Genome-wide association study data from the InterLymph Consortium were available for 2,661 DLBCLs, 2,179 CLLs, 2,142 FLs, 824 MZLs, and 6,221 controls. SNPs associated (P < 5 x 10^–8) with high-density lipoprotein (HDL, n = 164), low-density lipoprotein (LDL, n = 137), total cholesterol (TC, n = 161), and triglycerides (TG, n = 123) were used as instrumental variables (IV), explaining 14.6%, 27.7%, 16.8%, and 12.8% of phenotypic variation, respectively. Associations between each lipid trait and NHL subtype were calculated using the MR inverse variance–weighted method, estimating odds ratios (OR) per standard deviation and 95% confidence intervals (CI).

HDL was positively associated with DLBCL (OR = 1.14; 95% CI, 1.00–1.30) and MZL (OR = 1.09; 95% CI, 1.01–1.18), while TG was inversely associated with MZL risk (OR = 0.90; 95% CI, 0.83–0.99), all at nominal significance (P < 0.05). A positive trend was observed for HDL with FL risk (OR = 1.08; 95% CI, 0.99–1.19; P = 0.087). No associations were noteworthy after adjusting for multiple testing.

We did not find evidence of a clear or strong association of these lipid traits with the most common NHL subtypes. While these IVs have been previously linked to other cancers, our findings do not support any causal associations with these NHL subtypes.

Our results suggest that prior reported inverse associations of lipid traits are not likely to be causal and could represent reverse causality or confounding.

We used Cox proportional hazards regression models to estimate the associations of serum levels of estradiol (premenopausal women only), testosterone, and/or SHBG with DCIS risk among 182,935 women. After a median follow-up of 7.1 years, 186 and 531 DCIS cases were ascertained in premenopausal and postmenopausal women, respectively.

Total and free estradiol were positively associated with risk of DCIS among premenopausal women. The HRs for the highest versus the lowest tertiles were 1.54 (1.06–2.23) and 1.72 [95% confidence interval (CI), 1.15–2.57], respectively. Among postmenopausal women, elevated levels of free testosterone (FT), and to a lesser extent, total testosterone, were positively associated with DCIS risk. The HRs for the highest versus the lowest quartiles were 1.42 (95% CI, 1.09–1.85) and 1.16 (95% CI, 0.91–1.48), respectively. Serum SHBG levels were inversely associated with risk of DCIS among postmenopausal women (HR_{q4 vs. q1}: 0.75; 95% CI, 0.56–0.99).

This study suggests that elevated levels of estradiol are associated with increased risk of DCIS among premenopausal women, and that among postmenopausal women, elevated levels of testosterone, and particularly those of FT, are associated with increased DCIS risk, while elevated levels of SHBG are associated with reduced risk.

These findings may be helpful in developing prevention strategies aimed at reducing breast cancer risk among premenopausal and postmenopausal women.

This retrospective cohort study assessed longitudinal changes in VBD measures in women with estrogen receptor–positive invasive breast cancer treated with ET. VBD, the ratio of fibroglandular volume (FGV) to breast volume (BV), was measured using Volpara software. Changes in measurements were evaluated using a multivariable linear mixed effects model.

Compared with white women (n = 191), black women (n = 107) had higher rates of obesity [mean ± SD body mass index (BMI) 34.5 ± 9.1 kg/m² vs. 30.6 ± 7.0 kg/m², P < 0.001] and premenopausal status (32.7% vs. 16.7%, P = 0.002). Age- and BMI-adjusted baseline FGV, BV, and VBD were similar between groups. Modeled longitudinal changes were also similar: During a follow-up of 30.7 ± 15.0 months (mean ± SD), FGV decreased over time in premenopausal women (slope = –0.323 cm³; SE = 0.093; P = 0.001), BV increased overall (slope = 2.475 cm³; SE = 0.483; P < 0.0001), and VBD decreased (premenopausal slope = –0.063%, SE = 0.011; postmenopausal slope = –0.016%, SE = 0.004; P < 0.0001). Race was not significantly associated with these longitudinal changes, nor did race modify the effect of time on these changes. Higher BMI was associated with lower baseline VBD (P < 0.0001). Among premenopausal women, VBD declined more steeply for women with lower BMI (time x BMI, P = 0.0098).

