Bidirectional relationship between acute pancreatitis and pancreatic cancer.

PURPOSE OF REVIEW: The burdens of pancreatic ductal adenocarcinoma (PDAC) and acute pancreatitis are increasing globally. We reviewed current literature on whether acute pancreatitis is a causal factor for PDAC and examined clinical manifestations of PDAC-associated acute pancreatitis. RECENT FINDINGS: Recent findings detail the timing of acute pancreatitis before and after PDAC occurrence, further solidifying the evidence for PDAC-associated acute pancreatitis and for acute pancreatitis as a causal risk factor for PDAC. The risk of PDAC remains elevated above the general population in patients with distant history of acute pancreatitis. PDAC risk also increases with recurrent acute pancreatitis episodes, independent of smoking and alcohol. Mechanisms linking acute pancreatitis to PDAC include inflammation and neutrophil infiltration, which can be attenuated by suppressing inflammation and/or epigenetic modulation, thus slowing the progression of acinar-to-ductal metaplasia. Clinical presentation and management of acute pancreatitis in the context of PDAC are discussed, including challenges acute pancreatitis poses in the diagnosis and treatment of PDAC, and novel interventions for PDAC-associated acute pancreatitis. SUMMARY: PDAC risk may be reduced with improved acute pancreatitis prevention and treatment, such as antiinflammatories or epigenetic modulators. Increased acute pancreatitis and PDAC burden warrant more research on better diagnosis and management of PDAC-associated acute pancreatitis.

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. Patients with prior GC or follow-up <30 days were excluded. Censoring occurred at GC, death, age 85 years, disenrollment, end of 5-year follow-up, or study conclusion. Cross-validated LASSO regression models were developed to identify the strongest of 20 candidate predictors (clinical, demographic, and laboratory parameters). Records from 12 of the medical service areas were used for training/initial validation while records from a separate medical service area were used for testing. RESULTS: 1,844,643 individuals formed the study cohort (1,555,392 training and validation, 289,251 testing). Mean age was 61.9 years with 53.3% female. GC incidence was 2.1 (95% CI 2.0-2.2) cases per 10,000 person-years (pyr). Higher incidence was seen with family history: 4.8/10,000 pyr, history of gastric ulcer: 5.3/10,000 pyr, H. pylori: 3.6/10,000 pyr and anemia: 5.3/10,000 pyr. The final model included age, gender, race/ethnicity, smoking, proton-pump inhibitor, family history of gastric cancer, history of gastric ulcer, H. pylori infection, and baseline hemoglobin. The means and standard deviations (SD) of c-index in validation and testing datasets were 0.75 (SD 0.03) and 0.76 (SD 0.02), respectively. CONCLUSIONS: This prediction model may serve as an aid for pre-endoscopic assessment of GC risk for identification of a high-risk population that could benefit from targeted screening.

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. The performance of random survival forests (RSF) and eXtreme gradient boosting (XGB) models were compared to that of COX proportional hazards regression (COX). Heterogeneity of the three models were assessed. RESULTS: The KPSC and the VA cohorts consisted of 1.8 and 2.7 million patients with 1792 and 4582 incident PDAC cases within 18 months, respectively. Predictors selected into all three models included age, abdominal pain, weight change, and glycated hemoglobin (A1c). Additionally, RSF selected change in alanine transaminase (ALT), whereas the XGB and COX selected the rate of change in ALT. The COX model appeared to have lower AUC (KPSC: 0.737, 95% CI 0.710-0.764; VA: 0.706, 0.699-0.714), compared to those of RSF (KPSC: 0.767, 0.744-0.791; VA: 0.731, 0.724-0.739) and XGB (KPSC: 0.779, 0.755-0.802; VA: 0.742, 0.735-0.750). Among patients with top 5% predicted risk from all three models (N = 29,663), 117 developed PDAC, of which RSF, XGB and COX captured 84 (9 unique), 87 (4 unique), 87 (19 unique) cases, respectively. CONCLUSIONS: The three models complement each other, but each has unique contributions.

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.

