Cancer Diagnoses After Recent Weight Loss.

Importance: Weight loss is common in primary care. Among individuals with recent weight loss, the rates of cancer during the subsequent 12 months are unclear compared with those without recent weight loss. Objective: To determine the rates of subsequent cancer diagnoses over 12 months among health professionals with weight loss during the prior 2 years compared with those without recent weight loss. Design, Setting, and Participants: Prospective cohort analysis of females aged 40 years or older from the Nurses' Health Study who were followed up from June 1978 until June 30, 2016, and males aged 40 years or older from the Health Professionals Follow-Up Study who were followed up from January 1988 until January 31, 2016. Exposure: Recent weight change was calculated from the participant weights that were reported biennially. The intentionality of weight loss was categorized as high if both physical activity and diet quality increased, medium if only 1 increased, and low if neither increased. Main Outcome and Measures: Rates of cancer diagnosis during the 12 months after weight loss. Results: Among 157 474 participants (median age, 62 years [IQR, 54-70 years]; 111 912 were female [71.1%]; there were 2631 participants [1.7%] who self-identified as Asian, Native American, or Native Hawaiian; 2678 Black participants [1.7%]; and 149 903 White participants [95.2%]) and during 1.64 million person-years of follow-up, 15 809 incident cancer cases were identified (incident rate, 964 cases/100 000 person-years). During the 12 months after reported weight change, there were 1362 cancer cases/100 000 person-years among all participants with recent weight loss of greater than 10.0% of body weight compared with 869 cancer cases/100 000 person-years among those without recent weight loss (between-group difference, 493 cases/100 000 person-years [95% CI, 391-594 cases/100 000 person-years]; P < .001). Among participants categorized with low intentionality for weight loss, there were 2687 cancer cases/100 000 person-years for those with weight loss of greater than 10.0% of body weight compared with 1220 cancer cases/100 000 person-years for those without recent weight loss (between-group difference, 1467 cases/100 000 person-years [95% CI, 799-2135 cases/100 000 person-years]; P < .001). Cancer of the upper gastrointestinal tract (cancer of the esophagus, stomach, liver, biliary tract, or pancreas) was particularly common among participants with recent weight loss; there were 173 cancer cases/100 000 person-years for those with weight loss of greater than 10.0% of body weight compared with 36 cancer cases/100 000 person-years for those without recent weight loss (between-group difference, 137 cases/100 000 person-years [95% CI, 101-172 cases/100 000 person-years]; P < .001). Conclusions and Relevance: Health professionals with weight loss within the prior 2 years had a significantly higher risk of cancer during the subsequent 12 months compared with those without recent weight loss. Cancer of the upper gastrointestinal tract was particularly common among participants with recent weight loss compared with those without recent weight loss.

Protein biomarkers and alternatively methylated cell-free DNA detect early stage pancreatic cancer.

OBJECTIVE: Pancreatic ductal adenocarcinoma (PDAC) is commonly diagnosed at an advanced stage. Liquid biopsy approaches may facilitate detection of early stage PDAC when curative treatments can be employed. DESIGN: To assess circulating marker discrimination in training, testing and validation patient cohorts (total n=426 patients), plasma markers were measured among PDAC cases and patients with chronic pancreatitis, colorectal cancer (CRC), and healthy controls. Using CA19-9 as an anchor marker, measurements were made of two protein markers (TIMP1, LRG1) and cell-free DNA (cfDNA) pancreas-specific methylation at 9 loci encompassing 61 CpG sites. RESULTS: Comparative methylome analysis identified nine loci that were differentially methylated in exocrine pancreas DNA. In the training set (n=124 patients), cfDNA methylation markers distinguished PDAC from healthy and CRC controls. In the testing set of 86 early stage PDAC and 86 matched healthy controls, CA19-9 had an area under the receiver operating characteristic curve (AUC) of 0.88 (95% CI 0.83 to 0.94), which was increased by adding TIMP1 (AUC 0.92; 95% CI 0.88 to 0.96; p=0.06), LRG1 (AUC 0.92; 95% CI 0.88 to 0.96; p=0.02) or exocrine pancreas-specific cfDNA methylation markers at nine loci (AUC 0.92; 95% CI 0.88 to 0.96; p=0.02). In the validation set of 40 early stage PDAC and 40 matched healthy controls, a combined panel including CA19-9, TIMP1 and a 9-loci cfDNA methylation panel had greater discrimination (AUC 0.86, 95% CI 0.77 to 0.95) than CA19-9 alone (AUC 0.82; 95% CI 0.72 to 0.92). CONCLUSION: A combined panel of circulating markers including proteins and methylated cfDNA increased discrimination compared with CA19-9 alone for early stage PDAC.