Race does not appear to impact ET-related longitudinal changes in VBD.

Racial disparities in estrogen receptor–positive breast cancer recurrence and mortality may not be explained by differential declines in breast density due to ET.

We examined associations of alcohol and tobacco use with PD, DA, and NDA in a population-based cohort of 23,456 women screened using full-field digital mammography machines manufactured by Hologic or General Electric. MD was measured using Cumulus. Machine-specific effects were estimated using linear regression, and combined using random effects meta-analysis.

Alcohol use was positively associated with PD (P_trend = 0.01), unassociated with DA (P_trend = 0.23), and inversely associated with NDA (P_trend = 0.02) adjusting for age, body mass index, reproductive factors, physical activity, and family history of breast cancer. In contrast, tobacco use was inversely associated with PD (P_trend = 0.0008), unassociated with DA (P_trend = 0.93), and positively associated with NDA (P_trend<0.0001). These trends were stronger in normal and overweight women than in obese women.

These findings suggest that associations of alcohol and tobacco use with PD result more from their associations with NDA than DA.

PD and NDA may mediate the association of alcohol drinking, but not tobacco smoking, with increased breast cancer risk. Further studies are needed to elucidate the modifiable lifestyle factors that influence breast tissue composition, and the important role of the fatty tissues on breast health.

In the Cancer Prevention Study-II Nutrition Cohort, men diagnosed with nonmetastatic prostate cancer between baseline in 1992/1993 and 2015 were followed for mortality until 2016. Analyses of pre- and postdiagnosis intakes of red and processed meat, poultry, fish, and eggs included 9,286 and 4,882 survivors, respectively. Multivariable-adjusted RRs and 95% confidence intervals (CI) were estimated using Cox proportional hazards models.

A total of 4,682 and 2,768 deaths occurred during follow-up in pre- and postdiagnosis analyses, respectively. Both pre- and postdiagnosis intakes of total red and processed meat were positively associated with all-cause mortality (quartile 4 vs. 1: RR = 1.13; 95% CI, 1.03–1.25; P_trend = 0.02; RR = 1.22; 95% CI, 1.07–1.39; P_trend = 0.03, respectively), and both pre- and postdiagnosis poultry intakes were inversely associated with all-cause mortality (quartile 4 vs. 1 RR = 0.90; 95% CI, 0.82–0.98; P_trend = 0.04; RR = 0.84; 95% CI, 0.75–0.95; P_trend = 0.01, respectively). No associations were seen for prostate cancer–specific mortality, except that higher postdiagnosis unprocessed red meat intake was associated with lower risk.

Higher red and processed meat, and lower poultry, intakes either before or after prostate cancer diagnosis were associated with higher risk of all-cause mortality.

Our findings provide additional evidence that prostate cancer survivors should follow the nutrition guidelines limiting red and processed meat consumption to improve overall survival. Additional research on the relationship of specific meat types and mortality is needed.

A total of 96,018 American adults were identified from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. A ferric-reducing ability of plasma score was used to reflect an individual's TAC intake from diet and/or supplements. Cox regression was used to calculate hazard ratios (HR) for pancreatic cancer incidence, and competing risk regression was used to calculate subdistribution HRs for pancreatic cancer mortality. Restricted cubic spline regression was used to test nonlinearity.

A total of 393 pancreatic cancer cases and 353 pancreatic cancer–related deaths were documented. Total (diet + supplements) TAC was found to be inversely associated with pancreatic cancer incidence (HR _{quartile 4 vs. quartile 1} = 0.53; 95% confidence interval, 0.39–0.72; P_trend = 0.0002) and mortality (subdistribution HR _{quartile 4 vs. quartile 1} = 0.52; 95% confidence interval 0.38–0.72; P_trend = 0.0003) in a nonlinear dose–response manner (all P_nonlinearity < 0.01). Similar results were observed for dietary TAC. No association of supplemental TAC with pancreatic cancer incidence and mortality was found.

In the U.S. general population, dietary but not supplemental TAC level is inversely associated with risks of pancreatic cancer incidence and mortality in a nonlinear dose–response pattern.

This is the first prospective study indicating that a diet rich in antioxidants may be beneficial in decreasing pancreatic cancer incidence and mortality.

Tobacco smoking habits and other relevant information were obtained from 2,009 cases and 1,532 controls recruited in the PanGenEU study using standardized tools. Multivariate logistic regression analysis was performed to evaluate pancreatic cancer risk by smoking characteristics and interactions with other pancreatic cancer risk factors. Fractional polynomials and restricted cubic splines were used to test for nonlinearity of the dose–response relationships and to analyze their shape.

Relative to never-smokers, current smokers [OR = 1.72; 95% confidence interval (95% CI), 1.39–2.12], those inhaling into the throat (OR = 1.48; 95% CI, 1.11–1.99) or chest (OR = 1.33; 95% CI, 1.12–1.58), and those using nonfiltered cigarettes (OR = 1.69; 95% CI, 1.10–2.61), were all at an increased pancreatic cancer risk. Pancreatic cancer risk was highest in current black tobacco smokers (OR = 2.09; 95% CI, 1.31–3.41), followed by blond tobacco smokers (OR = 1.43; 95% CI, 1.01–2.04). Childhood exposure to tobacco smoke relative to parental smoking was also associated with increased pancreatic cancer risk (OR = 1.24; 95% CI, 1.03–1.49). Dose–response relationships for smoking duration, intensity, cumulative dose, and smoking cessation were nonlinear and showed different shapes by tobacco type. Effect modification by family history of pancreatic cancer and diabetes was likely.

This study reveals differences in pancreatic cancer risk by tobacco type and other habit characteristics, as well as nonlinear risk associations.

This characterization of smoking-related pancreatic cancer risk profiles may help in defining pancreatic cancer high-risk populations.

Within a nested case–control study of 500 pancreatic cancer cases diagnosed after blood collection and 1,091 matched controls enrolled in four U.S. prospective cohorts, we characterized absolute risk models that included clinical factors (e.g., body mass index, history of diabetes), germline genetic polymorphisms, and circulating biomarkers.

Model discrimination showed an area under ROC curve of 0.62 via cross-validation. Our final integrated model identified 3.7% of men and 2.6% of women who had at least 3 times greater than average risk in the ensuing 10 years. Individuals within the top risk percentile had a 4% risk of developing pancreatic cancer by age 80 years and 2% 10-year risk at age 70 years.

Risk models that include established clinical, genetic, and circulating factors improved disease discrimination over models using clinical factors alone.

Absolute risk models for pancreatic cancer may help identify individuals in the general population appropriate for disease interception.

3,986 participants from the Study of Colonoscopy Utilization, an ancillary study nested within the Prostate, Lung, Colorectal, and Ovarian Screening Trial, were included. Self-reports of polyp and adenoma were compared to medical records, and measures of sensitivity and specificity were calculated. Correlates of accurate self-report of polyp were assessed using logistic regression and weighted to account for study sampling.

The sensitivity and specificity of self-reported polyp findings were 88% and 85%, respectively, and for adenoma 11% and 99%, respectively. Among participants with a polyp, older age was associated with lower likelihood while polyp severity and non-white race were associated with increased likelihood of accurate recall. Among participants without a polyp, having multiple colonoscopies was associated with lower likelihood while family history of colorectal cancer was associated with increased likelihood of accurate recall. Among both groups, longer time since colonoscopy was associated with lower likelihood of accurate recall.

Participants recalled with reasonable accuracy whether they had a prior polyp; however, recall of histology, specifically adenoma, was much less accurate.

Identification of strategies to increase accurate self-report of colonic polyps are needed, particularly for patient–provider communications and patient reporting of results to family members.

We used reduced rank regression to derive three energy balance scores that associate lifestyle factors with combinations of prediagnostic, circulating levels of high-sensitivity C-reactive protein (hsCRP), C-peptide, and hemoglobin A_1c (HbA_1c) among 2,498 participants in the Cancer Prevention Study-II Nutrition Cohort. Among 114,989 participants, we verified 2,228 colorectal cancer cases. We assessed associations of each score with colorectal cancer incidence and by tumor molecular phenotypes using Cox proportional hazards regression.

