Objectives: The metabolic dysfunction driven by obesity, including hyperglycemia and dyslipidemia, increases risk for developing at least 13 cancer types. The concept of “metabolic dysfunction” is often defined by meeting various combinations of criteria for metabolic syndrome. However, the lack of a unified definition of metabolic dysfunction makes it difficult to compare findings across studies. This review summarizes 129 studies that evaluated variable definitions of metabolic dysfunction in relation to obesity‐related cancer risk and mortality after a cancer diagnosis. Strategies for metabolic dysfunction management are also discussed.MethodsA comprehensive search of relevant publications in MEDLINE (PubMed) and Google Scholar with review of references was conducted.ResultsMetabolic dysfunction, defined as metabolic syndrome diagnosis or any number of metabolic syndrome criteria out of clinical range, inflammatory biomarkers, or markers of metabolic organ function, has been associated with risk for, and mortality from, colorectal, pancreatic, postmenopausal breast, and bladder cancers. Metabolic dysfunction associations with breast and colorectal cancer risk have been observed independently of BMI, with increased risk in individuals with metabolically unhealthy normal weight or overweight/obesity compared with metabolically healthy normal weight.ConclusionMetabolic dysfunction is a key risk factor for obesity‐related cancer, regardless of obesity status. Nonetheless, a harmonized definition of metabolic dysfunction will further clarify the magnitude of the relationship across cancer types, enable better comparisons across studies, and further guide criteria for obesity‐related cancer risk stratification.

Thrombus formation on a foreign surface is a complicated process, involving many factors. However, there is little doubt that a foreign surface adsorbs plasma proteins upon blood contact and that the nature of this adsorbed layer may determine the mechanism of platelet adhesion and aggregation. The adhesion and aggregation of platelets play an important role in the initial events of thrombus formation on a foreign surface. In this work, adsorption studies using human blood plasma were done on several polymer surfaces. Some drugs which prevent platelet adhesion were utilized to verify the proposed mechanism for platelet adhesion which includes glycosyl transferase reaction. Also, adsorption and release of fatty acid salts, including fatty acid-bonded albumin, were investigated at different polymer interfaces. It is postulated that adsorbed fatty acid salts are released from the surface upon contact with plasma to form a high local concentration of fatty acid, and that this fatty acid suspension would cause platelet aggregation at the interface.

Background Metabolic syndrome (MetS), a group of risk factors that define metabolic dysfunction in adults, is strongly associated with obesity and is an emerging risk factor for cancer. However, the association of MetS and degree of metabolic dysfunction with obesity‐related cancer is unknown. Methods Using National Health and Nutrition Examination Survey data from 1999 to 2018, we identified 528 obesity‐related cancer cases and 18,972 cancer‐free participants. MetS was defined as the presence of or treatment for ≥3 of hyperglycemia, hypertension, hypertriglyceridemia, low HDL–cholesterol, and abdominal obesity. A metabolic syndrome score (MSS) was computed as the total number of abnormal MetS parameters to determine the severity of metabolic dysfunction. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using multivariable logistic regression models, adjusting for sociodemographic and lifestyle factors. Results About 45.7% of obesity‐related cancer cases were classified as having MetS compared with only 33.0% of cancer‐free participants. Overall, MetS and MSS were not associated with obesity‐related cancer. However, MSS was associated with higher obesity‐related cancer risk among participants under 50 years of age (OR [95% CI] = 1.28 [1.08–1.52]). When evaluating MSS categorically, compared with healthy participants with no abnormal MetS parameters (MSS = 0), participants with one or two abnormal parameters had a statistically significant higher risk of obesity‐related cancer (OR [95% CI] = 1.73 [1.06–2.83]). Conclusions Metabolic dysfunction is associated with a higher risk of obesity‐related cancer, particularly in young adults under 50 years of age, and among participants with one or two abnormal metabolic parameters. A more accurate indicator of metabolic dysfunction, beyond metabolic syndrome, is needed to better assist in stratifying individuals for obesity‐related cancer risk.

PURPOSE Histopathologic features are critical for studying risk factors of colorectal polyps, but remain deeply embedded within unstructured pathology reports, requiring costly and time-consuming manual abstraction for research. In this study, we developed and evaluated a natural language processing (NLP) pipeline to automatically extract histopathologic features of colorectal polyps from pathology reports, with an emphasis on individual polyp size. These data were then linked with structured electronic health record (EHR) data, creating an analysis-ready epidemiologic data set. METHODS We obtained 24,584 pathology reports from colonoscopies performed at the University of Utah’s Gastroenterology Clinic. Two investigators annotated 350 reports to determine inter-rater agreement, develop an annotation scheme, and create a reference standard for performance evaluation. The pipeline was then developed, and performance was compared against the reference for extracting polyp location, histology, size, shape, dysplasia, and the number of polyps. Finally, the pipeline was applied to 24,225 unseen reports and NLP-extracted data were linked with structured EHR data. RESULTS Across all features, our pipeline achieved a precision of 98.9%, a recall of 98.0%, and an F1-score of 98.4%. In patients with polyps, the pipeline correctly extracted 95.6% of sizes, 97.2% of polyp locations, 97.8% of histology, 98.3% of shapes, and 98.3% of dysplasia levels. When applied to unseen data, the pipeline classified 12,889 patients as having polyps, 4,907 patients without polyps, and extracted the features of 28,387 polyps. Tubular adenomas were the most common subtype (55.9%), 8.1% of polyps were advanced adenomas, and the mean polyp size was 0.57 (±0.4) cm. CONCLUSION Our pipeline extracted histopathologic features of colorectal polyps from colonoscopy pathology reports, most notably individual polyp sizes, with considerable accuracy. This study demonstrates the utility of NLP for extracting polyp features and linking these data with EHR data to create an epidemiologic data set to study colorectal polyp risk factors and outcomes.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Background: Diabetes has been associated with an increased risk of the development of multiple cancers, however, evidence for development of diabetes after cancer diagnosis is limited. Methods: Using data on 7,702 cancer patients treated at the Huntsman Cancer Institute, a comprehensive cancer center in Utah, we examined the association of systemic cancer treatments (chemotherapy, immunotherapy, hormone therapy, and corticosteroids) and obesity-related cancer (ORC) status (presence of breast, colorectal, ovarian, endometrial, kidney, thyroid, meningioma, multiple myeloma, gallbladder, gastric cardia, esophageal adenocarcinoma, liver, or pancreatic cancer), with the development of diabetes after cancer diagnosis. Cox proportional-hazards regression models adjusting for relevant covariates [age, sex, race, body mass index at cancer diagnosis, and ORC status (in treatment-related models only)] were used to calculate hazard ratios (HR) and 95% confidence intervals (CI). Diabetes, cancer treatment type, and cancer sites were identified using ICD codes and tumor histology. Results: 975(12.7%) cancer patients had incident diabetes (723 of which were type-2 diabetes), and the average time to diabetes diagnosis after cancer diagnosis was 4.4 years. 35.1% used chemotherapy, 11.8% used immunotherapy, 19.5% used hormone therapy, 38.8% used corticosteroids, and 40.8% had an ORC. ORC patients and patients who used corticosteroids had a statistically significant higher hazard of new-onset diabetes [HR(95% CI) 1.43(1.24-1.65), 1.29(1.13-1.47), respectively] compared to patients with a non-ORC and patients who did not use corticosteroids, respectively. Interestingly, patients who received chemotherapy or hormone therapy had a statistically significant lower hazard of new-onset diabetes [HR(95% CI) 0.69(0.60-0.79), 0.68(0.58-0.81), respectively] compared to patients who did not receive chemotherapy or hormone therapy, respectively. Analyses by cancer site and diabetes type and evaluating death as a competing risk factor are ongoing. Conclusions: We observed statistically significant 1.43-times and 1.29-times higher hazards of incident diabetes after cancer diagnosis in ORC patients and corticosteroid users. These results suggest that certain cancers and cancer treatments may increase diabetes risk. As monitoring cancer patients for persistent hyperglycemia and diabetes is currently not a clinical standard, understanding the risk of chronic diseases, including diabetes, can inform strategies to monitor patients and decrease disease burden in this vulnerable population. Citation Format: Maci Winn, Svenja Pauleck, Richard Viskochil, Stephanie Richardson, Michelle Litchman, Howard Colman, Neli Ulrich, Siwen Hu-Lieskovan, Mary Playdon, Sheetal Hardikar. Incident diabetes by obesity-related cancer status and cancer treatment type [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 741.

Introduction: Obesity-related cancer (ORC) diagnosed individuals are at an elevated risk of new-onset diabetes compared with cancer-free individuals. However, less is known about mortality among those with incident type 2 diabetes after cancer. Methods: In the Women’s Health Initiative (N=14,455 ORC cases), we measured the association of incident type 2 diabetes diagnosed 0-1 years, >1-3, >3-5, >5-7 and >7-10 years after ORC diagnosis with cancer-specific and overall mortality using stratified Cox proportional hazards regression analysis. Results: The participants were post-menopausal females with ORC and predominantly white. The number of WHI participants with ORC who developed diabetes after cancer diagnosis were: 0-1 years - 205/12992 (1.58%); 1-3 years - 326/11322 (2.88%); 3-5 years - 276/9784 (2.82%); 5-7 years - 268/8420 (3.18%); and 7-10 years - 510/6419 (7.95%). The median survival after the first year of cancer diagnosis for participants without diabetes was 16.6 years (95% CI: 16.17-17.0 years) and for those with diabetes was 10.3 years (95% CI: 7.97-14.9 years). New-onset diabetes after ORC diagnosis showed elevated overall mortality and cancer-specific mortality when compared with no diabetes diagnosis. Conclusions: Incident type 2 diabetes is associated with worse cancer-specific and overall survival, particularly in the year after diagnosis, among women with ORC. Type 2 Diabetes from time since cancer diagnosis Overall mortality HR (95% CI)a Cancer-specific mortality HR (95% CI)a 0-1 years 1.79 (1.41-2.29) 1.56 (1.04-2.34) >1-3 years 1.22 (0.99-1.51) 1.05 (0.72-1.55) >3-5 years 1.21 (0.95-1.55) 1.37 (0.89-2.12) >5-7 years 1.02 (0.78-1.33) 0.80 (0.47-1.36) >7-10 years 1.10 (0.87-1.40) 0.97 (0.59-1.60) aModel adjusted for demographics (age, education, race/ethnicity, marital status), body mass index (BMI)) and cancer characteristics (cancer type, stage, grade). CI = confidence interval; HR = Hazard ratio. Citation Format: Prasoona Karra, Maci Winn, Benjamin Haaland, Garnet Anderson, Cynthia A. Thomson, Aladdin H. Shadyab, Juhua Luo, Nazmus Saquib, Howard Strickler, Rowan Chlebowski, Rhonda Arthur, Sheetal Hardikar, Mary C. Playdon. Diabetes incidence after obesity-related cancer diagnosis and survival in the women’s health initiative [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5880.