A blood-based metabolomic signature predictive of risk for pancreatic cancer.

Emerging evidence implicates microbiome involvement in the development of pancreatic cancer (PaCa). Here, we investigate whether increases in circulating microbial-related metabolites associate with PaCa risk by applying metabolomics profiling to 172 sera collected within 5 years prior to PaCa diagnosis and 863 matched non-subject sera from participants in the Prostate, Lung, Colorectal, and Ovarian (PLCO) cohort. We develop a three-marker microbial-related metabolite panel to assess 5-year risk of PaCa. The addition of five non-microbial metabolites further improves 5-year risk prediction of PaCa. The combined metabolite panel complements CA19-9, and individuals with a combined metabolite panel + CA19-9 score in the top 2.5th percentile have absolute 5-year risk estimates of >13%. The risk prediction model based on circulating microbial and non-microbial metabolites provides a potential tool to identify individuals at high risk of PaCa that would benefit from surveillance and/or from potential cancer interception strategies.

Being Breastfed in Infancy and Risk of Colorectal Cancer and Precursor Lesions.

BACKGROUND & AIMS: Emerging evidence implicates the importance of perinatal and early-life exposures in colorectal cancer (CRC) development. However, it remains unclear whether being breastfed in infancy is associated with CRC risk in adult life, particularly early adulthood. METHODS: We prospectively investigated the association between history of being breastfed and risk of CRC and its precursor lesions among 66,634 women 46-93 years of age from the Nurses' Health Study and 92,062 women 27-68 years of age from the Nurses' Health Study II. Cox regression and logistic regression for clustered data were used to estimate hazard ratios for CRC and odds ratios for CRC precursors, respectively. RESULTS: During 3.5 million person-years of follow-up, we identified 1490 incident cases of CRC in 2 cohorts. Having been breastfed was associated with a 23% (95% confidence interval [CI], 10% to 38%) increased risk of CRC. The risk of CRC increased with duration of being breastfed (Ptrend < .001). These findings were validated using breastfeeding information from the mothers of a subset of participants. Among younger participants from the Nurses' Health Study II, a significant association was observed between being breastfed and increased risk of high-risk adenomas under 50 years of age (odds ratio, 1.46; 95% CI, 1.16 to 1.83). Consistently, having been breastfed was associated with increased risk of CRC among participants ≤55 years of age (hazard ratio, 1.38; 95% CI, 1.06 to 1.80). CONCLUSIONS: Being breastfed in infancy was associated with increased risk of CRC in adulthood, including among younger adults. However, further research is needed to understand the underlying biological mechanisms, as this association does not establish causation.

Sex-Specific Associations between Adiponectin and Leptin Signaling and Pancreatic Cancer Survival.

BACKGROUND: Circulating adiponectin and leptin have been associated with risk of pancreatic cancer. However, the relationship between long-term exposure to these adipokines in the prediagnostic period with patient survival has not been investigated. METHODS: Adipokine levels were measured in prospectively collected samples from 472 patients with pancreatic cancer. Because of sex-specific differences in adipokine levels, associations were evaluated separately for men and women. In a subset of 415 patients, we genotyped 23 SNPs in adiponectin receptor genes (ADIPOR1 and ADIPOR2) and 30 SNPs in the leptin receptor gene (LEPR). RESULTS: Adiponectin levels were inversely associated with survival in women [HR, 1.71; 95% confidence interval (CI), 1.15-2.54]; comparing top with bottom quartile but not in men (HR, 0.89; 95% CI, 0.46-1.70). The SNPs rs10753929 and rs1418445 in ADIPOR1 were associated with survival in the combined population (per minor allele HR, 0.66; 95% CI, 0.51-0.84, and HR, 1.33; 95% CI, 1.12-1.58, respectively). Among SNPs in LEPR, rs12025906, rs3790431, and rs17127601 were associated with survival in the combined population [HRs, 1.54 (95% CI, 1.25-1.90), 0.72 (95% CI, 0.59-0.88), and 0.70 (95% CI, 0.56-0.89), respectively], whereas rs11585329 was associated with survival in men only (HR, 0.39; 95% CI, 0.23-0.66; Pinteraction = 0.0002). CONCLUSIONS: High levels of adiponectin in the prediagnostic period were associated with shorter survival among women, but not among men with pancreatic cancer. Several polymorphisms in ADIPOR1 and LEPR are associated with patient survival. IMPACT: Our findings reveal the association between adipokine signaling and pancreatic cancer survival and demonstrate the importance of examining obesity-associated pathways in relation to pancreatic cancer in a sex-specific manner.

Adipose tissue and skeletal muscle wasting precede clinical diagnosis of pancreatic cancer.

Patients with pancreatic cancer commonly develop weight loss and muscle wasting. Whether adipose tissue and skeletal muscle losses begin before diagnosis and the potential utility of such losses for earlier cancer detection are not well understood. We quantify skeletal muscle and adipose tissue areas from computed tomography (CT) imaging obtained 2 months to 5 years before cancer diagnosis in 714 pancreatic cancer cases and 1748 matched controls. Adipose tissue loss is identified up to 6 months, and skeletal muscle wasting is identified up to 18 months before the clinical diagnosis of pancreatic cancer and is not present in the matched control population. Tissue losses are of similar magnitude in cases diagnosed with localized compared with metastatic disease and are not correlated with at-diagnosis circulating levels of CA19-9. Skeletal muscle wasting occurs in the 1-2 years before pancreatic cancer diagnosis and may signal an upcoming diagnosis of pancreatic cancer.

Genetic Susceptibility to Nonalcoholic Fatty Liver Disease and Risk for Pancreatic Cancer: Mendelian Randomization.

BACKGROUND: There are conflicting data on whether nonalcoholic fatty liver disease (NAFLD) is associated with susceptibility to pancreatic cancer. Using Mendelian randomization (MR), we investigated the relationship between genetic predisposition to NAFLD and risk for pancreatic cancer. METHODS: Data from genome-wide association studies (GWAS) within the Pancreatic Cancer Cohort Consortium (PanScan; cases n = 5,090, controls n = 8,733) and the Pancreatic Cancer Case Control Consortium (PanC4; cases n = 4,163, controls n = 3,792) were analyzed. We used data on 68 genetic variants with four different MR methods [inverse variance weighting (IVW), MR-Egger, simple median, and penalized weighted median] separately to predict genetic heritability of NAFLD. We then assessed the relationship between each of the four MR methods and pancreatic cancer risk, using logistic regression to calculate ORs and 95% confidence intervals (CI), adjusting for PC risk factors, including obesity and diabetes. RESULTS: No association was found between genetically predicted NAFLD and pancreatic cancer risk in the PanScan or PanC4 samples [e.g., PanScan, IVW OR, 1.04; 95% confidence interval (CI), 0.88-1.22; MR-Egger OR, 0.89; 95% CI, 0.65-1.21; PanC4, IVW OR, 1.07; 95% CI, 0.90-1.27; MR-Egger OR, 0.93; 95% CI, 0.67-1.28]. None of the four MR methods indicated an association between genetically predicted NAFLD and pancreatic cancer risk in either sample. CONCLUSIONS: Genetic predisposition to NAFLD is not associated with pancreatic cancer risk. IMPACT: Given the close relationship between NAFLD and metabolic conditions, it is plausible that any association between NAFLD and pancreatic cancer might reflect host metabolic perturbations (e.g., obesity, diabetes, or metabolic syndrome) and does not necessarily reflect a causal relationship between NAFLD and pancreatic cancer.

Pancreatic cancer is associated with medication changes prior to clinical diagnosis.

Patients with pancreatic ductal adenocarcinoma (PDAC) commonly develop symptoms and signs in the 1-2 years before diagnosis that can result in changes to medications. We investigate recent medication changes and PDAC diagnosis in Nurses' Health Study (NHS; females) and Health Professionals Follow-up Study (HPFS; males), including up to 148,973 U.S. participants followed for 2,994,057 person-years and 991 incident PDAC cases. Here we show recent initiation of antidiabetic (NHS) or anticoagulant (NHS, HFS) medications and cessation of antihypertensive medications (NHS, HPFS) are associated with pancreatic cancer diagnosis in the next 2 years. Two-year PDAC risk increases as number of relevant medication changes increases (P-trend <1 × 10-5), with participants who recently start antidiabetic and stop antihypertensive medications having multivariable-adjusted hazard ratio of 4.86 (95%CI, 1.74-13.6). These changes are not associated with diagnosis of other digestive system cancers. Recent medication changes should be considered as candidate features in multi-factor risk models for PDAC, though they are not causally implicated in development of PDAC.

Helicobacter pylori Seropositivity, ABO Blood Type, and Pancreatic Cancer Risk From 5 Prospective Cohorts.

BACKGROUND: Helicobacter pylori infection may be a risk factor for pancreatic cancer, particularly infection by strains without the cytotoxin-associated gene A (CagA) virulence factor. Non-O blood type is a known risk factor for pancreatic cancer, and H. pylori gastric colonization occurs largely from bacterial adhesins binding to blood group antigens on gastric mucosa. METHODS: We included 485 pancreatic cancer cases and 1,122 matched controls from 5 U.S. prospective cohorts. Prediagnostic plasma samples were assessed for H. pylori and CagA antibody titers. Conditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for pancreatic cancer. ABO blood type was assessed using genetic polymorphisms at the ABO gene locus or self-report. RESULTS: Compared with H. pylori -seronegative participants, those who were seropositive did not demonstrate an increased risk of pancreatic cancer (OR 0.83, 95% CI 0.65-1.06). This lack of association was similar among CagA-seropositive (OR 0.75, 95% CI 0.53-1.04) and -seronegative (OR 0.89, 95% CI 0.65-1.20) participants. The association was also similar when stratified by time between blood collection and cancer diagnosis ( P -interaction = 0.80). Consistent with previous studies, non-O blood type was associated with increased pancreatic cancer risk, but this increase in risk was similar regardless of H. pylori seropositivity ( P -interaction = 0.51). DISCUSSION: In this nested case-control study, history of H. pylori infection as determined by H. pylori antibody serology was not associated with pancreatic cancer risk, regardless of CagA virulence factor status. The elevated risk associated with non-O blood type was consistent in those with or without H. pylori seropositivity.

Utility of Normalized Body Composition Areas, Derived From Outpatient Abdominal CT Using a Fully Automated Deep Learning Method, for Predicting Subsequent Cardiovascular Events.

BACKGROUND. CT-based body composition (BC) measurements have historically been too resource intensive to analyze for widespread use and have lacked robust comparison with traditional weight metrics for predicting cardiovascular risk. OBJECTIVE. The aim of this study was to determine whether BC measurements obtained from routine CT scans by use of a fully automated deep learning algorithm could predict subsequent cardiovascular events independently from weight, BMI, and additional cardiovascular risk factors. METHODS. This retrospective study included 9752 outpatients (5519 women and 4233 men; mean age, 53.2 years; 890 patients self-reported their race as Black and 8862 self-reported their race as White) who underwent routine abdominal CT at a single health system from January 2012 through December 2012 and who were given no major cardiovascular or oncologic diagnosis within 3 months of undergoing CT. Using publicly available code, fully automated deep learning BC analysis was performed at the L3 vertebral body level to determine three BC areas (skeletal muscle area [SMA], visceral fat area [VFA], and subcutaneous fat area [SFA]). Age-, sex-, and race-normalized reference curves were used to generate z scores for the three BC areas. Subsequent myocardial infarction (MI) or stroke was determined from the electronic medical record. Multivariable-adjusted Cox proportional hazards models were used to determine hazard ratios (HRs) for MI or stroke within 5 years after CT for the three BC area z scores, with adjustment for normalized weight, normalized BMI, and additional cardiovascular risk factors (smoking status, diabetes diagnosis, and systolic blood pressure). RESULTS. In multivariable models, age-, race-, and sex-normalized VFA was associated with subsequent MI risk (HR of highest quartile compared with lowest quartile, 1.31 [95% CI, 1.03-1.67], p = .04 for overall effect) and stroke risk (HR of highest compared with lowest quartile, 1.46 [95% CI, 1.07-2.00], p = .04 for overall effect). In multivariable models, normalized SMA, SFA, weight, and BMI were not associated with subsequent MI or stroke risk. CONCLUSION. VFA derived from fully automated and normalized analysis of abdominal CT examinations predicts subsequent MI or stroke in Black and White patients, independent of traditional weight metrics, and should be considered an adjunct to BMI in risk models. CLINICAL IMPACT. Fully automated and normalized BC analysis of abdominal CT has promise to augment traditional cardiovascular risk prediction models.

Common Analgesic Use for Menstrual Pain and Ovarian Cancer Risk.

Menstrual pain has been associated with increased ovarian cancer risk, presumably through increased inflammation, which is known to play a critical role in ovarian carcinogenesis. Analgesic medications are frequently used to treat menstrual pain, some of which lower ovarian cancer risk. In this study, we examined the association between analgesic use for menstrual pain during the premenopausal period and ovarian cancer risk among women with history of menstrual pain. We used data from the New England Case-Control Study, including 1,187 epithelial ovarian cancer cases and 1,225 population-based controls enrolled between 1998 and 2008 with detailed information on analgesic use for their menstrual pain. We used unconditional logistic regression to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for the association between analgesic use (i.e., aspirin, ibuprofen, acetaminophen) for menstrual pain and ovarian cancer risk. We further conducted a stratified analysis by intensity of menstrual pain (mild/moderate, severe). Among women with menstrual pain during their 20s and 30s, ever use of analgesics for menstrual pain was not significantly associated with ovarian cancer risk. However, among women with severe menstrual pain, ever use of aspirin or acetaminophen for menstrual pain was inversely associated with risk (OR, 0.41; 95% CI, 0.18-0.94 and OR, 0.43; 95% CI, 0.21-0.88 compared with never users, respectively). No significant association was observed between analgesic use and ovarian cancer risk among women with mild/moderate menstrual pain (P interaction ≤ 0.03). Our results suggest that use of aspirin or acetaminophen for severe menstrual pain may be associated with lower risk of ovarian cancer. PREVENTION RELEVANCE: This study investigates whether analgesic use specifically for menstrual pain during the premenopausal period influences ovarian cancer risk. Our results suggest use of aspirin or acetaminophen for severe menstrual pain may be associated with lower risk of ovarian cancer among women with severe menstrual pain.

Hepcidin-regulating iron metabolism genes and pancreatic ductal adenocarcinoma: a pathway analysis of genome-wide association studies.

BACKGROUND: Epidemiological studies have suggested positive associations for iron and red meat intake with risk of pancreatic ductal adenocarcinoma (PDAC). Inherited pathogenic variants in genes involved in the hepcidin-regulating iron metabolism pathway are known to cause iron overload and hemochromatosis. OBJECTIVES: The objective of this study was to determine whether common genetic variation in the hepcidin-regulating iron metabolism pathway is associated with PDAC. METHODS: We conducted a pathway analysis of the hepcidin-regulating genes using single nucleotide polymorphism (SNP) summary statistics generated from 4 genome-wide association studies in 2 large consortium studies using the summary data-based adaptive rank truncated product method. Our population consisted of 9253 PDAC cases and 12,525 controls of European descent. Our analysis included 11 hepcidin-regulating genes [bone morphogenetic protein 2 (BMP2), bone morphogenetic protein 6 (BMP6), ferritin heavy chain 1 (FTH1), ferritin light chain (FTL), hepcidin (HAMP), homeostatic iron regulator (HFE), hemojuvelin (HJV), nuclear factor erythroid 2-related factor 2 (NRF2), ferroportin 1 (SLC40A1), transferrin receptor 1 (TFR1), and transferrin receptor 2 (TFR2)] and their surrounding genomic regions (±20 kb) for a total of 412 SNPs. RESULTS: The hepcidin-regulating gene pathway was significantly associated with PDAC (P = 0.002), with the HJV, TFR2, TFR1, BMP6, and HAMP genes contributing the most to the association. CONCLUSIONS: Our results support that genetic susceptibility related to the hepcidin-regulating gene pathway is associated with PDAC risk and suggest a potential role of iron metabolism in pancreatic carcinogenesis. Further studies are needed to evaluate effect modification by intake of iron-rich foods on this association.

Prediagnostic Inflammation and Pancreatic Cancer Survival.

BACKGROUND: Chronic inflammation may promote initiation and progression of pancreatic cancer, but no studies have examined the association between inflammation in the period before diagnosis and pancreatic cancer survival. METHODS: We prospectively examined the association of prediagnostic plasma levels of C-reactive protein, interleukin-6, and tumor necrosis factor-α receptor 2 with survival among 492 participants from 5 large US prospective cohort studies who developed pancreatic cancer. Using an empirical dietary inflammatory pattern (EDIP) score, we evaluated whether long-term proinflammatory diets were associated with survival among 1153 patients from 2 of the 5 cohorts. Cox proportional hazards regression was used to estimate hazard ratios for death with adjustment for potential confounders. All statistical tests were 2-sided. RESULTS: Higher prediagnostic levels of C-reactive protein, interleukin-6, and tumor necrosis factor-α receptor 2 were individually associated with reduced survival (Ptrend = .03, .01, and .04, respectively). Compared with patients with a combined inflammatory biomarker score of 0 (all 3 marker levels below medians), those with a score of 3 (all 3 marker levels above medians) had a hazard ratio for death of 1.57 (95% confidence interval = 1.16 to 2.12; Ptrend = .003), corresponding to median overall survival times of 8 vs 5 months. Patients consuming the most proinflammatory diets (EDIP quartile 4) in the prediagnostic period had a hazard ratio for death of 1.34 (95% confidence interval = 1.13 to 1.59; Ptrend = .01), compared with those consuming the least proinflammatory diets (EDIP quartile 1). CONCLUSION: Prediagnostic levels of inflammatory biomarkers and long-term proinflammatory diets were inversely associated with pancreatic cancer survival.

