New-onset diabetes in pancreatic cancer: a study in the primary care setting

Assessing NODM Patients for Early PDAC Diagnosis: Incidence of NODM Before PDAC Diagnosis and Subsequent PDAC Risk

BACKGROUND

New-Onset Diabetes Mellitus (NODM) is often an early manifestation of pancreatic cancer (Pancreatic Ductal Adenocarcinoma, PDAC). However, there is limited information about (1) the duration prior to PDAC diagnosis when the annual incidence of NODM starts significantly exceeding that in age-matched controls, (2) the percentage of PDAC patients diagnosed with NODM in the years preceding, and (3) the risk of PDAC following NODM in time when the PDAC risk is significantly higher than in controls.

METHODS

Using the nationwide VA database, we evaluated the annual incidence of NODM for 15 years preceding the PDAC diagnosis and in the age- and sex-matched controls (1:5 matching). In the second part, we evaluated the long-term risk and predictors of PDAC in NODM patients and controls.

RESULTS

The case-control study comprised 8198 PDAC patients and 40,992 matched controls. The higher annual incidence of NODM in PDAC patients was statistically significant up to 15 years before PDAC diagnosis. 69.2% of PDAC patients had NODM in the preceding 15 years versus 38.0% of controls. PDAC risk in the 15 years following NODM was 0.60% compared to 0.13% in the controls (aHR 3.83, 95% CI 3.68-3.98, p < 0.001). The risk of PDAC is more pronounced in the 1 year following NODM (aHR 9.07, 95% CI 8.33-9.87) than the subsequent 5 years (aHR 2.98, 95% CI 2.82-3.15).

CONCLUSION

NODM pre-dates PDAC diagnosis in most patients with PDAC. Further evaluation of NODM patients for PDAC has the potential to become a feasible strategy for diagnosing more early-stage resectable PDACs.

Can AI Be Useful in the Early Detection of Pancreatic Cancer in Patients with New-Onset Diabetes?

Pancreatic cancer is one of the most lethal neoplasms. Despite considerable research conducted in recent decades, not much has been achieved to improve its survival rate. That may stem from the lack of effective screening strategies in increased pancreatic cancer risk groups. One population that may be appropriate for screening is new-onset diabetes (NOD) patients. Such a conclusion stems from the fact that pancreatic cancer can cause diabetes several months before diagnosis. The most widely used screening tool for this population, the ENDPAC (Enriching New-Onset Diabetes for Pancreatic Cancer) model, has not achieved satisfactory results in validation trials. This provoked the first attempts at using artificial intelligence (AI) to create larger, multi-parameter models that could better identify the at-risk population, which would be suitable for screening. The results shown by the authors of these trials seem promising. Nonetheless, the number of publications is limited, and the downfalls of using AI are not well highlighted. This narrative review presents a summary of previous publications, recent advancements and feasible solutions for effective screening of patients with NOD for pancreatic cancer.

Aspirin is associated with lower risk of pancreatic cancer and cancer-related mortality in patients with diabetes mellitus

BACKGROUND

Patients with type 2 diabetes mellitus (T2DM) have higher pancreatic cancer (PC) risk. While aspirin has chemopreventive effects on digestive cancers, its effect on PC among patients with T2DM is unclear.

METHODS

This retrospective cohort study identified newly diagnosed adult patients with T2DM in Hong Kong between 2001 and 2015 from a territory-wide healthcare registry. Exclusion criteria were history of PC, pancreatic cyst, IgG4 disease, or pancreatectomy. To address reverse causality between PC and T2DM, we excluded patients with PC diagnosed within 1 year of T2DM. We also excluded patients with less than 1 year of observation. Primary outcome was PC, and secondary outcomes were PC-related and all-cause mortality. Aspirin use was treated as time-varying variable (≥180 day-use/year) to address immortal-time bias, and multivariable Cox regression model was employed to derive adjusted HR (aHR). Propensity-score (PS) matching was used as secondary analysis.

RESULTS

Among 343 966 newly diagnosed patients with T2DM (median follow-up: 10.5 years; IQR: 7.7-14.5 years), 1224 (0.36%) developed PC. There were 51 151 (14.9%) deaths from any cause, and 787 (0.2%) died from PC. Aspirin use was associated with lower PC risk in both time-dependent (aHR: 0.58; 95% CI 0.49 to 0.69) and PS matching analysis (aHR: 0.61; 95% CI 0.48 to 0.77). An inverse relationship was observed with increasing dose and duration of aspirin use (P trend<0.001). Aspirin was also associated with a lower risk of PC-related mortality (aHR: 0.43; 95% CI 0.34 to 0.53) and all-cause mortality (aHR: 0.78; 95% CI 0.76 to 0.80).

CONCLUSION

Aspirin use may be an oncopreventive strategy to reduce PC risk in patients with T2DM. Further studies are warranted to validate the study findings.

Assessment of Glucose and HbA1c Monitoring in a Pancreatic Cancer Surveillance Program for High-Risk Individuals

INTRODUCTION

Several studies suggest that new-onset diabetes mellitus is an early manifestation of pancreatic ductal adenocarcinoma (PDAC). Therefore, the International Cancer of the Pancreas Screening Consortium recommends glucose and hemoglobin A1c (HbA1c) monitoring in high-risk individuals (HRIs) undergoing surveillance. However, evidence that such monitoring improves PDAC detection is lacking. Our aim was to investigate the association between serum glucose and HbA1c values and the development of PDAC in HRIs undergoing surveillance.

METHODS

Participants were recruited from the familial pancreatic cancer surveillance cohort, which follows hereditary predisposed HRIs yearly by magnetic resonance imaging and/or endoscopic ultrasound and blood sampling. Those who underwent fasting glucose and/or HbA1c monitoring at least once were eligible candidates.

RESULTS

Four hundred four HRIs met the inclusion criteria. During a median follow-up of 41 months (range 14-120), 9 individuals developed PDAC and 4 (without PDAC) were diagnosed with new-onset diabetes mellitus. Glucose levels ranged from 3.4 to 10.7 mmol/L (mean 5.6 ± 0.7) and HbA1c levels from 25 to 68 mmol/mol (mean 37.7 ± 4.1). The mean values did not differ significantly between PDAC cases and controls. The percentage of individuals with at least one elevated value were comparable between PDAC cases and controls for glucose (33% and 27%, P = 0.707) and HbA1c (22% and 14%, P = 0.623). No consistent glucose or HbA1c trends over time suggested a correlation with PDAC development.

DISCUSSION

In this HRI surveillance cohort, measuring glucose and HbA1c values did not contribute to PDAC detection. Larger and longer-term studies are needed to determine the final role of glucose and HbA1c monitoring in PDAC surveillance.

Machine Learning Predicts Patients With New-onset Diabetes at Risk of Pancreatic Cancer

BACKGROUND

New-onset diabetes represent a high-risk cohort to screen for pancreatic cancer.

GOALS

Develop a machine model to predict pancreatic cancer among patients with new-onset diabetes.

STUDY

A retrospective cohort of patients with new-onset diabetes was assembled from multiple health care networks in the United States. An XGBoost machine learning model was designed from a portion of this cohort (the training set) and tested on the remaining part of the cohort (the test set). Shapley values were used to explain the XGBoost's model features. Model performance was compared with 2 contemporary models designed to predict pancreatic cancer among patients with new-onset diabetes.

RESULTS

In the test set, the XGBoost model had an area under the curve of 0.80 (0.76 to 0.85) compared with 0.63 and 0.68 for other models. Using cutoffs based on the Youden index, the sensitivity of the XGBoost model was 75%, the specificity was 70%, the accuracy was 70%, the positive predictive value was 1.2%, and the negative predictive value was >99%. The XGBoost model obtained a positive predictive value of at least 2.5% with a sensitivity of 38%. The XGBoost model was the only model that detected at least 50% of patients with cancer one year after the onset of diabetes. All 3 models had similar features that predicted pancreatic cancer, including older age, weight loss, and the rapid destabilization of glucose homeostasis.