The derived scores comprised BMI, physical activity, screen time, and 14 food groups, and explained 5.1% to 10.5% of the variation in biomarkers. The HR and 95% confidence interval (CI) for quartile 4 versus 1 of the HbA_1c+C peptide–based score and colorectal cancer was 1.30 (1.15–1.47), the hsCRP-based score was 1.35 (1.19–1.53), and the hsCRP, C-peptide, and HbA_1c-based score was 1.35 (1.19–1.52). The latter score was associated with non-CIMP tumors (HR_Q4vsQ1: 1.59; 95% CI: 1.17–2.16), but not CIMP-positive tumors (P_{heterogeneity} = 0.04).

These results further support hypotheses that systemic biomarkers of metabolic health—inflammation and abnormal glucose homeostasis—mediate part of the relationship between several energy balance–related modifiable factors and colorectal cancer risk.

Results support cancer prevention guidelines for maintaining a healthful body weight, consuming a healthful diet, and being physically active. More research is needed on these clusters of exposures with molecular phenotypes of tumors.

We developed a VAT prediction score by regression equations averaged across 100 least absolute shrinkage and selection operator models in a cross-sectional study of 1,801 older adults in the Multiethnic Cohort (MEC). The score was then used as proxy for VAT in case–control studies of postmenopausal breast (950 case–control pairs) and colorectal (831 case–control pairs) cancer in an independent sample in MEC. Abdominal MRI–derived VAT; circulating biomarkers of metabolic, hormonal, and inflammation dysfunctions; and ORs for incident cancer adjusted for BMI and other risk factors were assessed.

The final score, composed of nine biomarkers, BMI, and height, explained 11% and 15% more of the variance in VAT than BMI alone in men and women, respectively. The area under the receiver operator curve for VAT >150 cm² was 0.90 in men and 0.86 in women. The VAT score was associated with risk of breast cancer [OR (95% confidence interval [CI]) by increasing tertiles: 1.00, 1.09 (0.86–1.39), 1.48 (1.16–1.89); P_trend = 0.002] but not with colorectal cancer (P = 0.84), although an association [1.00, 0.98 (0.68–1.39), 1.24 (0.88–1.76); P_trend = 0.08] was suggested for this cancer after excluding cases that occurred within 7 years of blood draw (P_{heterogeneity} = 0.06).

The VAT score predicted risks of postmenopausal breast cancer and can be used for risk assessment in diverse populations.

These findings provide specific evidence for a role of VAT in breast cancer.

SMI, VAT, and SAT were assessed from abdominal CT images for 1,998 patients with stage I–III colorectal cancer diagnosed between 2006 and 2015. Restricted cubic splines (RCS) were used to investigate associations of SMI, VAT, and SAT with overall mortality.

Average age of the participants was 67.9 ± 10.6 years and 58% were men. During a median follow-up of 4.3 years, 546 (27%) patients died. Among men, the association of SMI and mortality was statistically significant in a nonlinear way in the RCS analyses, with lower SMI levels associated with higher mortality. SMI was not associated with mortality among women. SAT was associated with mortality in a nonlinear way for men and for women, with lower SAT levels being associated with higher mortality. VAT was not significantly associated with mortality in men or women.

Associations of abdominal skeletal muscle mass with mortality among patients with colorectal cancer were not the same for men and for women.

This study stresses the importance for more attention on sex-related differences in body composition and cancer outcomes.

We used electronic medical records of 190 patients with head and neck squamous cell carcinoma who completed radiotherapy, with or without concurrent chemotherapy, at Roswell Park Comprehensive Cancer Center (Buffalo, NY) between 2015 and 2017. Throughout a 7-week treatment course, patient mouth and throat soreness (MTS) was self-reported weekly using a validated oral mucositis questionnaire, with responses 0 (no) to 4 (extreme). Average treatment times from day 1 until the day before each mucositis survey were categorized into seven groups. Multivariable-adjusted marginal average scores (LSmeans) were estimated for the repeated- and maximum-MTS, using a linear-mixed model and generalized-linear model, respectively.

Radiation treatment time was significantly associated with oral mucositis severity using both repeated-MTS (n = 1,156; P = 0.02) and maximum-MTS (n = 190; P = 0.04), with consistent patterns. The severity was lowest for patients treated during 8:30 to <9:30 am (LSmeans for maximum-MTS = 2.24; SE = 0.15), increased at later treatment times and peaked at early afternoon (11:30 am to <3:00 pm, LSmeans = 2.66–2.71; SEs = 0.16/0.17), and then decreased substantially after 3 pm.

We report a significant association between radiation treatment time and oral mucositis severity in patients with head and neck cancer.

Although additional studies are needed, these data suggest a potential simple treatment time solution to limit severity of oral mucositis during radiotherapy without increasing cost.

We sought to quantify and assess heterogeneity of the preferences of AML patients for treatment outcomes. An AML-specific discrete choice experiment (DCE) was developed involving multiple stakeholders. Attributes included in the DCE were event-free survival (EFS), complete remission (CR), time in the hospital, short-term side effects, and long-term side effects. Continuously coded conditional, stratified, and latent-class logistic regressions were used to model preferences of 294 patients with AML.

Most patients were white (89.4%) and in remission (95.0%). A 10% improvement in the chance of CR was the most meaningful offered benefit (P < 0.001). Patients were willing to trade up to 22 months of EFS or endure 8.7 months in the hospital or a two-step increase in long-term side effects to gain a 10% increase in chance of CR. Patients diagnosed at 60 years or older (21.6%) more strongly preferred to avoid short-term side effects (P = 0.03). Latent class analysis showed significant differences of preferences across gender and insurance status.

In this national sample of mostly AML survivors, patients preferred treatments that maximized chance at remission; however, significant preference heterogeneity for outcomes was identified. Age and gender may affect patients' preferences.

Survivor preferences for outcomes can inform patient-focused drug development and shared decision-making. Further studies are necessary to investigate the use of DCEs to guide treatment for individual patients.

Medical records were retrieved and abstracted for cases enrolled in a Los Angeles County case–control study of non-Hodgkin lymphoma (NHL). Cases were linked to the Los Angeles County cancer registry (CSP), the California state hospitalization discharge database (OSHPD), and the SEER-Medicare database. We assessed sensitivity, specificity, and positive predictive value (PPV) of cancer treatment in linked databases, compared with medical record abstraction.

We successfully retrieved medical records for 918 of 1,004 participating NHL cases and abstracted treatment for 698. We linked 59% of cases (96% of cases >65 years old) to SEER-Medicare and 96% to OSHPD. Chemotherapy was the most common treatment and best captured, with the highest sensitivity in SEER-Medicare (80%) and CSP (74%); combining all three data sources together increased sensitivity (92%), at reduced specificity (56%). Sensitivity for radiotherapy was moderate: 77% with aggregated data. Sensitivity of BMT was low in the CSP (42%), but high for the administrative databases, especially OSHPD (98%). Sensitivity for surgery reached 83% when considering all three datasets in aggregate, but PPV was 60%. In general, sensitivity and PPV for chronic lymphocytic leukemia/small lymphocytic lymphoma were low.

Chemotherapy was accurately captured by all data sources. Hospitalization data yielded the highest performance values for BMTs. Performance measures for radiotherapy and surgery were moderate.

Various administrative databases can supplement epidemiologic studies, depending on treatment type and NHL subtype of interest.

The Li-Fraumeni Exploration (LiFE) Consortium's DCC was created using multiple open source packages, including LAM/G Application (Linux, Apache, MySQL, Grails), Extraction-Transformation-Loading (ETL) Pentaho Data Integration Tool, and the Saiku-Mondrian client. This document serves as a resource for building a rare disease DCC for multi-institutional collaborative research.

The primary scientific and technological objective to create an online central repository into which data from all participating sites could be deposited, harmonized, aggregated, disseminated, and analyzed was completed. The cohort now include 2,193 participants from six contributing sites, including 1,354 individuals from families with a pathogenic or likely variant in TP53. Data on cancer diagnoses are also available. Challenges and lessons learned are summarized.

