# Effects of confounding and effect-modifying lifestyle, environmental and medical factors on risk of radiation-associated cardiovascular disease

Mark P Little, Marjan Boerma, Marie-Odile Bernier, Tamara V Azizova, Lydia B Zablotska, Andrew J Einstein, Nobuyuki Hamada

<figure><img src="image_1.png" /></figure>

## To cite this version:

Mark P Little, Marjan Boerma, Marie-Odile Bernier, Tamara V Azizova, Lydia B Zablotska, et al. Effects of confounding and effect-modifying lifestyle, environmental and medical factors on risk of radiation-associated cardiovascular disease. BMC Public Health, 2024, 24, pp.1601. 10.1186/s12889-024-18701-9. irsn-04685482

HAL Id: irsn-04685482

https://asnr.hal.science/irsn-04685482v1

Submitted on 3 Sep 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
RESEARCH

Open Access

<figure><img src="image_3.png" /></figure>

Check for
updates

# Effects of confounding and effect-modifying lifestyle, environmental and medical factors on risk of radiation-associated cardiovascular disease

Mark P. Little¹,²*† ID, Marjan Boerma³† ID, Marie-Odile Bernier⁴† ID, Tamara V. Azizova⁵ ID, Lydia B. Zablotska⁶ ID, Andrew J. Einstein⁷† ID and Nobuyuki Hamada⁸† ID

**Abstract**

**Background** Cardiovascular disease (CVD) is the leading cause of death worldwide. It has been known for some considerable time that radiation is associated with excess risk of CVD. A recent systematic review of radiation and CVD highlighted substantial inter-study heterogeneity in effect, possibly a result of confounding or modifications of radiation effect by non-radiation factors, in particular by the major lifestyle/environmental/medical risk factors and latent period.

**Methods** We assessed effects of confounding by lifestyle/environmental/medical risk factors on radiation-associated CVD and investigated evidence for modifying effects of these variables on CVD radiation dose-response, using data assembled for a recent systematic review.

**Results** There are 43 epidemiologic studies which are informative on effects of adjustment for confounding or risk modifying factors on radiation-associated CVD. Of these 22 were studies of groups exposed to substantial doses of medical radiation for therapy or diagnosis. The remaining 21 studies were of groups exposed at much lower levels of dose and/or dose rate. Only four studies suggest substantial effects of adjustment for lifestyle/environmental/ medical risk factors on radiation risk of CVD; however, there were also substantial uncertainties in the estimates in all of these studies. There are fewer suggestions of effects that modify the radiation dose response; only two studies, both at lower levels of dose, report the most serious level of modifying effect.

**Conclusions** There are still large uncertainties about confounding factors or lifestyle/environmental/medical variables that may influence radiation-associated CVD, although indications are that there are not many studies in which there are substantial confounding effects of these risk factors.

**Keywords** Cardiovascular disease, Ionising radiation, Heart disease, Stroke, Coronary heart disease, Confounding

<footnote>†Mark P. Little, Marjan Boerma and Marie-Odile Bernier to be regarded as joint first authors.</footnote>

<footnote>‡Andrew J. Einstein and Nobuyuki Hamada to be regarded as joint last authors.</footnote>

<footnote>*Correspondence:</footnote>

<footnote>Mark P. Little
mark.little@nih.gov</footnote>

<footnote>Full list of author information is available at the end of the article</footnote>
## Introduction

Cardiovascular disease (CVD) is the leading cause of death worldwide [1–3]. The main independent risk factors for CVD are cigarette smoking, hypertension, diabetes, obesity and elevated total cholesterol or elevated low density lipoprotein (LDL) cholesterol [4–6]. It has been known for some considerable time that high dose radiotherapy is also associated with excess risk of CVD [7, 8]. More recently, it has become clear that there are also radiation-associated excess risks in the Life Span Study (LSS) of the Japanese atomic-bomb survivors [9, 10], and in a number of groups exposed at still lower levels of radiation dose and at lower dose rates [11]. A recent systematic review and meta-analysis of epidemiological studies highlighted evidence of association between radiation exposure and CVD at high dose, and to a lesser extent at low dose, with some indications of differences in risk between acute and chronic exposures [12]. There was inter-study heterogeneity, possibly a result of confounding or modifications of radiation effect by other factors, which complicates a causal interpretation of these findings [12]. Although a number of studies assessed in the previous review adjusted for many of the major lifestyle risk factors, relatively few studies undertook investigation of the modifying effect of these risk factors on the radiation associated CVD.

In this paper we assess effects of confounding by lifestyle, environmental, and medical risk factors, and also investigate evidence for modifying effects of these variables on radiation dose response.

## Methods

The data used are those assembled in a recent systematic review [12]. In brief, the review was conducted, and reported according to PRISMA and registered in PROSPERO (https://www.crd.york.ac.uk/prospero/) (reg. no. 202036). PubMed/MEDLINE, Embase, Scopus, and Web of Science: Core Collection were used to systematically search the literature, with no limits applied (date, language), on 6th October 2022. We excluded animal studies, and any study without an abstract. The database search yielded a total of 15,098 articles.

## Outcomes

CVD was defined as those causes of mortality and incidence with International Classification of Diseases 10th revision (ICD10) codes I00-I99 (or equivalently the ICD 8th revision (ICD8) codes 390–458 or ICD 9th revision (ICD9) codes 390–459).

## Main exposure

Only those studies with individual organ dosimetry that enable estimation of excess relative risk per unit absorbed dose in Gy (ERR/Gy) in relation to heart or brain dose or other closely related tissue doses were used.

## Potentially confounding and effect modifying variables considered

We only used those studies in which there was adjustment for any factor other than the standard demographic risk factors (age, sex, year of birth etc.), and in which ERR/Gy were reported both with and without adjustment, or alternatively in which ERR/Gy were reported of the modifying effect on radiation response of these variables. In other words, to assess potential confounding a relative risk model had been fitted of the form $RR = \exp[\beta V](1 + \alpha D)$ with adjustment for a potentially modifying variable V and also without adjustment for that potentially modifying variable V. A modifying variable in a particular study was any variable V for which had been assessed the interactions with radiation dose, in other words in which a model had been fitted of the form $RR = 1 + \alpha D \exp[\beta V]$. In some cases the only reported effect was a p-value (e.g. of significance of modification). All these studies are listed in Tables 1 and 2.

## Methods to evaluate the effects of confounding and effect modifying variables

The methods employed to assess the effects of potential confounding variable are comparison of the fitted ERR unadjusted for the potential confounding variable, ERR unadj, and the ERR $ERR_{adj[V]}$ adjusted for the confounding variable V. We categorized those estimates in which adjustment for potential confounders resulted in changes of the following magnitudes:

a) more than 50% difference, i.e., with ratio of estimates outside the interval [0.667, 1.5] – labelled *

b) more than 100% difference, i.e., with ratio of estimates outside the interval [0.5, 2.0] – labelled **

c) estimates with different signs, i.e. one positive, the other negative, labelled ***

Likewise any variable whose interaction with radiation dose resulted in the following degree of change in the ERR was labelled as follows:

a) more than 50% difference, i.e., with ratio of estimates (with/without modification) outside the interval
<table><caption>**Table 1** Unadjusted or adjusted estimated excess relative risk of cardiovascular diseases in various therapeutically and diagnostically treated groups, exposed at moderate or high radiation doses and high dose rates. All analyses adjust for age</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td>Therapeutically treated groups</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Childhood Cancer</td><td>Mulrooney et al. [13]</td><td>Heart</td><td>Smoking, BMI, diabetes, hypertension, dyslipidemia, racial/ethnic group, education, chemotherapy</td><td>Heart failure CTCAE v4.03 ≥ 3</td><td>Incidence</td><td>NA</td><td>0.022 (-0.093 to 0.138)<sup>a</sup></td><td>Presented RR of various cardiac endpoints are adjusted for race, BMI, smoking, exercise intensity. Unadjusted analyses not presented. Additional analysis in which cardiotoxic exposures are adjusted for did not appreciably change RR for heart failure, coronary artery disease, valvular disease, pericardial disease, arrhythmia in relation to initial cancer endpoint: change in RR always &lt; 10%</td></tr><tr><td>Survivor Study</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>Coronary artery disease CTCAE v4.03 ≥ 3</td><td></td><td>NA</td><td>0.066 (-0.020 to 0.152)<sup>a</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>Valvular disease CTCAE v4.03 ≥ 3</td><td></td><td>NA</td><td>0.064 (0.178 to 0.306)<sup>a</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>Pericardial disease CTCAE v4.03 ≥ 3</td><td></td><td>NA</td><td>-0.005 (-0.082 to 0.072)<sup>a</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>Arrhythmia CTCAE v4.03 ≥ 3</td><td></td><td>NA</td><td>0.005 (-0.049 to 0.058)<sup>a</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>Cardiac disease</td><td>Mortality</td><td>NA</td><td>0.6 (0.2 to 2.5)</td><td>Presented ERR is adjusted for alkylating agents, vinca alkaloids, anthra-cyclines (including dose), antimetabolites. No unadjusted ERR are presented. Radiation dose did not significantly interact with exposure to anthracyclines (p &gt; 0.3) or any other type of drug</td></tr><tr><td>French-UK childhood cancer study</td><td>Tukenova et al. [14]</td><td>Heart</td><td>Epipodophylotoxins, anthracyclines, alkylating agents, vinca alkaloids, antimetabolites, antibiotics</td><td>Cardiac disease (ICD9 391, 393–397, 410–413, 420, 423–424, 426–428; ICD10 I05–I09; I20–I25, I30–I32, I44–I50); without anthracyclines</td><td>Incidence</td><td>0.49 (0.26 to 1.3)</td><td>NA</td><td>ERR are not adjusted for any variable. RR in highest dose group (&gt; 30 Gy) are “similar” when the analysis is controlled for smoking status and BMI<sup>b</sup></td></tr><tr><td></td><td></td><td></td><td></td><td>Cardiac disease: with anthracyclines</td><td></td><td>0.07 (0.03 to 0.13)</td><td>NA</td><td></td></tr><tr><td>French (Institut Gustave Roussy) childhood cancer cardiac study</td><td>Haddy et al. [15]</td><td>Heart</td><td>Smoking, BMI, anthra-cyclines, alkylating agents, vinca alkaloids, epipodophylotoxins, antimetabolites</td><td>Cardiac disease (ICD9 391, 393–397, 410–413, 420, 423–424, 426–428; ICD10 I05–I09; I20–I25, I30–I32, I44–I50); without anthracyclines</td><td>Incidence</td><td>0.49 (0.26 to 1.3)</td><td>NA</td><td>ERR are not adjusted for any variable. RR in highest dose group (&gt; 30 Gy) are “similar” when the analysis is controlled for smoking status and BMI<sup>b</sup></td></tr></tbody></table>
<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td>French Childhood Cancer Study case-control study</td><td>Mansouri et al. [16]</td><td>Heart</td><td>Smoking, BMI, physical activity, anthracyclines, alkylating agents, vinca alkaloids</td><td>Heart failure (CTCAE v4.03 grade ≥ 1) with concomitant anthracyclines</td><td>Incidence</td><td>NA</td><td>0.09 (0.02 to 0.22)</td><td>ERR were adjusted for splenectomy, type of first malignancy, vinca alkaloids, alkylating agents and other chemotherapy. A modifying effect of anthracycline suggested (but no test of significance). Apart from effect of anthracyclines "no other factors significantly modified the effects of radiation. However, HF risk increased with each category of age, with ERR/ Gy values for the MHD of 0.06, 0.33, 0.38 and 0.48 in those aged &lt;15, 15–25, 25–35, and ≥35 years, respectively."</td></tr><tr><td>Netherlands Hodgkin lymphoma coronary heart disease case-control study</td><td>van Nimwegen et al. [17]</td><td>Heart EQD2</td><td>Smoking, BMI, diabetes, hypertension, hypercholesterolemia, physical activity, alkylating agents, procarbazine, vincristine, anthracyclines, splenectomy</td><td>Heart failure (CTCAE v4.03 grade ≥ 1) without concomitant anthracyclines</td><td>Incidence</td><td>NA</td><td>0.44 (0.18 to 1.12)</td><td>ERR is adjusted for chemotherapy. There is no unadjusted analysis. There is "no evidence for statistically significant modification of the effect of MHD on CHD risk by chemotherapy, sex, cardiovascular disease risk factors, and recent smoking at HL diagnosis."</td></tr><tr><td>Netherlands Hodgkin lymphoma heart failure case-control study</td><td>van Nimwegen et al. [18]</td><td>Heart EQD2</td><td>Smoking, BMI, diabetes, hypertension, hypercholesterolemia, physical activity, anthracyclines, splenectomy</td><td>Heart failure (CTCAE v3.0, v4.0 grades ≥ 2)</td><td>Incidence</td><td>0.038 (-0.001 to 0.146)<sup>b</sup></td><td>NA</td><td>Although many adjusting variables are available, only RR for unadjusted analysis are presented. RR in high dose group (≥26 Gy) "did not differ significantly according to use of anthracycline chemotherapy (p = 0.45 for MHD, 0.09 for MLVD) or with splenectomy (p = 0.71 for MHD, 0.62 for MLVD)." No additional significant interactions by sex (p = 0.72), age at HL diagnosis (p = 0.43), or time since HL diagnosis (p = 0.92)</td></tr></tbody></table>
<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td>Nordic breast cancer case-control study</td><td>Darby et al. [19]</td><td>Heart</td><td>Smoking, BMI, diabetes, hypertension, analgesic medication, thyroid medication, surgery, HRT, chemotherapy, ovarian ablation, history of IHD or COPD</td><td>IHD (ICD10 I20-I25)</td><td>Incidence</td><td>NA</td><td>0.074 (0.029 to 0.145)</td><td>ERR was estimated adjusting for cardiac risk factor (history of IHD or other circulatory disease, smoking, BMI, history of COPD, diabetes, analgesic medication). The risk was very "similar for women with and those with-out cardiac risk factors" (ERR/Gy = 0.074 (95% CI 0.018, 0.178) for those with no cardiac risk factors vs 0.074 (95% CI 0.011, 0.195) for those with at least one cardiac risk factor, p = 0.99 heterogeneous). Unadjusted analysis not presented</td></tr><tr><td>Netherlands-Groningen breast cancer study</td><td>Roos et al. [20]</td><td>Heart</td><td>Smoking, BMI, diabetes, hypertension, hypercholesterolemia, COPD, pulmonary embolism, chemotherapy, endocrine therapy, history of IHD, CAC</td><td>Acute coronary event (myocardial infarction (ICD10 I21-I24), coronary revascularization, death from ischemic heart disease (ICD10 I20-I25))</td><td>Incidence</td><td>0.17 (0.00 to 0.37)</td><td>0.18 (0.00 to 0.39)</td><td>ERR adjusted for history of IHD, diabetes, BMI, hypercholesterolemia, hypertension, CAC. A number of simpler models also presented, e.g., as shown here adjusted for history of IHD, diabetes, CAC</td></tr><tr><td>Netherlands-Groningen breast cancer study</td><td>van den Bogaard et al. [21]</td><td>Heart</td><td>Smoking, BMI, diabetes, hypertension, hypercholesterolemia, chemotherapy, hormonal therapy, trastuzumab, other heart disease</td><td>Myocardial infarction (ICD10 I21-24), coronary revascularisation or death from IHD (ICD10 I20-I25) among patients with atherosclerotic plaque in LAD</td><td>Incidence</td><td>0.116 (-0.079 to 0.353)</td><td>0.117 (-0.098 to 0.383)</td><td>ERR adjusted for history of IHD, hypertension, hypercholesterolemia, diabetes. Unadjusted ERR are also presented</td></tr><tr><td></td><td></td><td></td><td></td><td>Myocardial infarction (ICD10 I21-24), coronary revascularisation or death from IHD (ICD10 I20-I25) among patients without atherosclerotic plaque in LAD</td><td></td><td></td><td>0.153 (-0.017 to 0.353)</td><td>0.161 (-0.034 to 0.395)</td></tr></tbody></table>
<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td>Netherlands-NKI- Rotterdam breast cancer case-control study</td><td>Jacobse et al. [22]</td><td>Heart</td><td>Smoking, BMI, hypertension, diabetes, surgery, chemotherapy, endocrine therapy, prior CVD</td><td>Myocardial infarction</td><td>Incidence</td><td>0.064 (0.013 to 0.160)</td><td>NA</td><td>Although many adjusting variables are available, only ERR for unadjusted analysis is presented. The “dose response relationship for women with and without cardiovascular risk factors at BC diagnosis was similar (p > 0.5)”. There are modifications in risk by age at exposure (ERR/Gy age < 45 = 0.242 (95% CI 0.044, 0.823), age 45–49 = 0.111 (95% CI 0.012, 0.401), age 50–70 = 0.025, 95% CI -0.014, 0.119, heterogeneity p = 0.07), and also increased with longer follow-up (ERR/Gy < 10 y = 0.001 (95% CI -0.029, 0.095), 10–14 y = 0.072 (95% CI -0.008, 0.323), ≥ 15 y = 0.151, 95% CI 0.029, 0.493, heterogeneity p = 0.25)</td></tr><tr><td>Netherlands-NKI- Rotterdam breast cancer case-control study</td><td>Boekel et al. [23]</td><td>Heart</td><td>Smoking, BMI, diabetes, hypertension, hypercholesterolemia, menopausal status, chemotherapy, endocrine therapy, surgery</td><td>Heart failure (CTCAE v3.0, v4.0 grade ≥ 2) – no treatment with anthracyclines</td><td>Incidence</td><td>0.00 (-0.03 to 0.08)</td><td>NA</td><td>Although many adjusting variables are available, only ERR for unadjusted analysis is presented. A modifying effect of anthracycline is suggested (but there is no test of significance)</td></tr><tr><td></td><td></td><td></td><td></td><td>Heart failure (CTCAE v3.0, v4.0 grade ≥ 2) – treatment with anthracyclines</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>Heart failure (CTCAE v3.0, v4.0 grade ≥ 2)</td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><caption>Table 1 (continued)</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td>Case-control study nested within ESCaRa breast cancer cohort study</td><td>Baaken et al. [24]</td><td>Heart</td><td>BMI, chemotherapy, endocrine therapy, previous CVD</td><td>Myocardial infarction, angina pectoris, congestive heart failure, dysrhythmia, valvular heart disease, or mortality from cardiac infarction (ICD10 I21.1-123), chronic IHD (ICD10 I25.0-I25.9), acute IHD (ICD10 I21.0-I24.9), congestive heart failure (ICD10 I50.0-I50.9), angina pectoris (ICD10 I20.0-I20.9), cardiac arrest (ICD10 I46), dysrhythmia/conduction disorder (ICD10 I44.0-I49.9), vitium cords (ICD10 I34.0-I37.9)</td><td>Incidence</td><td>-0.01 (-0.06 to 0.05)</td><td>-0.01 (-0.06 to 0.05)</td><td>Analysis adjusted for chemotherapy, endocrine therapy and BMI. Unadjusted ERR also presented</td></tr><tr><td>Severance Hospital breast cancer study</td><td>Chung et al. [25]</td><td>Heart</td><td>Smoking, BMI, diabetes, hypertension, exercise, surgery, chemotherapy, endocrine treatment</td><td>Stable angina pectoris, unstable angina, myocardial infarction, IHD, heart failure, atrial fibrillation, coronary revascularisation, death from IHD</td><td>Incidence</td><td>0.22 (0.13 to 0.30)</td><td>0.23 (0.15 to 0.32)</td><td>Analysis adjusted for exercise status, BMI, hypertension, diabetes, previous heart disease, anthracycline, anti-HER2 treatment, aromatase inhibitors. Unadjusted analysis also presented</td></tr><tr><td>Severance Hospital breast cancer substudy</td><td>Kim et al. [26]</td><td>Heart</td><td>Smoking, BMI, diabetes, hypertension, exercise, anthracycline and other chemotherapy, anti-HER2 treatment, surgery, previous CVD</td><td>Acute coronary events (ST-elevation/non-ST-elevation myocardial infarction and unstable angina pectoris)</td><td>Incidence</td><td>0.03 (0.00 to 0.05)<sup>**</sup></td><td>0.22 (0.01 to 0.46)<sup>**</sup></td><td>Analysis adjusted for BMI, laterality, diabetes, smoking, anthracyclines, history of heart disease. Unadjusted analysis also presented</td></tr><tr><td>University of Michigan non-small cell lung cancer study</td><td>Dess et al. [27]</td><td>Heart EQD2</td><td>Smoking, diabetes, systolic blood pressure, cholesterol, previous CVD, KPS</td><td>Heart disease other than acute coronary events</td><td>Incidence</td><td>0.20 (0.11, 0.29)<sup>*</sup></td><td>0.13 (0.03 to 0.24)<sup>*</sup></td><td>Analysis adjusted for BMI, laterality, diabetes, smoking, type of surgery, anthracyclines, anti-HER2 treatment, CAC score. Unadjusted analysis also presented</td></tr></tbody></table>
<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td>University of Michigan non-small cell lung cancer study</td><td>Xue et al. [28]</td><td>Pericardium</td><td>Smoking, hypertension, COPD, chemotherapy, previous CVD, KPS</td><td>Pericardial effusion</td><td>Incidence</td><td>0.066 (0.028 to 0.105)</td><td>0.050 (0.009 to 0.093)</td><td>Analysis adjusted for sex, smoking, hypertension, COPD, chemotherapy, previous CVD, KPS. Unadjusted analysis also presented</td></tr><tr><td>Dana Farber/Brigham Women's Hospital non-small cell lung cancer study</td><td>Atkins et al. [29, 30]</td><td>Heart</td><td>Smoking, BMI, diabetes, hypertension, cholesterol, hyperlipidemia, previous CVD, chemotherapy, statins</td><td>Major adverse cardiac events (cardiac death, unstable angina, myocardial infarction, heart failure hospitalization or urgent visit, coronary revascularization)</td><td>Incidence/ mortality</td><td>0.02 (0.00 to 0.06)</td><td>0.03 (0.00 to 0.06)</td><td>Adjusted for hypertension, hyperlipidemia, diabetes, previous CVD (stroke, peripheral vascular disease, coronary artery disease, myocardial infarction, congestive heart failure), arrhythmia, valvulopathy, Framingham score, statins. Unadjusted analysis also presented</td></tr><tr><td>New Jersey non-small cell lung cancer study</td><td>Yegya-Raman et al. [31]</td><td>Heart</td><td>Smoking, blood pressure, diabetes, chemotherapy, pre-treatment CAD</td><td>First symptomatic cardiac event (myocardial infarction, unstable angina, significant arrhythmia, symptomatic pericardial effusion, pericarditis, congestive heart failure)</td><td>Incidence</td><td>0.058 (0.034 to 0.082)</td><td>0.065 (0.038 to 0.093)<sup>a</sup><br>0.059 (0.032 to 0.086)<sup>e</sup></td><td>Two different adjusted models, adjusted for (a) CAD or (b) WHO/ISH stratum, also unadjusted</td></tr><tr><td>Chenyang thymoma study</td><td>Liao et al. [32]</td><td>Heart</td><td>Smoking, BMI, diabetes, hypertension, hyperlipidemia, chemotherapy, myasthenia gravis, family history of CVD</td><td>CTCAE v4.0 grade ≥ 2 cardiovascular disease</td><td>Incidence</td><td>0.074 (0.012 to 0.136)<sup>f</sup></td><td>0.084 (0.026 to 0.143)<sup>a</sup></td><td>Adjusted for chemotherapy status, hypertension, hyperlipidemia, diabetes, BMI, family history of CVD. Unadjusted case and control numbers also given</td></tr><tr><td>Israeli tinea capitis prevalence study</td><td>Saderzki et al. [33]</td><td>Breast</td><td>Smoking, BMI, diabetes, hypertension, SES</td><td>IHD</td><td>Prevalence</td><td>NA</td><td>7 (1 to 14)<sup>h</sup></td><td>Adjusted for sex, smoking, SES, hypertension, diabetes. Unadjusted analysis not presented for dose response, although analysis of exposure to radiation (yes vs no) suggests that adjustment for these variables made difference of &lt;2% (all CVD RR = 1.21 unadjusted vs 1.19 adjusted)</td></tr><tr><td></td><td></td><td>Brain</td><td></td><td>CeVD</td><td></td><td>NA</td><td>0.20 (0.12 to 0.29)<sup>h</sup></td><td></td></tr><tr><td></td><td></td><td>Salivary</td><td></td><td>Carotid artery stenosis</td><td></td><td>NA</td><td>0.33 (0.04 to 0.71)<sup>h</sup></td><td></td></tr></tbody></table>
<table><caption>Table 1 (continued)</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td rowspan="2">Rochester thymus enlargement study</td><td rowspan="2">Adams et al. [34]</td><td rowspan="2">Heart</td><td rowspan="2">Smoking, dyslipidemia, diabetes, hypertension, family history of myocardial infarction</td><td>Coronary heart disease (ICD10 I21-I25, I46)</td><td rowspan="2">Incidence</td><td>0.08 (-0.01 to 0.20)***</td><td>-0.03 (-0.07 to 0.10)***</td><td rowspan="2">Adjusted for sex, diabetes, dyslipidemia, smoking, hypertension. Unadjusted analysis (adjusted for sex) also presented</td></tr><tr><td>Myocardial infarction (ICD10 I21-I24)</td><td>-0.05 (-0.13 to 0.08)</td><td>-0.06 (-0.16 to 0.06)</td></tr><tr><td rowspan="10">Diagnostically exposed groups</td><td rowspan="10">Canadian and Massachusetts tuberculosis fluoroscopy cohorts</td><td rowspan="10">Lung</td><td rowspan="10">Smoking, diabetes, alcohol consumption, antibiotic use, tuberculosis stage</td><td>CVD (ICD9 390-459)</td><td rowspan="10">Mortality</td><td>-0.024 (-0.042 to -0.005)<sup>i</sup></td><td>NA</td><td rowspan="10">Main analyses adjust for cohort, sex, smoking, tuberculosis status. Additional analysis for some endpoints adjusts for alcohol consumption, diabetes, antibiotic use in Massachusetts cohort</td></tr><tr><td>CVD (ICD9 390-459) &lt; 0.5 Gy</td><td>0.246 (0.036 to 0.469)</td><td>0.262 (0.042 to 0.476)<sup>i</sup></td></tr><tr><td>Ischemic heart disease (ICD9 410-414)</td><td>-0.037 (-0.060 to -0.013)<sup>i</sup></td><td>NA</td></tr><tr><td>Ischemic heart disease (ICD9 410-414) &lt; 0.5 Gy</td><td>0.268 (0.003 to 0.552)</td><td>0.286 (0.020 to 0.572)<sup>i</sup></td></tr><tr><td>Cerebrovascular disease (ICD9 430-438)</td><td>-0.014 (-0.067 to 0.044)<sup>i</sup></td><td>NA</td></tr><tr><td>Cerebrovascular disease (ICD9 430-438) &lt; 0.5 Gy</td><td>0.441 (-0.119 to 1.090)<sup>i</sup></td><td>0.435 (-0.125 to 1.083)<sup>i</sup></td></tr><tr><td>Hypertensive heart disease (ICD9 401-405)</td><td>-0.035 (-0.152 to 0.153)<sup>i</sup></td><td>NA</td></tr><tr><td>Hypertensive heart disease (ICD9 401-405) &lt; 0.5 Gy</td><td>1.121 (-0.351 to 3.228)<sup>i</sup></td><td>1.147 (-0.333 to 3.266)<sup>i</sup></td></tr><tr><td>Heart disease apart from hypertensive and IHD (ICD9 390-400, 406-410)</td><td>-0.010 (-0.064 to 0.043)<sup>i</sup></td><td>NA</td></tr></tbody></table>
<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td></td><td></td><td></td><td></td><td>Heart disease apart from hypertensive and IHD (ICD9 390-400, 406-410) &lt; 0.5 Gy</td><td></td><td>-0.226 (-0.679 to 0.307)<sup>1</sup></td><td>-0.240 (-0.691 to 0.291)<sup>1</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>CVD apart from heart and cerebrovascular (ICD9 439-459)</td><td></td><td>0.055 (-0.028 to 0.164)<sup>1</sup></td><td>NA</td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>CVD apart from heart and cerebrovascular (ICD9 439-459) &lt; 0.5 Gy</td><td></td><td>0.507 (-0.322 to 1.541)<sup>1</sup></td><td>0.511 (-0.320 to 1.547)<sup>1</sup></td><td></td></tr></tbody></table>

BC breast cancer, BMI body mass index, CAC coronary artery calcium, CAD coronary artery disease, CI confidence interval, COPD chronic obstructive pulmonary disease, CTCAE v Common Terminology Criteria for Adverse Events version, CVD cardiovascular disease, ERR excess relative risk, HER2 human epidermal growth factor receptor 2, HL Hodgkin lymphoma, HRT hormone replacement therapy, ICD International Classification of Diseases, IHD ischemic heart disease, KPS Karnovsky performance score, LAD left anterior descending artery, MHD mean heart dose, MLVD mean left ventricular dose, NA not available, RR relative risk, SES socioeconomic status, WHO/ISH World Health Organization/International Society of Hypertension

* ratio of adjusted to unadjusted estimates outside the interval [0.667, 1.5]

** ratio of adjusted to unadjusted estimates outside the interval [0.5, 2]

*** ratio of adjusted to unadjusted estimates negative

† ratio of estimate with interaction modifier to that without modifier outside the interval [0.667, 1.5],

‡ ratio of estimate with interaction modifier to that without modifier outside the interval [0.5, 2]

††† ratio of estimate with interaction modifier to that without modifier negative

a estimate derived by fitting a linear model by (inverse-variance) weighted least squares, applied to the aggregate data provided in Table 3 of Mulrooney et al. [36] and in Table 2 of Shrestha et al. [36]. For the data of Mulrooney et al. [13] (all endpoints except all cardiac disease) average cardiac doses of 0, 7.5, 25, and 45 Gy were assumed for the respective groups with the following specified ranges of cardiac doses: 0, 1–15, 15.1–34.99 Gy, ≥ 35 Gy. For the data of Shrestha et al. [36] average cardiac doses of 0, 5, 15, 25 and 35 Gy were assumed for the respective groups with the following specified ranges of cardiac doses: 0, 0.1–9.9, 10–19.9, 20–29.9 Gy, ≥ 30 Gy, and the central estimates of ERR/Gy given in Figure 5 of Shrestha et al. [36] were used to correct the central estimates of trend

b estimate derived by fitting a linear binomial odds model to aggregate numbers of cases and controls, and assuming mean heart doses of 0, 16, 23, 28, 33 Gy for the 0, 1–20, 21–25, 26–36 ≥ 3 Gy mean heart dose groups given in Table 2 of van Nimwegen et al. [18]; see Supplements S1 and S2 of Little et al. [12]

c using midpoint estimates for $[D_{min} + 3]/2$ and $[D_{max} + 3]/2$ Gy (using given minimum and maximum heart doses, $D_{min}$ and $D_{max}$) and ln[odds ratio] (and CI) for > 3 Gy vs < 3 Gy from Kim et al. [26]

d adjusted using CAD in study of Yegya-Raman et al. [31]

e adjusted using WHO/ISH in study of Yegya-Raman et al. [31]

f estimate derived by fitting a log-linear binomial odds model to aggregate numbers of cases and controls, and assuming mean heart doses of 5, 15, 25 Gy for the 0–10, 10–20 and 20–30 Gy mean heart dose groups given in Table 4 of Liao et al. [32]; see Supplements S1 and S2 of Little et al. [12]

g estimate derived by fitting a log-linear model by (inverse-variance) weighted least squares, applied to the multivariate adjusted ln(OR) and assuming mean heart doses of 5, 15, 25 Gy for the 0–10, 10–20 and 20–30 Gy mean heart dose groups given in Table 4 of Liao et al. [32]

h prevalence excess odds ratio per Gy

i based on 5-year lagged lung dose

j additional adjustment for alcohol consumption, diabetes, antibiotic use
<table><caption>**Table 2** Unadjusted or adjusted estimated excess relative risks of cardiovascular diseases in the Japanese atomic bomb survivors and in other groups with moderate- or low-dose radiation exposure, with mean dose generally < 0.5 Gy</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td rowspan="2">Japanese atomic bomb survivors</td><td>Shimizu et al. [10]</td><td rowspan="2">Colon</td><td rowspan="2">Smoking, obesity (BMI), diabetes, alcohol intake, education, type of household occupation, city</td><td rowspan="2">Heart disease</td><td rowspan="2">Mortality</td><td rowspan="2">0.122</td><td rowspan="2">0.123</td><td rowspan="2">Main analyses unadjusted for anything apart from sex, city. Additional analysis adjusting for smoking, alcohol intake, education, type of household occupation, obesity (BMI), diabetes. There were significant modifying effects on CeVD risk of attained age (p=0.04) and age at exposure (p=0.007) (with ERR decreasing with increases in each of these), but no such modifications for heart disease (p&gt;0.2). There are significant modifying effects of sex for heart disease (p=0.022) but not for any other endpoint (p&gt;0.5)</td></tr><tr><td>Little et al. [11]</td><td></td></tr><tr><td rowspan="2">Japanese atomic bomb survivors</td><td rowspan="2">Yamada et al. [9]</td><td rowspan="2">Stomach</td><td rowspan="2">Smoking, alcohol consumption, city</td><td>CeVD</td><td></td><td>0.081</td><td>0.072</td><td rowspan="2">All analyses adjusted for city, sex. Additional analyses adjust for smoking and drinking</td></tr><tr><td>Other CVD</td><td></td><td>0.024**</td><td>0.009**</td></tr><tr><td rowspan="2">Japanese atomic bomb survivors</td><td rowspan="2">Yamada et al. [9]</td><td rowspan="2">Stomach</td><td rowspan="2">Smoking, alcohol consumption, city</td><td>CVD (ICD9 390-459)</td><td></td><td>0.100</td><td>0.096</td><td rowspan="2">All analyses adjusted for city, sex. Additional analyses adjust for smoking and drinking</td></tr><tr><td>Hypertension, 1958-1998 (ICD9 401)</td><td></td><td>0.04 (-0.01 to 0.09)<sup>a</sup></td><td>0.05 (-0.01 to 0.10)<sup>a</sup></td></tr><tr><td rowspan="2">Japanese atomic bomb survivors</td><td rowspan="2">Yamada et al. [9]</td><td rowspan="2">Stomach</td><td rowspan="2">Smoking, alcohol consumption, city</td><td>Hypertensive heart disease, 1958-1998 (ICD9 402, 404)</td><td></td><td>0.01 (-0.08 to 0.10)<sup>a***</sup></td><td>-0.01 (-0.09 to 0.09)<sup>a***</sup></td><td rowspan="2">All analyses adjusted for city, sex. Additional analyses adjust for smoking and drinking</td></tr><tr><td>IHD, 1958-1998 (ICD9 410-414)</td><td></td><td>0.04 (-0.06 to 0.14)<sup>a</sup></td><td>0.05 (-0.05 to 0.16)<sup>a</sup></td></tr><tr><td rowspan="2">Japanese atomic bomb survivors</td><td rowspan="2">Yamada et al. [9]</td><td rowspan="2">Stomach</td><td rowspan="2">Smoking, alcohol consumption, city</td><td>Myocardial infarction, 1964-1998 (ICD9 410)</td><td></td><td>0.11 (-0.10 to 0.46)<sup>a</sup></td><td>0.12 (-0.16 to 0.60)<sup>a</sup></td><td rowspan="2">All analyses adjusted for city, sex. Additional analyses adjust for smoking and drinking</td></tr><tr><td>Occlusion, 1958-1998 (ICD9 433, 434)</td><td></td><td>0.05 (-0.12 to 0.27)<sup>a</sup></td><td>0.06 (-0.11 to 0.30)<sup>a</sup></td></tr><tr><td rowspan="2">Japanese atomic bomb survivors</td><td rowspan="2">Yamada et al. [9]</td><td rowspan="2">Stomach</td><td rowspan="2">Smoking, alcohol consumption, city</td><td>Aortic aneurysm, 1958-1998 (ICD9 441, 442)</td><td></td><td>0.05 (-0.12 to 0.44)<sup>a**</sup></td><td>0.02 (-0.22 to 0.41)<sup>a**</sup></td><td rowspan="2">All analyses adjusted for city, sex. Additional analyses adjust for smoking and drinking</td></tr><tr><td>Stroke, 1958-1998 (ICD9 430, 431, 433, 434, 436)</td><td></td><td>0.06 (-0.08 to 0.23)<sup>a</sup></td><td>0.07 (-0.08 to 0.24)<sup>a</sup></td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td>Japanese atomic bomb survivors 1958–2014</td><td>Takahashi et al. [37]</td><td>Skin</td><td>Smoking, BMI, diabetes, blood pressure, total + LDL and HDL cholesterol, triglycerides, dyslipidemia, high sensitivity CRP, white blood cell count, GFR, city</td><td>Peripheral artery disease</td><td>Prevalence</td><td>-0.11 (0.39, 0.30)*</td><td>-0.17 (-0.43 to 0.22)*</td><td>Analyses adjusted for sex, smoking, CRP, GFR, hypertension, diabetes, dyslipidemia, also unadjusted</td></tr><tr><td>Occupational studies</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>International Agency for Research on Cancer 15-country nuclear worker study</td><td>Vrijheid et al. [38]</td><td>Colon</td><td>Employer/facility, SES</td><td>CVD (ICD10 I00-I99, J60-J69, O88.2, R00-R02, R57)</td><td>Mortality</td><td>NA</td><td>0.09 (-0.43 to 0.70)<sup>c</sup></td><td>Analyses adjusted for employer/facility, sex, SES. No unadjusted analyses presented. There is no significant variation of ERR by gender, age at exposure or attained age for all CVD (p≥0.1), although there is highly significant increase in ERR with increasing duration of employment (p=0.01)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>IHD (ICD10 I20-I25)</td><td></td><td>NA</td><td>-0.01 (-0.59 to 0.69)<sup>c</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>Heart failure (ICD10 I50)</td><td></td><td>NA</td><td>-0.03 (<0 to 4.91)<sup>c</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>Deep vein thrombosis and pulmonary embolism (ICD10 I26, I80, I82, O88.2)</td><td></td><td>NA</td><td>-0.95 (-1.00 to 9.09)<sup>c</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>CeVD (ICD10 I60-I69)</td><td></td><td>NA</td><td>0.88 (-0.67 to 3.16)<sup>c</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>All other CVD (ICD10 R00-R02, R57, I00-I99 excluding I20-I26, I50, I60-I69, I80, I82)</td><td></td><td>NA</td><td>0.29 (<0 to 2.40)<sup>c</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>CVD (ICD10 I00-I99)</td><td>Mortality</td><td>NA</td><td>0.22 (0.08 to 0.37)<sup>m</sup></td><td></td></tr><tr><td>International Nuclear Workers Study (INWORKS)</td><td>Gillies et al. [39]</td><td>Film badge (H<sub>2</sub>p<sub>10</sub>)</td><td>Employer/facility, SES</td><td></td><td></td><td></td><td></td><td>Analyses adjusted for employer/facility, sex, SES. No unadjusted analyses presented. There are significant differences in ERR by sex for CVD (p=0.005) and for IHD (p=0.004), but not for CeVD (p>0.5). There are no significant differences in ERR by attained age or duration of employment (p>0.5 for all endpoints)</td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td></td><td></td><td></td><td></td><td>CVD (ICD10 I00-I99)</td><td></td><td>NA</td><td>0.20 (0.07 to 0.36)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>males</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>CVD (ICD10 I00-I99)</td><td></td><td>NA</td><td>4.22 (1.72 to 7.21)<sup>m</sup><sup>++</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>females</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>CVD (ICD10 I00-I99)</td><td></td><td>NA</td><td>0.27 (-0.31 to 0.90)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>duration of employment &lt; 10 y</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>CVD (ICD10 I00-I99)</td><td></td><td>NA</td><td>0.15 (-0.14 to 0.47)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>duration of employment 10–19 y</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>CVD (ICD10 I00-I99)</td><td></td><td>NA</td><td>0.27 (0.06 to 0.49)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>duration of employment 20–29 y</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>CVD (ICD10 I00-I99)</td><td></td><td>NA</td><td>0.19 (-0.03 to 0.42)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>duration of employment ≥ 30 y</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>CVD (ICD10 I00-I99)</td><td></td><td>NA</td><td>0.59 (0.15 to 1.08)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>age &lt; 60</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>CVD (ICD10 I00-I99)</td><td></td><td>NA</td><td>0.05 (-0.20 to 0.31)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>age 60–69</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>CVD (ICD10 I00-I99)</td><td></td><td>NA</td><td>0.23 (0.06 to 0.41)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>age ≥ 70</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>IHD (I20-I25)</td><td></td><td>NA</td><td>0.18 (0.004 to 0.36)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>IHD (I20-I25) males</td><td></td><td>NA</td><td>0.16 (-0.01 to 0.34)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>IHD (I20-I25) females</td><td></td><td>NA</td><td>6.17 (2.44 to 10.92)<sup>m</sup><sup>++</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>IHD (I20-I25) duration of employment &lt; 10 y</td><td></td><td>NA</td><td>0.04 (-0.67 to 0.83)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>IHD (I20-I25) duration of employment 10–19 y</td><td></td><td>NA</td><td>0.17 (-0.19 to 0.57)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>IHD (I20-I25) duration of employment 20–29 y</td><td></td><td>NA</td><td>0.16 (-0.09 to 0.42)<sup>m</sup></td><td></td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td></td><td></td><td></td><td>IHD (I20-I25) duration of employment ≥ 30 y</td><td></td><td></td><td>NA</td><td>0.21 (<0.06 to 0.51)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>IHD (I20-I25) age &lt; 60</td><td></td><td></td><td>NA</td><td>0.64 (0.14 to 1.20)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>IHD (I20-I25) age 60-69</td><td></td><td></td><td>NA</td><td>-0.02 (-0.30 to 0.29)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>IHD (I20-I25) age ≥ 70</td><td></td><td></td><td>NA</td><td>0.18 (<0.04 to 0.41)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>Acute myocardial infarction (I21)</td><td></td><td></td><td>NA</td><td>0.26 (0.03 to 0.51)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>Chronic ischemic heart disease (I25)</td><td></td><td></td><td>NA</td><td>0.07 (<0.19 to 0.36)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>CeVD (I60-I69)</td><td></td><td></td><td>NA</td><td>0.50 (0.12 to 0.94)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>CeVD (ICD10 I60-I69) males</td><td></td><td></td><td>NA</td><td>0.48 (0.10 to 0.91)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>CeVD (ICD10 I60-I69) females</td><td></td><td></td><td>NA</td><td>2.67 (&lt;0 to 9.79)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>CeVD (I60-I69) duration of employment &lt; 10 y</td><td></td><td></td><td>NA</td><td>1.01 (<0.58 to 2.90)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>CeVD (I60-I69) duration of employment 10-19 y</td><td></td><td></td><td>NA</td><td>0.35 (<0.34 to 1.19)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>CeVD (I60-I69) duration of employment 20-29 y</td><td></td><td></td><td>NA</td><td>0.70 (0.16 to 1.35)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>CeVD (I60-I69) duration of employment ≥ 30 y</td><td></td><td></td><td>NA</td><td>0.21 (<0.36 to 0.94)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>CeVD (ICD10 I60-I69) age &lt; 60</td><td></td><td></td><td>NA</td><td>0.06 (&lt;0 to 1.99)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>CeVD (ICD10 I60-I69) age 60-69</td><td></td><td></td><td>NA</td><td>-0.18 (&lt;0 to 0.72)<sup>m</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>CeVD (ICD10 I60-I69) age ≥ 70</td><td></td><td></td><td>NA</td><td>0.66 (0.22 to 1.17)<sup>m</sup></td><td></td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td>Mayak workers IHD</td><td>Azizova et al. [40, 41]</td><td>External gamma</td><td>Smoking, BMI, hypertension, alcohol consumption, migration status</td><td>IHD (ICD9 410-414) &lt; 4 Gy</td><td>Incidence</td><td>0.16 (0.10 to 0.23)<sup>b</sup></td><td>0.14 (0.08 to 0.21)<sup>b</sup></td><td>Smoking, alcohol consumption, hypertension, BMI, sex adjusted for. For the mortality data migration status also adjusted for, but there was no adjustment for hypertension. The authors note that in the morbidity data: "The exclusion of the smoking and alcohol consumption adjustments had no effect on the risk estimate for the full data set, but the risk for the dose-restricted data set became significant. Additional adjustment for hypertension did not change the result while the BMI adjustment caused the increase of the risk estimates for ... both data sets and the risk became significant;"; while in the mortality data: "In male residents, exclusion and inclusion of additional adjustments for non-radiation factors in the model changed the magnitude of the risk and made confidence intervals wider, but not the significance, except the adjustment for BMI in the IHD analysis, which increased the ERR/Gy by 116% and produced a significant result ... meanwhile the [ischemic stroke] mortality risk for male residents remained significant."</td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td rowspan="10">Mayak workers</td><td rowspan="10">Azizova et al. [41–43]</td><td rowspan="10">External gamma</td><td rowspan="10">Smoking, BMI, diabetes, alcohol consumption</td><td>IHD (ICD9 410-414) &lt; 4 Gy</td><td rowspan="10">Mortality</td><td>0.17 (0.11 to 0.25)<sup>c</sup></td><td>0.15 (0.09 to 0.22)<sup>c</sup></td><td rowspan="10">Adjusted for smoking, alcohol consumption, hypertension, BMI, sex. The authors noted that "adjusting for additional non-radiation factors (hypertension, body mass index, duration of employment, smoking index) or liver dose from internal alpha-particle radiation did not significantly change this [ERR trend] result." Partially unadjusted analysis (adding BMI or hypertension to analysis already adjusted for other factors, or dropping smoking and alcohol consumption) also presented, and made &lt; 5% difference</td></tr><tr><td>IHD (ICD9 410-414) &lt; 4 Gy</td><td>0.17 (0.11 to 0.25)<sup>d</sup></td><td>0.17 (0.10 to 0.25)<sup>d</sup></td></tr><tr><td>IHD (ICD9 410-414) &lt; 4 Gy</td><td>0.08 (0.01 to 0.17)<sup>b</sup></td><td>0.07 (&lt; 0 to 0.16)<sup>b</sup></td></tr><tr><td>IHD (ICD9 410-414) &lt; 4 Gy</td><td>0.08 (0.01 to 0.17)<sup>c</sup></td><td>0.07 (&gt; 0 to 0.16)<sup>c</sup></td></tr><tr><td>IHD (ICD9 410-414) &lt; 4 Gy</td><td>0.08 (0.01 to 0.17)<sup>d</sup></td><td>0.07 (&lt; 0 to 0.16)<sup>d</sup></td></tr><tr><td>IHD (ICD9 410-414) &lt; 4 Gy</td><td>0.07 (&gt; 0 to 0.14)<sup>e</sup></td><td>0.04 (&lt; 0.02 to 0.11)<sup>e</sup></td></tr><tr><td>CeVD (ICD9 430–438)</td><td>0.46 (0.35 to 0.53)<sup>b</sup></td><td>0.46 (0.37 to 0.56)<sup>b</sup></td></tr><tr><td>Smoking, BMI, hypertension, alcohol consumption</td><td>Incidence</td><td></td></tr><tr><td>Liver external gamma</td><td>Mortality</td><td></td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td rowspan="3">Mayak workers all cardiovascular disease</td><td rowspan="3">Azizova et al. [41, 44]</td><td rowspan="3">External gamma</td><td rowspan="3">Smoking, BMI, hypertension, alcohol consumption, migration status</td><td>CeVD (ICD9 430-438)</td><td rowspan="3">Mortality</td><td rowspan="3">0.05 (-0.03 to 0.15)<sup>b</sup></td><td rowspan="3">0.05 (-0.04 to 0.16)<sup>b</sup></td><td rowspan="3">Analysis adjusted for sex, smoking, BMI, hypertension, alcohol consumption. Partially unadjusted analysis (dropping smoking and alcohol consumption) also presented</td></tr><tr><td>CeVD (ICD9 430-438)</td><td>0.49 (0.37 to 0.57)<sup>c</sup></td><td>0.49 (0.39 to 0.60)<sup>c</sup></td></tr><tr><td>CeVD (ICD9 430-438)</td><td>0.53 (0.41 to 0.66)<sup>d</sup></td><td>0.53 (0.43 to 0.65)<sup>d</sup></td></tr><tr><td></td><td></td><td></td><td></td><td>Smoking, BMI, diabetes, alcohol consumption</td><td></td><td>0.42 (0.34 to 0.51)<sup>c,e</sup></td><td>0.39 (0.31 to 0.48)<sup>c</sup></td><td>Analysis adjusted for sex, smoking, BMI, diabetes, alcohol consumption. Partially unadjusted analysis (dropping smoking and alcohol consumption) also presented</td></tr><tr><td></td><td></td><td></td><td></td><td>Smoking, BMI, hypertension, alcohol consumption, migration status</td><td></td><td></td><td></td><td>Analysis adjusted for sex, smoking, BMI, hypertension, alcohol consumption. Partially unadjusted analysis (adding BMI or hypertension to unlagged analysis already adjusted for other factors, or dropping smoking and alcohol consumption) also presented, and made little difference (ERR/Gy in range 0.05—0.08)</td></tr><tr><td></td><td></td><td></td><td></td><td>CeVD (ICD9 430-438)</td><td></td><td>0.06 (-0.03 to 0.16)<sup>c</sup></td><td>0.05 (-0.03 to 0.16)<sup>c</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>CeVD (ICD9 430-438)</td><td></td><td>0.07 (-0.02 to 0.17)<sup>d</sup></td><td>0.06 (-0.03 to 0.18)<sup>d</sup></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>CVD (ICD9 390-459) &lt; 4 Gy</td><td></td><td>0.08 (0.03 to 0.15)<sup>b</sup></td><td>0.08 (0.02 to 0.14)<sup>b</sup></td><td>Adjusted for smoking, alcohol consumption, BMI, hypertension, sex. The authors noted that "The results observed for both the full dataset and the dose-restricted one remained unchanged after ... exclusion of adjustments for smoking and alcohol consumption and inclusion of adjustments for additional non-radiation factors"</td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td rowspan="2">Mayak workers lower extremity arterial disease</td><td rowspan="2">Azizova et al. [45]</td><td>Liver external gamma</td><td>Smoking, BMI, diabetes, alcohol consumption, hypertension</td><td>CVD (ICD9 390-459)</td><td></td><td>0.09 (0.03 to 0.15)<sup>c</sup><br>0.09 (0.03 to 0.16)<sup>d</sup><br>0.06 (0.01 to 0.12)<sup>e</sup></td><td>0.08 (0.02 to 0.15)<sup>c</sup><br>0.09 (0.03 to 0.16)<sup>d</sup><br>0.03 (-0.01 to 0.09)<sup>e</sup></td><td rowspan="2">Analysis in which various adjustment factors (smoking, BMI, diabetes, hypertension) were individually added as adjustments made little difference for component CVD endpoints</td></tr><tr><td>External gamma</td><td>Smoking, BMI, hypertension, alcohol consumption, diabetes</td><td>Lower extremity arterial disease (ICD9 440.2)</td><td>Incidence</td><td>0.34 (0.16 to 0.58)<sup>b</sup></td><td>0.30 (0.13 to 0.53)<sup>b</sup></td></tr><tr><td colspan="9"></td><td>Adjusted for sex, smoking, BMI, hypertension, alcohol consumption, diabetes. The authors note that "ERR/Gy" ... slightly increases with the exclusion of adjustments for smoking and alcohol consumption. Inclusion of adjustments for hypertension, diabetes mellitus and duration of employment shows no change in the obtained result. On the contrary, inclusion of additional adjustments for BMI and smoking index (rather than smoking status) results in a slight decrease of ERR/Gy<sup>g</sup>.</td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td>Mayak workers hypertension</td><td>Azizova et al. [46]</td><td>Liver external gamma</td><td>Smoking, BMI, alcohol consumption</td><td>Hypertension (ICD9 401-404)</td><td>Incidence</td><td>0.14 (0.08 to 0.20)<sup>b</sup></td><td>0.15 (0.09 to 0.21)<sup>b</sup></td><td>Adjusted for sex, smoking, BMI, alcohol consumption. The authors note that: "The hypertension risk estimates ... decreased after exclusion of adjustments for smoking status and alcohol consumption and inclusion of an adjustment for the baseline blood pressure level. The hypertension incidence risk was revealed to increase with inclusion into stratification of adjustments for additional non-radiation factors (body mass index and duration of employment), but the smoking index adjustment did not modify the risk estimate."</td></tr><tr><td>French nuclear fuel cycle workers</td><td>Bouet et al. [47]</td><td>External gamma</td><td>Smoking, BMI, glycemic level, hypertension, SES</td><td>CVD (ICD10 I00-I99, G45-G46) (subgroup 2, adjusted for SES, blood pressure, BMI, smoking status, glycemic level)<br/>IHD (ICD10 I20-I25) (subgroup 1)</td><td>Mortality</td><td>0.16 (0.10 to 0.22)<sup>c</sup><br/>0.17 (0.11 to 0.24)<sup>d</sup><br/>-3.5 (NA to 15.0)<sup>**</sup></td><td>0.17 (0.11 to 0.24)<sup>c</sup><br/>0.19 (0.12 to 0.26)<sup>d</sup><br/>-0.1 (NA to 48.4)<sup>**</sup></td><td>Adjusted for smoking, BMI, glycemic level, hypertension, SES</td></tr><tr><td>French uranium min-ers case-control study</td><td>Drubay et al. [48]</td><td>External gamma</td><td>Smoking, BMI, diabetes, hypertension, hypercholesterolemia, hyper-triglyceridemia, resting heart rate, chronic kidney disease (via GFR), hyperuricemia, gamma glutamyl transpeptidase</td><td>CVD (ICD10 I00-I99)<br/>CeVD (ICD10 I60-I69 + G45 (exc G45.3, G45.4) + G46) (sub-group 1)</td><td>Mortality</td><td>-4.0 (NA to 34.7)<br/>-0.3 (NA to 61.4)</td><td>NA<br/>NA</td><td>Adjusted for sex, SES. Fully adjusted analysis not presented</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td>0.4 (-1.8 to 3.0)<sup>***</sup><br/>0.4 (-1.6 to 2.9)<sup>g</sup></td><td>-0.7 (-3.2 to 2.9)<sup>***</sup></td><td>Adjusted for smoking, BMI, diabetes, hypertension, hypercholesterolemia, hyper-triglyceridemia, resting heart rate, chronic kidney disease (via GFR), hyperuricemia, gamma glutamyl transpeptidase. Adjusted and unadjusted ERR presented, as well as counter-matched analysis</td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td></td><td></td><td></td><td>CVD (ICD10 I00-I83, I85-I99) male</td><td></td><td></td><td>-0.7 (-7.6 to 7.6) <sup>+++</sup></td><td>NA</td><td></td></tr><tr><td></td><td></td><td></td><td>CVD (ICD10 I00-I83, I85-I99) female</td><td></td><td></td><td>42.1 (3.0 to 99.2) <sup>+++</sup></td><td>NA</td><td></td></tr><tr><td></td><td></td><td></td><td>CVD (ICD10 I00-I83, I85-I99) age&lt;50 y</td><td></td><td></td><td>9.8 (0.2 to 21.0) <sup>+++</sup></td><td>NA</td><td></td></tr><tr><td></td><td></td><td></td><td>CVD (ICD10 I00-I83, I85-I99) age≥50 y</td><td></td><td></td><td>-5.1 (-12.0 to 3.5) <sup>+++</sup></td><td>NA</td><td></td></tr><tr><td></td><td></td><td></td><td>CVD (ICD10 I00-I83, I85-I99) birth &lt; 1970</td><td></td><td></td><td>-1.8 (-8.8 to 6.7) <sup>+++</sup></td><td>NA</td><td></td></tr><tr><td></td><td></td><td></td><td>CVD (ICD10 I00-I83, I85-I99) birth ≥ 1970</td><td></td><td></td><td>14.5 (-0.1 to 31.7) <sup>+++</sup></td><td>NA</td><td></td></tr><tr><td></td><td></td><td></td><td>CVD (ICD10 I00-I83, I85-I99) year started work &lt; 2000</td><td></td><td></td><td>-0.6 (-7.3 to 7.6) <sup>+++</sup></td><td>NA</td><td></td></tr><tr><td></td><td></td><td></td><td>CVD (ICD10 I00-I83, I85-I99) year started work ≥ 2000</td><td></td><td></td><td>44.5 (13.4 to 82.2) <sup>+++</sup></td><td>NA</td><td></td></tr><tr><td></td><td></td><td></td><td>CVD (ICD10 I00-I83, I85-I99) years worked &lt; 10 y</td><td></td><td></td><td>45.8 (5.3 to 97.1) <sup>+++</sup></td><td>NA</td><td></td></tr><tr><td></td><td></td><td></td><td>CVD (ICD10 I00-I83, I85-I99) years worked 10–19 y</td><td></td><td></td><td>11.1 (-0.8 to 25.2) <sup>+++</sup></td><td>NA</td><td></td></tr><tr><td></td><td></td><td></td><td>CVD (ICD10 I00-I83, I85-I99) years worked ≥ 20 y</td><td></td><td></td><td>-3.6 (-10.6 to 4.9) <sup>+++</sup></td><td>NA</td><td></td></tr><tr><td></td><td></td><td></td><td>Hypertension (ICD10 I10-I15)</td><td></td><td></td><td>0.3 (-6.9 to 9.6) <sup>***</sup></td><td>-1.8 (-8.3 to 6.8) <sup>***</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>IHD (ICD10 I20-I25)</td><td></td><td></td><td>8.7 (-7.8 to 38.2) <sup>*</sup></td><td>5.3 (-11.3 to 32.4) <sup>*</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>CeVD (ICD10 I60-I69)</td><td></td><td></td><td>12.2 (-12.2 to 60.0)</td><td>12.0 (-12.3 to 58.8)</td><td></td></tr><tr><td></td><td></td><td></td><td>Other CVD (ICD10 I70-I83, I85-I99)</td><td></td><td></td><td>-0.4 (-11.9 to 15.0) <sup>*</sup></td><td>-0.2 (-11.7 to 15.5) <sup>*</sup></td><td></td></tr><tr><td></td><td></td><td></td><td>CVD excluding CeVD and others (ICD10 I53-I59, I70-I83, I85-I99)</td><td></td><td></td><td>1.3 (-5.0 to 9.0) <sup>***</sup></td><td>-0.5 (-6.3 to 6.7) <sup>***</sup></td><td></td></tr></tbody></table>
<table><caption>**Table 2 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td>Korean radiation workers prevalence study</td><td>Park et al. [52]</td><td>Film badge (H<sub>2</sub> (10))</td><td>Smoking, BMI, diabetes, alcohol consumption, hyperlipidemia, cataracts, hepatitis, diseases of thyroid, musculoskeletal and respiratory systems, occupation, duration of employment, regular exercise, night shift work</td><td>CVD (ICD10 (00-99))</td><td>Prevalence</td><td>8 (6 to 9)**</td><td>0 (-2 to 2)**</td><td>Adjusted for sex, occupation, duration of employment, smoking, alcohol consumption, regular exercise, BMI, might shift work. Unadjusted OR also presented</td></tr><tr><td colspan="9"><strong>Environmental studies</strong></td></tr><tr><td>Semipalatinsk nuclear test hypertension study</td><td>Markabayeva et al. [53]</td><td>Effective dose</td><td>Smoking, BMI, total cholesterol, hypercholesterolemia, alcohol consumption</td><td>Essential hypertension (ICD10 I10)</td><td>Prevalence</td><td>3.528 (-3.188 to 10.245)**</td><td>10.325 (-6.142 to 26.793)**</td><td>Adjusted for BMI, total cholesterol, smoking, alcohol, also adjusted only for age, sex</td></tr></tbody></table>

BMI, body mass index, CI, confidence interval, CRP, C-reactive protein, CeVD, cerebrovascular disease, CVD, cardiovascular disease, ICD, International Classification of Diseases, ERR, excess relative risk, GFR, glomerular filtration rate, HDL, high density lipoprotein, H₂ (10), personal dose equivalent at 10 mm depth, LDL, low density lipoprotein, OR, odds ratio, SES, socioeconomic status

* ratio of adjusted to unadjusted estimates outside the interval [0.667, 1.5]

** ratio of adjusted to unadjusted estimates outside the interval [0.5, 2]

*** ratio of adjusted to unadjusted estimates negative

† ratio of estimate with interaction modifier to that without modifier outside the interval [0.667, 1.5]

†† ratio of estimate with interaction modifier to that without modifier outside the interval [0.5, 2]

††† ratio of estimate with interaction modifier to that without modifier negative

a analysis derived from Table 3 of Yamada et al. [9] with smoking and drinking in the stratification

b assuming a lag period of 5 years

c assuming a lag period of 10 years

d assuming a lag period of 15 years

e dropping smoking and alcohol consumption from adjustment

f adjusting for sex, SES

g based on counter-matched analysis

h adjusting for age at exit

i adjusting for age at exit + entrance, medical diagnostic dose

j prevalence excess odds ratio per Gy

k estimate derived by fitting a linear model by (inverse-variance) weighted least squares, applied to the adjusted odds ratio (OR) provided in Table 2 of Markabayeva et al. [53]. Median cardiac doses of 0.009, 0.041, 0.070, and 0.326 Sv were assumed for the respective groups with the following specified ranges of effective doses: < 20, 20–59, 60–185, > 185 mSv, as given by Markabayeva et al. [53]

l estimate derived from log-linear model, evaluated at 1 Sv

m 90% CI
[0.667, 1.5] and the heterogeneity was statistically significant (*p* < 0.05) – labelled †

b) more than 100% difference, i.e., with ratio of estimates (with/without modification) outside the interval [0.5, 2.0] and the heterogeneity was statistically significant (*p* < 0.05) – labelled ††

c) estimates with different signs, i.e. one (with modification) positive, the other (without modification) negative or vice versa and the heterogeneity was statistically significant (*p* < 0.05), labelled †††

We specifically highlight the most serious discrepancies of both sorts (***, †††) in the text below. We describe these as potential confounders and potential effect modifiers, respectively. Table 3 reports those studies and results (taken from Tables 1, 2) in which one of these six categories of potentially confounding or modifying effects is observed. Table 4 separately reports effects of variation of latency.

## Results

Of the total of 93 studies from the original systematic review and meta-analysis (detailed in Little et al. [12]), 43 studies satisfied the a priori selection criteria and were retained for this analysis.

Of the 50 studies that were omitted, the high dose radiotherapeutic studies (of the type shown in Table 1) in many cases [55–79] had information on many lifestyle and environmental variables, but only presented one type of analysis (generally fully adjusted); however, there were some high dose studies in which there was little or no information on potential confounders [80, 81]. The Danish study of Lorenzen et al. [82] was omitted as it is largely subsumed by the Nordic study of Darby et al. [19]. There was a similar situation for the lower dose studies (of the type shown in Table 2), which in some cases had rich lifestyle information but only presented a single type of analysis [83–88] although in many instances the lower dose studies that were omitted had little or no information, apart from crude markers of socioeconomic status [54, 89–111]. Of the final selected studies, 22 were of groups exposed to substantial doses of medical radiation for therapy or diagnosis (Table 1). The remaining 21 studies were of groups exposed at much lower levels of dose and/or dose rate (Tables 2 and 3). There is substantial overlap in the populations studied in some of these groups. For example three of the studies relate to various CVD endpoints in the LSS [9, 10, 37], and there are various studies of a number of CVD endpoints in the Mayak nuclear workers [40–46].

## Effects of adjustment for potential confounding variables

Very few studies suggested substantial effects of adjustment for lifestyle, environmental, or medical risk factors. In the Rochester study of Adams et al. [34] the unadjusted ERR/Gy for coronary heart disease was 0.08 (95% confidence interval (CI) -0.01 to 0.20), and the ERR/Gy adjusted for sex, diabetes, dyslipidemia, smoking and hypertension was -0.03 (95% CI -0.07 to 0.10) (Tables 1 and 3). In the LSS the unadjusted ERR/Gy for hypertensive heart disease incidence was 0.01 (95% CI -0.08 to 0.10), and the ERR/Gy adjusted for smoking and drinking was -0.01 (95% CI -0.09 to 0.09) [9] (Tables 2 and 3). In the French uranium miners case-control study of Drubay et al. [48] the unadjusted ERR/Gy for all CVD was 0.4 (95% CI -1.8 to 3.0), and adjusted for smoking, body mass index (BMI), diabetes, hypertension, hypercholesterolemia, hypertriglyceridemia, resting heart rate, chronic kidney disease, hyperuricemia, gamma-glutamyl transpeptidase was -0.7 (95% CI -3.2 to 2.9) (Tables 2 and 3). The unadjusted ERR/Gy for hypertension, or CVD excluding cerebrovascular disease (CeVD) and some other endpoints in the Korean medical diagnostic workers were 0.3 (95% CI -6.9 to 9.6) and 1.3 (95% CI -5.0 to 9.0), whereas for the same endpoints adjusted for sex, smoking, alcohol intake, BMI, blood pressure, cholesterol and blood glucose the ERR/Gy were -1.8 (95% CI -8.3 to 6.8) and -0.5 (95% CI -6.3 to 6.7), respectively [51] (Tables 2 and 3).

## Modifying effects of radiation

There are only two studies reporting the most serious level of modifying effect, those of the International Nuclear Workers Study (INWORKS) workers by Gillies et al. [39] and the Korean medical diagnostic worker study of Cha et al. [51] (Tables 2 and 3). Gillies et al. [39] reported markedly higher risks for females, with ERR/Gy of 4.22 (90% CI 1.72 to 7.21) for all CVD, 6.17 (90% CI 2.44 to 10.92) for ischemic heart disease (IHD), and 2.67 (90% CI <0 to 9.79) for CeVD, compared with ERR/Gy for males for the same endpoints of 0.20 (90% CI 0.07 to 0.36), 0.16 (90% CI -0.01 to 0.34), and 0.48 (90% CI 0.10 to 0.91), respectively; these differences were highly significant for all CVD (p=0.005) and IHD (p=0.004), but not for CeVD (p > 0.50) (Tables 2 and 3). Gillies et al. [39] also reported modifications by attained age and duration of employment, and although some of these were substantial for certain groups (Tables 2 and 3) none were statistically significant (p > 0.10). The Korean worker study of Cha et al. [51] also reported markedly higher ERR/Gy for females, with CVD ERR/Gy of 42.1 (95% CI 3.0 to 99.2) compared with ERR/Gy for males of -0.7 (95% CI -7.6 to 7.6). This study also reported
<table><caption>**Table 3** Unadjusted or adjusted estimated excess relative risk of cardiovascular diseases in various groups in which there is pronounced effect of adjustment for potential confounder variables, or significant variation by modifying factors. All analyses adjust for age</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td colspan="9"><strong>Therapeutically treated groups</strong></td></tr><tr><td>Rochester thymus enlargement study</td><td>Adams et al. [34]</td><td>Heart</td><td>Smoking, dyslipidemia, diabetes, hypertension, family history of myocardial infarction</td><td>Coronary heart disease (ICD10 I21-I25, I46)</td><td>Incidence</td><td>0.08 (-0.01 to 0.20)***</td><td>-0.03 (-0.07 to 0.10)***</td><td>Adjusted for sex, diabetes, dyslipidemia, smoking, hypertension. Unadjusted analysis (adjusted for sex) also presented</td></tr><tr><td colspan="9"><strong>Japanese atomic bomb survivors</strong></td></tr><tr><td>Japanese atomic bomb survivors</td><td>Shimizu et al. [10]<br/>Little et al. [11]</td><td>Colon</td><td>Smoking, obesity (BMI), diabetes, alcohol intake, education, type of household occupation, city</td><td>CeVD</td><td>Mortality</td><td>0.081</td><td>0.072</td><td>Main analyses unadjusted for anything apart from sex, city. Additional analysis adjusting for smoking, alcohol intake, education, type of household occupation, obesity (BMI), diabetes. There were significant modifying effects on CeVD risk of attained age (p=0.04) and age at exposure (p=0.007) (with ERR decreasing with increases in each of these), but no such modifications for heart disease (p&gt;0.2). There are significant modifying effects of sex for heart disease (p=0.022) but not for any other endpoint (p&gt;0.5)</td></tr><tr><td>Japanese atomic bomb survivors</td><td>Yamada et al. [9]</td><td>Stomach</td><td>Smoking, alcohol consumption, city</td><td>Hypertensive heart disease, 1958–1998 (ICD9 402, 404)<br/>Aortic aneurysm, 1958–1998 (ICD9 441, 442)</td><td>Incidence</td><td>0.01 (-0.08 to 0.10)***</td><td>-0.01 (-0.09 to 0.09)***</td><td>All analyses adjusted for city, sex. Additional analyses adjust for smoking and drinking</td></tr><tr><td>Japanese atomic bomb survivors<br/>1958–2014</td><td>Takahashi et al. [37]</td><td>Skin</td><td>Smoking, BMI, diabetes, blood pressure, total + LDL and HDL cholesterol, triglycerides, dyslipidemia, high sensitivity CRP, white blood cell count, GFR, city</td><td>Peripheral artery disease</td><td>Prevalence</td><td>-0.11 (-0.39, 0.30)*</td><td>-0.17 (-0.43 to 0.22)*</td><td>Analyses adjusted for sex, smoking, CRP, GFR, hypertension, diabetes, dyslipidemia, also unadjusted</td></tr></tbody></table>
<table><caption>**Table 3 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td colspan="9"><strong>Occupational studies</strong></td></tr><tr><td>International Nuclear Workers Study (INWORKS)</td><td>Gillies et al. [39]</td><td>Film badge (H<sub>2</sub>F<sub>1</sub>(10))</td><td>Employer/facility, SES</td><td>CVD (ICD10 I00-I99) females<br/>IHD (I20-I25) females</td><td>Mortality</td><td>NA</td><td>4.22 (1.72 to 7.21)<sup>b</sup></td><td rowspan="2">Analyses adjusted for employer/facility, sex, SES. No unadjusted analyses presented. There are significant differences in ERR by sex for CVD (p = 0.005) and for IHD (p = 0.004), but not for CVD (p > 0.5). There are no significant differences in ERR by attained age or duration of employment (p > 0.5 for all endpoints)</td></tr><tr><td>Mayak workers</td><td>Azizova et al. [41]</td><td>Liver external gamma</td><td>Smoking, BMI, diabetes, alcohol consumption</td><td>IHD (ICD9 410-414)</td><td>Mortality</td><td>0.07 (&gt;0 to 0.14)<sup>c</sup></td><td>0.04 (&lt;0.02 to 0.11)<sup>c</sup></td></tr><tr><td>French nuclear fuel cycle workers</td><td>Bouet et al. [47]</td><td>External gamma</td><td>Smoking, BMI, glycemic level, hypertension, SES</td><td>CVD (ICD10 I00-I99, G45-G46) (subgroup 2, adjusted for SES, blood pressure, BMI, smoking status, glycemic level)</td><td>Mortality</td><td>CVD (ICD9 390-459)</td><td>0.06 (0.01 to 0.12)<sup>c</sup></td><td>0.03 (&lt;0.01 to 0.09)<sup>c</sup></td><td>Smoking, alcohol consumption, BMI, sex, migration status adjusted for. The authors note that: "In male residents, exclusion and inclusion of additional adjustments for non-radiation factors in the model changed the magnitude of the risk and made confidence intervals wider, but not the significance, except the adjustment for BMI in the IHD analysis, which increased the ERR/Gy by 116% and produced a significant result. ... meanwhile the [ischemic stroke] mortality risk for male residents remained significant." Analysis in which various adjustment factors (smoking, BMI, diabetes, hypertension) were individually added as adjustments made little difference for component CVD endpoints<br/>Adjusted for smoking, BMI, glycemic level, hypertension, SES</td></tr></tbody></table>
<table><caption>**Table 3 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td rowspan="3">French uranium min- ers case-control study</td><td rowspan="3">Drubay et al. [48]</td><td rowspan="3">External gamma</td><td rowspan="3">Smoking, BMI, diabetes, hypertension, hyper- cholesterolemia, hyper-triglyceridemia, resting heart rate, chronic kidney disease (via GFR), hyperuricemia, gamma glutamyl transpeptidase</td><td>CVD (ICD10 I00-I99)</td><td rowspan="3">Mortality</td><td>0.4 (-1.8 to 3.0)<sup>***</sup><br>0.4 (-1.6 to 2.9)<sup>e</sup></td><td>-0.7 (-3.2 to 2.9)<sup>***</sup></td><td rowspan="3">Adjusted for smoking, BMI, diabetes, hypertension, hyper-cholesterolemia, hyper-triglyceridemia, resting heart rate, chronic kidney disease (via GFR), hyperuricemia, gamma glutamyl transpeptidase. Adjusted and unadjusted ERR presented, as well as counter-matched analysis</td></tr><tr><td>IHD (ICD10 I20-I25)</td><td>-1.1 (-4.0 to 3.2)<sup>**</sup><br>-1.0 (-3.9 to 3.3)<sup>e</sup></td><td>-2.6 (-6.3 to 5.1)<sup>**</sup></td></tr><tr><td>CeVD (ICD10 I60-I69)</td><td>3.7 (-0.9 to 10.6)<sup>*</sup><br>2.4 (-0.6 to 11.4)<sup>e</sup></td><td>1.9 (-3.5 to 11.8)<sup>*</sup></td></tr><tr><td rowspan="11">Korean medical diagnostic workers</td><td rowspan="11">Cha et al. [51]</td><td rowspan="11">Heart</td><td rowspan="11">Smoking, BMI, blood glucose, systolic + diastolic blood pressure, total + low-density LDL + high-density LDL cholesterol, alcohol intake</td><td>CVD (ICD10 I00-I83, I85-I99)</td><td rowspan="11">Incidence</td><td>1.5 (-3.9 to 8.0)<sup>**</sup></td><td>0.6 (-4.6 to 6.8)<sup>**</sup></td><td rowspan="11">Adjusted for sex, smoking, alcohol intake, BMI, systolic + diastolic blood pressure, total + LDL + HDL cholesterol, blood glucose. Unadjusted analyses also presented, adjusted only for sex. The modifications in ERR (adjusted for age, sex, birth year) were significant for sex (p=0.03), attained age (p=0.004), year starting work (p=0.003) and total years worked (p=0.007). There were similar generally significant modifications in ERR for hypertension, and CVD excluding CeVD and others, but not for IHD, CeVD and other CVD</td></tr><tr><td>CVD (ICD10 I00-I83, I85-I99) male</td><td>-0.7 (-7.6 to 7.6)<sup>+++</sup></td><td>NA</td></tr><tr><td>CVD (ICD10 I00-I83, I85-I99) female</td><td>42.1 (3.0 to 99.2)<sup>+++</sup></td><td>NA</td></tr><tr><td>CVD (ICD10 I00-I83, I85-I99) age &lt; 50 y</td><td>9.8 (0.2 to 21.0)<sup>+++</sup></td><td>NA</td></tr><tr><td>CVD (ICD10 I00-I83, I85-I99) age ≥ 50 y</td><td>-5.1 (-12.0 to 3.5)<sup>+++</sup></td><td>NA</td></tr><tr><td>CVD (ICD10 I00-I83, I85-I99) birth &lt; 1970</td><td>-1.8 (-8.8 to 6.7)<sup>+++</sup></td><td>NA</td></tr><tr><td>CVD (ICD10 I00-I83, I85-I99) birth ≥ 1970</td><td>14.5 (-0.1 to 31.7)<sup>+++</sup></td><td>NA</td></tr><tr><td>CVD (ICD10 I00-I83, I85-I99) year started work &lt; 2000</td><td>-0.6 (-7.3 to 7.6)<sup>+++</sup></td><td>NA</td></tr><tr><td>CVD (ICD10 I00-I83, I85-I99) year started work ≥ 2000</td><td>44.5 (13.4 to 82.2)<sup>+++</sup></td><td>NA</td></tr><tr><td>CVD (ICD10 I00-I83, I85-I99) years worked &lt; 10 y</td><td>45.8 (5.3 to 97.1)<sup>+++</sup></td><td>NA</td></tr><tr><td>CVD (ICD10 I00-I83, I85-I99) years worked 10-19 y</td><td>11.1 (-0.8 to 25.2)<sup>+++</sup></td><td>NA</td></tr><tr><td>CVD (ICD10 I00-I83, I85-I99) years worked ≥ 20 y</td><td>-3.6 (-10.6 to 4.9)<sup>+++</sup></td><td>NA</td></tr><tr><td>Hypertension (ICD10 I10-I15)</td><td>0.3 (-6.9 to 9.6)<sup>***</sup></td><td>-1.8 (-8.3 to 6.8)<sup>***</sup></td><td></td></tr><tr><td>IHD (ICD10 I20-I25)</td><td>8.7 (-7.8 to 38.2)<sup>*</sup></td><td>5.3 (-11.3 to 32.4)<sup>*</sup></td><td></td></tr><tr><td>Other CVD (ICD10 I70-I83, I85-I99)</td><td>-0.4 (-11.9 to 15.0)<sup>*</sup></td><td>-0.2 (-1.7 to 15.5)<sup>*</sup></td><td></td></tr><tr><td>CVD excluding CeVD and others (ICD10 I53-I59, I70-I83, I85-I99)</td><td>1.3 (-5.0 to 9.0)<sup>***</sup></td><td>-0.5 (-6.3 to 6.7)<sup>***</sup></td><td></td></tr></tbody></table>
<table><caption>**Table 3 (continued)**</caption><thead><tr><th>Study</th><th>Reference</th><th>Organ used</th><th>Variables (other than age, sex, year) available to assess possible confounding</th><th>Endpoint</th><th>Mortality, incidence or prevalence</th><th>Unadjusted (or less adjusted) excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Fully adjusted excess relative risk Gy<sup>-1</sup> (95% CI)</th><th>Notes</th></tr></thead><tbody><tr><td>Korean radiation workers prevalence study</td><td>Park et al. [52]</td><td>Film badge (H<sub>2</sub>(10))</td><td>Smoking, BMI, diabetes, alcohol consumption, hyperlipidemia, cataracts, hepatitis, diseases of thyroid, musculo-skeletal and respiratory systems, occupation, duration of employment, regular exercise, night shift work</td><td>CVD (ICD10 I00-I99)</td><td>Prevalence</td><td>8 (6 to 9)<sup>***</sup></td><td>0 (-2 to 2)<sup>***</sup></td><td>Adjusted for sex, occupation, duration of employment, smoking, alcohol consumption, regular exercise, BMI, night shift work. Unadjusted OR also presented</td></tr><tr><td colspan="9"><strong>Environmental studies</strong></td></tr><tr><td>Semipalatinsk nuclear test hypertension study</td><td>Markabayeva et al. [53]</td><td>Effective dose</td><td>Smoking, BMI, total cholesterol, hypercholesterolemia, alcohol consumption</td><td>Essential hypertension (ICD10 I10)</td><td>Prevalence</td><td>3,528 (-3,188 to 10,245)<sup>g*</sup></td><td>10,325 (-6,142 to 26,793)<sup>g*</sup></td><td>Adjusted for BMI, total cholesterol, smoking, alcohol also adjusted only for age, sex</td></tr></tbody></table>

BMI body mass index, CI confidence interval, CRP C-reactive protein, CeVD cerebrovascular disease, CVD cardiovascular disease, ICD International Classification of Diseases, ERR excess relative risk, GFR glomerular filtration rate, HDL high density lipoprotein, H<sub>2</sub>(10) personal dose equivalent at 10 mm depth, LDL low density lipoprotein, OR odds ratio, SES socioeconomic status

* ratio of adjusted to unadjusted estimates outside the interval [0.667, 1.5]

** ratio of adjusted to unadjusted estimates outside the interval [0.5, 2]

*** ratio of adjusted to unadjusted estimates negative

† ratio of estimate with interaction modifier to that without modifier outside the interval [0.667, 1.5]

†† ratio of estimate with interaction modifier to that without modifier outside the interval [0.5, 2]

††† ratio of estimate with interaction modifier to that without modifier negative

a analysis derived from Table 3 of Yamada et al. [9] with smoking and drinking in the stratification

b 90% CI

c assuming a lag period of 10 years

d adjusting for sex, SES

e based on counter-matched analysis

f prevalence excess odds ratio per Gy

g estimate derived by fitting a linear model by (inverse-variance) weighted least squares, applied to the adjusted odds ratio (OR) provided in Table 2 of Markabayeva et al. [53]. Median cardiac doses of 0.009, 0.041, 0.070, and 0.326 Sv were assumed for the respective groups with the following specified ranges of effective doses: < 20, 20–59, 60–185, > 185 mSv, as given by Markabayeva et al. [53]
significant modifications of ERR/Gy for CVD in relation to age, birth year, year started work and years worked (Tables 2 and 3). There were similar indications of heterogeneity for all these variables for hypertension and CVD excluding CeVD and other CVD (ICD10 I70-I83, I85-99). The French Childhood Cancer Study of Mansouri et al. [16] reported marked discrepancies with treatment status by anthracyclines (cardiotoxic anticancer drugs), with an ERR/Gy of 0.44 (95% CI 0.18 to 1.12) for those not treated compared with an ERR/Gy of 0.09 (95% CI 0.02 to 0.22) for those treated with anthracyclines (Table 1). They also reported that “HF [heart failure] risk increased with each category of age, with ERR/Gy values for the MHD [mean heart dose] of 0.06, 0.33, 0.38 and 0.48 in those aged <15, 15–25, 25–35, and ≥35 years, respectively” [16]. The Netherlands-NKI-Rotterdam breast cancer case control study of Jacobse et al. [22] reported borderline significant modifications in risk by age at exposure (ERR/Gy age < 45 = 0.242 (95% CI 0.044 to 0.823), age 45–49 = 0.111 (95% CI 0.012 to 0.401), age 50–70 = 0.025 (95% CI -0.014 to 0.119), heterogeneity *p* = 0.07) (Table 1). In no other high radiation dose studies (reported in Table 1) were any modifying effects reported [17–19, 22, 23]. In the LSS, there are significant modifying effects on CeVD risk of attained age and age at exposure [10, 11], with ERR decreasing in each case with increases in each variable, but no such modifications in ERR by any of these variables when the investigators used only CVD as outcome; Little et al. [11] reported a change in ERR/Gy per year of age at exposure by -0.050 (95% CI -0.099, -0.015) for stroke and by -0.012 (95% CI -0.041, 0.018) for heart disease. There is a borderline significant effect (*p* = 0.022) of sex on heart disease but not for stroke (*p* > 0.9) [11].

Although not reported in Table 2, because the analysis was not generally aligned with that of the main analysis (using a lag of 5 years, and wherever possible dose < 4 Gy), there is analysis of the Mayak worker data by sex, attained age and duration of employment group; there was no statistically significant heterogeneity (*p* > 0.1) in effect suggested by these analyses [41, 42, 44–46].

### Modifying effects of latency

Table 4 shows the modifying effects of latency. There is very little variation of ERR/Gy with lag, although there is a slight tendency for ERR/Gy to increase with increasing lag period.

### Modifying effects in animal data

Table 5 illustrates what little is known about potential modifying factors from radiobiological animal data. There is some evidence of the modifying effects of age at exposure and chemotherapy in certain systems.

### Discussion

We have assessed effects of confounding by lifestyle, environmental or medical risk factors on radiation-associated CVD, using data assembled for a recent systematic review [12]. We found only limited evidence that adjustment for potential confounding made substantial difference to risk estimates. Only in four studies, in a group treated in childhood for hemangioma [34], in the LSS [9] and in two groups of nuclear workers [48, 51], were the adjusted and unadjusted ERR substantially different (Tables 1, 2 and 3). However, it was hard to assess whether these variables were true confounders of the association between radiation and CVD; there were also substantial uncertainties in all of these studies, so that not much weight can be attached.

We also investigated evidence for modifying effects of these variables on CVD radiation dose response, again using data assembled for the systematic review [12]. There are fewer suggestions of the most serious level of modifying effect, with age at exposure modifications in the same direction reported in two studies [11, 16], although for different disease endpoints. In the study of Mansouri et al. [16] there were substantial modifying effects of anthracycline exposure (Tables 1, 2 and 3). In the LSS and in two groups of nuclear workers there are significant modifying effects of sex [11, 39, 51], although for discrepant endpoints. However, in most of the studies reported here no analysis has been reported of modifying effects of these or any other variable (Tables 1, 2 and 3). There is little variation of ERR with lagging period, although there is a slight tendency for ERR/Gy to increase with increasing lag period. (Table 4).

The radiobiological animal data has rather less information (Table 5). The metrics used are heterogeneous, and in general the internal dose trends (ERR/Gy) used in the epidemiological data given in Tables 1, 2 and 3 are not given. Indeed, in most studies there is only a single irradiated group, and the relative effects of the extra covariate on the radiation-associated relative risk (irradiated vs control) difficult to determine. Given the heterogeneity in endpoints used and in the animal systems employed one should probably not attach much weight to these findings.

Assessment of outcomes is a complication, as mortality outcomes could be less accurate than studies of incidence. In incidence studies, medical and lifestyle factors are more likely to be collected, as reported in our systematic review [12]. Pooling mortality and incidence data could explain part of the heterogeneity of the summarized results observed in the meta-analysis. Indeed, summarized risks were significantly higher for mortality endpoints compared with those of incidence in the meta-analysis [12]. An additional complication in
<table><caption>**Table 4** Variation with latency of estimated excess relative risks of cardiovascular diseases in occupationally and environmentally exposed groups</caption><thead><tr><th>Cohort/Study</th><th>Reference</th><th>Average Organ<br>Dose (Gy or Sv)<br>mean/ median<br>(range)</th><th>Organ used</th><th>Variables<br>(other than<br>age, sex, year<br>available to<br>assess possible<br>confounding</th><th>Persons<br>(person years of<br>follow-up)</th><th>Deaths/ cases<br>or<br>incidence</th><th>Mortality<br>or<br>incidence</th><th>Lag<br>period<br>(years)</th><th>Endpoint</th><th>Excess relative<br>risk Gy<sup>-1</sup> (95%<br>CI)</th></tr></thead><tbody><tr><td rowspan="2">Occupational<br>studies<br>Mayak workers<br>IHD</td><td rowspan="2">Azizova et al. [40, 41]</td><td rowspan="2">0.51 (0 to &gt; 4.5)<sup>a</sup></td><td rowspan="2">External gamma</td><td>Smoking, BMI,<br>hypertension,<br>alcohol con-<br>sumption</td><td>22,377 (447,281)</td><td>7225</td><td>Incidence</td><td>5</td><td>IHD (ICD9<br>410-414) &lt; 4 Gy</td><td>0.14 (0.08 to 0.21)</td></tr><tr><td>22,377 (836,048)</td><td>2848</td><td>Mortality</td><td>5</td><td>IHD (ICD9<br>410-414) &lt; 4 Gy<br>IHD (ICD9<br>410-414) &lt; 4 Gy<br>IHD (ICD9<br>410-414) &lt; 4 Gy<br>IHD (ICD9<br>410-414) &lt; 4 Gy<br>IHD (ICD9<br>410-414) &lt; 4 Gy</td><td>0.15 (0.09 to 0.22)<br>0.17 (0.10 to 0.25)<br>0.07 (&lt;0 to 0.16)<br>0.07 (&gt;0 to 0.16)<br>0.07 (&lt;0 to 0.16)</td></tr><tr><td rowspan="2">Mayak workers<br>CeVD</td><td rowspan="2">Azizova et al. [41-43]</td><td rowspan="2">0.43 (&lt;0.1<br>to &gt; 3.0)</td><td rowspan="2">Liver external<br>gamma</td><td>Smoking, BMI,<br>diabetes, alcohol<br>consumption</td><td>22,377 (890,132)</td><td>3481</td><td>Incidence</td><td>5</td><td>CeVD (ICD9<br>430-438)</td><td>0.04 (-0.02 to 0.11)</td></tr><tr><td>Smoking, BMI,<br>hypertension,<br>alcohol con-<br>sumption</td><td>22,377 (425,735)</td><td>8717</td><td>Incidence</td><td>5</td><td>CeVD (ICD9<br>430-438)</td><td>0.46 (0.37 to 0.56)</td></tr><tr><td rowspan="2">Mayak workers<br>CeVD</td><td rowspan="2">Azizova et al. [41-43]</td><td rowspan="2">0.51 (0 to &gt; 4.5)<sup>a</sup></td><td rowspan="2">External gamma</td><td>Smoking, BMI,<br>diabetes, alcohol<br>consumption</td><td>22,377 (459,520)</td><td>9469</td><td>Incidence</td><td>5</td><td>CeVD (ICD9<br>430-438)</td><td>0.49 (0.39 to 0.60)</td></tr><tr><td>Smoking, BMI,<br>hypertension,<br>alcohol con-<br>sumption</td><td>22,377 (836,078)</td><td>1578</td><td>Mortality</td><td>5</td><td>CeVD (ICD9<br>430-438)</td><td>0.53 (0.43 to 0.65)<br>0.39 (0.31 to 0.48)</td></tr><tr><td rowspan="2">Mayak workers<br>CeVD</td><td rowspan="2">Azizova et al. [41-43]</td><td rowspan="2">0.43 (&lt;0.1 to &gt; 3)</td><td rowspan="2">Liver external<br>gamma</td><td>Smoking, BMI,<br>diabetes, alcohol<br>consumption</td><td>22,377 (836,078)</td><td>1578</td><td>Incidence</td><td>5</td><td>CeVD (ICD9<br>430-438)</td><td>0.05 (-0.04 to 0.16)</td></tr><tr><td>Smoking, BMI,<br>hypertension,<br>alcohol con-<br>sumption</td><td>22,377 (836,078)</td><td>1578</td><td>Mortality</td><td>5</td><td>CeVD (ICD9<br>430-438)</td><td>0.05 (-0.04 to 0.16)</td></tr></tbody></table>
<table><caption>**Table 4 (continued)**</caption><thead><tr><th>Cohort/Study</th><th>Reference</th><th>Average Organ<br>Dose (Gy or Sv)<br>mean/ median<br>(range)</th><th>Organ used</th><th>Variables<br>(other than<br>age, sex, year<br>available to<br>assess possible<br>confounding</th><th>Persons<br>(person years of<br>follow-up)</th><th>Deaths/ cases</th><th>Mortality<br>or<br>incidence</th><th>Lag<br>period<br>(years)</th><th>Endpoint</th><th>Excess relative<br>risk Gy<sup>-1</sup> (95%<br>CI)</th></tr></thead><tbody><tr><td rowspan="2">Mayak workers<br>all cardiovascular<br>disease</td><td rowspan="2">Azizova et al. [41,<br>44]</td><td>0.43 (&lt;0.1 to &gt; 3)</td><td>Liver external<br>gamma</td><td>Smoking, BMI,<br>diabetes, alcohol<br>consumption</td><td>22,377 (890,132)</td><td>1808</td><td></td><td>15</td><td>CeVD (ICD9<br>430-438)</td><td>0.06 (-0.03 to 0.18)</td></tr><tr><td>0.51 (0 to &lt; 4)</td><td>External gamma</td><td>Smoking, BMI,<br>hypertension,<br>alcohol con-<br>sumption</td><td>22,334 (836,048)</td><td>5010</td><td>Mortality</td><td>5</td><td>CeVD (ICD9<br>430-438)</td><td>0.03 (-0.05 to 0.13)</td></tr><tr><td rowspan="2">Mayak workers<br>lower extremity<br>arterial disease</td><td rowspan="2">Azizova et al. [45]</td><td>0.43 (&lt;0.1 to &gt; 3)</td><td>Liver external<br>gamma</td><td>Smoking, BMI,<br>diabetes, alcohol<br>consumption</td><td>22,377 (890,132)</td><td>6019</td><td></td><td>10</td><td></td><td></td></tr><tr><td>0.51 (0 to &gt; 4.5)</td><td>External gamma</td><td>Smoking, BMI,<br>hypertension,<br>alcohol con-<br>sumption</td><td>21,122 (512,801)</td><td>943</td><td>Incidence</td><td>5</td><td>CVD (ICD9<br>390-459)</td><td>0.08 (0.02 to 0.14)</td></tr><tr><td rowspan="2">Environmental<br>studies</td><td rowspan="2">Krestinina et al.<br>[54]</td><td rowspan="2">0.034 (0 to 0.995)</td><td rowspan="2">Muscle</td><td rowspan="2">Ethnic group, set-<br>tlement status</td><td rowspan="2">60,205 (1,836,203)</td><td rowspan="2">14,830</td><td rowspan="2">Mortality</td><td rowspan="2">5</td><td rowspan="2">CVD (ICD9<br>390-459)</td><td>0.08 (0.02 to 0.15)</td></tr><tr><td></td><td>0.09 (0.03 to 0.16)</td></tr><tr><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td>0.03 (-0.01 to 0.09)</td></tr><tr><td></td><td>0.30 (0.13 to 0.53)</td></tr><tr><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td rowspan="2"></td><td>0.28 (0.12 to 0.50)</td></tr><tr><td></td><td>0.32 (0.14 to 0.57)</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><caption>**Table 5** Effect of modifying variables on absolute risk in radiobiological animal data</caption><thead><tr><th>Reference</th><th>Animal model</th><th>Variable</th><th>Endpoints</th><th>Variable effect on radiation endpoints</th><th>Notes</th></tr></thead><tbody><tr><td>Sex</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sridharan et al. [112]</td><td>Adult mice, high activated protein C expressers, exposed to leg-out partial body γ-rays</td><td>Sex</td><td>Cardiac function, cardiac collagen deposition, cardiac microvascular density</td><td>Radiation endpoints differ between the sexes</td><td>No quantitative data on differences in relative radiation effect (irradiated vs not) by sex presented (but possibly could be derived from data provided in supplement). Only tissue level data presented</td></tr><tr><td>Stewart et al. [113]</td><td>Adult ApoE<sup>-/-</sup> mice, exposed to aortic arch and carotid artery X-rays</td><td>Sex</td><td>Number of plaques, plaque histology</td><td>No sex difference in plaque burden, some differences in plaque immune cells</td><td>Few quantitative data on sex difference presented, and difficult to assess sex modifications of relative effects</td></tr><tr><td>Andruska et al. [114]</td><td>Adult Dahl SS rats, exposed to local heart X-rays</td><td>Sex</td><td>Cardiac function, pericardial effusions</td><td>Endpoints more severe in female rats, but may be due to a higher volume of irradiated lung. Female pericardial effusion prevalence significantly greater than in males among irradiated rats (p &lt; 0.001), but male survival significantly worse (p &lt; 0.01) than females. Various cardiac output measures suggest females have more rapid onset of cardiac dysfunction than males</td><td>Few quantitative data on sex difference presented, and difficult to assess sex modifications of relative radiation effects (irradiated vs control)</td></tr><tr><td>Chmielewski-Stivers et al. [115]</td><td>Adult wild-type mice, exposed to local heart X-rays</td><td>Sex</td><td>Survival, echocardiography, histopathology of the heart</td><td>Males exhibited lower survival than females. Males showed echocardiographic and histopathological changes, but not in females</td><td>Few quantitative data on sex differences presented, and difficult to assess sex modifications of relative radiation effects (irradiated vs control)</td></tr><tr><td></td><td>Adult RhoB<sup>-/-</sup> mice, exposed to local heart X-rays</td><td>Sex</td><td>Survival, echocardiography, histopathology of the heart</td><td>Females exhibited lower survival than males. Females showed histopathological changes, but not in males. Both sexes showed no echocardiographic changes</td><td>In males, RhoB<sup>-/-</sup> mice were more radioresistant than wild-type counterparts. The reverse held true for females. As above, few quantitative data on sex differences presented, and difficult to assess sex modifications of relative radiation effects (irradiated vs control)</td></tr></tbody></table>
<table><caption>**Table 5 (continued)**</caption><thead><tr><th>Reference</th><th>Animal model</th><th>Variable</th><th>Endpoints</th><th>Variable effect on radiation endpoints</th><th>Notes</th></tr></thead><tbody><tr><td>Lenarczyk et al. [116]</td><td>Male WAG/RijCmcr rats exposed to whole body X-rays at the age of 6 weeks or 6 months</td><td>Age at exposure</td><td>Blood levels of cardiovascular risk factors, perivascular fibrosis, systemic blood pressure</td><td>Different dose- and time-dependent effects on cardiovascular risk factors between young and old animals. Increasing age at exposure resulted in more strongly positive dose response for albumin (p = 0.0003), protein (p = 0.0014), AST (p = 0.0014), and alkaline phosphatase (p = 0.0003), but more negative dose response for cholesterol (p = 0.0008), HDL (p = 0.0030), triglycerides (p = 0.0333), BUN (p = 0.0068) and calcium (p = 0.0299). More severe radiation-induced perivascular fibrosis and blood pressure increase in young animals</td><td>Few quantitative data on age at exposure differences presented, and difficult to assess age at exposure modifications of relative radiation effects (irradiated vs control)</td></tr><tr><td>Mitchel et al. [117]</td><td>ApoE<sup>-/-</sup>, p53<sup>-/-</sup> mice, exposed to whole body γ-rays at 8 weeks or 7 months of age</td><td>Age at exposure</td><td>Vascular lesion size, lesion frequency, serum total cholesterol</td><td>p53 heterozygosity alters the effects of radiation on all endpoints. The type of modification depends on age at exposure (8 weeks s 7 months)</td><td>Higher age is associated with more severe atherosclerosis at the time of radiation. However, few quantitative data on age at exposure differences presented, and difficult to assess age at exposure modifications of relative radiation effects (irradiated vs control)</td></tr><tr><td colspan="6"><strong>Anti-cancer treatment</strong></td></tr><tr><td>Fajardo et al. [118], Eitringham et al. [119]</td><td>Young adult New Zealand White rabbit, exposed to local heart X-rays and adriamycin</td><td>Anthracycline</td><td>Cardiac histopathology</td><td>Cardiac histopathology worse in combined treatment (radiation + adriamycin) group</td><td>Difficult to determine magnitude of differential effect on radiation response (irradiated vs control) of adriamycin</td></tr><tr><td>Myers and Lu [120] Yan et al. [121] Du et al. [122]</td><td>Adult mice, thorax exposure to X-rays, pretreated with anti-PD-1 antibody or control IgG</td><td>Anti-PD-1</td><td>Animal survival, cardiac function, cardiac cytokine levels, cardiac immune cell infiltration</td><td>All outcomes are worse in combined treatment group (radiation + anti-PD-1)</td><td>Sex of the mice unknown. Difficult to determine magnitude of differential effect on radiation response (irradiated vs control) of anti-PD-1 or control IgG</td></tr><tr><td>Seemann et al. [123]</td><td>Adult male mice, exposed to local heart irradiation and lapatinib</td><td>Lapatinib (tyrosine kinase inhibitor)</td><td>Cardiac function, Cardiac microvascular density, cardiac immune cell infiltration, cardiac fibrosis</td><td>Lapatinib reduced immune cell infiltration. No other modification of radiation effects</td><td>Difficult to determine magnitude of differential effect on radiation response (irradiated vs control) of lapatinib</td></tr></tbody></table>
<table><caption>**Table 5 (continued)**</caption><thead><tr><th>Reference</th><th>Animal model</th><th>Variable</th><th>Endpoints</th><th>Variable effect on radiation endpoints</th><th>Notes</th></tr></thead><tbody><tr><td>Sridharan et al. [124]</td><td>Adult male Sprague-Dawley rats, exposed to local heart irradiation and sunitinib</td><td>Sunitinib (tyrosine kinase inhibitor)</td><td>Cardiac cell apoptosis, cardiac oxidative stress, mitochondrial swelling</td><td>Sunitinib reduced the effects of radiation on apoptosis, did not alter oxidative stress, and aggravated mitochondrial swelling</td><td>Difficult to determine magnitude of differential effect on radiation response (irradiated vs control) of sunitinib</td></tr><tr><td>Kotla et al. [125]</td><td>Adult LDLR<sup>-/-</sup> mice on high fat diet and exposed to neck and thorax X-rays, followed by TAC and PARP inhibitor treatment</td><td>PARP inhibitor</td><td>Cardiac function, artery stenosis, artery wall thickness, perivascular fibrosis, Mac3<sup>+</sup> cells (macrophages) in vascular lesions</td><td>PARP inhibition reduced the effects of radiation on cardiac function, artery stenosis, and Mac3<sup>+</sup> cell number</td><td>High fat diet and TAC were used to induce atherosclerosis. Difficult to determine magnitude of differential effect on radiation response (irradiated vs control) of PARP inhibitor</td></tr></tbody></table>

ApoE apolipoprotein E, AST aspartate immunotransferase, BUN blood urea nitrogen, HDL high-density lipoprotein, IgG immunoglobulin G, LDLR low-density lipoprotein receptor, PARP poly(ADP-ribose) polymerase, PD-1 programmed cell death protein 1, TAC thoracic aorta coarctation
many of the studies presented, particularly of the LSS [9–11, 37], groups of nuclear workers (IARC 15-country and INWORKS nuclear worker studies [38, 39], Mayak nuclear workers [40–42, 44–46]) is the overlap in subjects included, a feature also of the systematic review from which they were drawn [12]. It is very likely that there is inter-study heterogeneity of effect in the present study, reflecting the heterogeneity that was observed in the systematic review from which it is drawn [12]. Some part of the heterogeneity in the previous review is clearly driven by differences in endpoint sensitivity, by age at exposure, by dose and dose rate, and as noted above mortality vs incidence, but even after accounting for the effect of these heterogeneity remained [12]. Such heterogeneity complicates any causal interpretation of the results presented.

Confounding is likely to be specific to each study and the effects of adjustment could rarely be generalized to other studies. Residual confounding could be an issue, if the potential confounding variable is measured with substantial error. Effect modification is likely to be much more easily compared between studies, although the evidence assembled here does not suggest that even for such easily and reliably measured variables as sex and age at exposure there are consistent effects within studies (Tables 1, 2 and 3). These differences in modifying effect between cohort may reflect the play of chance, but it is also possible that there are underlying differences between the cohorts. Medical and lifestyle factors are differently available in the studies considered, with more detailed information among studies of radiotherapeutic exposure, where radiation doses are high to moderate. However, the number of patients included in these medical studies is generally rather small, limiting study of specific endpoints. In contrast, in studies on workers or in general population, generally few potential confounding variables can be collected as the large number of people recruited and the way of collecting the information does not usually allow such information to be obtained. In our systematic review [12], among the lower dose studies with detailed information on lifestyle factors and a large number of included people there were only a few occupational cohorts, principally the Mayak worker cohort [40–42, 44–46], the Semipalatinsk cohort [53], and, with a rather smaller number of people included, the French nuclear fuel cycle workers [47, 48] and the Korean radiation worker cohorts [51, 52]. For the purposes of maximizing statistical power, specific CVD outcomes are analyzed together, but potential confounders could act differently on the different outcomes and their specific

effect could be unseen in a pooled analysis of heterogeneous outcomes.

As summarized in Tables 1, 2 and 3, in general many epidemiological studies now have quite rich lifestyle, environmental and medical information. As highlighted in the Results there are over 30 other studies that clearly have such cofactor information, although in all cases best use has not been made of this in the publications for the purposes of assessing effects of potential confounding factors or effect modifying factors.

A limitation of our analysis is that statistical significance cannot be attached to the difference made by potentially confounding factors, since the reported coefficients would necessarily be highly correlated, and from the published data this correlation is impossible to determine. We therefore judge that this has to remain as we describe it in the Methods, based simply on the size and sign of the coefficients. However, as we outline in the Methods, one of the criteria for risk modifying factors is based on statistical significance. Clearly the particular levels of magnitude we chose to determine the seriousness of potentially confounding variables, likewise the levels of difference made by risk modifying factors are both somewhat arbitrary. Another limitation of the analysis is the degree of overlap in two particular studies, specifically two of the most important and informative ones, the LSS [9, 10, 37] and the Mayak workers [40–46], although not in any of the other studies listed in Tables 1, 2, 3 and 4. However, given the form of the analysis, bias would not result from this. At most there would be a tendency for findings (of potential confounding or risk modification) to be inflated by these correlated findings. As may be inferred from the results presented in Tables 3 and 4, there is little evidence for this, although the Mayak worker data do show a similar direction of effect made by adjustment to two overlapping mortality endpoints, IHD and all CVD [41].

In many studies in which adjustment is made for certain covariates, these are assayed at a number of time points and this information is then used to adjust for health endpoints after that point. Some of these covariates may also affect competing risks, for example cancer, and it is possible that they may affect both baseline CVD risk as well as radiation-associated excess risk; however, the evidence we have presented (Tables 1, 2 and 3) does not suggest that this is likely. Competing risks may well not be independent of CVD, so that the censoring they introduce will be informative. In this case consideration may have to be given to non-standard ways of analyzing the data. There are a number of statistical methods to assess effects of two or more competing risks [126]. One
of the most popular is the so-called subdistribution hazard of Fine and Gray [127].

In summary, because of the multifactorial etiology of CVD, medical and lifestyle factors are clearly crucial variables to take into account in analysis of the dose response of these endpoints. The heterogeneity of the studied populations and of the type of exposure and dosimetry complicates drawing conclusions on the impact of medical and lifestyle factors on the dose response relationship between exposure to radiation and CVD. Nevertheless, we found a large number of studies in which there is information on effect of adjusting for certain lifestyle/environmental/medical variables, although in the larger number of studies previously assessed this information was not available, even if the relevant variables had clearly been assessed. We found limited evidence of potential confounding of radiation effects on CVD (Tables 1, 2 and 3); substantial differences were made by adjustment in four studies, but the uncertainties in all cases were substantial, so that little weight can be attached. There is much less information on potential modifying variables of radiation effect; nevertheless there is some evidence of the effects of age at exposure and sex, although not always in the same endpoints in different studies. However, in most of the studies reported here no analysis was reported of modifying effects of these or any other variable (Tables 1, 2 and 3). There is little evidence of modification resulting from variation in lagging period (Table 4). Efforts should be made to include in future studies as much as possible precise information on these variables and if available specific analysis on their impact on the dose response relationship should be assessed. It is important that analyses of radiation-associated CVD clearly demonstrate the effect of adjustment for the available lifestyle/environmental/medical variables, and also assess the potential modifying effect of these variables on the radiation dose response.

### Acknowledgements

The authors gratefully acknowledge the detailed and helpful comments of the three referees. The work of MPL was supported by the Intramural Research Program of the National Institutes of Health, the National Cancer Institute, Division of Cancer Epidemiology and Genetics.

### Authors' contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by MPL. The first draft of the manuscript was written by MPL and all authors commented on subsequent versions of the manuscript. All authors read and approved the final manuscript.

### Funding

The work of Mark Little was supported by the Intramural Research Program of the National Institutes of Health, the National Cancer Institute, Division of Cancer Epidemiology and Genetics.

### Availability of data and materials

All data used are listed in Tables 1, 2, 3 and 4.

### Declarations

#### Ethics approval and consent to participate

Ethical approval is not required, as all data used are in the public domain. Consent to participate in the study is not required, as all data used are in the public domain.

#### Consent for publication

Consent to publish is not required, as all data used are in the public domain.

#### Competing interests

Andrew Einstein has received speaker fees from Ionetix; has received consulting fees from WL Gore & Associates; has received authorship fees from Wolters Kluwer Healthcare–UpToDate; and has received grants to his institution from Attralus, Canon Medical Systems, Eidos Therapeutics, GE Healthcare, Pfizer, Roche Medical Systems, WL Gore & Associates, and XyloCor Therapeutics; none of these are related to the present work. No other authors report conflicts of interest.

#### Author details

¹Radiation Epidemiology Branch, National Cancer Institute, Room 7E546, 9609 Medical Center Drive MSC 9778, Bethesda, MD 20892-9778, USA. ²Faculty of Health and Life Sciences, Oxford Brookes University, Headington Campus, Oxford OX3 0BP, UK. ³Division of Radiation Health, University of Arkansas for Medical Sciences, Little Rock, AR, USA. ⁴Institut de Radioprotection et de Sureté Nucléaire, Fontenay Aux Roses, France. ⁵Clinical Department, Southern Ursals Biophysics Institute, Chelyabinsk Region, Ozyorskoe Shosse 19, Ozyorsk 456780, Russia. ⁶Department of Epidemiology and Biostatistics, School of Medicine, University of California San Francisco, 550 16th St 2nd floor, San Francisco, CA 94143, USA. ⁷Seymour, Paul, and Gloria Milstein Division of Cardiology, Department of Medicine, and Department of Radiology, Columbia University Irving Medical Center/New York-Presbyterian Hospital, New York, NY, USA. ⁸Biology and Environmental Chemistry Division, Sustainable System Research Laboratory, Central Research Institute of Electric Power Industry (CRIEPI), 1646 Abiko, Chiba 270-1194, Japan.

Received: 23 November 2023 Accepted: 23 April 2024

Published online: 15 June 2024

### References

1. World Health Organization (WHO): WHO Health statistics and information systems https://www.who.int/healthinfo/statistics/mortalityRawdata/en/. World Health Organization (WHO); 2019.

2. The top 10 causes of death. https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death#:~:text=The%20world's%20biggest%20killer%20is,8.9%20million%20deaths%20in%202019.

3. Cardiovascular diseases https://www.who.int/health-topics/cardiovascular-diseases#tab=tab_1.

4. Wilson PWF, D'Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97(18):1837–47.

5. Dhingra R, Vasan RS. Age as a risk factor. Med Clin North America. 2012;96(1):87–91.

6. Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, McQueen M, Budaj A, Pais P, Varigos J, Lisheng L. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet. 2004;364(9438):937–52.

7. Adams MJ, Hardenbergh PH, Constine LS, Lipshultz SE. Radiation-associated cardiovascular disease. Crit Rev Oncol Hematol. 2003;45(1):55–75.

8. International Commission on Radiological Protection (ICRP). Non-stochastic effects of ionizing radiation. Publication 41. Annals ICRP. 1984;14(3):1–33.
9. Yamada M, Wong FL, Fujiwara S, Akahoshi M, Suzuki G. Noncancer disease incidence in atomic bomb survivors, 1958–1998. Radiat Res. 2004;161(6):622–32.

10. Shimizu Y, Kodama K, Nishi N, Kasagi F, Suyama A, Soda M, Grant EJ, Sugiyama H, Sakata R, Moriwaki H, et al. Radiation exposure and circulatory disease risk: Hiroshima and Nagasaki atomic bomb survivor data, 1950–2003. BMJ. 2010;340:b5349.

11. Little MP, Azizova TV, Bazyka D, Bouffler SD, Cardis E, Chekin S, Chumak VV, Cucinotta FA, de Vathaire F, Hall P, et al. Systematic review and meta-analysis of circulatory disease from exposure to low-level ionizing radiation and estimates of potential population mortality risks. Environ Health Perspect. 2012;120(11):1503–11.

12. Little MP, Azizova TV, Richardson DB, Tapio S, Bernier MO, Kreuzer M, Cucinotta FA, Bazyka D, Chumak V, Ivanov VK, et al. Ionising radiation and cardiovascular disease: systematic review and meta-analysis. BMJ. 2023;380:e072924.

13. Mulrooney DA, Hyun G, Ness KK, Ehrhardt MJ, Yasui Y, Duprez D, Howell RM, Leisenring WM, Constine LS, Tonorezos E, et al. Major cardiac events for adult survivors of childhood cancer diagnosed between 1970 and 1999: report from the childhood cancer survivor study cohort. BMJ. 2020;368:m6794.

14. Tukenova M, Guibout C, Oberlin O, Doyon F, Mousannif A, Haddy N, Guérin S, Pacquement H, Aouba A, Hawkins M, et al. Role of cancer treatment in long-term overall and cardiovascular mortality after childhood cancer. J Clin Oncol. 2010;28(8):1308–15.

15. Haddy N, Diallo S, El-Fayech C, Schwartz B, Pein F, Hawkins M, Veres C, Oberlin O, Guibout C, Pacquement H, et al. Cardiac diseases following childhood cancer treatment: cohort study. Circulation. 2016;133(1):31–8.

16. Mansouri I, Allodji RS, Hill C, El-Fayech C, Pein F, Diallo S, Schwartz B, Vu-Bezin G, Veres C, Souchard V, et al. The role of irradiated heart and left ventricular volumes in heart failure occurrence after childhood cancer. Eur J Heart Fail. 2019;21(4):509–18.

17. van Nimwegen FA, Schaapveld M, Cutter DJ, Janus CPM, Krol AD, Hauptmann M, Kooijman K, Roesink J, van der Maazen R, Darby SC, et al. Radiation dose-response relationship for risk of coronary heart disease in survivors of Hodgkin lymphoma. J Clin Oncol. 2016;34(3):235–43.

18. van Nimwegen FA, Ntentas G, Darby SC, Schaapveld M, Hauptmann M, Lugtenburg PJ, Janus CPM, Daniels L, van Leeuwen FE, Cutter DJ, Aleman BMP. Risk of heart failure in survivors of Hodgkin lymphoma: effects of cardiac exposure to radiation and anthracyclines. Blood. 2017;129(16):2257–65.

19. Darby SC, Ewertz M, McGale P, Bennet AM, Blom-Goldman U, Brønnum D, Correa C, Cutter D, Gagliardi G, Gigante B, et al. Risk of ischemic heart disease in women after radiotherapy for breast cancer. N Engl J Med. 2013;368(11):987–98.

20. Roos CTG, van den Bogaard VAB, Greuter MJW, Vliegenthart R, Schuit E, Langendijk JA, van der Schaaf A, Crijns APG, Maduro JH. Is the coronary artery calcium score associated with acute coronary events in breast cancer patients treated with radiotherapy? Radiother Oncol. 2018;126(1):170–6.

21. van den Bogaard VAB, Spoor DS, van der Schaaf A, van Dijk LV, Schuit E, Sijtsema NM, Langendijk JA, Maduro JH, Crijns APG. The importance of radiation dose to the atherosclerotic plaque in the left anterior descending coronary artery for radiation-induced cardiac toxicity of breast cancer patients? Int J Radiat Oncol Biol Phys. 2021;110(5):1350–9.

22. Jacobse JN, Duane FK, Boekel NB, Schaapveld M, Hauptmann M, Hooning MJ, Seynaeve CM, Baaijens MHA, Gietema JA, Darby SC, et al. Radiation dose-response for risk of myocardial infarction in breast cancer survivors. Int J Radiat Oncol Biol Phys. 2019;103(3):595–604.

23. Boekel NB, Duane FK, Jacobse JN, Hauptmann M, Schaapveld M, Sonke GS, Gietema JA, Hooning MJ, Seynaeve CM, Maas A, et al. Heart failure after treatment for breast cancer. Eur J Heart Fail. 2020;22(2):366–74.

24. Baaken D, Merzenich H, Schmidt M, Bekes I, Schwentner L, Janni W, Wöckel A, Mayr M, Mose S, Merz T, et al. A nested case-control study on radiation dose-response for cardiac events in breast cancer patients in Germany. The Breast. 2022;65:1–7.

25. Chung SY, Oh J, Chang JS, Shin J, Kim KH, Chun K-H, Keum KC, Suh C-O, Kang S-M, Kim YB. Risk of cardiac disease in patients with breast cancer: impact of patient-specific factors and individual heart dose from

three-dimensional radiation therapy planning. Int J Radiat Oncol Biol Phys. 2021;110(2):473–81.

26. Kim K, Chung SY, Oh C, Cho I, Kim KH, Byun HK, Yoon HI, Oh J, Chang JS. Automated coronary artery calcium scoring in patients with breast cancer to assess the risk of heart disease following adjuvant radiation therapy. The Breast. 2022;65:77–83.

27. Dess RT, Sun Y, Matuszak MM, Sun G, Soni PD, Bazzi L, Murthy VL, Hearn JWD, Kong FM, Kalemkerian GP, et al. Cardiac events after radiation therapy: combined analysis of prospective multicenter trials for locally advanced non-small-cell lung cancer. J Clin Oncol. 2017;35(13):1395–402.

28. Xue J, Han C, Jackson A, Hu C, Yao H, Wang W, Hayman J, Chen W, Jin J, Kalemkerian GP, et al. Doses of radiation to the pericardium, instead of heart, are significant for survival in patients with non-small cell lung cancer. Radiother Oncol. 2019;133:213–9.

29. Atkins KM, Bitterman DS, