New-Onset Diabetes, Longitudinal Trends in Metabolic Markers, and Risk of Pancreatic Cancer in a Heterogeneous Population

Predictive biomarkers of pancreatic cancer metastasis: A comprehensive review

This review provides a comprehensive overview of predictive biomarkers associated with metastasis in pancreatic cancer (PC), one of the most aggressive malignancies characterized by late-stage diagnosis and poor prognosis. Metastasis, particularly to the liver, lungs, and lymph nodes, significantly worsens patient outcomes by compromising organ function and promoting disease progression. Reliable biomarkers for predicting and detecting metastasis at early stages are critical for improving survival rates and guiding personalized therapies. This paper highlights both general and specific biomarkers, including genetic mutations, protein expression changes, and carbohydrate tumor markers such as CA19-9. Immunological factors, including PD-L1, inflammatory cytokines, and chemokines, further influence the metastatic process within the tumor microenvironment (TME). Specific biomarkers play pivotal roles in promoting metastasis through mechanisms such as epithelial-to-mesenchymal transition (EMT), tumor microenvironment remodeling, and immune evasion. Emerging markers such as circulating tumor cells (CTCs) and volatile organic compounds (VOCs) offer promising non-invasive tools for metastasis detection and monitoring. This review not only consolidates existing knowledge but also highlights the mechanisms through which specific biomarkers facilitate metastasis. Despite recent progress, challenges such as biomarker standardization, technical variability, and clinical validation remain, and addressing these hurdles is essential for integrating predictive biomarkers into clinical practice. Ultimately, this review contributes to advancing early detection strategies, personalized treatment options, and improved prognosis for PC patients.

Current Approaches of Pancreatic Cancer Surveillance in High-Risk Individuals

Currently, those recommended to undergo pancreatic cancer (PC) surveillance include appropriately aged individuals at high risk of PC due to an identifiable genetic susceptibility or those without identifiable genetic susceptibility who nonetheless have a strong family history of PC. With increases in identification of individuals at high risk for PC and increased use of PC surveillance in clinical practice, there has been increasing debate about who should undergo surveillance as well as how surveillance should be performed including use of imaging and blood-based testing. Furthermore, there is increasing interest in the outcomes of PC surveillance in high-risk individuals with some studies demonstrating that surveillance leads to downstaging of PC and improvements in survival. In this review, we summarize the current state of PC surveillance in high-risk individuals, providing an overview of the risk factors associated with PC, selection of high-risk individuals for PC surveillance, and the current, but non-uniform, recommendations for performing PC surveillance. Additionally, we review approaches to apply various imaging and blood-based tests to surveillance and the outcomes of PC surveillance.

Persistent Health Inequalities in the Burden of Gastrointestinal Cancers Among the Elderly From 1990 to 2021: A Population-Based Study

IntroductionGlobally, aging populations highlight gastrointestinal cancers as a major public health concern. Our study aimed to quantify the trends and inequalities in the burden of gastrointestinal cancers among the elderly from 1990 to 2021.MethodsUtilizing the 2021 Global Burden of Diseases (GBD) database, our secondary analysis targeted disability-adjusted life-years (DALYs) for gastrointestinal cancers among the elderly (60+). DALYs are a composite indicator of health loss, calculated as the sum of years of life lost due to premature mortality and years lived with disability. The age-standardized DALYs rate (ASDR) was calculated using the direct standardization method. Trends were quantified by estimated annual percentage change in ASDR. The Slope index of inequality (SII) and concentration index were employed to quantify absolute and relative health inequalities.ResultsIn 2021, colon and rectum cancer (CRC) had the highest global ASDR among the elderly, followed by stomach cancer (SC), esophageal cancer (EC), pancreatic cancer (PC), liver cancer (LC), and gallbladder and biliary tract cancer (GBTC). Between 1990 and 2021, ASDR for gastrointestinal cancers decreased globally, except for PC. Health inequalities exhibited varied patterns: EC showed a worsening inequality among lower SDI countries in SII, while SC experienced a shift to higher burden among lower SDI countries in SII. LC displayed an improving inequality among lower SDI countries in SII. The concentration index for EC, SC, and LC demonstrated a transition towards higher SDI countries. CRC, GBTC, and PC maintained a higher burden in higher SDI countries, while the SII and concentration index reflected improvements in inequality.ConclusionFrom 1990 to 2021, a substantial decline was observed in the burden of gastrointestinal cancers, except for PC. Persistent and evolving health inequalities highlight the need for comprehensive, multi-level interventions to reduce disparities and achieve equitable health outcomes for all.

Genetic and other risk factors for pancreatic ductal adenocarcinoma (PDAC)

Pancreatic ductal adenocarcinoma (PDAC) is often diagnosed at an advanced stage, resulting in poor prognosis and low 5-year survival rates. While early evidence suggests increased long-term survival in those with screen-detected resectable cancers, surveillance imaging is currently only recommended for individuals with a lifetime risk of PDAC ≥ 5%. Identification of risk factors for PDAC provides opportunities for early detection, risk reducing interventions, and targeted therapies, thus potentially improving patient outcomes. Here, we summarize modifiable and non-modifiable risk factors for PDAC. We review hereditary cancer syndromes associated with risk for PDAC and their implications for patients and their relatives. In addition, other biologically relevant pathways and environmental and lifestyle risk factors are discussed. Future work may focus on elucidating additional genetic, environmental, and lifestyle risk factors that may modify PDAC risk to continue to identify individuals at increased risk for PDAC who may benefit from surveillance and risk reducing interventions.

The Added Value of Blood Glucose Monitoring in High-Risk Individuals Undergoing Pancreatic Cancer Surveillance

OBJECTIVES

The study aimed to investigate the added value of blood glucose monitoring in high-risk individuals (HRIs) participating in pancreatic cancer surveillance.

MATERIALS AND METHODS

High-risk individuals with a CDKN2A/p16 germline pathogenic variant participating in pancreatic cancer surveillance were included in this study. Multivariable logistic regression was performed to assess the relationship between new-onset diabetes (NOD) and pancreatic ductal adenocarcinoma (PDAC). To quantify the diagnostic performance of NOD as a marker for PDAC, receiver operating characteristic curve with area under the curve was computed.

RESULTS

In total, 220 HRIs were included between 2000 and 2019. Median age was 61 (interquartile range. 53-71) years and 62.7% of participants were female. During the study period, 26 (11.8%) HRIs developed NOD, of whom 5 (19.2%) later developed PDAC. The other 23 (82.1%) PDAC cases remained NOD-free. Multivariable analysis showed no statistically significant relationship between NOD and PDAC (odds ratio, 1.21; 95% confidence interval, 0.39-3.78) and 4 of 5 PDAC cases seemed to have NOD within 3 months before diagnosis. Furthermore, NOD did not differentiate between HRIs with and without PDAC (area under the curve, 0.54; 95% confidence interval, 0.46-0.61).

CONCLUSIONS

In this study, we found no added value for longitudinal glucose monitoring in CDKN2A pathogenic variant carriers participating in an imaging-based pancreatic cancer surveillance program.

The role of biomarkers in the early detection of pancreatic cancer

Pancreatic surveillance can detect early-stage pancreatic cancer and achieve long-term survival, but currently involves annual endoscopic ultrasound and MRI/MRCP, and is recommended only for individuals who meet familial/genetic risk criteria. To improve upon current approaches to pancreatic cancer early detection and to expand access, more accurate, inexpensive, and safe biomarkers are needed, but finding them has remained elusive. Newer approaches to early detection, such as using gene tests to personalize biomarker interpretation, and the increasing application of artificial intelligence approaches to integrate complex biomarker data, offer promise that clinically useful biomarkers for early pancreatic cancer detection are on the horizon.

Genetically predicted blood metabolites mediate the association between circulating immune cells and pancreatic cancer: A Mendelian randomization study

BACKGROUND

Pancreatic cancer is characterized by metabolic dysregulation and unique immunological profiles. Nevertheless, the comprehensive understanding of immune and metabolic dysregulation of pancreatic cancer remains unclear. In the present study, we aimed to investigate the causal relationship of circulating immune cells and pancreatic cancer and identify the blood metabolites as potential mediators.

METHODS

The exposure and outcome genome-wide association studies (GWAS) data used in the present study were obtained from the GWAS open-access database (https://gwas.mrcieu.ac.uk). The study used 731 circulating immune cell features, 1400 types of blood metabolites and pancreatic cancer from GWAS. We then performed bidirectional Mendelian randomization (MR) analyses to explore the causal relationships between the circulating immune cells and pancreatic cancer, and two-step MR to discover potential mediating blood metabolites in this process. All statistical analyses were performed in R software. The STROBE-MR (i.e. Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization) checklist for the reporting of MR studies was also used.

RESULTS

MR analysis identified seven types of circulating immune cells causally associated with pancreatic cancer. Furthermore, there was no strong evidence that genetically predicted pancreatic cancer had an effect on these seven types of circulating immune cells. Further two-step MR analysis found 10 types of blood metabolites were causally associated with pancreatic cancer and the associations between circulating CD39+CD8+ T cells and pancreatic cancer were mediated by blood orotates with proportions of 5.18% (p = 0.016).

CONCLUSIONS

The present study provides evidence supporting the causal relationships between various circulating immune cells, especially CD39+CD8+ T cells, and pancreatic cancer, with a potential effect mediated by blood orotates. Further research is needed on additional risk factors as potential mediators and establish a comprehensive immunity-metabolism network in pancreatic cancer.

The Association between Blood Test Trends and Undiagnosed Cancer: A Systematic Review and Critical Appraisal

Clinical guidelines include monitoring blood test abnormalities to identify patients at increased risk of undiagnosed cancer. Noting blood test changes over time may improve cancer risk stratification by considering a patient's individual baseline and important changes within the normal range. We aimed to review the published literature to understand the association between blood test trends and undiagnosed cancer. MEDLINE and EMBASE were searched until 15 May 2023 for studies assessing the association between blood test trends and undiagnosed cancer. We used descriptive summaries and narratively synthesised studies. We included 29 articles. Common blood tests were haemoglobin (24%, n = 7), C-reactive protein (17%, n = 5), and fasting blood glucose (17%, n = 5), and common cancers were pancreatic (29%, n = 8) and colorectal (17%, n = 5). Of the 30 blood tests studied, an increasing trend in eight (27%) was associated with eight cancer types, and a decreasing trend in 17 (57%) with 10 cancer types. No association was reported between trends in 11 (37%) tests and breast, bile duct, glioma, haematological combined, liver, prostate, or thyroid cancers. Our review highlights trends in blood tests that could facilitate the identification of individuals at increased risk of undiagnosed cancer. For most possible combinations of tests and cancers, there was limited or no evidence.

Mechanism exploration and biomarker identification of glycemic deterioration in patients with diseases of the exocrine pancreas

The damage to the endocrine pancreas among patients with diseases of the exocrine pancreas (DP) leads to reduced glycemic deterioration, ultimately resulting in diabetes of the exocrine pancreas (DEP). The present research aims to investigate the mechanism responsible for glycemic deterioration in DP patients, and to identify useful biomarkers, with the ultimate goal of enhancing clinical practice awareness. Gene expression profiles of patients with DP in this study were acquired from the Gene Expression Omnibus database. The original study defines DP patients to belong in one of three categories: non-diabetic (ND), impaired glucose tolerance (IGT) and DEP, which correspond to normoglycemia, early and late glycemic deterioration, respectively. After ensuring quality control, the discovery cohort included 8 ND, 20 IGT, and 12 DEP, while the validation cohort included 27 ND, 15 IGT, and 20 DEP. Gene set enrichment analysis (GSEA) employed differentially expressed genes (DEGs), while immunocyte infiltration was determined using single sample gene set enrichment analysis (ssGSEA). Additionally, correlation analysis was conducted to establish the link between clinical characteristics and immunocyte infiltration. The least absolute shrinkage and selection operator regression and random forest combined to identify biomarkers indicating glycemic deterioration in DP patients. These biomarkers were further validated through independent cohorts and animal experiments. With glycemic deterioration, biological processes in the pancreatic islets such as nutrient metabolism and complex immune responses are disrupted in DP patients. The expression of ACOT4, B2M, and ACKR2 was upregulated, whereas the expression of CACNA1F was downregulated. Immunocyte infiltration in the islet microenvironment showed a significant positive correlation with the age, body mass index (BMI), HbA1c and glycemia at the 2-h of patients. It was a crucial factor in glycemic deterioration. Additionally, B2M demonstrated a significant positive correlation with immunocyte infiltration and clinical features. Quantitative real-time PCR (qRT-PCR) and western blotting confirmed the upregulation in B2M. Immunofluorescent staining suggested the alteration of B2M was mainly in the alpha cells and beta cells. Overall, the study showed that gradually increased immunocyte infiltration was a significant contributor to glycemic deterioration in patients with DP, and it also highlighted B2M as a biomarker.

Comprehensive Review on Pancreatic Head Cancer: Pathogenesis, Diagnosis, and Treatment Challenges in the Quest for Improved Survival

This comprehensive review explores the complexities surrounding pancreatic head cancer, a highly fatal and challenging-to-treat illness with a survival rate of less than five years. Despite being a major contributor to cancer-related deaths, pancreatic head malignancy often eludes early detection due to its posterior location and high metastatic potential. The review delves into the associated symptoms, including gastric outlet obstruction and obstructive jaundice, highlighting the impact on the patient's eligibility for surgery. Examining recent advancements, the article discusses fast-track surgery recovery programs and emerging immunotherapeutic approaches, acknowledging the unique challenges posed by the immunosuppressive environment of pancreatic head cancer. Additionally, the review elucidates the intricate relationship between pancreatic cancer and glucose levels, emphasizing the role of islets of Langerhans in insulin production. The pathogenesis section explores lifestyle and genetic factors contributing to pancreatic head carcinoma, shedding light on risk factors such as smoking, obesity, diabetes, and hereditary predispositions. The extensive analysis of pancreatic cancer diagnosis methods encompasses imaging techniques, biopsies, and biomarkers, emphasizing the challenges posed by late-stage diagnoses. Addressing treatment modalities, the review emphasizes the significance of surgery, chemotherapy, radiotherapy, and targeted therapy. The intricate details of neoadjuvant, immunotherapy, and microbial therapy provide a comprehensive understanding of evolving treatment strategies. The review concludes by highlighting promising areas of research, including oncolytic viral therapy and gene editing technology, aiming to enhance the limited treatment options for this devastating disease.

Association of Glycated Hemoglobin With a Risk of Pancreatic Cancer in High-Risk Individuals Based on Genetic and Family History

INTRODUCTION

Screening for pancreatic cancer (PC) is suggested for high-risk individuals. Additional risk factors may enhance early detection in this population.

METHODS

Retrospective cohort study among patients with germline variants and/or familial pancreatic cancer in an integrated healthcare system between 2003 and 2019. We calculated the incidence rate (IR) by risk category and performed a nested case-control study to evaluate the relationship between HbA1C and PC within 3 years before diagnosis (cases) or match date (controls). Cases were matched 1:4 by age, sex, and timing of HbA1c. Logistic regression was performed to assess an independent association with PC.

RESULTS

We identified 5,931 high-risk individuals: 1,175(19.8%) familial PC, 45(0.8%) high-risk germline variants ( STK11, CDKN2A ), 4,097(69.1%) had other germline variants ( ATM, BRCA 1, BRCA 2, CASR, CDKN2A, CFTR, EPCAM, MLH1, MSH2, MSH6, PALB2, PRSS1, STK11, and TP53 ), and 614(10.4%) had both germline variants and family history. Sixty-eight patients (1.1%) developed PC; 50% were metastatic at diagnosis. High-risk variant was associated with greatest risk of PC, IR = 85.1(95% confidence interval: 36.7-197.6)/10,000 person-years; other germline variants and first-degree relative had IR = 33 (18.4, 59.3), whereas IR among ≥2 first-degree relative alone was 10.7 (6.1, 18.8). HbA1c was significantly higher among cases vs controls (median = 7.0% vs 6.4%, P = 0.02). In multivariable analysis, every 1% increase in HbA1c was associated with 36% increase in odds of PC (odds ratio 1.36, 95% confidence interval: 1.08-1.72). Pancreatitis was independently associated with a risk of PC (odds ratio 3.93, 95% confidence limit 1.19, 12.91).

DISCUSSION

Risk of PC varies among high-risk individuals. HbA1c and history of pancreatitis may be useful additional markers for early detection in this patient population.

Long non-coding RNAs and pancreatic cancer: A multifaceted view

Pancreatic cancer (PC) is a highly malignant disease with a 5-year survival rate of only 10%. Families with PC are at greater risk, as are type 2 diabetes, pancreatitis, and other factors. Insufficient early detection methods make this cancer have a poor prognosis. Additionally, the molecular mechanisms underlying PC development remain unclear. Increasing evidence suggests that long non-coding RNAs (lncRNAs) contribute to PC pathology,which may control gene expression by recruiting histone modification complexes to chromatin and interacting with proteins and RNAs. In recent studies, abnormal regulation of lncRNAs has been implicated in PC proliferation, metastasis, invasion, angiogenesis, apoptosis, and chemotherapy resistance suggesting potential clinical implications. The paper reviews the progress of lncRNA research in PC about diabetes mellitus, pancreatitis, cancer metastasis, tumor microenvironment regulation, and chemoresistance. Furthermore, lncRNAs may serve as potential therapeutic targets and biomarkers for PC diagnosis and prognosis. This will help improve PC patients' survival rate from a lncRNA perspective.

Clinical trajectory of intraductal papillary mucinous neoplasms progressing to pancreatic carcinomas during long-term surveillance: a prospective series of 100 carcinoma cases

BACKGROUND

Trajectories of serological and morphological signatures have not been documented in pancreatic carcinogenesis related to intraductal papillary mucinous neoplasms (IPMNs).

METHODS

Using a prospective cohort of 3437 IPMN patients, we identified 100 IPMN patients who developed pancreatic carcinomas during long-term surveillance. We examined serial changes of blood markers (carbohydrate antigen 19-9 [CA19-9], hemoglobin A1c [HbA1c], and pancreatic enzymes) and morphological features (worrisome features and high-risk stigmata) during the prediagnostic period of pancreatic carcinomas, overall and by carcinoma types (IPMN-derived vs. concomitant pancreatic carcinomas).

RESULTS

CA19-9 elevation was observed in 39 patients and was associated with a metastatic stage. Compared to IPMN-derived carcinomas, concomitant carcinomas were more likely to represent CA19-9 elevation (60% vs. 30%, respectively; P = 0.005). HbA1c levels elevated only in 3 patients. Pancreatic enzyme elevation was observed in 18 patients with no differences in frequencies between the carcinoma types. All patients with elevated levels of blood markers had positive findings on cross-sectional imaging. High-risk stigmata or worrisome features were observed in all patients but one with concomitant carcinoma. The most common types of worrisome features were the main pancreatic duct dilatation and CA19-9 elevation in IPMN-derived and concomitant carcinomas, respectively. Compared to IPMN-derived carcinomas, concomitant carcinomas were less likely to harbor high-risk stigmata (16% vs. 86%, respectively; P < 0.001).

CONCLUSIONS

The usefulness of currently available blood biomarkers was limited in early detection of pancreatic carcinomas related to IPMNs. Morphological alterations were well correlated with long-term risk of IPMN-derived carcinomas, but not with that of concomitant carcinomas.

Regional differences in islet amyloid deposition in the residual pancreas with new-onset diabetes secondary to pancreatic ductal adenocarcinoma

BACKGROUND

Islet amyloid deposition and reduced β-cell mass are pathological hallmarks in type 2 diabetes mellitus subjects. To date, the pathological features of the islets in diabetes secondary to pancreatic ductal adenocarcinoma (PDAC) have not been specifically addressed.

AIM

To provide further insight into the relationship between islet amyloid deposition of the residual pancreas in PDAC patients and to explore whether regional differences (proximal vs distal residual pancreas) are associated with islet amyloid deposition.

METHODS

We retrospectively collected clinical information and pancreatic tissue removed from tumors of 45 PDAC patients, including 14 patients with normal glucose tolerance (NGT), 16 patients with prediabetes and 15 new-onset diabetes (NOD) patients diagnosed before surgery by an oral glucose tolerance test at West China Hospital from July 2017 to June 2020. Pancreatic volume was calculated by multiplying the estimated area of pancreatic tissue on each image slice by the interval between slices based on abdominal computer tomography scans. Several sections of paraffin-embedded pancreas specimens from both the proximal and/or distal regions remote from the tumor were stained as follows: (1) Hematoxylin and eosin for general histological appearance; (2) hematoxylin and insulin for the determination of fractional β-cell area (immunohistochemistry); and (3) quadruple insulin, glucagon, thioflavin T and DAPI staining for the determination of β-cell area, α-cell area and amyloid deposits.

RESULTS

Screening for pancreatic histologic features revealed that duct obstruction with islet amyloid deposition, fibrosis and marked acinar atrophy were robust in the distal pancreatic regions but much less robust in the proximal regions, especially in the prediabetes and NOD groups. Consistent with this finding, the remnant pancreatic volume was markedly decreased in the NOD group by nearly one-half compared with that in the NGT group (37.35 ± 12.16 cm3 vs 69.79 ± 18.17 cm3, P < 0.001). As expected, islets that stained positive for amyloid (islet amyloid density) were found in the majority of PDAC cases. The proportion of amyloid/islet area (severity of amyloid deposition) was significantly higher in both prediabetes and NOD patients than in NGT patients (P = 0.002; P < 0.0001, respectively). We further examined the regional differences in islet amyloid deposits. Islet amyloid deposit density was robustly increased by approximately 8-fold in the distal regions compared with that in the proximal regions in the prediabetes and NOD groups (3.98% ± 3.39% vs 0.50% ± 0.72%, P = 0.01; 12.03% vs 1.51%, P = 0.001, respectively).

CONCLUSION

In conclusion, these findings suggest that robust alterations of the distal pancreas due to tumors can disturb islet function and structure with islet amyloid formation, which may be associated with the pathogenesis of NOD secondary to PDAC.

Epigenomic Blood-Based Early Detection of Pancreatic Cancer Employing Cell-Free DNA

BACKGROUND & AIMS

Early detection of pancreatic cancer (PaC) can drastically improve survival rates. Approximately 25% of subjects with PaC have type 2 diabetes diagnosed within 3 years prior to the PaC diagnosis, suggesting that subjects with type 2 diabetes are at high risk of occult PaC. We have developed an early-detection PaC test, based on changes in 5-hydroxymethylcytosine (5hmC) signals in cell-free DNA from plasma.