The methods leveraged mitigate challenges associated with successfully developing a DCC's technical infrastructure, data harmonization efforts, communications, and software development and applications.

These methods can serve as a framework in establishing other collaborative research efforts. Data from the consortium will serve as a great resource for collaborative research to improve knowledge on, and the ability to care for, individuals and families with Li-Fraumeni syndrome.

This study takes advantage of a unique population-level data resource, the Utah Population Database (UPDB), containing vast genealogy and statewide cancer data. Familial risk is measured using standardized incidence risk (SIR) ratios that account for sex, age, birth cohort, and person-years of the pedigree members.

We identify 1,023 families with a significantly higher bladder cancer rate than population controls (familial bladder cancer). Familial SIRs are then calculated across 25 cancer types, and a weighted Gower distance with K-medoids clustering is used to identify familial multicancer configurations (FMC). We found five FMCs, each exhibiting a different pattern of cancer aggregation. Of the 25 cancer types studied, kidney and prostate cancers were most commonly enriched in the familial bladder cancer clusters. Laryngeal, lung, stomach, acute lymphocytic leukemia, Hodgkin disease, soft-tissue carcinoma, esophageal, breast, lung, uterine, thyroid, and melanoma cancers were the other cancer types with increased incidence in familial bladder cancer families.

This study identified five familial bladder cancer FMCs showing unique risk patterns for cancers of other organs, suggesting phenotypic heterogeneity familial bladder cancer.

FMC configurations could permit better definitions of cancer phenotypes (subtypes or multicancer) for gene discovery and environmental risk factor studies.

The initiative was implemented through CRCHD's National Outreach Network (NON). NON is a national network of Community Health Educators (CHE), aligned with NCI-designated Cancer Centers across the nation. In phases I and II, the CHEs focused on the dissemination of cancer-related information and implementation of evidence-based educational outreach.

In total, 3,183 pre/post surveys were obtained from male and female participants, ages 50 to 74 years, during the 347 educational events held in phase I. Results demonstrated all racial/ethnic groups had an increase in colorectal cancer–related knowledge, and each group strongly agreed that the educational event increased the likelihood that they would engage in colorectal cancer–related healthful behaviors (e.g., obtain colorectal cancer screening and increase physical activity). For phase II, Connections to Care, event participants were linked to screening. Eighty-two percent of the participants who obtained colorectal cancer screening during the 3-month follow-up period obtained their screening results.

These results suggest that culturally tailored, standardized educational messaging and data collection tools are key change agents that can serve to inform the effectiveness of educational outreach to advance awareness and knowledge of colorectal cancer.

Future initiatives should focus on large-scale national efforts to elucidate effective models of connections to care, related to colorectal cancer screening, follow-up, and treatments that are modifiable to meet community needs.

We obtained stage-specific incidence and survival data from the Surveillance, Epidemiology, and End Results Program for 17 cancer types for all persons diagnosed ages 50 to 79 years in 18 geographic regions between 2006 and 2015. For a hypothetical cohort of 100,000 persons, we estimated cancer-related deaths under assumptions that cancers diagnosed at stage IV were diagnosed at earlier stages.

Stage IV cancers represented 18% of all estimated diagnoses but 48% of all estimated cancer-related deaths within 5 years. Assuming all stage IV cancers were diagnosed at stage III, 51 fewer cancer-related deaths would be expected per 100,000, a reduction of 15% of all cancer-related deaths. Assuming one third of metastatic cancers were diagnosed at stage III, one third diagnosed at stage II, and one third diagnosed at stage I, 81 fewer cancer-related deaths would be expected per 100,000, a reduction of 24% of all cancer-related deaths, corresponding to a reduction in all-cause mortality comparable in magnitude to eliminating deaths due to cerebrovascular disease.

Detection of multiple cancer types earlier than stage IV could reduce at least 15% of cancer-related deaths within 5 years, affecting not only cancer-specific but all-cause mortality.

Detecting cancer before stage IV, including modest shifts to stage III, could offer substantial population benefit.