Risk Factors for Pancreatic Cancer in Patients with New-Onset Diabetes: A Systematic Review and Meta-Analysis.
Claudia MellenthinDaniel Vasile BalabanAna DugicStéphane CullatiPublished in: Cancers (2022)
(1) Background: Patients with new-onset diabetes (NOD) are at risk of pancreatic ductal adenocarcinoma (PDAC), but the most relevant additional risk factors and clinical characteristics are not well established. (2) Objectives: To compare the risk for PDAC in NOD patients to persons without diabetes. Identify risk factors of PDAC among NOD patients. (3) Methods: Medline, Embase, and Google Scholar were last searched in June 2022 for observational studies on NOD patients and assessing risk factors for developing PDAC. Data were extracted, and Meta-Analysis was performed. Pooled effect sizes with 95% confidence intervals (CI) were estimated with DerSimonian & Laird random effects models. (4) Findings: Twenty-two studies were included, and 576,210 patients with NOD contributed to the analysis, of which 3560 had PDAC. PDAC cases were older than controls by 6.14 years (CI 3.64-8.65, 11 studies). The highest risk of PDAC involved a family history of PDAC (3.78, CI 2.03-7.05, 4 studies), pancreatitis (5.66, CI 2.75-11.66, 9 studies), cholecystitis (2.5, CI 1.4-4.45, 4 studies), weight loss (2.49, CI 1.47-4.22, 4 studies), and high/rapidly increasing glycemia (2.33, CI 1.85-2.95, 4 studies) leading to more insulin use (4.91, CI 1.62-14.86, 5 studies). Smoking (ES 1.20, CI 1.03-1.41, 9 studies) and alcohol (ES 1.23, CI 1.09-1.38, 9 studies) have a smaller effect. (5) Conclusion: Important risk factors for PDAC among NOD patients are age, family history, and gallstones/pancreatitis. Symptoms are weight loss and rapid increase in glycemia. The identified risk factors could be used to develop a diagnostic model to screen NOD patients.
Keyphrases
- end stage renal disease
- risk factors
- ejection fraction
- type diabetes
- newly diagnosed
- chronic kidney disease
- cardiovascular disease
- prognostic factors
- peritoneal dialysis
- clinical trial
- bariatric surgery
- high throughput
- metabolic syndrome
- machine learning
- glycemic control
- skeletal muscle
- adipose tissue
- electronic health record
- data analysis
- obese patients