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). Random survival forests models were built to identify the most relevant predictors from >500 variables and to predict risk of PDAC within 18 months of cohort entry. RESULTS: The Kaiser Permanente Southern California cohort consisted of 1.8 million patients (mean age 61.6) with 1,792 PDAC cases. The 18-month incidence rate of PDAC was 0.77 (95% confidence interval 0.73-0.80)/1,000 person-years. The final main model contained age, abdominal pain, weight change, HbA1c, and alanine transaminase change (c-index: mean = 0.77, SD = 0.02; calibration test: P value 0.4, SD 0.3). The final early detection model comprised the same features as those selected by the main model except for abdominal pain (c-index: 0.77 and SD 0.4; calibration test: P value 0.3 and SD 0.3). The VA testing cohort consisted of 2.7 million patients (mean age 66.1) with an 18-month incidence rate of 1.27 (1.23-1.30)/1,000 person-years. The recalibrated main and early detection models based on VA testing data sets achieved a mean c-index of 0.71 (SD 0.002) and 0.68 (SD 0.003), respectively. DISCUSSION: Using widely available parameters in electronic health records, we developed and externally validated parsimonious machine learning-based models for detection of PC. These models may be suitable for real-time clinical application.

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.

Patient Adherence to Lung CT Screening Reporting & Data System-Recommended Screening Intervals in the United States: A Systematic Review and Meta-Analysis.

Lung cancer screening (LCS) is effective in reducing mortality, particularly when patients adhere to follow-up recommendations standardized by the Lung CT Screening Reporting & Data System (Lung-RADS). Nevertheless, patient adherence to recommended intervals varies, potentially diminishing benefit from screening. We conducted a systematic review and meta-analysis of patient adherence to Lung-RADS-recommended screening intervals. We systematically searched MEDLINE, EMBASE, Web of Science, the Cochrane Central Register of Controlled Trials, and major radiology and oncology conference archives between April 28, 2014, and December 17, 2020. Eligible studies mentioned patient adherence to the recommendations of Lung-RADS. The review protocol was registered with PROSPERO (CRD42020189326). We identified 24 eligible studies for qualitative summary, of which 21 were suitable for meta-analysis. The pooled adherence rate was 57% (95% confidence interval: 46%-69%) for defined adherence (e.g., an annual incidence screen was performed within 15 mo) among 6689 patients and 65% (95% confidence interval: 55%-75%) for anytime adherence among 5085 patients. Large heterogeneity in adherence rates between studies was observed (I2 = 99% for defined adherence, I2 = 98% for anytime adherence). Heterogeneous adherence rates were associated with Lung-RADS scores, with significantly higher adherence rates among Lung-RADS 3 to 4 than Lung-RADS 1 to 2 (p < 0.05). Patient adherence to Lung-RADS-recommended screening intervals is suboptimal across clinical LCS programs in the United States, especially among patients with results of Lung-RADS categories 1 to 2. To improve adherence rates, future research may focus on implementing tailored interventions after identifying barriers to LCS. We also propose a minimum standardized set of data elements for future pooled analyses of LCS adherence on the basis of our findings.

A Case-CrossovEr study deSign to inform tailored interventions to prevent disease progression in Acute Pancreatitis (ACCESS-AP) - study design and population.

BACKGROUND/OBJECTIVES: Alcohol is the most common etiology of recurrent acute pancreatitis and chronic pancreatitis. The extent and timing of drinking that increases the transient risk of acute pancreatitis is yet unknown. METHODS: We designed a case-crossover study to determine the effective hazard period of drinking in relation to episodes of pancreatitis. We aim to evaluate the dose-response relationship between excess drinking and pancreatitis comparing the extent of drinking during case and control periods from the same individual. We aim to recruit 160 patients hospitalized with acute pancreatitis, whose AUDIT-C score reaches 3 or higher. Interviews of each enrolled patient to define their 15-day history of alcohol consumption employing the timeline follow-back method. Long-term drinking and smoking will be investigated as modifiers of the impact of short-term excess drinking. Patients are followed-up for evaluation of usual alcohol consumption during asymptomatic periods following the index hospitalization. Blood and urine specimens are collected while the patients are hospitalized and during a standard-of-care follow-up visit. RESULTS: We have recruited 31 patients to date, with a median age of 33 years. Females and non-White participants make up 26% and 35% of the enrolled population, respectively. Forty-eight % of patients have had a prior history of acute pancreatitis. CONCLUSIONS: Our study will shed light on the impact of short-term changes in drinking on triggering acute pancreatitis. It will provide data on other covarying factors of drinking and behaviors changes after acute pancreatitis.

Lifetime smoking history and cohort-based smoking prevalence in chronic pancreatitis.

BACKGROUND/OBJECTIVE: Smoking prevalence in patients with chronic pancreatitis [CP] is high. We aimed to understand lifetime history of smoking and cohort trends in CP patients to inform effective strategies for smoking cessation. METHOD: Data on 317 CP patients from the North American Pancreatitis Study 2 [NAPS2] Continuation and Validation Study and the NAPS2 Ancillary Study were analyzed. Smoking history was assessed for each phase of life from the onset of smoking to study enrollment. Data on second-hand smoke and drinking history were also collected. We compared demographic factors, drinking history, pain level and pancreas morphology by smoking status at age 25 (non-smoking, <1 pack per day [PPD], ≥1 PPD). We compared smoking prevalence by birth cohorts: 1930-1949, 1950-1969, 1970-1989. RESULT: Fifty-one percent of CP patients reported smoking at the time of enrollment. Those who smoked ≥1 PPD at age 25 smoked a cumulative total of 30.3 pack-years of cigarettes over a lifetime. Smoking at age 25 was associated with greater lifetime drinking and greater exposure to second-hand smoke at home and at workplace. Pancreatic atrophy and pseudocysts were more common among smokers. Pancreatic pain was more severe among smokers, and 12-13% of smokers reported smoking to alleviate pain. Male CP patients born in 1950-1969 reported the highest peak prevalence of smoking, and female CP patients born in 1970-1989 reported highest peak prevalence of smoking. CONCLUSION: CP patients exhibit intense and sustained smoking behavior once established in the 20s. Regardless, cohort analyses demonstrate that the behaviors could potentially be altered by policy changes.

Divergent trends in lifetime drinking and smoking between Black and White Americans diagnosed with chronic pancreatitis.

BACKGROUND/OBJECTIVES: Black Americans are at increased risk of chronic pancreatitis (CP) compared to their White counterparts. We aimed to describe the race-specific smoking history and lifetime drinking in patients diagnosed with CP. METHODS: We analyzed data on 334 Black and White CP participants of the North American Pancreatitis Study 2 Continuation and Validation Study and Ancillary Study. Lifetime drinking history and lifetime smoking history were collected through in-person interviews. Intensity, frequency, duration and current status of drinking and smoking were compared between Black and White CP participants, stratified by physician-defined alcohol etiology. In addition, drinking levels at each successive decades in life (20s, 30s, 40s) were compared by race and graphically portrayed as heat diagrams. RESULTS: Among patients with alcoholic CP, current smoking levels were not different by race (67-70%), but a smaller proportion of Black patients reported having smoked 1 or more packs per day in the past (32%) as compared to White patients (58%, p < 0.0001). Black patients were more likely to report current consumption of alcohol (31%), as opposed to White patients (17%, p = 0.016). Black patients also reported more intense drinking at age 35 and 45 years as compared to White patients, while age at CP onset were similar between the two groups. CONCLUSION: We found more intense drinking but less intense smoking history in Black CP patients as compared to White CP patients. Effective alcohol abstinence and smoking cessation program with sustained impact are needed in CP patients.

Endoscopic History and Provider Characteristics Influence Gastric Cancer Survival in Asian Americans.

Gastric carcinoma (GC) disproportionately affects Asian Americans. We examined whether history of upper gastrointestinal (GI) endoscopy was associated with lower stage at GC diagnosis among Asian Americans and whether origin of providers influenced referral for endoscopy. We employed Surveillance Epidemiology and End Results-Medicare data on Asian Americans diagnosed with GC in 2004-2013 (n = 1,554). Stage distribution, GI conditions at diagnosis, and history of endoscopy were compared between Asian ethnic groups. Multivariate logistic regression adjusting for age, sex, poverty level, tumor location, and histology was used to examine the association of ethnicity and endoscopic history with stage I disease at diagnosis of GC. Koreans were more likely to be diagnosed with stage I, T1a GC and have prior history of endoscopy, compared with other Asian ethnicities (24% vs. 8% for stage I, T1a; 40% vs. 15% for endoscopy). Patients with primary care providers of concordant ethnic origin were more likely to have history of endoscopy. Asian American patients with GC with history of endoscopy were more likely to be diagnosed with GC at stage I disease (adjusted OR, 3.07; 95% confidence interval, 2.34-4.02). Compared with other Asian Americans, Koreans were diagnosed with GC at earlier stages owing to common history of endoscopy, which was more often undergone by patients with primary care providers of concordant ethnic origin. Overall, upper GI endoscopy was associated with early detection of GC in Asian Americans. Novelty and Impact. It is well-established that Asian Americans in the United States are disproportionately affected by gastric cancer. In our study we found that Asian American patients treated by physicians of similar ethnic background are more likely to undergo upper GI endoscopy in the United States, leading to early detection of gastric cancer and longer survival. Given this, targeted endoscopic screening in Asian Americans should be considered for early detection of GC.

Identification of Individuals at Increased Risk for Pancreatic Cancer in a Community-Based Cohort of Patients With Suspected Chronic Pancreatitis.

OBJECTIVES: We lack reliable methods for identifying patients with chronic pancreatitis (CP) at increased risk for pancreatic cancer. We aimed to identify radiographic parameters associated with pancreatic cancer in this population. METHODS: We conducted a retrospective cohort study of patients with suspected CP within an integrated healthcare system in Southern California in 2006-2015. Patients were identified by a diagnostic code and confirmed by imaging findings (parenchymal calcification, ductal stones, glandular atrophy, pseudocyst, main duct dilatation, duct irregularity, abnormal side branch, or stricture) defined by the natural language processing of radiographic reports. We used Cox regression to determine the relationship of smoking, alcohol use, acute pancreatitis, diabetes, body mass index, and imaging features with the risk of incident pancreatic cancer at least 1 year after abnormal pancreas imaging. RESULTS: We identified 1,766 patients with a diagnostic code and an imaging feature for CP with a median follow-up of 4.5 years. There were 46 incident pancreatic cancer cases. Factors that predicted incident pancreatic cancer after 1-year of follow-up included obesity (hazard ratio 2.7, 95% confidence interval: 1.2-6.1) and duct dilatation (hazard ratio 10.5, 95% confidence limit: 4.0-27). Five-year incidence of pancreatic cancer in this population with duct dilatation was 6.3%. DISCUSSION: High incidence of pancreatic cancer in suspected patients with CP with pancreatic duct dilatation warrants regular surveillance for pancreatic cancer.

Prediction of Pancreatic Cancer Based on Imaging Features in Patients With Duct Abnormalities.

OBJECTIVES: Abnormalities of the main pancreatic duct may be an early indicator of pancreatic ductal adenocarcinoma (PDAC). We develop and validate algorithms that predict the risk of PDAC using features identified on cross-sectional imaging and other clinical characteristics collected through electronic medical records. METHODS: Adult patients with abdominal computed tomography or magnetic resonance imaging in January 2006 to June 2016 demonstrating dilatation of main pancreatic duct were identified. Pancreas-related morphologic features were extracted from radiology reports using natural language processing. The cumulative incidence of PDAC with death as a competing risk was estimated using multistate models. Model discrimination was assessed using c-index. The models were internally validated using bootstrapping. RESULTS: The cohort consisted of 7819 patients (mean age, 71 years; 65% female). A total of 781 patients (10%) developed PDAC within 3 years after the first eligible imaging study. The final models achieved reasonable discrimination (c-index, 0.825-0.833). The 3-year average risk of PDAC in the top 5% of the total eligible patients was 56.0%, more than 20 times of the average risk among the bottom 50% of patients. CONCLUSIONS: Prediction models combining imaging features and clinical measures can be used to further stratify the risk of pancreatic cancer among patients with pancreas ductal dilatation.

Early detection of pancreatic cancer.

Pancreatic ductal adenocarcinoma is most frequently detected at an advanced stage. Such late detection restricts treatment options and contributes to a dismal 5-year survival rate of 3-15%. Pancreatic ductal adenocarcinoma is relatively uncommon and screening of the asymptomatic adult population is not feasible or recommended with current modalities. However, screening of individuals in high-risk groups is recommended. Here, we review groups at high risk for pancreatic ductal adenocarcinoma, including individuals with inherited predisposition and patients with pancreatic cystic lesions. We discuss studies aimed at finding ways of identifying pancreatic ductal adenocarcinoma in high-risk groups, such as among individuals with new-onset diabetes mellitus and people attending primary and secondary care practices with symptoms that suggest this cancer. We review early detection biomarkers, explore the potential of using social media for detection, appraise prediction models developed using electronic health records and research data, and examine the application of artificial intelligence to medical imaging for the purposes of early detection.

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

BACKGROUND & AIMS: Observational studies of predominantly white populations have found new-onset diabetes to be associated with increased risk of pancreatic cancer. We sought to determine whether this relationship applies to other races or ethnicities and to identify metabolic profiles associated with increased risk of pancreatic cancer. METHODS: We conducted a population-based cohort study of Asian, black, Hispanic and white patients from Kaiser Permanente Southern California from 2006 through 2016 (n = 1,499,627). Patients with diabetes were identified based on glucose and hemoglobin A1c (HbA1c) measurements. We used Cox regression to assess the relationship between diabetes status and duration and pancreatic cancer. For patients with recent diagnoses of diabetes (1 year or less) we compared longitudinal changes in glucose, HbA1c, and weight, from time of diabetes diagnosis through 3 years prior to the diagnosis, in patients with vs without pancreatic cancer. RESULTS: We identified 2,002 incident cases of pancreatic cancer from nearly 7.5 million person-years of follow-up. Compared to patients without diabetes, individuals who received a recent diagnosis of diabetes had an almost 7-fold increase in risk of pancreatic cancer (relative risk, 6.91; 95% CI, 5.76-8.30). Among patients with a recent diagnosis of diabetes, those who developed pancreatic cancer had more rapid increases in levels of glucose (Δslope: cases, 37.47 mg/dL vs non-cases, 27.68 mg/dL) and HbA1c (Δslope: cases, 1.39% vs non-cases, 0.86%) in the month preceding the diagnosis of diabetes, and subtle weight loss in the prior years (slope: cases -0.18 kg/interval vs non-cases 0.33 kg/interval). These longitudinal changes in markers of metabolism were stronger for specific race and ethnic groups. CONCLUSIONS: In a study of a large ethnically diverse population, we found risk of pancreatic cancer to be increased among patients with a diagnosis of diabetes in the past year among different races and ethnicities. Weight loss and rapid development of poor glycemic control were associated with increased risk of pancreatic cancer in multiple races.

Lifetime Drinking History of Persons With Chronic Pancreatitis.

AIMS: Cumulative consumption of alcohol and variations of alcohol intake by age are unknown in chronic pancreatitis (CP) patients in North America. This study summarizes the lifetime drinking history (LDH) by physician attribution of alcohol etiology, smoking status and sex in persons with CP. METHODS: We analyzed data on 193 CP participants who completed the LDH questionnaire in the North American Pancreatitis Continuation and Validation Study (NAPS2-CV). We collected data on frequency of drinking and drinks per drinking day for each drinking phase of their lives. We examined differences in total number of alcoholic drinks and weight of ethanol consumed by physician's assessment of CP etiology, sex and smoking status. We also compared intensity of drinking in 20, 30 and 40s by timing of CP diagnosis. RESULTS: Persons diagnosed with alcoholic CP consumed median of 34,488 drinks (interquartile range 18,240-75,024) prior to diagnosis of CP, which occurred earlier than in persons with CP of other etiology (47 vs. 52 years). Cumulative drinking was greater in male vs. female patients. Male CP patients with a diagnosis of CP before the age of 45 drank more intensely in their 20s as compared to those with later onset of disease. Current smoking was prevalent (67%) among those diagnosed with alcoholic CP. Twenty-eight percent of patients without physician attribution of alcohol etiology reported drinking heavily in the past. CONCLUSIONS: Lifetime cumulative consumption of alcohol and prevalence of current smoking are high in persons diagnosed with alcoholic pancreatitis. Intense drinking in early years is associated with earlier manifestation of the disease.