatic cancer risk differ by years between blood collection &amp; and cancer diagnosis [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 468.