Objective: Coronary artery disease (CAD) and cancer are the two leading causes of death worldwide. Evidence suggests the existence of shared mechanisms for these two diseases. We aimed to conduct a systematic review and meta-analysis to investigateassociation between CAD and incident cancer risk.
Methods: We searched Cochrane, PubMed, and Embase from inception until October 20, 2021, without language restrictions. Observational cohort studies were used to investigate the association between CAD and incident cancer risk. Using random-effects models, the odds ratio (OR) and 95% confidence interval (CI) were calculated. We utilized subgroup and sensitivity analyses to determine the potential sources of heterogeneity and explore the association between CAD and specific cancers. This study was conducted under a pre-established, registered protocol on PROSPERO (CRD42022302507).
Results: We initially examined 8,533 articles, and included 14 cohort studies in our review, 11 of which were eligible for meta-analysis. Patients with CAD had significantly higher odds of cancer risk than those without CAD (OR = 1.15, 95% CI = [1.08-1.22], = 66%). Subgroup analysis revealed that the incident cancer risk was significantly higher in both sexes and patients with CAD with or without myocardial infarction. Sensitivity analysis revealed that the risk remained higher in patients with CAD even after >1 year of follow-up (OR = 1.23, 95% CI = [1.08-1.39], = 76%). Regarding the specific outcome, the incident risk for colorectal and lung cancers was significantly higher (OR = 1.06, 95% CI = [1.03-1.10], = 10%, and OR = 1.36, 95% CI = [1.15-1.60], = 90%, respectively) and that for breast cancer was lower (OR = 0.86, 95% CI = [0.77-0.97], = 57%) in patients with CAD than in those without CAD.
Conclusion: CAD may be associated with incident cancer risk, particularly for lung and colorectal cancers, in men and women as well as patients with or without myocardial infarction. Early detection of new-onset cancer and detailed cancer surveillance programs should be implemented in patients with CAD to reduce cancer-related morbidity and mortality.
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http://dx.doi.org/10.7717/peerj.14922 | DOI Listing |
Ann Intern Med
January 2025
Center for Hematology and Regenerative Medicine, Department of Medicine Huddinge, Karolinska Institutet, and Department of Hematology, Karolinska University Hospital, Stockholm, Sweden.
Gac Med Mex
January 2025
School of Medicine, Pontificia Universidad Javeriana.
Background: In Colombia, gastric cancer is fifth in incidence (12.8 cases per 100,000) and third in mortality (9.9 cases per 100,000).
View Article and Find Full Text PDFNeoplasma
December 2024
Department of Oncology, First Faculty of Medicine, Charles University and Thomayer University Hospital, Prague, Czech Republic.
The objective of this study was to investigate the prognostic significance of the frequency of primary cilia (PC) and β-catenin expression in 218 patients (pts) with non-small cell lung cancer (NSCLC), including 125 pts with adenocarcinoma and 93 pts with squamous cell carcinoma. In the whole group of 218 pts with NSCLC, overall survival (OS) was significantly inferior among pts with present PC than without PC (p=0.024) and with higher cytoplasmic β-catenin expression (25-75%) than with lower cytoplasmic β-catenin expression (<25%) (p=0.
View Article and Find Full Text PDFNeoplasma
December 2024
Department of Pediatric Hematology and Oncology, National Institute of Children's Diseases, Faculty of Medicine Comenius University, Bratislava, Slovakia.
Pediatric central nervous system (CNS) tumors represent 20-25% of childhood malignancies, with 35-40 new cases annually in Slovakia. Despite treatment advances, high mortality and poor quality of life in a lot of cases persist. This study assesses the clinical features, treatment modalities, and survival rates of pediatric CNS tumor patients in the single largest center in Slovakia.
View Article and Find Full Text PDFOncologist
January 2025
Department of Hepatic Surgery, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Background: Peritoneal metastasis (PM) after the rupture of hepatocellular carcinoma (HCC) is a critical issue that negatively affects patient prognosis. Machine learning models have shown great potential in predicting clinical outcomes; however, the optimal model for this specific problem remains unclear.
Methods: Clinical data were collected and analyzed from 522 patients with ruptured HCC who underwent surgery at 7 different medical centers.
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