METHODS

Blood was collected from 132 subjects with PaC and 528 noncancer subjects to generate epigenomic and genomic feature sets yielding a predictive PaC signal algorithm. The algorithm was validated in a blinded cohort composed of 102 subjects with PaC, 2048 noncancer subjects, and 1524 subjects with non-PaCs.

RESULTS

5hmC differential profiling and additional genomic features enabled the development of a machine learning algorithm capable of distinguishing subjects with PaC from noncancer subjects with high specificity and sensitivity. The algorithm was validated with a sensitivity for early-stage (stage I/II) PaC of 68.3% (95% confidence interval [CI], 51.9%-81.9%) and an overall specificity of 96.9% (95% CI, 96.1%-97.7%).

CONCLUSIONS

The PaC detection test showed robust early-stage detection of PaC signal in the studied cohorts with varying type 2 diabetes status. This assay merits further clinical validation for the early detection of PaC in high-risk individuals.

The association of new-onset diabetes with subsequent diagnosis of pancreatic cancer-novel use of a large administrative database

BACKGROUND

Screening options for pancreatic ductal adenocarcinoma (PDAC) are limited. New-onset type 2 diabetes (NoD) is associated with subsequent diagnosis of PDAC in observational studies and may afford an opportunity for PDAC screening. We evaluated this association using a large administrative database.

METHODS

Patients were identified using claims data from the OptumLabs® Data Warehouse. Adult patients with NoD diagnosis were matched 1:3 with patients without NoD using age, sex and chronic obstructive pulmonary disease (COPD) status. The event of PDAC diagnosis was compared between cohorts using the Kaplan-Meier method. Factors associated with PDAC diagnosis were evaluated with Cox's proportional hazards modeling.

RESULTS

We identified 640 421 patients with NoD and included 1 921 263 controls. At 3 years, significantly more PDAC events were identified in the NoD group vs control group (579 vs 505; P < 0.001). When controlling for patient factors, NoD was significantly associated with elevated risk of PDAC (HR 3.474, 95% CI 3.082-3.920, P < 0.001). Other factors significantly associated with PDAC diagnosis were increasing age, increasing age among Black patients, and COPD diagnosis (P ≤ 0.05).

CONCLUSIONS

NoD was independently associated with subsequent diagnosis of PDAC within 3 years. Future studies should evaluate the feasibility and benefit of PDAC screening in patients with NoD.

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.

Temporality of body mass index, blood tests, comorbidities and medication use as early markers for pancreatic ductal adenocarcinoma (PDAC): a nested case-control study

OBJECTIVE

Prior studies identified clinical factors associated with increased risk of pancreatic ductal adenocarcinoma (PDAC). However, little is known regarding their time-varying nature, which could inform earlier diagnosis. This study assessed temporality of body mass index (BMI), blood-based markers, comorbidities and medication use with PDAC risk .

DESIGN

We performed a population-based nested case-control study of 28 137 PDAC cases and 261 219 matched-controls in England. We described the associations of biomarkers with risk of PDAC using fractional polynomials and 5-year time trends using joinpoint regression. Associations with comorbidities and medication use were evaluated using conditional logistic regression.

RESULTS

Risk of PDAC increased with raised HbA1c, liver markers, white blood cell and platelets, while following a U-shaped relationship for BMI and haemoglobin. Five-year trends showed biphasic BMI decrease and HbA1c increase prior to PDAC; early-gradual changes 2-3 years prior, followed by late-rapid changes 1-2 years prior. Liver markers and blood counts (white blood cell, platelets) showed monophasic rapid-increase approximately 1 year prior. Recent diagnosis of pancreatic cyst, pancreatitis, type 2 diabetes and initiation of certain glucose-lowering and acid-regulating therapies were associated with highest risk of PDAC.

CONCLUSION

Risk of PDAC increased with raised HbA1c, liver markers, white blood cell and platelets, while followed a U-shaped relationship for BMI and haemoglobin. BMI and HbA1c derange biphasically approximately 3 years prior while liver markers and blood counts (white blood cell, platelets) derange monophasically approximately 1 year prior to PDAC. Profiling these in combination with their temporality could inform earlier PDAC diagnosis.

Pancreatic Cancer: Changing Epidemiology and New Approaches to Risk Assessment, Early Detection, and Prevention

Pancreatic cancer usually results in poor survival with limited options for treatment, as most affected individuals present with advanced disease. Early detection of preinvasive pancreatic neoplasia and identifying molecular therapeutic targets provide opportunities for extending survival. Although screening for pancreatic cancer is currently not recommended for the general population, emerging evidence indicates that pancreatic surveillance can improve outcomes for individuals in certain high-risk groups. Changes in the epidemiology of pancreatic cancer, experience from pancreatic surveillance, and discovery of novel biomarkers provide a roadmap for new strategies for pancreatic cancer risk assessment, early detection, and prevention.

Urine biomarkers enable pancreatic cancer detection up to 2 years before diagnosis

The poor prognosis of pancreatic ductal adenocarcinoma (PDAC) is mainly attributed to late diagnosis. We assessed the predictive performance of our previously reported urine biomarker panel for earlier detection of PDAC (LYVE1, REG1B and TFF1) in prediagnostic samples, alone and in combination with plasma CA19-9. This nested case-control study included 99 PDAC cases with urine samples prospectively collected up to 5 years prior to PDAC diagnosis and 198 matched controls. The samples were obtained from the Shanghai Women's Health Study (SWHS), the Shanghai Men's Health Studies (SMHS) and the Southern Community Cohort Study (SCCS). The urine biomarkers were measured by ELISA. Plasma CA19-9 was quantified by Luminex. Multiple logistic regression and Wilcoxon rank-sum and Mann-Whitney test were used for analysis. The internal validation approach was applied and the validated AUC estimators are reported on. The algorithm of urinary protein panel, urine creatinine and age named PancRISK, displayed similar AUC as CA19-9 up to 1 year before PDAC diagnosis (AUC = 0.79); however, the combination enhanced the AUCs to 0.89, and showed good discriminative ability (AUC = 0.77) up to 2 years. The combination showed sensitivity (SN) of 72% at 90% specificity (SP), and SP of 59% at 90% SN up to 1 year and 60% SN with 80% SP and 53% SP with 80% SN up to 2 years before PDAC diagnosis. Adding the clinical information on BMI value resulted in the overall improvement in performance of the PancRISK score. When combined with CA19-9, the urinary panel reached a workable model for detecting PDAC cases up to 2 years prior to diagnosis.

Screening for pancreatic cancer has the potential to save lives, but is it practical?

INTRODUCTION

Most patients with pancreatic cancer present with advanced stage, incurable disease. However, patients with high-grade precancerous lesions and many patients with low-stage disease can be cured with surgery, suggesting that early detection has the potential to improve survival. While serum CA19.9 has been a long-standing biomarker used for pancreatic cancer disease monitoring, its low sensitivity and poor specificity have driven investigators to hunt for better diagnostic markers.

AREAS COVERED

This review will cover recent advances in genetics, proteomics, imaging, and artificial intelligence, which offer opportunities for the early detection of curable pancreatic neoplasms.

EXPERT OPINION

From exosomes, to circulating tumor DNA, to subtle changes on imaging, we know much more now about the biology and clinical manifestations of early pancreatic neoplasia than we did just five years ago. The overriding challenge, however, remains the development of a practical approach to screen for a relatively rare, but deadly, disease that is often treated with complex surgery. It is our hope that future advances will bring us closer to an effective and financially sound approach for the early detection of pancreatic cancer and its precursors.

Obesity, diabetes mellitus, and pancreatic carcinogenesis: Correlations, prevention, and diagnostic implications

The prevalence of obesity, diabetes mellitus (DM), and pancreatic cancer (PC) has been consistently increasing in the last two decades worldwide. Sharing various influential risk factors in genetics and environmental inducers in pathogenesis, the close correlations of these three diseases have been demonstrated in plenty of clinical studies using multiple parameters among different populations. On the contrary, most measures aimed to manage and treat obesity and DM effectively reduce the risk and prevent PC occurrence, yet certain drugs can inversely promote pancreatic carcinogenesis instead. Most importantly, an elevation of blood glucose with or without a reduction in body weight, along with other potential tools, may provide valuable clues for detecting PC at an early stage in patients with obesity and DM, favoring a timely intervention and prolonging survival. Herein, the epidemiological and etiological correlations among these three diseases and the supporting clinical evidence of their connections are first summarized to favor a better and more thorough understanding of obesity- and DM-related pancreatic carcinogenesis. After comparing the distinct impacts of different weight-lowering and anti-diabetic treatments on the risk of PC, the possible diagnostic implications of hyperglycemia and weight loss in PC screening are also addressed in detail.

Difference of risk of pancreatic cancer in new-onset diabetes and long-standing diabetes: population-based cohort study

CONTEXT

Considering the absence of methods to find pancreatic cancer early, surveillance of high-risk groups is needed for early diagnosis.

OBJECTIVE

The study aimed to investigate the effect in the incidence of pancreatic cancer and the differences between new-onset DM (NODM) and long-standing DM (LSDM) since NODM group is a representative high-risk group.

METHODS

The Korean National Health Insurance Service-National Sample Cohort between 2002 and 2013 data was used. Regarding 88,396 people with DM (case group), we conducted a 1:1 propensity score matching to select a matched non-DM population (control group). To investigate the interaction between DM and the time variable distinguishing NODM and LSDM, we performed a multi-variable time-dependent Cox regression analysis.

RESULTS

The incidence of pancreatic cancer was higher in the DM group compared to the non-DM group (0.52% vs. 0.16%, P < 0.001). The DM group had shown different risk of pancreatic cancer development according to the duration since the DM diagnosis (NODM hazard ratio (HR): 3.81, 95% confidence interval (CI): 2.97-4.88, P < 0.001; LSDM HR: 1.53, 95% CI: 1.11-2.11, P < 0.001). When the NODM and the LSDM groups were compared, the risk of pancreatic cancer was higher in the NODM group than LSDM group (HR: 1.55, P = 0.020). In subgroup analysis, NODM group showed that men (HR = 4.42 95% CI: 3.15-6.19, P < 0.001) and patients who were in their 50 s (HR = 7.54, 95% CI: 3.24-17.56, P < 0.001) were at a higher risk of developing pancreatic cancer than matched same sex or age control group (non-DM population), respectively.

CONCLUSION

The risk of pancreatic cancer was greater in people with DM than non-DM population. Among people with DM, NODM showed a higher risk of pancreatic cancer than long standing DM.

The association between diabetes mellitus of different durations and risk of pancreatic cancer: an Australian national data-linkage study in women

AIMS

The bidirectional association between diabetes mellitus (DM) and pancreatic cancer (PC) is established; however, the strength of association between duration of DM and risk of PC needs further investigation.

METHODS

We conducted a case-control study nested within a population-based cohort of Australian women established using record linkage. Women diagnosed with PC from July 2007 to December 2013, were matched to five controls based on age and state of residence. DM was defined according to prescription of anti-diabetic medication from administrative prescription data. We used conditional logistic regression to calculate odds ratios (OR) and 95% confidence intervals (CI), adjusted for area-level socioeconomic status, rurality of residence, weighted comorbidity score, and predicted probability of obesity.

RESULTS

The analyses included 7,267 cases and 35,978 controls. The mean age at the time of DM diagnosis was 71 years whereas the mean age at the time of diagnosis of PC was 76 years. A history of DM of any duration was associated with a 2-fold increase in risk of PC (OR=2.12; 95%CI:1.96-2.29) compared to having no history of DM. The risk decreased with increasing duration of DM. The highest risk was in those who had recent-onset DM (OR=8.08; 95%CI:6.88-9.50 for <12 months of DM), but the risk remained elevated with ≥5 years of DM (OR=1.40; 95%CI:1.27-1.55).

CONCLUSION

The markedly increased risk of PC in those with recent-onset DM emphasises the need for further research to distinguish patients for whom new-onset DM is a manifestation of PC from those with type-2 DM. The elevated risk associated with long-standing DM suggests that preventing DM may contribute to a reduction in the incidence of PC.

Risk Factors for Pancreatic Cancer in Patients with New-Onset Diabetes: A Systematic Review and Meta-Analysis

(1) Background: Patients with new-onset diabetes (NOD) are at risk of pancreatic ductal adenocarcinoma (PDAC), but the most relevant additional risk factors and clinical characteristics are not well established. (2) Objectives: To compare the risk for PDAC in NOD patients to persons without diabetes. Identify risk factors of PDAC among NOD patients. (3) Methods: Medline, Embase, and Google Scholar were last searched in June 2022 for observational studies on NOD patients and assessing risk factors for developing PDAC. Data were extracted, and Meta-Analysis was performed. Pooled effect sizes with 95% confidence intervals (CI) were estimated with DerSimonian & Laird random effects models. (4) Findings: Twenty-two studies were included, and 576,210 patients with NOD contributed to the analysis, of which 3560 had PDAC. PDAC cases were older than controls by 6.14 years (CI 3.64–8.65, 11 studies). The highest risk of PDAC involved a family history of PDAC (3.78, CI 2.03–7.05, 4 studies), pancreatitis (5.66, CI 2.75–11.66, 9 studies), cholecystitis (2.5, CI 1.4–4.45, 4 studies), weight loss (2.49, CI 1.47–4.22, 4 studies), and high/rapidly increasing glycemia (2.33, CI 1.85–2.95, 4 studies) leading to more insulin use (4.91, CI 1.62–14.86, 5 studies). Smoking (ES 1.20, CI 1.03–1.41, 9 studies) and alcohol (ES 1.23, CI 1.09–1.38, 9 studies) have a smaller effect. (5) Conclusion: Important risk factors for PDAC among NOD patients are age, family history, and gallstones/pancreatitis. Symptoms are weight loss and rapid increase in glycemia. The identified risk factors could be used to develop a diagnostic model to screen NOD patients.

Risk Factors for Pancreatic Cancer in Patients with New-Onset Diabetes: A Systematic Review and Meta-Analysis

(1) Background: Patients with new-onset diabetes (NOD) are at risk of pancreatic ductal adenocarcinoma (PDAC), but the most relevant additional risk factors and clinical characteristics are not well established. (2) Objectives: To compare the risk for PDAC in NOD patients to persons without diabetes. Identify risk factors of PDAC among NOD patients. (3) Methods: Medline, Embase, and Google Scholar were last searched in June 2022 for observational studies on NOD patients and assessing risk factors for developing PDAC. Data were extracted, and Meta-Analysis was performed. Pooled effect sizes with 95% confidence intervals (CI) were estimated with DerSimonian & Laird random effects models. (4) Findings: Twenty-two studies were included, and 576,210 patients with NOD contributed to the analysis, of which 3560 had PDAC. PDAC cases were older than controls by 6.14 years (CI 3.64–8.65, 11 studies). The highest risk of PDAC involved a family history of PDAC (3.78, CI 2.03–7.05, 4 studies), pancreatitis (5.66, CI 2.75–11.66, 9 studies), cholecystitis (2.5, CI 1.4–4.45, 4 studies), weight loss (2.49, CI 1.47–4.22, 4 studies), and high/rapidly increasing glycemia (2.33, CI 1.85–2.95, 4 studies) leading to more insulin use (4.91, CI 1.62–14.86, 5 studies). Smoking (ES 1.20, CI 1.03–1.41, 9 studies) and alcohol (ES 1.23, CI 1.09–1.38, 9 studies) have a smaller effect. (5) Conclusion: Important risk factors for PDAC among NOD patients are age, family history, and gallstones/pancreatitis. Symptoms are weight loss and rapid increase in glycemia. The identified risk factors could be used to develop a diagnostic model to screen NOD patients.

Association between Temporal Glycemic Change and Risk of Pancreatic Cancer in Men: A Prospective Cohort Study

Hyperglycemia has been reported to increase the risk of pancreatic cancer (PC), while the association between glycemic change and PC risk has rarely been explored. Using data from a prospective cohort study conducted in China since 2006, 138,870 males with available fasting blood glucose (FBG) levels, including 106,632 males with at least two FBG measurements, were analyzed. The associations between FBG (level, change, and stability) and PC incidence were evaluated using Cox proportional hazard regression and restricted cubic splines. Baseline (p = 0.109) and recent (p = 0.070) FBG levels and incident PC were not significantly associated. U-shaped associations were observed between the annual FBG change and PC risk. Compared with stable FBG, participants with annual FBG change rates <−0.05 mmol/L or >0.15 mmol/L had about four-fold (HR, 4.010; 95% CI: 1.920−8.375) and six-fold (HR, 5.897; 95% CI: 2.935−11.848) higher PC risks, respectively. The PC risk increased by 2.5% (HRlinear = 1.025, 95% CI:1.009−1.042) for every 1% increase in the coefficient of variation for FBG. A subgroup analysis of males without diabetes at baseline showed stronger associations. Temporal FBG changes may be an important factor for identifying populations with high PC risks.

Imaging of the Pancreas in New-Onset Diabetes: A Prospective Pilot Study

INTRODUCTION

The aim of this study was to assess the feasibility of cross-sectional imaging for detection of pancreatic cancer (PDAC) in patients with new-onset hyperglycemia and diabetes (NOD).

METHODS

We conducted a prospective pilot study from November 2018 to March 2020 within an integrated health system. Patients aged 50-85 years with newly elevated glycemic parameters without a history of diabetes were invited to complete a 3-phase contrast-enhanced computed tomography pancreas protocol scan while participating in the Prospective Study to Establish a NOD Cohort. Abnormal pancreatic findings, incidental extrapancreatic findings, and subsequent clinical evaluation were identified. Variability in clinical reporting between medical centers based on descriptors of pancreatic duct and parenchyma was assessed.

RESULTS

A total of 130 of 147 participants (88.4%) consented to imaging; 93 scans were completed (before COVID-19 stay-at-home order). The median age was 62.4 years (interquartile range 56.3-68.8), 37.6% women; Hispanic (39.8%), White (29.0%), Black (14.0%), and Asian (13.3%). One (1.1%) case of PDAC (stage IV) was diagnosed, 12 of 93 participants (12.9%) had additional pancreatic findings: 5 fatty infiltration, 3 cysts, 2 atrophy, 1 divisum, and 1 calcification. There were 57 extrapancreatic findings among 52 of 93 (56%) unique patients; 12 of 57 (21.1%) prompted clinical evaluation with 2 additional malignancies diagnosed (nonsmall cell lung and renal oncocytoma). Reports from 1 participating medical center more frequently provided description of pancreatic parenchyma and ducts (92.9% vs 18.4%), P < 0.0001.

DISCUSSION

High proportion of incidental findings and variability in clinical reports are challenges to be addressed for a successful NOD-based early detection strategy for PDAC.

Glycemic Changes and Weight Loss Precede Pancreatic Ductal Adenocarcinoma by up to 3 Years in a Diverse Population

BACKGROUND & AIMS

Elevations in fasting blood glucose are observed prior to the development of pancreatic ductal adenocarcinoma (PDAC). Our aim was to describe glycemic and weight changes that occur prior to PDAC diagnosis in a diverse population.

METHODS

We conducted a case-control study comparing patients with PDAC with matched controls between January 2011 and November 2019 at a tertiary care institution. Normally distributed variables were compared using t tests, and the Wilcoxon rank sum test was used for non-normally distributed variables; logistic regression was used to estimate odds of PDAC based on changes over time in hemoglobin A1c (HbA1c) and body mass index (BMI), controlling for appropriate confounders.

RESULTS

A total of 4626 patients met inclusion criteria: 1542 cases and 3084 controls; the median age was 69.3 years, and 2487 (53.8%) were male; 751 cases (48.7%) were non-Hispanic white. In the 3 years prior to diagnosis, HbA1c was higher in patients with PDAC compared with controls (P ≤ .02 for all); a similar trend was seen for glucose values. BMI was greater for patients with PDAC for all study periods, except 0 to 6 months prior to cancer diagnosis when BMI was lower (P < .01 for all). The change in BMI (ΔBMI) of cases at 1 year and 6 months before diagnosis was -0.59 and -1.21 when compared with -0.08 and 0.03 for controls (P < .01 for both). Multivariable logistic regression demonstrated that HbA1c slope (adjusted odds ratio, 1.33; 95% confidence interval, 1.01-1.76) and BMI slope (adjusted odds ratio, 0.75; 95% confidence interval, 0.65-0.87) were predictors of PDAC.

CONCLUSION

Glycemic elevations and weight loss predate PDAC diagnosis. These metabolic changes may suggest an underlying PDAC.

Characterization of the deterioration of diabetes control in patients with a subsequent diagnosis of pancreatic cancer: A descriptive study

BACKGROUND

Deterioration of diabetes control can be the first harbinger of pancreatic cancer. However, little is known about how to distinguish patients with pancreatic cancer-related diabetes deterioration from those with type 2 diabetes progression. We aimed to characterize the glycated hemoglobin (HbA1c) and body weight profile of pancreatic cancer patients with deteriorating diabetes before the cancer diagnosis.

METHODS

Using data from the UK-based Clinical Practice Research Datalink (CPRD) GOLD, we established a study population including pancreatic cancer patients with diabetes deterioration in the >0.5-3 years before the cancer diagnosis and non-cancer patients with deterioration of type 2 diabetes (comparison group). Patients were considered to have diabetes deterioration if their glucose-lowering treatment was intensified. We characterized the longitudinal trajectories of HbA1c and body weight in pancreatic cancer patients compared with non-cancer patients before and after treatment intensification.

RESULTS

The mean absolute increase in HbA1c from the pre-deterioration period, i.e. the time >1-2 years before treatment intensification, to the time of treatment intensification, was 1.5% ± 1.6% in pancreatic cancer patients vs. 0.9% ± 1.4% in non-cancer patients. After treatment intensification, mean HbA1c remained elevated in pancreatic cancer patients, while it returned to the pre-deterioration level in non-cancer patients. Body weight decreased by 1.9% ± 6.4% in cancer patients and increased by 0.3% ± 5.2% in non-cancer patients between the pre-deterioration period and treatment intensification, on average.

CONCLUSIONS

Pancreatic cancer-related diabetes deterioration may frequently be characterized by pronounced increases in HbA1c, persistent elevation of HbA1c after treatment intensification, and concomitant weight loss.

Prediction of Pancreatic Cancer in Diabetes Patients with Worsening Glycemic Control

BACKGROUND

Worsening glycemic control indicates elevated risk of pancreatic ductal adenocarcinoma (PDAC). We developed prediction models for PDAC among those with worsening glycemic control after diabetes diagnosis.

METHODS

In 2000-2016 records within the Veterans Affairs Health System (VA), we identified three cohorts with progression of diabetes: (i) insulin initiation (n = 449,685), (ii) initiation of combination oral hypoglycemic medication (n = 414,460), and (iii) hemoglobin A1c (HbA1c) ≥8% with ≥Δ1% within 15 months (n = 593,401). We computed 12-, 36-, and 60-month incidence of PDAC and developed prediction models separately for males and females, with consideration of >30 demographic, behavioral, clinical, and laboratory variables. Models were selected to optimize Akaike's Information Criterion, and performance for predicting 12-, 36-, and 60-month incident PDAC was evaluated by bootstrap.

RESULTS

Incidence of PDAC was highest for insulin initiators and greater in males than in females. Optimism-corrected c-indices of the models for predicting 36-month incidence of PDAC in the male population were: (i) 0.72, (ii) 0.70, and (iii) 0.71, respectively. Models performed better for predicting 12-month incident PDAC [c-index (i) 0.78, (ii) 0.73, (iii) 0.76 for males], and worse for predicting 60-month incident PDAC [c-index (i) 0.69, (ii) 0.67, (iii) 0.68 for males]. Model performance was lower among females. For subjects whose model-predicted 36-month PDAC risks were ≥1%, the observed incidences were (i) 1.9%, (ii) 2.2%, and (iii) 1.8%.

CONCLUSIONS

Sex-specific models for PDAC can estimate risk of PDAC at the time of progression of diabetes.

IMPACT

Our models can identify diabetes patients who would benefit from PDAC screening.

Application of artificial intelligence to pancreatic adenocarcinoma

BACKGROUND AND OBJECTIVES

Pancreatic cancer (PC) is one of the deadliest cancers worldwide although substantial advancement has been made in its comprehensive treatment. The development of artificial intelligence (AI) technology has allowed its clinical applications to expand remarkably in recent years. Diverse methods and algorithms are employed by AI to extrapolate new data from clinical records to aid in the treatment of PC. In this review, we will summarize AI's use in several aspects of PC diagnosis and therapy, as well as its limits and potential future research avenues.

METHODS

We examine the most recent research on the use of AI in PC. The articles are categorized and examined according to the medical task of their algorithm. Two search engines, PubMed and Google Scholar, were used to screen the articles.

RESULTS

Overall, 66 papers published in 2001 and after were selected. Of the four medical tasks (risk assessment, diagnosis, treatment, and prognosis prediction), diagnosis was the most frequently researched, and retrospective single-center studies were the most prevalent. We found that the different medical tasks and algorithms included in the reviewed studies caused the performance of their models to vary greatly. Deep learning algorithms, on the other hand, produced excellent results in all of the subdivisions studied.

CONCLUSIONS

AI is a promising tool for helping PC patients and may contribute to improved patient outcomes. The integration of humans and AI in clinical medicine is still in its infancy and requires the in-depth cooperation of multidisciplinary personnel.

Type 2 diabetes prevention diet and the risk of pancreatic cancer: A large prospective multicenter study

BACKGROUND & AIMS

Type 2 diabetes prevention diet confers a lower risk of type 2 diabetes, which exhibits overlapping mechanisms with pancreatic cancer. We performed a prospective study to examine whether adherence to this dietary pattern is associated with a reduced risk of pancreatic cancer.

METHODS

A population-based cohort of 101,729 American adults was identified. A dietary diabetes risk reduction score was computed to reflect adherence to this dietary pattern, with higher scores representing greater adherence. Cox regression was used to compute hazard ratios (HRs) for pancreatic cancer incidence. Prespecified subgroup analyses were used to identify the potential effect modifiers.

RESULTS

After an average follow-up of 8.86 years (900,871.67 person-years), a total of 402 pancreatic cancer cases were observed. In the fully adjusted model, participants in the highest quartile of dietary diabetes risk reduction score were found to have a reduced risk of pancreatic cancer compared with those in the lowest quartile [HR_{quartiles 4versus1}: 0.62; 95% confidence interval (CI): 0.44, 0.86; P_trend = 0.004], which remained in a series of sensitivity analyses. Subgroup analyses further found that this favorable association was more pronounced in current or former smokers (HR_{quartiles 4versus1}: 0.48; 95% CI: 0.30, 0.77) than in never smokers (HR_{quartiles 4versus1}: 0.71; 95% CI: 0.44, 1.15), although the interaction test did not reach statistical significance (P_interaction = 0.095).

CONCLUSIONS

Greater adherence to type 2 diabetes prevention diet is associated with a lower risk of pancreatic cancer in this US population. More studies are needed to confirm our findings.

Pancreatogenic Diabetes, 2 Onset Forms and Lack of Metabolic Syndrome Components Differentiate It From Type 2 Diabetes

OBJECTIVES

We compared pancreatogenic (DM3c) and type 2 diabetes mellitus.

METHODS

We compared age-, sex-, and diabetes mellitus duration-matched DM3c cases (n = 142) and type 2 diabetes mellitus (n = 142). Pancreatogenic diabetes was considered when it appeared after the diagnosis of pancreatitis or after pancreatic surgery.

RESULTS

Pancreatogenic diabetes presented lower body mass index (BMI) [odds ratio (OR), 1.2; 95% confidence interval (CI), 1.13-1.28; P < 0.001], worse glycemic control (OR, 1.196; 95% CI, 1.058-1.35; P = 0.004), required insulin more frequently (OR, 4.21; 95% CI, 2.57-6.93; P = 0.0001), had more hypoglycemic episodes (OR, 3.65; 95% CI, 1.64-8.16; P = 0.001) but lower frequency of dyslipidemia (OR, 0.42; 95% CI, 0.26-0.68; P = 0.001) and arterial hypertension (OR, 0.52; 95% CI, 0.32-0.86; P = 0.01). Pancreatogenic diabetes cases on pancreatic enzyme replacement therapy had lower glycosylated hemoglobin (8.52% vs 9.44%; P = 0.026), serum carotenes (79.1 vs 116.1; P = 0.03), and BMI (23.4 vs 26.1; P = 0.0005) than those not on pancreatic enzyme replacement therapy. Pancreatogenic diabetes onset occurred earlier in necrotizing pancreatitis and after pancreatic surgery.

CONCLUSIONS

Pancreatogenic diabetes presents with low BMI and lacks metabolic syndrome components. The type of pancreatic disease or surgery defines its onset time.

Diabetes and pancreatic cancer: recent insights with implications for early diagnosis, treatment and prevention

PURPOSE OF REVIEW

Recent insights into the complex relationship between diabetes and pancreatic cancer have the potential to help direct future approaches to early detection, treatment and prevention.

RECENT FINDINGS

Insulin resistance and hyperinsulinemia have been identified as factors that relate to risk of pancreatic cancer among patients with long-standing diabetes. In contrast, weight loss in the setting of new-onset diabetes can help identify patients at an increased risk for harbouring pancreatic-cancer related disturbances in glucose metabolism. Insights into the implications of poor glycaemic control in patients undergoing resection for pancreatic cancer have the potential to improve both surgical and oncologic outcomes. Finally, among antidiabetic medications, metformin continues to be evaluated as a potential adjunctive therapeutic agent, although recent evidence supports the safety of incretins with respect to pancreatic cancer.

SUMMARY

This review highlights recent developments in these areas with an emphasis on opportunities for improved early diagnosis, treatment and prevention in pancreatic cancer.

Diabetes and pancreatic cancer: Exploring the two-way traffic

Pancreatic cancer (PC) is often associated with a poor prognosis. Long-standing diabetes mellitus is considered as an important risk factor for its development. This risk can be modified by the use of certain antidiabetic medications. On the other hand, new-onset diabetes can signal towards an underlying PC in the elderly population. Recently, several attempts have been made to develop an effective clinical tool for PC screening using a combination of history of new-onset diabetes and several other clinical and biochemical markers. On the contrary, diabetes affects the survival after treatment for PC. We describe this intimate and complex two-way relationship of diabetes and PC in this review by exploring the underlying pathogenesis.

Pancreatic cancer: A review of epidemiology, trend, and risk factors

Despite rapid advances in modern medical technology and significant improvements in survival rates of many cancers, pancreatic cancer is still a highly lethal gastrointestinal cancer with a low 5-year survival rate and difficulty in early detection. At present, the incidence and mortality of pancreatic cancer are increasing year by year worldwide, no matter in the United States, Europe, Japan, or China. Globally, the incidence of pancreatic cancer is projected to increase to 18.6 per 100000 in 2050, with the average annual growth of 1.1%, meaning that pancreatic cancer will pose a significant public health burden. Due to the special anatomical location of the pancreas, the development of pancreatic cancer is usually diagnosed at a late stage with obvious clinical symptoms. Therefore, a comprehensive understanding of the risk factors for pancreatic cancer is of great clinical significance for effective prevention of pancreatic cancer. In this paper, the epidemiological characteristics, developmental trends, and risk factors of pancreatic cancer are reviewed and analyzed in detail.

Pancreatic cancer cachexia: three dimensions of a complex syndrome

Cancer cachexia is a multifactorial syndrome that is characterised by a loss of skeletal muscle mass, is commonly associated with adipose tissue wasting and malaise, and responds poorly to therapeutic interventions. Although cachexia can affect patients who are severely ill with various malignant or non-malignant conditions, it is particularly common among patients with pancreatic cancer. Pancreatic cancer often leads to the development of cachexia through a combination of distinct factors, which, together, explain its high prevalence and clinical importance in this disease: systemic factors, including metabolic changes and pathogenic signals related to the tumour biology of pancreatic adenocarcinoma; factors resulting from the disruption of the digestive and endocrine functions of the pancreas; and factors related to the close anatomical and functional connection of the pancreas with the gut. In this review, we conceptualise the various insights into the mechanisms underlying pancreatic cancer cachexia according to these three dimensions to expose its particular complexity and the challenges that face clinicians in trying to devise therapeutic interventions.

Validation of the ENDPAC model: Identifying new-onset diabetics at risk of pancreatic cancer

BACKGROUND

Patients with new-onset diabetes are known to be at a higher risk of developing pancreatic cancer. The Enriching New-Onset Diabetes for Pancreatic Cancer (ENDPAC) model was recently developed to identify new-onset diabetics with this higher risk. Further validation is needed before the ENDPAC model is implemented as part of a screening program to identify pancreatic cancer.

METHODS

A retrospective case-control study was performed; a cohort of patients with new-onset diabetes was identified using hemoglobin A1c. Patients were scored by the ENDPAC model and then divided based on whether pancreatic cancer was diagnosed after the diagnosis of diabetes. The performance of the model was assessed globally and at different cutoffs.

RESULTS

There were 6254 controls and 48 cases of pancreatic cancer. Bivariate analysis showed that patients with pancreatic cancer lost weight before diagnosis while controls gained weight (-0.93 kg/m2 vs. 0.45 kg/m2, p < 0.00∗). Cases had a more significant increase in their HbA1C from one year before (1.3% vs. 0.82%, p = 0.02). Smoking and pancreatitis rates were higher in cases compared to controls (p < 0.00∗). The area under the curve (AUC) of the ENDPAC model was 0.72. A score >1 was the optimal cutoff. At this cutoff, the sensitivity was 56%, specificity was 75%, and pancreatic cancer prevalence increased from 0.78% at baseline to 1.7%.

CONCLUSION

The ENDPAC model was validated in an independent cohort of patients with new-onset diabetes.

Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review

ABSTRACT

Despite considerable research efforts, pancreatic cancer is associated with a dire prognosis and a 5-year survival rate of only 10%. Early symptoms of the disease are mostly nonspecific. The premise of improved survival through early detection is that more individuals will benefit from potentially curative treatment. Artificial intelligence (AI) methodology has emerged as a successful tool for risk stratification and identification in general health care. In response to the maturity of AI, Kenner Family Research Fund conducted the 2020 AI and Early Detection of Pancreatic Cancer Virtual Summit (www.pdac-virtualsummit.org) in conjunction with the American Pancreatic Association, with a focus on the potential of AI to advance early detection efforts in this disease. This comprehensive presummit article was prepared based on information provided by each of the interdisciplinary participants on one of the 5 following topics: Progress, Problems, and Prospects for Early Detection; AI and Machine Learning; AI and Pancreatic Cancer-Current Efforts; Collaborative Opportunities; and Moving Forward-Reflections from Government, Industry, and Advocacy. The outcome from the robust Summit conversations, to be presented in a future white paper, indicate that significant progress must be the result of strategic collaboration among investigators and institutions from multidisciplinary backgrounds, supported by committed funders.

Therapeutic resistance of pancreatic cancer: Roadmap to its reversal

Pancreatic cancer is a lethal disease with limited opportunity for resectable surgery as the first choice for cure due to its late diagnosis and early metastasis. The desmoplastic stroma and cellular genetic or epigenetic alterations of pancreatic cancer impose physical and biological barriers to effective therapies, including chemotherapy, radiotherapy, targeted therapy, and immunotherapy. Here, we review the current therapeutic options for pancreatic cancer, and underlying mechanisms and potential reversal of therapeutic resistance, a hallmark of this deadly disease.

Screening Strategy of Pancreatic Cancer in Patients with Diabetes Mellitus

The incidence of pancreatic cancer (PCa) is increasing worldwide and has become one of the leading causes of cancer-related death. Screening for high risk populations is fundamental to overcome this intractable malignancy. Diabetes mellitus (DM) is classically known as a risk factor for PCa. Recently the reverse causality is in the spotlight, that is to say, DM is considered to be a manifestation of PCa. Numbers of epidemiological studies clarified that new-onset DM (≤2-year duration) was predominant in PCa patients and the relative risk for PCa inversely correlated with duration of DM. Among patients with new-onset DM, elder onset, weight loss, and rapid exacerbation of glycemic control were reported to be promising risk factors and signs, and the model was developed by combining these factors. Several pilot studies disclosed the possible utility of biomarkers to discriminate PCa-associated DM from type 2 DM. However, there is no reliable biomarkers to be used in the practice. We previously reported the application of a multivariate index for PCa based on the profile of plasma free amino acids (PFAAs) among diabetic patients. We are further investigating on the PFAA profile of PCa-associated DM, and it can be useful for developing the novel biomarker in the near future.

Pancreatic Cancer: A Review of Risk Factors, Diagnosis, and Treatment

This review aims to summarize the latest knowledge on factors, diagnosis, and treatment of pancreatic cancer, and aims to promote further research on this under-studied malignant tumor. At present, we urgently need to identify high-risk patients with precancerous diseases through screening approaches, so that medical professionals and the general public may better understand prevention strategies or early detection measures. Pancreatic cancer is a highly invasive malignant tumor with a fatal risk, mainly seen in men and older adults (60-85 years old). Pancreatic cancer is now increasingly observed in young patients. Because the disease has no early symptoms and can quickly invade surrounding tissues and organs, it is one of the deadliest cancers. With a view to identify the important factors for the development of pancreatic cancer, previous studies have found that smoking, alcohol, and chronic pancreatitis are considered high-risk factors. Recent studies have shown that abnormal metabolism of human microorganisms, blood type, and glucose and lipid levels are also important factors in the development of pancreatic cancer. Identifying early diagnosis options is an important way to improve detection and survival rates of pancreatic cancer. None of the many tumor markers associated with pancreatic cancer are highly specific, which also indicates further research is required to improve the early detection rate. Future directions in terms of treatment evaluating the relationship between the microbiology-free system and immunotherapy will bring a major breakthrough and is expected to bring exciting clinical applications in improving the life-cycle of pancreatic cancer patients.