| Literature DB >> 33062319 |
Mengxia Zhang1, Lin-Ling Li1, Qian-Qian Zhao1, Xiao-Dong Peng1, Kui Wu1, Xin Li1, Yan-Fei Ruan1, Rong Bai1, Nian Liu1, Chang Sheng Ma1.
Abstract
BACKGROUND: There are distinct results for the relationship between new-onset atrial fibrillation (NOAF) and subsequent incident cancer. To date, no systematic analysis has been conducted on this issue. This study aims to explore the relationship between NOAF and the risk of developing cancer through a meta-analysis with a large sample size.Entities:
Year: 2020 PMID: 33062319 PMCID: PMC7537679 DOI: 10.1155/2020/2372067
Source DB: PubMed Journal: Cardiol Res Pract ISSN: 2090-0597 Impact factor: 1.866
Figure 1An example of the PubMed retrieval strategy.
Figure 2The flow diagram of the study selection process. AF, atrial fibrillation; OR, odds ratio; HR, hazard ratio.
The characteristics of studies included in the meta-analysis.
| Study | Design | Location | Participants | Total, N | Excluded | Period of enrollment | Follow-up duration (median) | Covariates in an adjusted model | NOS score |
|---|---|---|---|---|---|---|---|---|---|
| Conen 2016 [ | Prospective cohort study | USA | Female health professionals (>45) | 34691 | Prior AF/CA/CVD | 1993–2013 | 19.1 (17.6–19.7) | Age, BMI, HTN, DM, smoke, race, and comorbidity | 9 |
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| Wassertheil 2017 [ | Prospective cohort study | USA | Postmenopausal women (50–79) | 86046 | NA | From 1994 | 15.9 | Age, race, parity, age at first birth, and cancer-specific potential confounders | 8 |
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| Hung 2018 [ | Retrospective cohort study | Taipei, China | Individual from 2005 | 5130 | <20Y Prior AF/CA | 2005–2010 | 3.4 ± 2 | NA | 8 |
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| Saliba 2018 [ | Prospective case-control studies | USA and Israel | NA | 19991 | NA | From 1998 | >3Y | Age, sex, smoking, alcohol consumption, education, medication use, and comorbidity | 8 |
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| Vinter 2018 [ | Prospective cohort study | Denmark | NA | 55101 | Nonmelanoma skin cancer | 1993–2013 | 19.7 | Age, BMI, smoking duration, and alcohol consumption, | 7 |
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| Hung 2019 [ | Prospective cohort study | Taipei, China | NA | 332555 | <20Y Prior CA | 1996–2011 | 3.1 (0.97–6.53) | Age, sex, risk factors, and comorbidity | 8 |
AF, atrial fibrillation; CA, cancer; CVD, cardiovascular disease; BMI, body mass index; HTN, hypertension; DM, diabetes mellitus; NA, not applicable; NOS, Newcastle–Ottawa Quality Assessment Scale.
Patient characteristics of the five studies.
| Study | Age (years) | Sex (M/F %) | Hypertension | Hyperlipidemia | Diabetes | Definition | Incident cases | Types of cancer | |||||||
| NOAF | N-NOAF | NOAF | N-NOAF | NOAF | N-NOAF | NOAF | N-NOAF | NOAF | N-NOAF | NOAF | CA | NOAF | Sub-CA | ||
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| Conen 2016 [ | 58.0 (52.0–64.0) | 53 (49–58) | Female | NA | 610 | 8550 | 501 | 9988 | 64 | 870 | ECG or med report | Pathology/cytology reports | 1467 | 147 | Colon/breast cancer |
| Wassertheil 2017 [ | 66.9 ± 7.1 | 63.2 ± 7.3 | Female | NA | 2011 | 25716 | 905 | 11612 | 325 | 3199 | ECG or self-report | Medical diagnosis during the follow-up | 4,376 | 198 | Colorectal/breast cancer |
| Hung 2018 [ | 74 ± 13.6 | NA | 53.6/46.4 | NA | 3477 | NA | 864 | NA | 2981 | NA | ICD-9 | ICD-9 | 5130 | 330 | Colon/breast/liver/lung cancer |
| Saliba 2018 [ | 63.6 ± 13.6 | 64.3 ± 13.6 | 23.6/76.4 | NA | 4164 | 4868 | 3196 | 3990 | 1820 | 2147 | ECG | Pathology/cytology reports | 890 | 352 | Colorectal/breast cancer |
| Vinter 2018 [ | 56.2 (52.7–60.4) | NA | 47.6/52.4 | NA | NA | NA | NA | NA | NA | NA | ICD-8/10 or med report | ICD-10 | 2776 | 533 | Prostate/lung/colorectal/breast cancer |
| Hung 2019 [ | 70.8 ± 13.1 | NA | 55.2/44.8 | NA | 227956 | NA | 83207 | NA | 94515 | NA | ICD-9 | ICD-9 | 332555 | 22911 | 10 kinds of specific cancers |
NOAF, new-onset atrial fibrillation; N-NOAF, not new-onset atrial fibrillation; Sub-CA, subsequent cancer; NA, not applicable; ECG, electrocardiography; ICD, International Classification of Diseases; Med, medicine.
Figure 3The forest plot for the combined effect quantities of the risk of cancer in AF patients. SE, standard error; IV, inverse variance.
The subgroup analysis of the association between AF and CA..
| Study | Subgroup | Number of studies | RR | Meta-analysis | Heterogeneity | Test for subgroup differences | |
| 95% CI |
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| Gender | Male | 3 | 1.39 | 1.33, 1.45 | <0.00001 | 21 | 44.7 |
| Female | 3 | 1.26 | 1.11, 1.44 | 0.0005 | 78 | ||
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| Subtype of cancer | Colorectal cancer | 6 | 1.22 | 0.92, 1.60 | 0.16 | 92 | 87.9 |
| Lung cancer | 4 | 1.51 | 1.47, 1.55 | <0.00001 | 0 | ||
| Breast cancer | 5 | 1.10 | 0.94, 1.29 | 0.25 | 80 | ||
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| Time interval between CA diagnosis and AF | <3M | 4 | 3.44 | 2.29, 5.17 | <0.00001 | 88 | 92.9 |
| 3–12M | 4 | 1.38 | 0.90, 2.12 | 0.14 | 97 | ||
| >12M | 4 | 1.09 | 0.95, 1.24 | 0.24 | 92 | ||
AF, atrial fibrillation; CA, cancer; RR, risk ratio.
Figure 4The funnel plot for all studies. SE, standard error; RR, risk ratio.