CONCLUSION

Machine learning models isolate a high-risk cohort from those with new-onset diabetes at risk for pancreatic cancer.

Imaging for Early Detection of Pancreatic Ductal Adenocarcinoma: Updates and Challenges in the Implementation of Screening and Surveillance Programs

Pancreatic ductal adenocarcinoma (PDA) is one of the most aggressive cancers. It has a poor 5-year survival rate of 12%, partly because most cases are diagnosed at advanced stages, precluding curative surgical resection. Early-stage PDA has significantly better prognoses due to increased potential for curative interventions, making early detection of PDA critically important to improved patient outcomes. We examine current and evolving early detection concepts, screening strategies, diagnostic yields among high-risk individuals, controversies, and limitations of standard-of-care imaging.

Remnant Pancreas Volume Affects New-Onset Impaired Glucose Homeostasis Secondary to Pancreatic Cancer

BACKGROUND

New-onset diabetes (NOD) has been identified as a high-risk factor for the early detection of pancreatic ductal adenocarcinoma (PDAC). The role of tumor volume and remnant pancreas volume (RPV) in the progression from normal to NOD in PDAC patients is not fully illustrated yet.

METHODS

In this cross-sectional study, glycemic metabolism traits of 95 PDAC patients before pancreatic surgery were described and compared with chronic pancreatitis and type 2 diabetes mellitus patients based on the oral glucose tolerance test. The remnant RPV and tumor volume, calculated by three-dimensional reconstruction of radiological images, were included in the ordinal logistic regression models.

RESULTS

The prevalence of NOD was high among PDAC patients (38.9%). However, normal glucose tolerance (NGT) or prediabetes mellitus status were present as more than half (24/44) of advanced tumor stage patients. Indexes reflecting beta-cell function but not insulin sensitivity gradually worsened from NGT to NOD patients (all p < 0.05). The remnant pancreas volume (RPV) was identified as a potential protective factor for diabetes secondary to PDAC (odds ratio 0.95, 95% CI [0.92, 0.97], p < 0.001).

CONCLUSIONS

Reduced RPV causing beta-cell dysfunction might be one of the mechanisms of NOD secondary to PDAC. Subjects with sufficient pancreas volume could not be detected earlier when regarding patients with NOD as the population at risk for PDAC.

Diabetes and pancreatic cancer risk in a multiracial cohort

AIMS

To determine the relationship of diabetes with pancreatic cancer incidence among African American and Whites of similar socio-economic status.

METHODS

Using the Southern Community Cohort Study, we conducted a follow-up during 2002-2015 of pancreatic cancer incidence of 73,378 mostly low-income participants aged 40-79 years; 15,913 reported diabetes at baseline. Multivariable Cox analysis controlling for sex, family history of pancreatic cancer, BMI, smoking status, alcohol consumption, education, income and other important covariates, and with age as the timescale was used.

RESULTS

Totally, 265 incident pancreatic cancer cases were observed. Pancreatic cancer risk was increased among those with diabetes (HR 1.54, CI 1.16-2.05), with similar increases among African Americans (HR 1.51, CI 1.08-2.11) and Whites (HR 1.78, CI 1.00-3.16). No trend in risk was observed for diabetes duration among those with diabetes, with HRs of 1.39 (0.91-2.11), 2.31 (1.51-3.54) and 1.23 (0.80-1.89) for <5, 5-9 and 10+ years duration, respectively. African Americans were at increased risk of pancreatic cancer (HR = 1.40, 95% CI 1.05-1.87), which persisted after adjusting for diabetes (HR 1.36, CI 1.02-1.81). The effect sizes for other pancreatic cancer risk factors with pancreatic cancer were similar by diabetes status, although a stronger association with low BMI was evident among those with diabetes.

CONCLUSIONS

Diabetes increases pancreatic cancer risk similarly among African Americans and Whites in this Southern U.S.

COHORT

Determining the feasibility of calculating pancreatic cancer risk scores for people with new-onset diabetes in primary care (DEFEND PRIME): study protocol

INTRODUCTION

Worldwide, pancreatic cancer has a poor prognosis. Early diagnosis may improve survival by enabling curative treatment. Statistical and machine learning diagnostic prediction models using risk factors such as patient demographics and blood tests are being developed for clinical use to improve early diagnosis. One example is the Enriching New-onset Diabetes for Pancreatic Cancer (ENDPAC) model, which employs patients' age, blood glucose and weight changes to provide pancreatic cancer risk scores. These values are routinely collected in primary care in the UK. Primary care's central role in cancer diagnosis makes it an ideal setting to implement ENDPAC but it has yet to be used in clinical settings. This study aims to determine the feasibility of applying ENDPAC to data held by UK primary care practices.

METHODS AND ANALYSIS

This will be a multicentre observational study with a cohort design, determining the feasibility of applying ENDPAC in UK primary care. We will develop software to search, extract and process anonymised data from 20 primary care providers' electronic patient record management systems on participants aged 50+ years, with a glycated haemoglobin (HbA1c) test result of ≥48 mmol/mol (6.5%) and no previous abnormal HbA1c results. Software to calculate ENDPAC scores will be developed, and descriptive statistics used to summarise the cohort's demographics and assess data quality. Findings will inform the development of a future UK clinical trial to test ENDPAC's effectiveness for the early detection of pancreatic cancer.

ETHICS AND DISSEMINATION

This project has been reviewed by the University of Surrey University Ethics Committee and received a favourable ethical opinion (FHMS 22-23151 EGA). Study findings will be presented at scientific meetings and published in international peer-reviewed journals. Participating primary care practices, clinical leads and policy makers will be provided with summaries of the findings.

Elevated Glycated Haemoglobin (HbA1c) Is Associated with an Increased Risk of Pancreatic Ductal Adenocarcinoma: A UK Biobank Cohort Study

BACKGROUND

The role of dysglycaemia as a risk marker for Pancreatic Ductal Adenocarcinoma (PDAC) is uncertain. We investigated the relationship between glycated haemoglobin (HbA1c) and incident PDAC using a retrospective cohort study within the UK Biobank.

METHODS

A study involving 499,804 participants from the UK Biobank study was undertaken. Participants were stratified by diabetes mellitus (DM) status, and then by HbA1c values < 42 mmol/mol, 42-47 mmol/mol, or ≥48 mmol/mol. Cox proportional hazard models were used to describe the association between HbA1c category (with time-varying interactions) and incident PDAC.

RESULTS

PDAC occurred in 1157 participants during 11.6 (10.9-12.3) years follow up [(median (interquartile range)]. In subjects without known DM at baseline, 12 months after recruitment, the adjusted hazard ratios (aHR, 95% CI) for incident PDAC for HbA1c 42-47 mmol/mol compared to HbA1c < 42 mmol/mol (reference group) was 2.10 (1.31-3.37, p = 0.002); and was 8.55 (4.58-15.99, p < 0.001) for HbA1c ≥ 48 mmol/mol. The association between baseline HbA1c and incident PDAC attenuated with increasing duration of time of follow-up to PDAC diagnosis.

CONCLUSIONS

Dysglycaemia detected by elevated HbA1c is associated with an increased risk of PDAC. The strength of the association between elevated HbA1c and incident PDAC is inversely proportional to the time from detecting dysglycaemia but remains significant for at least 60 months following HbA1c testing.

Diabetes Mellitus in Pancreatic Cancer: A Distinct Approach to Older Subjects with New-Onset Diabetes Mellitus

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is associated with a very poor prognosis, with near-identical incidence and mortality. According to the World Health Organization Globocan Database, the estimated number of new cases worldwide will rise by 70% between 2020 and 2040. There are no effective screening methods available so far, even for high-risk individuals. The prognosis of PDAC, even at its early stages, is still mostly unsatisfactory. Impaired glucose metabolism is present in about 3/4 of PDAC cases.

METHODS

Available literature on pancreatic cancer and diabetes mellitus was reviewed using a PubMed database. Data from a national oncology registry (on PDAC) and information from a registry of healthcare providers (on diabetes mellitus and a number of abdominal ultrasound investigations) were obtained.

RESULTS

New-onset diabetes mellitus in subjects older than 60 years should be an incentive for a prompt and detailed investigation to exclude PDAC. Type 2 diabetes mellitus, diabetes mellitus associated with chronic non-malignant diseases of the exocrine pancreas, and PDAC-associated type 3c diabetes mellitus are the most frequent types. Proper differentiation of particular types of new-onset diabetes mellitus is a starting point for a population-based program. An algorithm for subsequent steps of the workup was proposed.

CONCLUSIONS

The structured, well-differentiated, and elaborately designed approach to the elderly with a new onset of diabetes mellitus could improve the current situation in diagnostics and subsequent poor outcomes of therapy of PDAC.

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.

FN1 encoding fibronectin as a pivotal signaling gene for therapeutic intervention against pancreatic cancer

The delayed diagnosis of pancreatic cancer has resulted in rising mortality rate and low survival rate that can be circumvented using potent theranostics biomarkers. The treatment gets complicated with delayed detection resulting in lowered 5-year relative survival rate. In our present study, we employed systems biology approach to identify central genes that play crucial roles in tumor progression. Pancreatic cancer genes collected from various databases were used to construct a statistically significant interactome with 812 genes that was further analysed thoroughly using topological parameters and functional enrichment analysis. The significant genes in the network were then identified based on the maximum degree parameter. The overall survival analysis indicated through hazard ratio [HR] and gene expression [log Fold Change] across pancreatic adenocarcinoma revealed the critical role of FN1 [HR 1.4; log2(FC) 5.748], FGA [HR 0.78; log2(FC) 1.639] FGG [HR 0.9; log2(FC) 1.597], C3 [HR 1.1; log2(FC) 2.637], and QSOX1 [HR 1.4; log2(FC) 2.371]. The functional significance of the identified hub genes signified the enrichment of integrin cell surface interactions and proteoglycan syndecan-mediated cell signaling. The differential expression, low overall survival and functional significance of FN1 gene implied its possible role in controlling metastasis in pancreatic cancer. Furthermore, alternate splice variants of FN1 gene showed 10 protein coding transcripts with conserved cell attachment site and functional domains indicating the variants' potential role in pancreatic cancer. The strong association of the identified hub-genes can be better directed to design potential theranostics biomarkers for metastasized pancreatic tumor.

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.

Recent advances in artificial intelligence for pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) remains the most lethal type of cancer. The 5-year survival rate for patients with early-stage diagnosis can be as high as 20%, suggesting that early diagnosis plays a pivotal role in the prognostic improvement of PDAC cases. In the medical field, the broad availability of biomedical data has led to the advent of the "big data" era. To overcome this deadly disease, how to fully exploit big data is a new challenge in the era of precision medicine. Artificial intelligence (AI) is the ability of a machine to learn and display intelligence to solve problems. AI can help to transform big data into clinically actionable insights more efficiently, reduce inevitable errors to improve diagnostic accuracy, and make real-time predictions. AI-based omics analyses will become the next alterative approach to overcome this poor-prognostic disease by discovering biomarkers for early detection, providing molecular/genomic subtyping, offering treatment guidance, and predicting recurrence and survival. Advances in AI may therefore improve PDAC survival outcomes in the near future. The present review mainly focuses on recent advances of AI in PDAC for clinicians. We believe that breakthroughs will soon emerge to fight this deadly disease using AI-navigated precision medicine.

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.

Noninvasive Models Screen New-Onset Diabetics at Low Risk of Early-Onset Pancreatic Cancer

OBJECTIVES

Several noninvasive models have been developed to identify new-onset diabetics at higher risk of developing pancreatic ductal adenocarcinoma (PDAC). However, they need external validation before implementation.

METHODS

This study validated one such model (Boursi model) among a cohort of new-onset diabetics. A bivariate analysis of the model's components was done between patients who developed PDAC and type 2 diabetics. The model performance was assessed through receiver-operative characteristic curve analysis.

RESULTS

Patients with PDAC had significantly lower total cholesterol and alkaline phosphatase at diagnosis of diabetes (P < 0.01). They were observed losing body mass index (BMI) preceding diagnosis (ΔBMI = -0.42 kg/m2, P < 0.01). The model's area under the curve was 0.83 (95% confidence interval, 0.79-0.88). The cutoff that maximized the Youden index was at 0.8%. At this cutoff, the sensitivity was 75%, specificity was 80%, and the prevalence of pancreatic cancer increased from 0.19% at baseline to 0.69%.

CONCLUSIONS

Boursi model enriches the prevalence of PDAC among new-onset diabetics.

Burden of Pancreatic Cancer: From Epidemiology to Practice

Pancreatic cancer is the seventh leading cause of cancer-related deaths worldwide with 432,242 related deaths in 2018. Unlike other cancers, the incidence of pancreatic cancer continues to increase, with little improvement in survival rates. We review the epidemiologic features of pancreatic cancer, covering surveillance and early detection in high-risk persons. We summarize data on worldwide incidence and mortality and analyze the 1975-2016 data from 9 registries of the National Cancer Institute's Surveillance, Epidemiology, and End Results study, on the overall burden of pancreatic cancer as well as age-, sex-, and race-specific incidence, survival rates and trends. It is important to increase our knowledge of the worldwide and regional epidemiologic features of and risk factors for pancreatic cancer, to identify new approaches for prevention, surveillance, and treatment.

Preoperative sarcopenia is associated with poor overall survival in pancreatic cancer patients following pancreaticoduodenectomy

OBJECTIVES

To analyze the effect of preoperative body composition on survival in patients with pancreatic cancer following pancreaticoduodenectomy (PD).

METHODS

Between October 2005 and August 2018, 116 patients (68 men, 48 women, mean age 66.2 ± 11.9 years) diagnosed with pancreatic adenocarcinoma following PD were retrospectively enrolled. The preoperative CT on vertebral level L3 was assessed for total abdominal muscle area (TAMA), visceral adipose tissue area (VAT), subcutaneous adipose tissue area (SAT), and mean skeletal muscle attenuation (SMD). The clinical data and pathological findings of tumors were collected. The impact of these factors on disease-free survival (DFS) and overall survival (OS) was evaluated by the Kaplan-Meier method and by univariable and multivariable Cox proportional hazards models.

RESULTS

The 3-year DFS and OS rates were 8% and 25%, respectively. Of 116 patients, 20 (17.2%), 3 (2.6%), and 46 (39.7%) patients were classified as having sarcopenia, sarcopenic obesity, and myosteatosis, respectively. The VAT-TAMA ratio (1.2 ± 0.7 vs 0.9 ± 0.5, p = 0.01) and the visceral to subcutaneous adipose tissue area ratio (1.3 ± 0.7 vs 0.9 ± 0.5, p = 0.04) were higher in sarcopenic patients than in the nonsarcopenic group. Preoperative sarcopenia and sarcopenic obesity were associated with shorter OS (p = 0.012 and p = 0.041, respectively), but not shorter DFS. Myosteatosis was neither associated with DFS nor OS. On multivariable analysis, sarcopenia was the only significant prognostic factor for OS (p = 0.039).

CONCLUSIONS

Preoperative sarcopenia assessed by CT is a poor prognostic factor for OS in pancreatic cancer patients after PD.

KEY POINTS

• Sarcopenia and sarcopenic obesity can be evaluated by abdominal CT on L3 level. • Patients with diabetes mellitus (DM) had lower sex-standardized subcutaneous adipose tissue area index and skeletal muscle density and higher visceral to subcutaneous adipose tissue area ratio than did those without DM. • Preoperative sarcopenia, sarcopenic obesity, and new-onset diabetes mellitus may predict poor overall survival in pancreatic cancer patients following pancreaticoduodenectomy.

Metabolomics Identifies Biomarker Signatures to Differentiate Pancreatic Cancer from Type 2 Diabetes Mellitus in Early Diagnosis

METHODS

Plasma metabolic profiles in 26 PC patients, 27 DM patients, and 23 healthy volunteers were examined using an ultraperformance liquid chromatography coupled with tandem mass spectrometry platform. Differential metabolite ions were then identified using the principal component analysis (PCA) model and the orthogonal partial least-squares discrimination analysis (OPLS-DA) model. The diagnosis performance of metabolite biomarkers was validated by logistic regression models.

RESULTS

We established a PCA model (R2X = 23.5%, Q2 = 8.21%) and an OPLS-DA model (R2X = 70.0%, R2Y = 84.9%, Q2 = 69.7%). LysoPC (16 : 0), catelaidic acid, cerebronic acid, nonadecanetriol, and asparaginyl-histidine were found to identify PC, with a sensitivity of 89% and a specificity of 91%. Besides, lysoPC (16 : 0), lysoPC (16 : 1), lysoPC (22 : 6), and lysoPC (20 : 3) were found to differentiate PC from DM, with higher accuracy (68% versus 55%) and higher AUC values (72% versus 63%) than those of CA19-9. The diagnostic performance of metabolite biomarkers was finally validated by logistic regression models.

CONCLUSION

We succeeded in screening differential metabolite ions among PC and DM patients and healthy individuals, thus providing a preliminary basis for screening the biomarkers for the early diagnosis of PC.

Immune Infiltration of CD8+ T Cells in Patients With Diabetic Pancreatic Cancer Reduces the Malignancy of Cancer Tissues: An In Silico Study

BACKGROUND

Although the functional damage of the diabetic pancreas can affect the postoperative recovery of pancreatic cancer patients, there is no significant difference in the prognosis of pancreatic cancer patients with a history of diabetes and ordinary pancreatic cancer patients. There is still no practical theory to explain this phenomenon.

MATERIALS AND METHOD

The mRNA expression profile data of 141 cases and 51 cases with clinical data of diabetes status were obtained from the TCGA database and the GEO database, respectively. The CRA001160 data set was obtained in the TISCH database. The Seurat was used to process single-cell expression profile sequencing data. The Cibersortx was used to construct a feature matrix of single-cell sequencing data and to deconvolve Bulk-RNAseq data to obtain each pancreatic cancer patients' tumour invasion score. TIDE was used to assess the immune escape potential of the tumour. MiRNet was used to construct the miRNA-mRNA regulatory network.

RESULT

Compared with regular pancreatic cancer patients, the immune-related signal transduction pathways in diabetic pancreatic cancer patients are in an activated state. In patients with diabetic pancreatic cancer, the infiltration score of CD8+ T cells is high, and the infiltration score of corresponding malignant tumour cells is low. The Bayesian classifier can distinguish diabetic pancreatic cancer patients from non-diabetic pancreatic cancer patients based on 10 signature genes. The miRNA-mRNA regulatory network suggests that regulation by miRNA can influence mRNA expression and thus prognostic survival of pancreatic cancer patients.

CONCLUSION

The activation of inflammatory-related signalling pathways in diabetic pancreatic cancer patients increases the immune infiltration of CD8+ T cells in cancer patients and reduces the development of malignant tumour tissues. The expression of 10 signature genes allowed the diagnosis of diabetic and non-diabetic pancreatic cancer patients. The miRNA-mRNA regulatory network may be the main cause of the differences in the tumour inflammatory microenvironment between the two groups of patients. These findings help us further understand the immune microenvironment of patients with diabetic pancreatic cancer.

Report of the National Cancer Institute and the Eunice Kennedy Shriver National Institute of Child Health and Human Development-sponsored workshop: gynecology and women's health-benign conditions and cancer

The Division of Cancer Prevention and the Division of Cancer Biology at the National Cancer Institute and the Gynecologic Health and Disease Branch in the National Institute of Child Health and Human Development organized a workshop in April 2019 to explore current insights into the progression of gynecologic cancers from benign conditions. Working groups were formed based on 3 gynecologic disease types: (1) Endometriosis or Endometrial Cancer and Endometrial-Associated Ovarian Cancer, (2) Uterine Fibroids (Leiomyoma) or Leiomyosarcoma, and (3) Adenomyosis or Adenocarcinoma. In this report, we highlight the key questions and current challenges that emerged from the working group discussions and present potential research opportunities that may advance our understanding of the progression of gynecologic benign conditions to cancer.

Validation of Indications for Surgery of European Evidence-Based Guidelines for Patients with Pancreatic Intraductal Papillary Mucinous Neoplasms

BACKGROUND

Which patients with pancreatic intraductal papillary mucinous neoplasms (IPMNs) should undergo surgical intervention remains a controversial issue. The aim of this retrospective study was to validate the new European evidence-based guidelines on pancreatic cystic neoplasms (EEBGPCN) for the management of IPMNs.

METHODS

One hundred fifty-eight patients with resected IPMNs at National Taiwan University Hospital between January 1994 and December 2016 were enrolled. Clinical information, including new-onset diabetes mellitus (DM) and preoperative CA 19-9 levels, were collected. All patients were stratified into three groups-absolute, relative indications, and conservative approach-according to EEBGPCN. The performance characteristics of EEBGPCN for high-grade dysplasia (HGD)/invasive carcinoma (IC) of IPMNs were calculated.

RESULTS

One hundred seven (67.7%) patients with low-grade dysplasia and 51 patients with HGD/IC, including 10 HGD and 41 IC, were analyzed. The missed rate for HGD/IC by EEBGPCN was 1.9% (3/158). The sensitivity, specificity, positive and negative predictive values, and accuracy of the absolute or relative indications for resecting IPMN according to EEBGPCN were 94.1%, 28.0%, 38.4%, 90.9%, and 49.4%. Jaundice, enhancing mural nodule < 5 mm, cyst diameter > 40 mm, increased levels of serum CA 19-9, new-onset DM, and main pancreatic duct dilation were associated with HGD/IC.

CONCLUSIONS

The missed rate for HGD/IC is low by EEBGPCN. Increased serum CA 19-9 and new-onset DM in EEBGPCN were verified as the indications for the surgical resection of IPMNs.

Early Diagnosis of Pancreatic Cancer: The Key for Survival

Pancreatic cancer (PC) is one of the most aggressive forms of cancer. Negative prognosis is mainly due to the late diagnosis in advanced stages, when the disease is already therapeutically overcome. Studies in recent years have focused on identifying biomarkers that could play a role in early diagnosis, leading to the improvement of morbidity and mortality. Currently, the only biomarker widely used in the diagnosis of PC is carbohydrate antigen 19-9 (CA19.9), which has, however, more of a prognostic role in the follow-up of postoperative recurrence than a diagnostic role. Other biomarkers, recently identified as the methylation status of ADAMTS1 (A disintegrin and metalloproteinase with thrombospondin motifs 1) and BNC1 (zinc finger protein basonuclin-1) in cell-free deoxyribonucleic acid (DNA), may play a role in the early detection of PC. This review focuses on the diagnosis of PC in its early stages.

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 stellate cells: Aiding and abetting pancreatic cancer progression

Tumour-stromal interactions have now been acknowledged to play a major role in pancreatic cancer (PC) progression. The abundant collagenous stroma is produced by a specific cell type in the pancreas-the pancreatic stellate cell (PSC). Pancreatic stellate cells (PSCs) are a unique resident cell type of pancreas and with a critical role in both healthy and diseased pancreas. Accumulating evidence indicates that PSCs interact closely with cancer cells as well as with other cell types of the stroma such as immune cells, endothelial cells and neuronal cells, to set up a growth permissive microenvironment for pancreatic tumours, which facilitates local tumour growth as well as distant metastasis. Consequently, recent work in the field has focused on the development of novel therapeutic approaches targeting the stroma to inhibit PC progression. Such a multi-pronged approach targeting both tumour and stromal elements of PC has been successfully applied in pre-clinical settings. The challenge now is to translate the pre-clinical findings into the clinical setting to achieve better outcomes for pancreatic cancer patients.

Islets and pancreatic ductal adenocarcinoma - An opportunity for translational research from the 'Bench to the Bedside'

The islet-acinar axis is of prime importance to the optimal functioning of the human pancreas. Not only is this inter-relationship important for normal physiological processes, it is also relevant in diseased states, including chronic pancreatitis and pancreatic ductal adenocarcinoma (PDAC). Early experiments, nearly 4 decades ago, explored the role of islets in the development and progression of PDAC. These led to further studies that provided compelling evidence to support the role of islets and their hormones in PDAC. This association presents oncologists with therapeutic options not only for managing, but potentially preventing PDAC, a cancer that is well known for its poor patient outcomes. This review will discuss the accumulated evidence regarding the role of islets and their hormones in PDAC and highlight areas for future research.

Unique circulating immune signatures for recurrent acute pancreatitis, chronic pancreatitis and pancreatic cancer: A pilot study of these conditions with and without diabetes

OBJECTIVE

This exploratory study seeks to identify distinct circulating immune signatures among patients having recurrent acute pancreatitis (RAP), chronic pancreatitis (CP), and pancreatic adenocarcinoma (PDAC).

METHODS

A retrospective analysis of human serum samples from collaborating institutions of the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer (CPDPC) was performed. Samples came from the North American Pancreatitis Studies 2 (NAPS2) cohort and the Pancreatic Adenocarcinoma Gene Environment Risk Study (PAGER) and were analyzed using a 62-plex Luminex assay in a blinded fashion. Group and pairwise comparisons were performed to identify unique immune signature panels and to calculate diagnostic utility using area under the curve analysis.

RESULTS

A total of 179 patients' samples were included: 41 controls, 40 CP, 78 PDAC and 20 RAP patients, of which 20 controls, 20 CP, and 58 PDAC patients had diabetes mellitus (DM). A unique immune signature panel could discriminate RAP, CP, and PDAC from controls with an AUC range from 0.77 to 0.86 (95% CI range: 0.64-0.94), RAP from CP, and CP from PDAC with an AUC of 0.77 (95% CI 0.64-0.90) and 0.76 (95% CI 0.67-0.86), respectively. Furthermore, an immune signature panel could also discriminate PDAC-DM from DM controls with an AUC of 0.96 (95% CI: 0.93-1.00) CONCLUSION: This study identifies unique immune analytes that may serve as novel diagnostic and predictive non-invasive biomarkers of RAP, CP, and PDAC. Further validation is warranted in prospective cohorts as developed by the CPDPC.

Temporal patterns of new-onset diabetes in pancreatic cancer

BACKGROUND

ancreatic carcinoma (PCa) is a malignant tumor occurring in the exocrine glands of the pancreas. It has a hidden onset, a high degree of malignancy, and a low 5-year survival rate of less than 1%. Early clinical symptoms are often atypical and there is a lack of specific means of examination. Most of the cases have progressed to the middle and late stages of the disease and the prognosis is poor. A large number of studies have shown that diabetes is closely related to PCa, but the causal relationship between them is not clear. This study aimed to retrospectively analyze patients with PCa in order to find early diagnostic clues for PCa.

AIM

To explore the relationship between PCa and new-onset diabetes.

METHODS

Four hundred and sixty-three PCa patients were included in a PCa group, and 658 patients without tumour, alimentary system or non-metabolic abnormality were included in a control group. The age and course of diabetes mellitus (DM) of patients in the PCa group and control group were analyzed and compared.

RESULTS

The average age of new-onset diabetes patients in the PCa group was 70.09 years (95%CI: 69.00-71.18), and the average age of patients with type 2 diabetes was 58.68 years (95%CI: 57.84-59.53); the difference was statistically significant (P < 0.01). Patients in the PCa group were divided into seven groups according to the course of diabetes. The prevalence of diabetes in the pancreatic cancer group with diabetes disease duration < 1 year, 1-2 years, and > 10 years was significantly higher than that of the control group (19.87% vs 1.52%, P < 0.01; 6.48% vs 1.67%, P < 0.05; 2.16% vs 0.91%, P < 0.05).

CONCLUSION

New-onset diabetes can act as a clue for early diagnosis of PCa. Clinicians should be alert to the possibility of PCa for elderly patients with a diagnosis of DM in 2 years or great blood glucose fluctuation in short time．

A Prospective Study to Establish a New-Onset Diabetes Cohort: From the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer

The National Cancer Institute and the National Institute for Diabetes and Digestive and Kidney Diseases initiated the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer (CPDPC) in 2015 (the CPDPC's origin, structure, governance, and research objectives are described in another article in this journal). One of the key objectives of CPDPC is to assemble a cohort of 10,000 subjects 50 years or older with new-onset diabetes, called the NOD cohort. Using a define, enrich, and find early detection approach, the aims of the NOD study are to (a) estimate the 3-year probability of pancreatic ductal adenocarcinoma (PDAC) in NOD (define), (b) establish a biobank of clinically annotated biospecimens from presymptomatic PDAC and control new-onset type 2 diabetes mellitus subjects, (c) conduct phase 3 validation studies of promising biomarkers for identification of incident PDAC in NOD patients (enrich), and (d) provide a platform for development of a future interventional screening protocol for early detection of PDAC in patients with NOD that incorporates imaging studies and/or clinical algorithms (find). It is expected that 85 to 100 incidences of PDAC will be diagnosed during the study period in this cohort of 10,000 patients.

Evaluating Susceptibility to Pancreatic Cancer: ASCO Provisional Clinical Opinion

Purpose

An ASCO provisional clinical opinion (PCO) offers timely clinical direction to ASCO’s membership and other health care providers. This PCO addresses identification and management of patients and family members with possible predisposition to pancreatic adenocarcinoma.

Methods

ASCO convened an Expert Panel and conducted a systematic review of the literature published from January 1998 to June 2018. Results of the databases searched were supplemented with hand searching of the bibliographies of systematic reviews and selected seminal articles and contributions from Expert Panel members’ curated files.

Provisional Clinical Opinion

All patients diagnosed with pancreatic adenocarcinoma should undergo assessment of risk for hereditary syndromes known to be associated with an increased risk for pancreatic adenocarcinoma. Assessment of risk should include a comprehensive review of family history of cancer. Individuals with a family history of pancreatic cancer affecting two first-degree relatives meet criteria for familial pancreatic cancer (FPC). Individuals (cancer affected or unaffected) with a family history of pancreatic cancer meeting criteria for FPC, those with three or more diagnoses of pancreatic cancer in same side of the family, and individuals meeting criteria for other genetic syndromes associated with increased risk for pancreatic cancer have an increased risk for pancreatic cancer and are candidates for genetic testing. Germline genetic testing for cancer susceptibility may be discussed with individuals diagnosed with pancreatic cancer, even if family history is unremarkable. Benefits and limitations of pancreatic cancer screening should be discussed with individuals whose family history meets criteria for FPC and/or genetic susceptibility to pancreatic cancer. Additional information is available at www.asco.org/gastrointestinal-cancer-guidelines .

Pancreatic Cancer Following Incident Diabetes in African Americans and Latinos: The Multiethnic Cohort

Background

Diabetes has been proposed to be a risk factor for and a consequence of pancreatic cancer (PC). The relationship between recent-onset diabetes and PC is not well understood, and data in minorities are sparse. We examined the relationships between recent-onset diabetes and PC incidence in African Americans and Latinos in the Multiethnic Cohort.

Methods

A total of 48 995 African Americans and Latinos without prior diabetes and cancer at baseline (1993-1996) were included in the study. Questionnaires, Medicare data, and California hospital discharge files were used to identify new diabetes diagnoses. Cox regressions were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for cancer associated with diabetes and with diabetes duration.

Results

A total of 15 833 (32.3%) participants developed diabetes between baseline and 2013. A total of 408 incident PC cases were identified during follow-up. Diabetes was associated with PC (HRage75 = 2.39, 95% CI = 1.91 to 2.98). Individuals with recent-onset diabetes (within three or fewer years of PC diagnosis) had a greater risk compared with those with long-term diabetes across all ages. The HRage75 for recent-onset diabetes was 4.08 (95% CI = 2.76 to 6.03) in Latinos and 3.38 (95% CI = 2.30 to 4.98) in African Americans.

Conclusions

Diabetes was associated with a more than twofold higher risk of PC in African Americans and Latinos, but recent-onset diabetes was associated with a 2.3-fold greater increase in risk of PC than long-standing diabetes. Our findings support the hypothesis that recent-onset diabetes is a manifestation of PC and that long-standing diabetes is a risk factor for this malignancy.

Type-3c Diabetes Mellitus, Diabetes of Exocrine Pancreas - An Update

BACKGROUND

The incidence of diabetes is increasing steeply; the number of diabetics has doubled over the past three decades. Surprisingly, the knowledge of type 3c diabetes mellitus (T3cDM) is still unclear to the researchers, scientist and medical practitioners, leading towards erroneous diagnosis, which is sometimes misdiagnosed as type 1 diabetes mellitus (T1DM), or more frequently type 2 diabetes mellitus (T2DM). This review is aimed to outline recent information on the etiology, pathophysiology, diagnostic procedures, and therapeutic management of T3cDM patients.

METHODS

The literature related to T3cDM was thoroughly searched from the public domains and reviewed extensively to construct this article. Further, existing literature related to the other forms of diabetes is reviewed for projecting the differences among the different forms of diabetes. Detailed and updated information related to epidemiological evidence, risk factors, symptoms, diagnosis, pathogenesis and management is structured in this review.

RESULTS

T3cDM is often misdiagnosed as T2DM due to the insufficient knowledge differentiating between T2DM and T3cDM. The pathogenesis of T3cDM is explained which is often linked to the history of chronic pancreatitis, pancreatic cancer. Inflammation, and fibrosis in pancreatic tissue lead to damage both endocrine and exocrine functions, thus leading to insulin/glucagon insufficiency and pancreatic enzyme deficiency.

CONCLUSION

Future advancements should be accompanied by the establishment of a quick diagnostic tool through the understanding of potential biomarkers of the disease and newer treatments for better control of the diseased condition.

Pancreatic Cancer and Diabetes Mellitus

PURPOSE OF REVIEW

The relationship between pancreatic ductal adenocarcinoma (PDAC) and diabetes mellitus (DM) is complex. We reviewed the recent medical literature regarding the effect of anti-diabetic medication on PDAC risk and survival, risk of PDAC in DM, and role of DM in early detection of PDAC.

RECENT FINDINGS

Studies report that while some anti-diabetic medications (e.g., metformin) may decrease the risk of PDAC, others (insulin, sulfonylureas and incretin-based therapies) may increase the risk. However, these observations may be subject to protopathic biases. Metformin's anti-tumor activity may have influence overall survival of PDAC, but epidemiological reports have largely been inconsistent to defend these findings due to heterogeneous methodologies. There is congruent data to support the association between DM and PDAC, with an inverse relationship to DM duration. Older subjects with new-onset DM are the only known high-risk group for PDAC, and strategy using this group for early detection has led to development of clinical risk prediction models that define a very high-risk PDAC group. Role of anti-diabetic medication in PDAC risk modification or survival is controversial. With successful efforts to distinguish type 2-DM from PDAC-DM using risk-stratifying models, there is an opportunity to initiate screening protocols for early detection of PDAC in a sub-set of DM subjects.

Model to Determine Risk of Pancreatic Cancer in Patients With New-Onset Diabetes

BACKGROUND & AIMS

Of patients with new-onset diabetes (NOD; based on glycemic status) older than 50 years, approximately 1% are diagnosed with pancreatic cancer (PC) within 3 years. We aimed to develop and validate a model to determine risk of PC in patients with NOD.

METHODS

We retrospectively collected data from 4 independent and nonoverlapping cohorts of patients (N = 1,561) with NOD (based on glycemic status; data collected at date of diagnosis and 12 months previously) in the Rochester Epidemiology Project from January 1, 2000 through December 31, 2015 to create our model. The model weighed scores for 3 factors identified in the discovery cohort to be most strongly associated with PC (64 patients with PC and 192 with type 2 diabetes): change in weight, change in blood glucose, and age at onset of diabetes. We called our model Enriching New-Onset Diabetes for Pancreatic Cancer (ENDPAC). We validated the locked-down model and cutoff score in an independent population-based cohort of 1,096 patients with diabetes; of these, 9 patients (82%) had PC within 3 years of meeting the criteria for NOD.

RESULTS

In the discovery cohort, the END-PAC model identified patients who developed PC within 3 years of diabetes onset (area under receiver operating characteristic curve 0.87); a score of at least 3 identified patients who developed PC with 80% sensitivity and specificity. In the validation cohort, a score of at least 3 identified 7 of 9 patients with PC (78%) with 85% specificity; the prevalence of PC in patients with a score of at least 3 (3.6%) was 4.4-fold greater than in patients with NOD. A high END-PAC score in patients who did not have PC (false positives) was often due to such factors as recent steroid use or different malignancy. An ENDPAC score no higher than 0 (in 49% of patients) meant that patients had an extremely low risk for PC. An END-PAC score of at least 3 identified 75% of patients in the discovery cohort more than 6 months before a diagnosis of PC.

CONCLUSIONS

Based on change in weight, change in blood glucose, and age at onset of diabetes, we developed and validated a model to determine risk of PC in patients with NOD based on glycemic status (END-PAC model). An independent prospective study is needed to further validate this model, which could contribute to early detection of PC.

Serum Biomarker Signature-Based Liquid Biopsy for Diagnosis of Early-Stage Pancreatic Cancer

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with a 5-year survival of < 10% because of diffuse symptoms leading to late-stage diagnosis. That survival could increase significantly if localized tumors could be detected early. Therefore, we used multiparametric analysis of blood samples to obtain a novel biomarker signature of early-stage PDAC. The signature was derived from a large patient cohort, including patients with well-defined early-stage (I and II) PDAC. This biomarker signature was validated subsequently in an independent patient cohort.

PATIENTS AND METHODS

The biomarker signature was derived from a case-control study, using a Scandinavian cohort, consisting of 16 patients with stage I, 132 patients with stage II, 65 patients with stage III, and 230 patients with stage IV PDAC, and 888 controls. This signature was validated subsequently in an independent case-control cohort in the United States with 15 patients with stage I, 75 patients with stage II, 15 patients with stage III, and 38 patients with stage IV PDAC, and 219 controls. An antibody microarray platform was used to identify the serum biomarker signature associated with early-stage PDAC.

RESULTS

Using the Scandinavian case-control study, a biomarker signature was created, discriminating samples derived from patients with stage I and II from those from controls with a receiver operating characteristic area under the curve value of 0.96. This signature, consisting of 29 biomarkers, was then validated in an independent case-control study in the United States. The biomarker signature could discriminate patients with stage I and II PDAC from controls in this independent patient cohort with a receiver operating characteristic area under the curve value of 0.96.

CONCLUSION

This serum biomarker signature might represent a tenable approach to detecting early-stage, localized PDAC if these findings are supported by a prospective validation study.

Adverse Oncologic Impact of New-Onset Diabetes Mellitus on Recurrence in Resected Pancreatic Ductal Adenocarcinoma: A Comparison With Long-standing and Non-Diabetes Mellitus Patients

OBJECTIVES

Diabetes mellitus (DM) is prevalent with pancreatic ductal adenocarcinoma (PDAC). Importantly, new-onset DM is characteristic of the disease and could be an early sign of PDAC. The clinical outcome of PDAC with new-onset DM may differ from that in patients without DM or long-standing DM.

METHODS

We retrospectively reviewed medical records of PDAC patients who underwent curative resection between 2006 and 2014. New-onset DM was defined as a diagnosis of DM within 24 months before the diagnosis of PDAC. Survival analysis and Cox regression were performed to evaluate oncologic outcomes.

RESULTS

No significant differences in clinical characteristics were found in 3 groups. Overall survival of patients with new-onset DM was worse than non-DM (22 vs 33 months, P = 0.039). New-onset DM was highly associated with early recurrence (hazard ratio, 1.451; 95% confidence interval, 1.054-1.999; P = 0.022). Poor oncologic outcome of new-onset DM was more pronounced in low T stage patients (overall survival in low vs high T stage, 33 vs 18 months; P = 0.129).

CONCLUSIONS

Pancreatic ductal adenocarcinoma with new-onset DM has worse oncologic outcomes than non-DM or long-standing DM. These results suggest that new-onset DM represents aggressive tumor biology, especially in the early stage of PDAC.

Detection of early pancreatic ductal adenocarcinoma with thrombospondin-2 and CA19-9 blood markers

Markers are needed to facilitate early detection of pancreatic ductal adenocarcinoma (PDAC), which is often diagnosed too late for effective therapy. Starting with a PDAC cell reprogramming model that recapitulated the progression of human PDAC, we identified secreted proteins and tested a subset as potential markers of PDAC. We optimized an enzyme-linked immunosorbent assay (ELISA) using plasma samples from patients with various stages of PDAC, from individuals with benign pancreatic disease, and from healthy controls. A phase 1 discovery study (n = 20), a phase 2a validation study (n = 189), and a second phase 2b validation study (n = 537) revealed that concentrations of plasma thrombospondin-2 (THBS2) discriminated among all stages of PDAC consistently. The receiver operating characteristic (ROC) c-statistic was 0.76 in the phase 1 study, 0.84 in the phase 2a study, and 0.87 in the phase 2b study. The plasma concentration of THBS2 was able to discriminate resectable stage I cancer as readily as stage III/IV PDAC tumors. THBS2 plasma concentrations combined with those for CA19-9, a previously identified PDAC marker, yielded a c-statistic of 0.96 in the phase 2a study and 0.97 in the phase 2b study. THBS2 data improved the ability of CA19-9 to distinguish PDAC from pancreatitis. With a specificity of 98%, the combination of THBS2 and CA19-9 yielded a sensitivity of 87% for PDAC in the phase 2b study. A THBS2 and CA19-9 blood marker panel measured with a conventional ELISA may improve the detection of patients at high risk for PDAC.

The Association of Recently Diagnosed Diabetes and Long-term Diabetes With Survival in Pancreatic Cancer Patients: A Pooled Analysis

OBJECTIVES

It is unclear whether long-standing diabetes or new-onset pancreatogenic diabetes contributes to poor prognosis in patients with pancreatic ductal adenocarcinoma (PDAC).

METHODS

We investigated the influence of diabetes diagnosed shortly before PDAC and long-term diabetes on overall survival in 2792 PDAC patients who had participated in 3 PDAC case-control studies in the Pancreatic Cancer Case-Control Consortium. There were 300 patients with long-term diabetes of more than 3 years' duration (11%) and 418 patients with recently diagnosed diabetes of 3-year duration or less (15%). We performed Cox regression to determine the association of long-term diabetes and recently diagnosed diabetes with overall survival, adjusting for study site, age, sex, race, stage of disease, surgery, chemotherapy, smoking history, and body mass index at diagnosis.

RESULTS

In the overall population, neither long-term diabetes (hazard ratio [HR], 1.10; 95% confidence interval [CI], 0.97-1.26) nor recently diagnosed diabetes (HR, 1.06; 95% CI, 0.94-1.18) was associated with shorter survival. When stratified by stage of disease, long-term diabetes was associated with 42% increase in rate of death in persons with resectable PDAC (HR, 1.42; 95% CI, 1.13-1.78), whereas it was not associated with survival in PDAC patients with more advanced disease.

CONCLUSION

Long-term diabetes was associated with increased rate of death in patients with resectable PDAC.

Metabolic biomarker signature to differentiate pancreatic ductal adenocarcinoma from chronic pancreatitis

OBJECTIVE

Current non-invasive diagnostic tests can distinguish between pancreatic cancer (pancreatic ductal adenocarcinoma (PDAC)) and chronic pancreatitis (CP) in only about two thirds of patients. We have searched for blood-derived metabolite biomarkers for this diagnostic purpose.

DESIGN

For a case-control study in three tertiary referral centres, 914 subjects were prospectively recruited with PDAC (n=271), CP (n=282), liver cirrhosis (n=100) or healthy as well as non-pancreatic disease controls (n=261) in three consecutive studies. Metabolomic profiles of plasma and serum samples were generated from 477 metabolites identified by gas chromatography-mass spectrometry and liquid chromatography-tandem mass spectrometry.

RESULTS

A biomarker signature (nine metabolites and additionally CA19-9) was identified for the differential diagnosis between PDAC and CP. The biomarker signature distinguished PDAC from CP in the training set with an area under the curve (AUC) of 0.96 (95% CI 0.93-0.98). The biomarker signature cut-off of 0.384 at 85% fixed specificity showed a sensitivity of 94.9% (95% CI 87.0%-97.0%). In the test set, an AUC of 0.94 (95% CI 0.91-0.97) and, using the same cut-off, a sensitivity of 89.9% (95% CI 81.0%-95.5%) and a specificity of 91.3% (95% CI 82.8%-96.4%) were achieved, successfully validating the biomarker signature.

CONCLUSIONS

In patients with CP with an increased risk for pancreatic cancer (cumulative incidence 1.95%), the performance of this biomarker signature results in a negative predictive value of 99.9% (95% CI 99.7%-99.9%) (training set) and 99.8% (95% CI 99.6%-99.9%) (test set). In one third of our patients, the clinical use of this biomarker signature would have improved diagnosis and treatment stratification in comparison to CA19-9.

Early Detection of Pancreatic Cancer: The Role of Industry in the Development of Biomarkers

A diagnosis of pancreatic cancer is devastating owing to its poor prognosis, with a 5-year survival rate of only 9%. Currently, most individuals are diagnosed at a late stage when treatment options are limited. Early detection of pancreatic cancer provides the greatest hope for making substantial improvements in survival. The Kenner Family Research Fund in partnership with the American Pancreatic Association has sponsored a series of fora to stimulate discussion and collaboration on early detection of pancreatic cancer. At the first forum in 2014, "Early Detection of Sporadic Pancreatic Cancer Summit Conference," a strategic plan was set forth by an international group of interdisciplinary scientific representatives and subsequently The Strategic Map for Innovation was generated. The current conference report is the third forum in the series, "Early Detection of Pancreatic Cancer: The Role of Industry in the Development of Biomarkers," which was held in Boston, Massachusetts, on October 27, 2016. This report provides an overview of examples of innovative initiatives by industry and confirms the critical need for collaboration among industry, government, research institutions, and advocacy groups in order to make pancreatic cancer more easily detectable in its earlier stages, when it is more treatable.

Pregnancy with concomitant pancreatic cancer

We report a rare case of pregnancy with concomitant pancreatic cancer. At 28 weeks' gestation, the patient was diagnosed with a large tumoral mass in the head of the pancreas. She had a cesarean section at 32 weeks' gestation due to premature labor and underwent surgery for pancreatic cancer in her third month postpartum.

A Clinical Prediction Model to Assess Risk for Pancreatic Cancer Among Patients With New-Onset Diabetes

BACKGROUND & AIMS

Approximately 50% of all patients with pancreatic ductal adenocarcinoma (PDA) develop diabetes mellitus before their cancer diagnosis. Screening individuals with new-onset diabetes might allow earlier diagnosis of PDA. We sought to develop and validate a PDA risk prediction model to identify high-risk individuals among those with new-onset diabetes.

METHODS

We conducted a retrospective cohort study in a population representative database from the United Kingdom. Individuals with incident diabetes after the age of 35 years and 3 or more years of follow-up after diagnosis of diabetes were eligible for inclusion. Candidate predictors consisted of epidemiologic and clinical characteristics available at the time of diabetes diagnosis. Variables with P values <.25 in the univariable analyses were evaluated using backward stepwise approach. Model discrimination was assessed using receiver operating characteristic curve analysis. Calibration was evaluated using the Hosmer-Lemeshow test. Results were internally validated using a bootstrapping procedure.

RESULTS

We analyzed data from 109,385 patients with new-onset diabetes. Among them, 390 (0.4%) were diagnosed with PDA within 3 years. The final model (area under the curve, 0.82; 95% confidence interval, 0.75-0.89) included age, body mass index, change in body mass index, smoking, use of proton pump inhibitors, and anti-diabetic medications, as well as levels of hemoglobin A1C, cholesterol, hemoglobin, creatinine, and alkaline phosphatase. Bootstrapping validation showed negligible optimism. If the predicted risk threshold for definitive PDA screening was set at 1% over 3 years, only 6.19% of the new-onset diabetes population would undergo definitive screening, which would identify patients with PDA with 44.7% sensitivity, 94.0% specificity, and a positive predictive value of 2.6%.

CONCLUSIONS

We developed a risk model based on widely available clinical parameters to help identify patients with new-onset diabetes who might benefit from PDA screening.

Genetically Determined Chronic Pancreatitis but not Alcoholic Pancreatitis Is a Strong Risk Factor for Pancreatic Cancer

OBJECTIVE

To study if chronic pancreatitis (CP) is a risk factor for pancreatic cancer.

METHODS

Through a cohort and a case-control study design, CP and other important risk factors including smoking, diabetes, alcohol, obesity, and genetic mutations were studied for their association with pancreatic cancer.

RESULTS

In the cohort study, 402 patients with CP were included. During 3967.74 person-years of exposure, 5 of the 402 patients (4 idiopathic CP, 1 hereditary CP) developed pancreatic cancer after 16.60 ± 3.51 years of CP. The standardized incidence ratio was 121. In the case-control study, 249 pancreatic cancer patients and 1000 healthy controls were included. Of the 249 patients with pancreatic cancer, 24 had underlying idiopathic CP, and none had alcoholic pancreatitis. SPINK1 gene mutation was present in 16 of 26 patients with idiopathic CP who had pancreatic cancer. Multivariable analysis showed CP (odds ratio [OR], 97.67; 95% confidence interval [CI], 12.69-751.36), diabetes (>4 years duration) (OR, 3.05; 95% CI, 1.79-5.18), smoking (OR, 1.93; 95% CI, 1.38-2.69) as significant risk factors for pancreatic cancer. The population attributable risk was 9.41, 9.06, and 9.50 for diabetes, CP, and smoking, respectively.

CONCLUSIONS

Genetically determined CP but not alcoholic CP is a strong risk factor for pancreatic cancer.

Type 3c (pancreatogenic) diabetes mellitus secondary to chronic pancreatitis and pancreatic cancer

Diabetes mellitus is a group of diseases defined by persistent hyperglycaemia. Type 2 diabetes, the most prevalent form, is characterised initially by impaired insulin sensitivity and subsequently by an inadequate compensatory insulin response. Diabetes can also develop as a direct consequence of other diseases, including diseases of the exocrine pancreas. Historically, diabetes due to diseases of the exocrine pancreas was described as pancreatogenic or pancreatogenous diabetes mellitus, but recent literature refers to it as type 3c diabetes. It is important to note that type 3c diabetes is not a single entity; it occurs because of a variety of exocrine pancreatic diseases with varying mechanisms of hyperglycaemia. The most commonly identified causes of type 3c diabetes are chronic pancreatitis, pancreatic ductal adenocarcinoma, haemochromatosis, cystic fibrosis, and previous pancreatic surgery. In this Review, we discuss the epidemiology, pathogenesis, and clinical relevance of type 3c diabetes secondary to chronic pancreatitis and pancreatic ductal adenocarcinoma, and highlight several important knowledge gaps.

A Metabolic Inhibitory Cocktail for Grave Cancers: Metformin, Pioglitazone and Lithium Combination in Treatment of Pancreatic Cancer and Glioblastoma Multiforme

Pancreatic cancer (PC) and glioblastoma multiforme (GBM) are among the human cancers with worst prognosis which require an urgent need for efficient therapies. Here, we propose to apply to treat both malignancies with a triple combination of drugs, which are already in use for different indications. Recent studies demonstrated a considerable link between risk of PC and diabetes. In experimental models, anti-diabetogenic agents suppress growth of PC, including metformin (M), pioglitazone (P) and lithium (L). L is used in psychiatric practice, yet also bears anti-diabetic potential and selectively inhibits glycogen synthase kinase-3 beta (GSK-3β). M, a biguanide class anti-diabetic agent shows anticancer activity via activating AMP-activated protein kinase (AMPK). Glitazones bind to PPAR-γ and inhibit NF-κB, triggering cell proliferation, apoptosis resistance and synthesis of inflammatory cytokines in cancer cells. Inhibition of inflammatory cytokines could simultaneously decrease tumor growth and alleviate cancer cachexia, having a major role in PC mortality. Furthermore, mutual synergistic interactions exist between PPAR-γ and GSK-3β, between AMPK and GSK-3β and between AMPK and PPAR-γ. In GBM, M blocks angiogenesis and migration in experimental models. Very noteworthy, among GBM patients with type 2 diabetes, usage of M significantly correlates with better survival while reverse is true for sulfonylureas. In experimental models, P synergies with ligands of RAR, RXR and statins in reducing growth of GBM. Further, usage of P was found to be lesser in anaplastic astrocytoma and GBM patients, indicating a protective effect of P against high-grade gliomas. L is accumulated in GBM cells faster and higher than in neuroblastoma cells, and its levels further increase with chronic exposure. Recent studies revealed anti-invasive potential of L in GBM cell lines. Here, we propose that a triple-agent regime including drugs already in clinical usage may provide a metabolic adjuvant therapy for PC and GBM.

Serum microRNA-196 and microRNA-200 in pancreatic ductal adenocarcinoma of patients with diabetes mellitus

BACKGROUND/OBJECTIVES

Our aim was to compare expressions of 6 microRNAs (miRNAs) in patients with pancreatic ductal adenocarcinoma (PAC) and non-cancer patients, moreover according to the presence or absence of diabetes mellitus.

METHODS

Expressions of miRNA-192, -196, -200, -21, -30 and -423 were measured in 77 patients with PAC and 64 non-cancer patients (34 patients with type 2 DM and 30 control persons). 60 patients with PAC (78%) had DM or prediabetes and it was of new-onset (less than 2 years before the cancer diagnosis) in 44 out of them.

RESULTS

The expressions of all microRNAs were 1.4-3.7 times higher (significantly) in the PAC group compared to non-cancer patients. No difference was found between PAC diabetic and PAC non-diabetic patients. MicroRNA-200 was significantly higher in PAC patients with significant body weight loss against those without weight loss. Adding miRNA-196 and -200 to the current marker CA 19-9 improved the discriminative ability of the test (compared to CA 19-9 alone).

CONCLUSION

MicroRNA-196 and -200 could be used as additional markers in PAC diagnosis.