
==== Front
Oncology
Oncology
OCL
OCL
Oncology
0030-2414
1423-0232
S. Karger AG Basel, Switzerland

38272000
536449
10.1159/000536449
Clinical Study
Association of Cancer and Its Interaction with Conventional Risk Factors on Cardiovascular Disease Risk
Cancer and Cardiovascular Risk
2727363
Suzuki Yuta a b
2727364
Kaneko Hidehiro a c
2727365
Okada Akira d
2727366
Matsuoka Satoshi a e
2727367
Kashiwabara Kosuke f
2727368
Fujiu Katsuhito a c
2727369
Michihata Nobuaki g
2727370
Jo Taisuke g
2727371
Takeda Norifumi a
2727372
Morita Hiroyuki a
2727373
Node Koichi h
2727374
Yasunaga Hideo i
2727375
Komuro Issei a j k
a Department of Cardiovascular Medicine, The University of Tokyo, Tokyo, Japan
b Center for Outcomes Research and Economic Evaluation for Health, National Institute of Public Health, Saitama, Japan
c The Department of Advanced Cardiology, The University of Tokyo, Tokyo, Japan
d Department of Prevention of Diabetes and Lifestyle-Related Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
e The Department of Cardiology, New Tokyo Hospital, Matsudo, Japan
f Clinical Research Promotion Center, The University of Tokyo Hospital, Tokyo, Japan
g The Department of Health Services Research, The University of Tokyo, Tokyo, Japan
h Department of Cardiovascular Medicine, Saga University, Saga, Japan
i The Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, Tokyo, Japan
j International University of Health and Welfare, Tokyo, Japan
k Department of Frontier Cardiovascular Science, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
Correspondence to: Hidehiro Kaneko, kanekohidehiro@gmail.com
25 1 2024
102 9 775784
18 12 2023
17 1 2024
2024
© 2024 The Author(s). Published by S. Karger AG, Basel
2024
https://creativecommons.org/licenses/by-nc/4.0/ This article is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC) (http://www.karger.com/Services/OpenAccessLicense). Usage and distribution for commercial purposes requires written permission.
Abstract

Introduction

We sought to examine the association of cancer history with the incidence of individual cardiovascular disease events and to clarify whether the history of cancer modifies the relationship between conventional cardiovascular risk factors and incident cardiovascular disease.

Methods

This retrospective cohort study used the JMDC Claims Database, including 3,531,683 individuals. The primary endpoint was the composite cardiovascular disease outcome, which included myocardial infarction, angina pectoris, stroke, heart failure, and atrial fibrillation.

Results

During a follow-up, 144,162 composite endpoints were recorded. Individuals with a history of cancer had a higher risk of developing composite cardiovascular disease events (hazard ratio [HR] 1.26, 95% confidence interval [CI] 1.22–1.29). The HRs for myocardial infarction, angina pectoris, stroke, heart failure, and atrial fibrillation were 1.11 (95% CI 0.98–1.27), 1.15 (95% CI 1.10–1.20), 1.11 (95% CI 1.05–1.18), 1.39 (95% CI 1.34–1.44), and 1.22 (95% CI 1.13–1.32), respectively. Individuals who required chemotherapy for cancer had a higher risk of developing cardiovascular disease. Although conventional risk factors (e.g., overweight/obesity, hypertension, and diabetes) were associated with incident composite cardiovascular disease even in individuals with a history of cancer, the total population-attributable fractions of conventional risk factors were less in individuals with a history of cancer.

Conclusion

Individuals with a history of cancer (particularly those requiring chemotherapy) have a higher risk of cardiovascular disease. Traditional risk factors are important in the development of cardiovascular disease in individuals with and without a history of cancer. In individuals with a history of cancer, however, the total population-attributable fractions of conventional risk factors decreased.

