Heterogeneity in Pancreatitis: Recognizing Heterogeneity and Its Role in the Management of Pancreatitis. Summary of a National Institute of Diabetes and Digestive and Kidney Diseases Workshop.

Both the clinical management and study of recurrent acute pancreatitis (RAP) and chronic pancreatitis (CP) is complicated by significant heterogeneity in the etiology, mechanisms, symptoms, and complications of pancreatitis. The National Institutes of Diabetes and Digestive and Kidney Disease (NIDDK) recently convened a workshop to address current knowledge and knowledge gaps in the field. Preclinical models that better replicate human disease are important for development of new therapies.

A screen-and-treat strategy for eradication of Helicobacter pylori among patients with family history of gastric cancer in a diverse U.S. population.

Background: Screening and eradication of Helicobacter pylori (H. pylori) reduce the risk of gastric cancer in patients with family history. We assessed patient perspectives on H.

Prediction of pancreatic cancer in patients with new onset hyperglycemia: A modified ENDPAC model.

Background/objectives: The Enriching New-Onset Diabetes for Pancreatic Cancer (ENDPAC) model relies primarily on fasting glucose values. Health systems have increasingly shifted practice towards use of glycated hemoglobin (HbA1c) measurement. We modified the ENDPAC model using patients with new onset hyperglycemia.

Stomach Cancer Prediction Model (SCoPM): An approach to risk stratification in a diverse U.S. population.

Background And Aims: Population-based screening for gastric cancer (GC) in low prevalence nations is not recommended. The objective of this study was to develop a risk-prediction model to identify high-risk patients who could potentially benefit from targeted screening in a racial/ethnically diverse regional US population.

Methods: We performed a retrospective cohort study from Kaiser Permanente Southern California from January 2008-June 2018 among individuals age ≥50 years.

Early Hypophosphatemia as a Prognostic Marker in Acute Pancreatitis.

Objectives: Acute pancreatitis (AP) is a complex disease representing a significant portion of gastrointestinal-related hospitalizations in the U.S. Understanding risk factors of AP might provide attractive therapeutic targets.

Early features of pancreatic cancer on magnetic resonance imaging (MRI): a case-control study.

Purpose: Magnetic resonance imaging has been recommended as a primary imaging modality among high-risk individuals undergoing screening for pancreatic cancer. We aimed to delineate potential precursor lesions for pancreatic cancer on MR imaging.

Methods: We conducted a case-control study at Kaiser Permanente Southern California (2008-2018) among patients that developed pancreatic cancer who had pre-diagnostic MRI examinations obtained 2-36 months prior to cancer diagnosis (cases) matched 1:2 by age, gender, race/ethnicity, contrast status and year of scan (controls).

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.

Lactated Ringers Use in the First 24 Hours of Hospitalization Is Associated With Improved Outcomes in 999 Patients With Acute Pancreatitis.

Introduction: Recent pilot trials in acute pancreatitis (AP) found that lactated ringers (LR) usage may result in decreased risk of moderately severe/severe AP compared with normal saline, but their small sample sizes limit statistical power. We investigated whether LR usage is associated with improved outcomes in AP in an international multicenter prospective study.

Methods: Patients directly admitted with the diagnosis of AP were prospectively enrolled at 22 international sites between 2015 and 2018.

Machine learning versus regression for prediction of sporadic pancreatic cancer.

Background/objectives: There is currently no widely accepted approach to identify patients at increased risk for sporadic pancreatic cancer (PC). We aimed to compare the performance of two machine-learning models with a regression-based model in predicting pancreatic ductal adenocarcinoma (PDAC), the most common form of PC.

Methods: This retrospective cohort study consisted of patients 50-84 years of age enrolled in either Kaiser Permanente Southern California (KPSC, model training, internal validation) or the Veterans Affairs (VA, external testing) between 2008 and 2017.

Risk Prediction of Pancreatic Cancer in Patients With Abnormal Morphologic Findings Related to Chronic Pancreatitis: A Machine Learning Approach.

Background And Aims: A significant factor contributing to poor survival in pancreatic cancer is the often late stage at diagnosis. We sought to develop and validate a risk prediction model to facilitate the distinction between chronic pancreatitis-related vs potential early pancreatic ductal adenocarcinoma (PDAC)-associated changes on pancreatic imaging.

Methods: In this retrospective cohort study, patients aged 18-84 years whose abdominal computed tomography/magnetic resonance imaging reports indicated duct dilatation, atrophy, calcification, cyst, or pseudocyst between January 2008 and November 2019 were identified.

Quantitative Radiomic Features From Computed Tomography Can Predict Pancreatic Cancer up to 36 Months Before Diagnosis.

Introduction: Pancreatic cancer is the third leading cause of cancer deaths among men and women in the United States. We aimed to detect early changes on computed tomography (CT) images associated with pancreatic ductal adenocarcinoma (PDAC) based on quantitative imaging features (QIFs) for patients with and without chronic pancreatitis (CP).

Methods: Adults 18 years and older diagnosed with PDAC in 2008-2018 were identified.

Derivation and External Validation of Machine Learning-Based Model for Detection of Pancreatic Cancer.

Introduction: There is currently no widely accepted approach to screening for pancreatic cancer (PC). We aimed to develop and validate a risk prediction model for pancreatic ductal adenocarcinoma (PDAC), the most common form of PC, across 2 health systems using electronic health records.

Methods: This retrospective cohort study consisted of patients aged 50-84 years having at least 1 clinic-based visit over a 10-year study period at Kaiser Permanente Southern California (model training, internal validation) and the Veterans Affairs (VA, external testing).

Gastric Cancer Screening in First-Degree Relatives: A Pilot Study in a Diverse Integrated Healthcare System.

Introduction: Family history of gastric cancer has been shown as an independent risk factor of gastric cancer development and is associated with increased risk of progression to gastric cancer among patients with gastric intestinal metaplasia (GIM).

Methods: Between 2017 and 2020, we conducted a prospective pilot screening program of patients with a confirmed first-degree relative with gastric cancer to evaluate the feasibility of screening and prevalence of precursor lesions (e.g.

Satisfaction With Telehealth Among Patients With Irritable Bowel Syndrome During COVID-19: Cross-Sectional Survey Findings.

Introduction: Coronavirus disease 2019 rapidly shifted health care toward telehealth. We assessed satisfaction with and preferences for telehealth among patients with irritable bowel syndrome (IBS).

Methods: We conducted a cross-sectional survey in an integrated healthcare system in Southern California with members aged 18-90 years with an International Classification of Diseases 9 and 10 codes for IBS from office-based encounters between June 1, 2018, and June 1, 2020.

Clinical and Imaging Predictors of Pancreatic Cancer in Patients Hospitalized for Acute Pancreatitis.

Background And Aims: Identifying factors associated with increased short-term risk of pancreatic cancer in the setting of acute pancreatitis (AP) can inform clinical care decisions and expedite cancer diagnosis.

Methods: A retrospective cohort study of patients hospitalized for AP between 2007 and 2017 in an integrated health-care system in Southern California. AP cases were identified by diagnosis code with laboratory confirmation.

Risk Prediction of Pancreatic Cancer in Patients With Recent-onset Hyperglycemia: A Machine-learning Approach.

Background: New-onset diabetes (NOD) has been suggested as an early indicator of pancreatic cancer. However, the definition of NOD by the American Diabetes Association requires 2 simultaneous or consecutive elevated glycemic measures. We aimed to apply a machine-learning approach using electronic health records to predict the risk in patients with recent-onset hyperglycemia.

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.

Predicting pancreatic ductal adenocarcinoma using artificial intelligence analysis of pre-diagnostic computed tomography images.

Background: Early stage diagnosis of Pancreatic Ductal Adenocarcinoma (PDAC) is challenging due to the lack of specific diagnostic biomarkers. However, stratifying individuals at high risk of PDAC, followed by monitoring their health conditions on regular basis, has the potential to allow diagnosis at early stages.

Objective: To stratify high risk individuals for PDAC by identifying predictive features in pre-diagnostic abdominal Computed Tomography (CT) scans.

Early Detection Initiative: A randomized controlled trial of algorithm-based screening in patients with new onset hyperglycemia and diabetes for early detection of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is the only leading cause of cancer death without an early detection strategy. In retrospective studies, 0.5-1% of subjects >50 years of age who newly develop biochemically-defined diabetes have been diagnosed with PDAC within 3 years of meeting new onset hyperglycemia and diabetes (NOD) criteria.

The relationship between pre-existing diabetes mellitus and the severity of acute pancreatitis: Report from a large international registry.

Background/objectives: The relationship between pre-existing diabetes mellitus (DM) and acute pancreatitis (AP) severity has not been established. We assessed the impact of pre-existing DM on AP severity in an international, prospectively ascertained registry.

Methods: APPRENTICE registry prospectively enrolled 1543 AP patients from 22 centers across 4 continents (8 US, 6 Europe, 5 Latin America, 3 India) between 2015 and 2018, and collected detailed clinical information.