Intrauterine device use and risk of ovarian cancer: Results from the New England Case-Control study and Nurses' Health Studies.

Results of studies assessing intrauterine device (IUD) use and ovarian cancer risk are inconsistent. We examined the association between IUD use, including duration, type and timing of use, and ovarian cancer risk using three population-based studies. Data from the New England Case-Control Study (NEC) and two prospective cohort studies, the Nurses' Health Studies (NHS/NHSII), were included in the analysis. Information on IUD use was collected by in-person interview in NEC and by biennial questionnaire in NHS/NHSII. We used unconditional logistic regression to calculate odds ratios (OR) and 95% confidence intervals (CI) in NEC and Cox regression to calculate hazard ratios (HR) and 95% CI in NHS/NHSII. We used meta-analysis to combine the NEC and the pooled NHS/NHSII results. Overall, IUD use was not associated with epithelial ovarian cancer risk (OR = 0.96, 95% CI: 0.81-1.14 in NEC; HR = 0.89, 95% CI: 0.69-1.15 in NHS/NHSII; combined RR = 0.94, 95% CI: 0.81-1.08). Among IUD users, older age at first use was associated with increased ovarian cancer risk (P-trend = .03). We did not observe significant associations by IUD type or duration of use. In conclusion, IUD use was not associated with ovarian cancer risk in our study.

Preexisting Type 2 Diabetes and Survival among Patients with Colorectal Cancer.

BACKGROUND: Type 2 diabetes increases risk of developing colorectal cancer, but the association of preexisting diabetes with colorectal cancer survival remains unclear. METHODS: We analyzed survival by diabetes status at cancer diagnosis among 4,038 patients with colorectal cancer from two prospective U.S. cohorts. Cox proportional hazards regression was used to calculate HRs and 95% confidence intervals (CI) for overall and cause-specific mortality, with adjustment for tumor characteristics and lifestyle factors. RESULTS: In the first 5 years after colorectal cancer diagnosis, diabetes was associated with a modest increase in overall mortality in women (HR, 1.22; 95% CI, 1.00-1.49), but not in men (HR, 0.83; 95% CI, 0.62-1.12; P heterogeneity by sex = 0.04). Beyond 5 years, diabetes was associated with substantially increased overall mortality with no evidence of sex heterogeneity; in women and men combined, the HRs were 1.45 (95% CI, 1.09-1.93) during >5-10 years and 2.58 (95% CI, 1.91-3.50) during >10 years. Compared with those without diabetes, patients with colorectal cancer and diabetes had increased mortality from other malignancies (HR, 1.78; 95% CI, 1.18-2.67) and cardiovascular disease (HR, 1.93; 95% CI, 1.29-2.91). Only women with diabetes for more than 10 years had increased mortality from colorectal cancer (HR, 1.33; 95% CI, 1.01-1.76). CONCLUSIONS: Among patients with colorectal cancer, preexisting diabetes was associated with increased risk of long-term mortality, particularly from other malignancies and cardiovascular disease. IMPACT: Our findings highlight the importance of cardioprotection and cancer prevention to colorectal cancer survivors with diabetes.

Smoking Modifies Pancreatic Cancer Risk Loci on 2q21.3.

Germline variation and smoking are independently associated with pancreatic ductal adenocarcinoma (PDAC). We conducted genome-wide smoking interaction analysis of PDAC using genotype data from four previous genome-wide association studies in individuals of European ancestry (7,937 cases and 11,774 controls). Examination of expression quantitative trait loci data from the Genotype-Tissue Expression Project followed by colocalization analysis was conducted to determine whether there was support for common SNP(s) underlying the observed associations. Statistical tests were two sided and P < 5 × 10-8 was considered statistically significant. Genome-wide significant evidence of qualitative interaction was identified on chr2q21.3 in intron 5 of the transmembrane protein 163 (TMEM163) and upstream of the cyclin T2 (CCNT2). The most significant SNP using the Empirical Bayes method, in this region that included 45 significantly associated SNPs, was rs1818613 [per allele OR in never smokers 0.87, 95% confidence interval (CI), 0.82-0.93; former smokers 1.00, 95% CI, 0.91-1.07; current smokers 1.25, 95% CI 1.12-1.40, P interaction = 3.08 × 10-9). Examination of the Genotype-Tissue Expression Project data demonstrated an expression quantitative trait locus in this region for TMEM163 and CCNT2 in several tissue types. Colocalization analysis supported a shared SNP, rs842357, in high linkage disequilibrium with rs1818613 (r 2 = 0. 94) driving both the observed interaction and the expression quantitative trait loci signals. Future studies are needed to confirm and understand the differential biologic mechanisms by smoking status that contribute to our PDAC findings. SIGNIFICANCE: This large genome-wide interaction study identifies a susceptibility locus on 2q21.3 that significantly modified PDAC risk by smoking status, providing insight into smoking-associated PDAC, with implications for prevention.

