Dataset Information

Acute and Chronic Pancreatitis Disease Prevalence, Classification, and Comorbidities: A Cohort Study of the UK BioBank.

ABSTRACT:

Introduction

Pancreatitis is a complex syndrome that results from many etiologies. Large well-characterized cohorts are needed to further understand disease risk and prognosis.

Methods

A pancreatitis cohort of more than 4,200 patients and 24,000 controls were identified in the UK BioBank (UKBB) consortium. A descriptive analysis was completed, comparing patients with acute (AP) and chronic pancreatitis (CP). The Toxic-metabolic, Idiopathic, Genetic, Autoimmune, Recurrent, and severe pancreatitis and Obstructive checklist Version 2 classification was applied to patients with AP and CP and compared with the control population.

Results

CP prevalence in the UKBB is 163 per 100,000. AP incidence increased from 21.4/100,000 per year from 2001 to 2005 to 48.2/100,000 per year between 2016 and 2020. Gallstones and smoking were confirmed as key risk factors for AP and CP, respectively. Both populations carry multiple risk factors and a high burden of comorbidities, including benign and malignant neoplastic disorders.

Discussion

The UKBB serves as a rich cohort to evaluate pancreatitis. Disease burden of AP and CP was high in this population. The association of common risk factors identified in other cohort studies was confirmed in this study. Further analysis is needed to link genomic risks and biomarkers with disease features in this population.

SUBMITTER: Spagnolo DM

PROVIDER: S-EPMC8806365 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Acute and Chronic Pancreatitis Disease Prevalence, Classification, and Comorbidities: A Cohort Study of the UK BioBank.

Spagnolo Daniel M DM Greer Phil J PJ Ohlsen Celeste Shelton CS Mance Shannon S Ellison Mitchell M Breze Cameron C Busby Ben B Whitcomb David C DC Haupt Mark M

Clinical and translational gastroenterology 20220119 1

<h4>Introduction</h4>Pancreatitis is a complex syndrome that results from many etiologies. Large well-characterized cohorts are needed to further understand disease risk and prognosis.<h4>Methods</h4>A pancreatitis cohort of more than 4,200 patients and 24,000 controls were identified in the UK BioBank (UKBB) consortium. A descriptive analysis was completed, comparing patients with acute (AP) and chronic pancreatitis (CP). The Toxic-metabolic, Idiopathic, Genetic, Autoimmune, Recurrent, and seve ...[more]

PMID: 35060944

Similar Datasets

Project description:BackgroundThe number of people living with obesity or who are overweight presents a global challenge, and the development of effective interventions is hampered by a lack of research which takes a joined up, whole system, approach that considers multiple elements of the complex obesity system together. We need to better understand the collective characteristics and behaviours of those who are overweight or have obesity and how these differ from those who maintain a healthy weight.MethodsUsing the UK Biobank cohort we develop an obesity classification system using k-means clustering. Variable selection from the UK Biobank cohort is informed by the Foresight obesity system map across key domains (Societal Influences, Individual Psychology, Individual Physiology, Individual Physical Activity, Physical Activity Environment).ResultsOur classification identifies eight groups of people, similar in respect to their exposure to known drivers of obesity: 'Younger, urban hard-pressed', 'Comfortable, fit families', 'Healthy, active and retirees', 'Content, rural and retirees', 'Comfortable professionals', 'Stressed and not in work', 'Deprived with less healthy lifestyles' and 'Active manual workers'. Pen portraits are developed to describe the characteristics of these different groups. Multinomial logistic regression is used to demonstrate that the classification can effectively detect groups of individuals more likely to be living with overweight or obesity. The group identified as 'Comfortable, fit families' are observed to have a higher proportion of healthy weight, while three groups have increased relative risk of being overweight or having obesity: 'Active manual workers', 'Stressed and not in work' and 'Deprived with less healthy lifestyles'.ConclusionsThis paper presents the first study of UK Biobank participants to adopt this obesity system approach to characterising participants. It provides an innovative new approach to better understand the complex drivers of obesity which has the potential to produce meaningful tools for policy makers to better target interventions across the whole system to reduce overweight and obesity.