Keywords

Cancer
Onco-cardiology
Preventive cardiology
Epidemiology
Cardiovascular disease risk
This work was supported by grants from the Ministry of Health, Labour and Welfare, Japan (21AA2007), and the Ministry of Education, Culture, Sports, Science and Technology, Japan (20H03907, 21H03159, 21K08123, and 22K21133). The funding sources played no role in the current study.
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pmcIntroduction

Cancer survivors are known to have a greater risk of subsequent cardiovascular disease (CVD) events [1–3]. In light of the continuously increasing number of cancer survivors, CVD events in cancer survivors are becoming increasingly important from a clinical perspective. However, epidemiological issues remain to be resolved. First, comprehensive analyses of the association between cancer and individual cardiovascular events are limited. Among CVDs, for each CVD (e.g., atherosclerotic CVD, heart failure [HF], atrial fibrillation [AF]), the underlying pathological mechanism and risk factors would differ. Thus, it is important to comprehensively analyze the association between cancer and individual CVD events. Second, there are insufficient data on whether the association between conventional CVD risk factors (e.g., obesity, hypertension, and diabetes) and the development of CVD differs between cancer and non-cancer patients. We have previously reported that hypertension and Life’s Simple 7 cardiovascular health metrics are useful for risk stratification of cardiovascular events, even in cancer survivors [4, 5]. It is intriguing to see whether the association between these risk factors and cardiovascular events would be modified by the presence of cancer. Third, most reports examining CVD events in patients with cancer are from Western countries, with limited reports from Asian populations. However, racial and ethnic differences in the epidemiology of onco-cardiology should be considered. For example, CVD is the leading cause of death in the USA and the EU, whereas cancer is the leading cause of death in Japan. Given these racial epidemiological differences, there is a need to accumulate clinical data on onco-cardiology in Asian populations. Here, we analyzed a large-scale health checkup and administrative claims database in Japan and examined the relationship between cancer history and individual CVD events. In addition, we sought to clarify whether the presence of cancer modifies the association between conventional CVD risk factors and incident CVD.

Methods

Study Population

We performed a retrospective cohort study using the JMDC Claims Database (JMDC; Tokyo, Japan) [6–8]. The database includes information on individual health insurance records for more than 60 insurers and health checkup data (e.g., blood pressure measurement). This database includes outpatient and inpatient administrative claims data and allows investigators to follow individuals even if they move to a different hospital during medical treatment. The claims data included diagnostic procedure codes from the International Classification of Diseases, 10th Revision (ICD-10). The study population included 4,534,334 subjects who were 18 years of age or older with available data on health checkups from January 2005 through April 2021, including blood pressure, fasting plasma glucose, and lipid profile, more than 1 year after insurance enrollment. The study population required continuous insurance enrollment for at least 1 year. We excluded individuals who met the following criteria: prior history of CVD, including myocardial infarction (MI), angina pectoris (AP), stroke, HF, or AF (n = 200,265); prior history of renal replacement therapy (n = 1,092); missing cigarette smoking data (n = 276,351); missing alcohol consumption data (n = 365,977); and missing physical inactivity data (n = 158,966). Finally, this cohort study included 3,531,683 participants (online suppl. Fig. 1; for all online suppl. material, see https://doi.org/10.1159/000536449).

Definition of Cancer History

We defined individuals with a history of cancer as patients diagnosed with malignant neoplasms (ICD-10 codes: C00-D09) prior to the initial health checkup based on the ICD-10 codes. To examine the association between cancer sites and CVD events, we also obtained data on whether these cases had a history of selected cancer types, for which the Japanese population has a relatively higher incidence rate (https://ganjoho.jp/reg_stat/statistics/stat/summary.html). ICD-10 codes for each cancer diagnosis are provided in the online supplementary material.

Definition

Overweight/obesity was defined as having a body mass index ≥25 kg/m2. Hypertension was defined as systolic blood pressure ≥140 mm Hg, diastolic pressure ≥90 mm Hg, or the use of antihypertensive medications. Diabetes mellitus was defined as a fasting glucose level of ≥126 mg/dL or the use of antidiabetic medications (including insulin). Dyslipidemia was defined as a low-density lipoprotein cholesterol level ≥140 mg/dL, a high-density lipoprotein cholesterol level <40 mg/dL, a triglyceride level ≥150 mg/dL, or the use of antihyperlipidemic medications. Information regarding smoking (current or noncurrent/never) and alcohol consumption (every day or not every day) was collected from a self-report questionnaire during the health checkup. We also defined physical inactivity as not performing 30 min of exercise ≥ twice a week or not walking for more than 1 h per day.

Outcomes

The clinical outcomes were collected between January 2005 and April 2021. We defined a composite endpoint that included MI, AP, stroke, HF, and AF as the primary outcomes. We analyzed each MI, AP, stroke, HF, and AF event separately as secondary outcomes. ICD-10 codes for each CVD event are provided in the online supplementary material.

Statistical Procedures

Baseline characteristics stratified by cancer history were presented as numbers (%) and medians (with interquartile range). We used a χ2 test for categorical variables and a Mann-Whitney U test for continuous variables to compare the two groups. The incidence of CVD according to cancer history was examined using the Kaplan-Meier method. The log-rank test was used to examine the group differences. A Cox proportional hazard regression model was used to determine the association between cancer history and CVD incidence. Model 1 included only the cancer history. The hazard ratio (HR) was adjusted for age and sex (model 2). HR was further adjusted for body mass index, hypertension, diabetes mellitus, dyslipidemia, cigarette smoking, alcohol consumption, and physical inactivity (model 3).

Additionally, study participants were classified into three groups: those who had no history of cancer, those who had a history of cancer but did not receive active chemotherapy, and those who had a history of cancer and received active chemotherapy. Given that the Japanese system of universal health insurance allows for a 3-month maximum prescription term, active chemotherapy was defined as the use of antineoplastic agents within 3 months before the initial health checkup based on the WHO-ATC code (WHO-ATC codes: L01). We performed a Cox proportional hazard regression model analysis using these three groupings to evaluate the association of the combination of cancer history and chemotherapy with composite CVD events. We assessed the HRs for incident CVD among individuals with the five cancer sites with the highest number of patients in our dataset using the Cox proportional hazard regression model.

Furthermore, we performed a multivariable Cox proportional hazard regression model including age, sex, overweight/obesity, hypertension, diabetes mellitus, dyslipidemia, cigarette smoking, alcohol consumption, and physical inactivity stratified by the presence of cancer history. We estimated the population-attributable fraction (PAF) as the proportion of each CVD incident that could be attributed to each conventional CVD risk factor (i.e., overweight/obesity, hypertension, diabetes mellitus, dyslipidemia, cigarette smoking, alcohol consumption, and physical inactivity) using the Stata command “punafcc.” [7]. We calculated the total PAF of overweight/obesity, hypertension, diabetes mellitus, dyslipidemia, cigarette smoking, alcohol consumption, and physical inactivity for each CVD outcome. Further, to take the communality of risk factors into account, weighting was included in the calculation of total PAF based on the previous studies [9, 10]. The weighting was calculated as 1 minus communality for each risk factor. Four sensitivity analyses were conducted. First, a complete case analysis was performed in the primary analysis; therefore, we imputed missing data on exposures using multiple imputations with chained equations in this sensitivity analysis. The missing values were assumed to be random, and 20 iterations were performed [11, 12]. Second, we fitted the Fine-Gray proportional subdistribution hazards model to estimate the associations between the presence of cancer history and CVD events, considering the effect of death as a competing risk. Third, 2,844,576 individuals with a 1-year follow-up period were examined (i.e., the induction period). Fourth, we conducted a subgroup analysis to examine the effect modifications of the association between cancer history and CVD events based on sex (men, women) and age (≥50 years, <50 years). p values were two-sided and evaluated at a <0.05 level of significance. All statistical analyses were performed using the Stata software (version 17; StataCorp LLC, College Station, TX, USA).

Results

Basic Characteristics

Of the total study population, 3,449,448 individuals had no history of cancer, and 82,235 individuals had a history of cancer (Table 1). The median age was 44 years (interquartile range, 37–52 years), and 2,048,422 patients were men (58.0%). Individuals with a history of cancer were older, more likely to be female, more likely to have hypertension, diabetes mellitus, and dyslipidemia, and fewer were current smokers.

Table 1. Baseline characteristics

	Total	Cancer history (−)	Cancer history (+)	p value	
n = 3,531,683	n = 3,449,448	n = 82,235	
Age, years	44 (37–52)	44 (37–52)	54 (46–61)	<0.001	
Men, n (%)	2,048,422 (58.0)	2,013,566 (58.4)	34,856 (42.4)	<0.001	
Body mass index, kg/m2	22.4 (20.2–24.9)	22.4 (20.2–24.9)	22.1 (20–24.6)	<0.001	
Overweight/obesity, n (%)	865,678 (24.5)	846,986 (24.6)	18,692 (22.7)	<0.001	
Hypertension, n (%)	643,317 (18.2)	620,279 (18.0)	23,038 (28.0)	<0.001	
Diabetes mellitus, n (%)	115,426 (3.3)	111,351 (3.2)	4,075 (5.0)	<0.001	
Dyslipidemia, n (%)	1,395,309 (39.5)	1,358,250 (39.4)	37,059 (45.1)	<0.001	
Cigarette smoking, n (%)	896,976 (25.4)	885,718 (25.7)	11,258 (13.7)	<0.001	
Alcohol consumption, n (%)	797,003 (22.6)	778,847 (22.6)	18,156 (22.1)	<0.001	
Physical inactivity, n (%)	1,849,630 (52.4)	1,806,622 (52.4)	43,008 (52.3)	0.67	
Systolic blood pressure, mm Hg	118 (107–128)	118 (107–128)	120 (108–131)	<0.001	
Diastolic blood pressure, mm Hg	73 (65–81)	72 (65–81)	74 (66–82)	<0.001	
Glucose, mg/dL	91 (86–98)	91 (85–98)	94 (87–101)	<0.001	
Low-density lipoprotein cholesterol, mg/dL	118 (98–140)	118 (98–140)	120 (100–142)	<0.001	
High-density lipoprotein cholesterol, mg/dL	62 (52–74)	62 (52–74)	66 (54–78)	<0.001	
Triglycerides, mg/dL	81 (56–122)	81 (56–121)	83 (59–122)	<0.001	
Values are shown as n (%) or median (interquartile range). p values were calculated using a χ2 test for categorical variables and Mann-Whitney U test for continuous variables.

Cancer History and CVD Events

The mean follow-up period was 1,179 ± 927 days. During the follow-up, 144,162 composite CVD endpoints, 7,300 MI, 63,195 AP, 31,218 strokes, 67,073 HF, and 16,381 AF events were recorded (since we counted individual CVD events separately, the sum of these exceeded the number of composite CVD endpoints). Compared to individuals without a history of cancer, the cumulative incidence for each CVD event was higher in individuals with a history of cancer (log-rank test, p < 0.001) (online suppl. Fig. 2). Individuals with a history of cancer had a higher risk of composite CVD events (HR 1.26, 95% confidence interval [95% CI] 1.22–1.29), AP (HR 1.15, 95% CI 1.10–1.20), stroke (HR 1.11, 95% CI 1.05–1.18), HF (HR 1.39, 95% CI 1.34–1.44), and AF (HR 1.22, 95% CI 1.13–1.32) than individuals without a history of cancer (Fig. 1). In the multivariable model (model 3), the HR of cancer history for MI was 1.11 (0.98–1.27). Furthermore, compared to individuals without a history of cancer, the HR of composite CVD events was highest in individuals with a history of cancer who received chemotherapy, followed by individuals with a history of cancer who did not receive chemotherapy (Fig. 2).

Fig. 1. Association between cancer history and the risk for CVD. We performed the Cox proportional hazard regression model to disclose the association between cancer history and incidents of CVD. Model 1 included only the presence of cancer history. Model 2 included age, sex, and the presence of cancer history. Model 3 included age, sex, body mass index, hypertension, diabetes mellitus, dyslipidemia, cigarette smoking, alcohol consumption, physical inactivity, and the presence of cancer history. The incidence rate was per 10,000 person-years. Hazard ratios (95% confidence interval) are presented.

Fig. 2. Association of cancer history and chemotherapy with the risk for composite event. We classified study participants into three groups: individuals without cancer history, individuals with cancer history who did not receive active chemotherapy, or individuals with a cancer history who received active chemotherapy within 3 months before the initial health checkup. We performed the Cox proportional hazard regression model using these three groupings. Model 1 included only the three-category classification. Model 2 included age, sex, and the three-category classification. Model 3 included age, sex, body mass index, hypertension, diabetes mellitus, dyslipidemia, cigarette smoking, alcohol consumption, physical inactivity, and the three-category classification. The incidence rate was per 10,000 person-years. Hazard ratios (95% confidence interval) are presented.

After excluding individuals with multiple cancers, the five cancer sites with the highest number of patients among men were as follows: colorectal cancer (n = 6,918), stomach cancer (n = 4,937), prostate cancer (n = 3,970), lung cancer (n = 2,240), and renal, pelvic, and ureteral cancer (n = 2,046). The five cancer sites with the highest number of patients among women were as follows: breast cancer (n = 18,923), thyroid cancer (n = 4,109), colorectal cancer (n = 3,654), cervical cancer (n = 3,371), and uterine cancer (n = 2,548) (online suppl. Fig. 3). Compared with individuals without a history of cancer, individuals with a history of lung cancer had the highest risk of composite CVD events among men. The HRs of breast cancer, thyroid cancer, colorectal cancer, cervical cancer, and uterine cancer for composite CVD events were 1.18 (1.11–1.26), 1.25 (1.10–1.43), 1.11 (0.96–1.27), 1.29 (1.10–1.51), and 1.20 (1.01–1.41) when comparing with individuals without a history of cancer among women.

Conventional Risk Factors for CVD Stratified by the Presence of Cancer History

Overweight/obesity, hypertension, diabetes, and dyslipidemia were significantly associated with a higher risk of composite CVD events in patients with and without a history of cancer. p values for cancer history-associated interactions were significant for overweight/obesity, hypertension, and dyslipidemia in the composite CVD events (online suppl. Table 1). PAF for composite CVD events associated with overweight/obesity, hypertension, diabetes, and dyslipidemia was lower in individuals with a history of cancer. As a result, in the multivariate analysis, those with a history of cancer had lower overall PAF (i.e., unadjusted). Further, overall PAF, which involved weighting for each risk factor (i.e., adjusted), was lower in those with a history of cancer (Fig. 3; online suppl. Table 2).

Fig. 3. Total population attributable fractions for cardiovascular disease with conventional risk factors. We calculated the total amount of PAFs of overweight/obesity, hypertension, diabetes mellitus, dyslipidemia, cigarette smoking, alcohol consumption, and physical inactivity for CVD: (a) composite event, (b) MI, (c) AP, (d) stroke, (e) HF, and (f) AF. Multivariable Cox proportional hazard regression model including age, sex, overweight/obesity, hypertension, diabetes mellitus, dyslipidemia, cigarette smoking, alcohol consumption, and physical inactivity was performed among those with and without cancer history. Using hazard ratios of each risk factor, we calculated PAFs associated with overweight/obesity, hypertension, diabetes mellitus, dyslipidemia, cigarette smoking, alcohol consumption, and physical inactivity for CVD. Finally, PAFs for each factor were summed. The sums of the PAFs for each factor are presented as unadjusted values. The overall PAFs accounting for the weighted based on the communality of each risk factor are presented as adjusted values. Using a principal components analysis of the tetrachoric correlation coefficient, the communality was calculated as the sum of the square of the loadings on the first two principal components because the first two principal components had eigenvalues ≥1. Although the third principal component had an eigenvalue ≥1, it seemed to be representative of only one risk factor (physical inactivity). Therefore, we excluded the third principal component from the calculation of communality.

Sensitivity Analyses

First, we imputed missing data on cigarette smoking, alcohol consumption, and physical inactivity by using multiple imputations by chained equations and included 4,332,977 individuals in this model. Individuals with a history of cancer had a greater risk of composite CVD events, AP stroke, HF, and AF, than those without a history of cancer (online suppl. Fig. 4). Second, our main findings were unchanged in the analyses using the Fine-Gray proportional subdistribution hazards model to consider the effect of death as a competing risk (online suppl. Fig. 5). Third, compared to individuals without a history of cancer, individuals with a history of cancer had a higher risk for each CVD event, even if we accounted for an induction period of 1 year (online suppl. Fig. 6). Fourth, the relationship between cancer history and the risk of composite CVD events was consistent irrespective of age and sex (online suppl. Fig. 7).

Discussion

Our analysis of a nationwide epidemiological dataset, including 3,531,683 individuals with and without a history of cancer, demonstrated that individuals with a history of cancer had a greater risk of developing a variety of CVD events. The subsequent risk of developing CVD is further increased in patients with cancer requiring active chemotherapy. Conventional risk factors are associated with a higher risk of CVD events in individuals with and without cancer. However, conventional risk factors contributed more to the development of CVD in individuals without cancer than in those with cancer.

Clinical outcomes, including the survival of patients diagnosed with cancer, have improved through developments in early detection, novel treatments (e.g., molecular targeted therapy), and supportive management. Accordingly, the number of patients with cancer is increasing in developed countries, including Japan. Currently, there are 17 million cancer survivors in the USA, and by 2030, this number is anticipated to increase to more than 22 million [2]. In Europe, it is estimated that there are over 12 million cancer survivors [13]. In this context, various CVD events could develop in the chronic phase of cancer survivors with increasing of CVD and CVD risk burden, resulting in the clinical recognition of CVD as an essential clinical issue [14]. A recent study examining 12,414 adults (mean age 54 years, 45% female) registered in the Atherosclerosis Risk in Communities (ARIC) cohort examined the relationship of cancer history with a risk of developing CVD and found that cancer survivors were more likely than non-survivors to develop CVD during a follow-up (HR: 1.37, 95% CI: 1.26–1.50) [1]. Similarly, cancer survivors had greater cardiovascular mortality than those without a history of cancer in a population-based, retrospective cohort analysis of 224,016 people (HR: 1.33, 95% CI: 1.29–1.37) [15]. It is consistent with earlier epidemiological research that showed cancer patients had an increased risk of CVD [1–3]. This clinical and epidemiological background would make it more important to stratify CVD risk among cancer survivors.

Our findings were distinguishable from those of previous studies by the following points and have clinical implications. Individuals with a history of cancer have a higher risk of a variety of CVD events, including coronary artery disease, stroke, HF, and AF; therefore, we need multifaceted CVD assessment and management for each CVD event. In addition, Kaplan-Meier curves showed that CVD events continued to occur, and the difference in the incidence of CVD events between those with and without cancer widened with time without attenuation, suggesting the importance of continuous careful observation in cancer survivors. As expected, cancer patients who received active chemotherapy had a higher CVD risk than those who did not receive active chemotherapy. Furthermore, the risk of CVD events could differ between individual cancer sites. For example, individuals with lung cancer have a relatively higher risk of composite CVD events than those with other cancers. Risk assessment based on individual conditions, such as cancer and treatment status, is undoubtedly necessary, and more detailed evidence needs to be accumulated in this regard.

As we previously reported [4, 5], conventional CVD risk factors may be associated with an increased risk of developing CVD even in cancer survivors (e.g., breast cancer, colorectal cancer, and stomach cancer). However, the association between conventional risk factors and incident CVD is attenuated in individuals with a history of cancer. For example, the hazard ratios of overweight/obesity, hypertension, and dyslipidemia for composite CVD events were lower in individuals with a history of cancer than in those without a history of cancer. p values for the interaction between the presence of cancer history and these risk factors were statistically significant, suggesting that the relationship between conventional risk factors and incident CVD was modified by the presence of cancer. Furthermore, the total PAF (both unadjusted and adjusted) associated with these conventional CVD risk factors for composite CVD events was greater in individuals without a history of cancer than in those with a history of cancer. We acknowledge that the significance of summing the PAFs for each factor is controversial and should be further debated, but it is intriguing to note that the PAFs for conventional risk factors (particularly overweight/obesity, hypertension, and diabetes mellitus) were generally lower in individuals with a history of cancer. These results may indicate that the potential contribution of conventional risk factors to the development of CVD is attenuated in individuals with a history of cancer compared to individuals without a history of cancer. Given that individuals with a history of cancer had a higher risk of subsequent CVD events compared to individuals without a history of cancer even after adjustment of conventional risk factors, this reduction could also be attributed to cardiovascular events related to cancer itself or cancer treatment, thus reaffirming the importance of onco-cardiology. At the same time, the association between conventional risk factors and incident CVD was attenuated in individuals with a history of cancer; however, a substantial proportion of CVD events were still attributable to conventional risk factors even in individuals with a history of cancer. The management of these risk factors might be essential not only in individuals without cancer but also in those with cancer.

We recognize that the present study has inherent limitations that may have affected our results. Although the current study used multivariable analyses, residual confounders are an inherent risk involved in this study. The CVD incidence in the JMDC Claims Database was comparable to that in other Japanese epidemiological datasets [16, 17]. Further, the specificity of recorded diagnoses (such as cancer and CVD) in Japanese administrative claims databases has been noted to be high [18, 19]. However, our findings must be validated using other epidemiological datasets. The data extracted for this study do not include the information on cancer severity (e.g., stage of cancer) and cardiovascular procedures. Additionally, the cumulative incidence for each CVD event was higher in individuals with a history of cancer compared to individuals without a history of cancer in this study. The potential presence of detection bias should be considered because individuals with a history of cancer are expected to visit the health care provider more frequently. Although the primary purpose of this study was to examine the association between a history of cancer at the initial health checkup and individual CVD events, the new development of cancer among individuals without a history of cancer could influence our results. We conducted this study using a Japanese administrative claims database. Therefore, our results may have limited generalizability to other populations. It was not possible to obtain sufficient information on the electrocardiogram in this study. Some chemotherapies may cause a significant increase in the risk of developing ventricular arrhythmia [20].

In conclusion, our analysis of a nationwide epidemiological database demonstrated that individuals with a history of cancer have a greater risk of developing a variety of CVD events. Patients with cancer who require active chemotherapy are at a higher risk of developing CVD. Conventional CVD risk factors are associated with a higher risk of a subsequent CVD event, even in individuals with a history of cancer. However, the relationship between conventional risk factors and the risk of developing CVD could be attenuated in individuals with a history of cancer. The importance of onco-cardiology is underscored by the possibility that this decrease was also caused by CVD events associated with cancer or cancer treatment.

Statement of Ethics

The Ethics Committee of the University of Tokyo approved the present study (approval number: 2018-10862), which was performed in accordance with the Declaration of Helsinki.

This study protocol was reviewed and approved by the Ethics Committee of the University of Tokyo, approval number [2018-10862]. Written informed consent from participants was not required in accordance with local/national guidelines. Because this retrospective study using the JMDC Claims Database involved analysis of de-identified data, individuals did not need to provide informed consent.

Conflict of Interest Statement

Research funding and scholarship funds (Hidehiro Kaneko and Katsuhito Fujiu) were received from Medtronic Japan Co., LTD, Abbott Medical Japan Co., LTD, Boston Scientific Japan Co., LTD, and Fukuda Denshi, Central Tokyo Co., Ltd. The authors have no conflicts of interest to declare.

Funding Sources

This work was supported by grants from the Ministry of Health, Labour and Welfare, Japan (21AA2007), and the Ministry of Education, Culture, Sports, Science and Technology, Japan (20H03907, 21H03159, 21K08123, and 22K21133). The funding sources played no role in the current study.

Author Contributions

Conception and design: Hidehiro Kaneko, Yuta Suzuki, Akira Okada, Koichi. Node, and Issei Komuro. Analysis of data: Yuta Suzuki, Akira Okada, Satoshi Matsuoka, Kosuke Kashiwabara, Katsuhito Fujiu, Nobuaki Michihata, Taisuke Jo, and Hideo Yasunaga. Interpretation of data: Hidehiro Kaneko, Akira Okada, Katsuhito Fujiu, Hiroyuki Morita, Koichi Node, Hideo Yasunaga, and Issei Komuro. Drafting of the manuscript: Hidehiro Kaneko, Yuta Suzuki, Akira Okada, Norifumi Takeda, and Hiroyuki Morita. Critical revision for important intellectual content: Norifumi Takeda, Hiroyuki Morita, Hideo Yasunaga, and Issei Komuro. Final approval of the submitted manuscript: all authors.

Data Availability Statement

The data that support the findings of this study are not publicly available due to privacy reasons but are available for purchase from JMDC Inc. (Tokyo, Japan, https://www.jmdc.co.jp/en/).

Supplementary Material

Supplementary Material
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