Population-Scale CT-based Body Composition Analysis of a Large Outpatient Population Using Deep Learning to Derive Age-, Sex-, and Race-specific Reference Curves.

Background Although CT-based body composition (BC) metrics may inform disease risk and outcomes, obtaining these metrics has been too resource intensive for large-scale use. Thus, population-wide distributions of BC remain uncertain. Purpose To demonstrate the validity of fully automated, deep learning BC analysis from abdominal CT examinations, to define demographically adjusted BC reference curves, and to illustrate the advantage of use of these curves compared with standard methods, along with their biologic significance in predicting survival. Materials and Methods After external validation and equivalency testing with manual segmentation, a fully automated deep learning BC analysis pipeline was applied to a cross-sectional population cohort that included any outpatient without a cardiovascular disease or cancer who underwent abdominal CT examination at one of three hospitals in 2012. Demographically adjusted population reference curves were generated for each BC area. The z scores derived from these curves were compared with sex-specific thresholds for sarcopenia by using χ2 tests and used to predict 2-year survival in multivariable Cox proportional hazards models that included weight and body mass index (BMI). Results External validation showed excellent correlation (R = 0.99) and equivalency (P < .001) of the fully automated deep learning BC analysis method with manual segmentation. With use of the fully automated BC data from 12 128 outpatients (mean age, 52 years; 6936 [57%] women), age-, race-, and sex-normalized BC reference curves were generated. All BC areas varied significantly with these variables (P < .001 except for subcutaneous fat area vs age [P = .003]). Sex-specific thresholds for sarcopenia demonstrated that age and race bias were not present if z scores derived from the reference curves were used (P < .001). Skeletal muscle area z scores were significantly predictive of 2-year survival (P = .04) in combined models that included BMI. Conclusion Fully automated body composition (BC) metrics vary significantly by age, race, and sex. The z scores derived from reference curves for BC parameters better capture the demographic distribution of BC compared with standard methods and can help predict survival. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Summers in this issue.

Lead-Time Trajectory of CA19-9 as an Anchor Marker for Pancreatic Cancer Early Detection.

BACKGROUND & AIMS: There is substantial interest in liquid biopsy approaches for cancer early detection among subjects at risk, using multi-marker panels. CA19-9 is an established circulating biomarker for pancreatic cancer; however, its relevance for pancreatic cancer early detection or for monitoring subjects at risk has not been established. METHODS: CA19-9 levels were assessed in blinded sera from 175 subjects collected up to 5 years before diagnosis of pancreatic cancer and from 875 matched controls from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. For comparison of performance, CA19-9 was assayed in blinded independent sets of samples collected at diagnosis from 129 subjects with resectable pancreatic cancer and 275 controls (100 healthy subjects; 50 with chronic pancreatitis; and 125 with noncancerous pancreatic cysts). The complementary value of 2 additional protein markers, TIMP1 and LRG1, was determined. RESULTS: In the PLCO cohort, levels of CA19-9 increased exponentially starting at 2 years before diagnosis with sensitivities reaching 60% at 99% specificity within 0 to 6 months before diagnosis for all cases and 50% at 99% specificity for cases diagnosed with early-stage disease. Performance was comparable for distinguishing newly diagnosed cases with resectable pancreatic cancer from healthy controls (64% sensitivity at 99% specificity). Comparison of resectable pancreatic cancer cases to subjects with chronic pancreatitis yielded 46% sensitivity at 99% specificity and for subjects with noncancerous cysts, 30% sensitivity at 99% specificity. For prediagnostic cases below cutoff value for CA19-9, the combination with LRG1 and TIMP1 yielded an increment of 13.2% in sensitivity at 99% specificity (P = .031) in identifying cases diagnosed within 1 year of blood collection. CONCLUSION: CA19-9 can serve as an anchor marker for pancreatic cancer early detection applications.

Mendelian Randomization Analysis of n-6 Polyunsaturated Fatty Acid Levels and Pancreatic Cancer Risk.

BACKGROUND: Whether circulating polyunsaturated fatty acid (PUFA) levels are associated with pancreatic cancer risk is uncertain. Mendelian randomization (MR) represents a study design using genetic instruments to better characterize the relationship between exposure and outcome. METHODS: We utilized data from genome-wide association studies within the Pancreatic Cancer Cohort Consortium and Pancreatic Cancer Case-Control Consortium, involving approximately 9,269 cases and 12,530 controls of European descent, to evaluate associations between pancreatic cancer risk and genetically predicted plasma n-6 PUFA levels. Conventional MR analyses were performed using individual-level and summary-level data. RESULTS: Using genetic instruments, we did not find evidence of associations between genetically predicted plasma n-6 PUFA levels and pancreatic cancer risk [estimates per one SD increase in each PUFA-specific weighted genetic score using summary statistics: linoleic acid odds ratio (OR) = 1.00, 95% confidence interval (CI) = 0.98-1.02; arachidonic acid OR = 1.00, 95% CI = 0.99-1.01; and dihomo-gamma-linolenic acid OR = 0.95, 95% CI = 0.87-1.02]. The OR estimates remained virtually unchanged after adjustment for covariates, using individual-level data or summary statistics, or stratification by age and sex. CONCLUSIONS: Our results suggest that variations of genetically determined plasma n-6 PUFA levels are not associated with pancreatic cancer risk. IMPACT: These results suggest that modifying n-6 PUFA levels through food sources or supplementation may not influence risk of pancreatic cancer.

Diabetes, Weight Change, and Pancreatic Cancer Risk.

Importance: Pancreatic cancer is the third-leading cause of cancer death in the United States; however, few high-risk groups have been identified to facilitate early diagnosis strategies. Objective: To evaluate the association of diabetes duration and recent weight change with subsequent risk of pancreatic cancer in the general population. Design, Setting, and Participants: This cohort study obtained data from female participants in the Nurses' Health Study and male participants in the Health Professionals Follow-Up Study, with repeated exposure assessments over 30 years. Incident cases of pancreatic cancer were identified from self-report or during follow-up of participant deaths. Deaths were ascertained through reports from the next of kin, the US Postal Service, or the National Death Index. Data collection was conducted from October 1, 2018, to December 31, 2018. Data analysis was performed from January 1, 2019, to June 30, 2019. Exposures: Duration of physician-diagnosed diabetes and recent weight change. Main Outcome and Measures: Hazard ratios (HRs) for subsequent development of pancreatic cancer. Results: Of the 112 818 women (with a mean [SD] age of 59.4 [11.7] years) and 46 207 men (with a mean [SD] age of 64.7 [10.8] years) included in the analysis, 1116 incident cases of pancreatic cancers were identified. Compared with participants with no diabetes, those with recent-onset diabetes had an age-adjusted HR for pancreatic cancer of 2.97 (95% CI, 2.31-3.82) and those with long-standing diabetes had an age-adjusted HR of 2.16 (95% CI, 1.78-2.60). Compared with those with no weight loss, participants who reported a 1- to 4-lb weight loss had an age-adjusted HR for pancreatic cancer of 1.25 (95% CI, 1.03-1.52), those with a 5- to 8-lb weight loss had an age-adjusted HR of 1.33 (95% CI, 1.06-1.66), and those with more than an 8-lb weight loss had an age-adjusted HR of 1.92 (95% CI, 1.58-2.32). Participants with recent-onset diabetes accompanied by weight loss of 1 to 8 lb (91 incident cases per 100 000 person-years [95% CI, 55-151]; HR, 3.61 [95% CI, 2.14-6.10]) or more than 8 lb (164 incident cases per 100 000 person-years [95% CI, 114-238]; HR, 6.75 [95% CI, 4.55-10.00]) had a substantially increased risk for pancreatic cancer compared with those with neither exposure (16 incident cases per 100 000 person-years; 95% CI, 14-17). Incidence rates were even higher among participants with recent-onset diabetes and weight loss with a body mass index of less than 25 before weight loss (400 incident cases per 100 000 person-years) or whose weight loss was not intentional judging from increased physical activity or healthier dietary choices (334 incident cases per 100 000 person-years). Conclusions and Relevance: This study demonstrates that recent-onset diabetes accompanied by weight loss is associated with a substantially increased risk for developing pancreatic cancer. Older age, previous healthy weight, and no intentional weight loss further elevate this risk.