Project description:ImportanceKeloids and hypertrophic scars (excessive scarring) are relatively understudied disfiguring chronic skin conditions with high treatment resistance.ObjectiveTo evaluate established comorbidities of excessive scarring in European individuals, with comparisons across ethnic groups, and to identify novel comorbidities via a phenome-wide association study (PheWAS).Design, setting, and participantsThis multicenter cross-sectional population-based cohort study used UK Biobank (UKB) data and fitted logistic regression models for testing associations between excessive scarring and a variety of outcomes, including previously studied comorbidities and 1518 systematically defined disease categories. Additional modeling was performed within subgroups of participants defined by self-reported ethnicity (as defined in UK Biobank). Of 502 701 UKB participants, analyses were restricted to 230078 individuals with linked primary care records.ExposuresKeloid or hypertrophic scar diagnoses.Main outcomes and measuresPreviously studied disease associations (hypertension, uterine leiomyoma, vitamin D deficiency, atopic eczema) and phenotypes defined in the PheWAS Catalog.ResultsOf the 972 people with excessive scarring, there was a higher proportion of female participants compared with the 229 106 controls (65% vs 55%) and a lower proportion of White ethnicity (86% vs 95%); mean (SD) age of the total cohort was 64 (8) years. Associations were identified with hypertension and atopic eczema in models accounting for age, sex, and ethnicity, and the association with atopic eczema (odds ratio [OR], 1.68; 95% CI, 1.36-2.07; P < .001) remained statistically significant after accounting for additional potential confounders. Fully adjusted analyses within ethnic groups revealed associations with hypertension in Black participants (OR, 2.05; 95% CI, 1.13-3.72; P = .02) and with vitamin D deficiency in Asian participants (OR, 2.24; 95% CI, 1.26-3.97; P = .006). The association with uterine leiomyoma was borderline significant in Black women (OR, 1.93; 95% CI, 1.00-3.71; P = .05), whereas the association with atopic eczema was significant in White participants (OR, 1.68; 95% CI, 1.34-2.12; P < .001) and showed a similar trend in Asian (OR, 2.17; 95% CI, 1.01-4.67; P = .048) and Black participants (OR, 1.89; 95% CI, 0.83-4.28; P = .13). The PheWAS identified 110 significant associations across disease systems; of the nondermatological, musculoskeletal disease and pain symptoms were prominent.Conclusions and relevanceThis cross-sectional study validated comorbidities of excessive scarring in UKB with comprehensive coverage of health outcomes. It also documented additional phenome-wide associations that will serve as a reference for future studies to investigate common underlying pathophysiologic mechanisms.

Project description:Introduction: Our meta-analysis indicated that aging influences the outcomes of acute pancreatitis (AP), however, a potential role for comorbidities was implicated, as well. Here, we aimed to determine how age and comorbidities modify the outcomes in AP in a cohort-analysis of Hungarian AP cases. Materials and Methods: Data of patients diagnosed with AP by the revised Atlanta criteria were extracted from the Hungarian Registry for Pancreatic Patients. Outcomes of interest were mortality, severity, length of hospitalization, local, and systemic complications of AP. Comorbidities were measured by means of Charlson Comorbidity Index (CCI) covering pre-existing chronic conditions. Non-parametric univariate and multivariate statistics were used in statistical analysis. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Results: A total of 1203 patients from 18 centers were included. Median age at admission was 58 years (range: 18-95 years), median CCI was 2 (range: 0-10). Only severe comorbidities (CCI ≥ 3) predicted mortality (OR = 4.48; CI: 1.57-12.80). Although severe comorbidities predicted AP severity (OR = 2.10, CI: 1.08-4.09), middle (35-64 years) and old age (≥65 years) were strong predictors with borderline significance, as well (OR = 7.40, CI: 0.99-55.31 and OR = 6.92, CI: 0.91-52.70, respectively). Similarly, middle and old age predicted a length of hospitalization ≥9 days. Interestingly, the middle-aged patients (35-64 years) were three times more likely to develop pancreatic necrosis than young adults (OR = 3.21, CI: 1.26-8.19), whereas the old-aged (≥65 years) were almost nine times more likely to develop systemic complications than young adults (OR = 8.93, CI: 1.20-66.80), though having severe comorbidities (CCI ≥ 3) was a predisposing factor, as well. Conclusion: Our results proved that both aging and comorbidities modify the outcomes of AP. Comorbidities determine mortality whereas both comorbidities and aging predict severity of AP. Regarding complications, middle-aged patients are the most likely to develop local complications; in contrast, those having severe comorbidities are prone to develop systemic complications. Studies validating the implementation of CCI-based predictive scores are awaited.

Dataset Information

Acute and Chronic Pancreatitis Disease Prevalence, Classification, and Comorbidities: A Cohort Study of the UK BioBank.

Introduction

Methods

Results

Discussion

Publications

Acute and Chronic Pancreatitis Disease Prevalence, Classification, and Comorbidities: A Cohort Study of the UK BioBank.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets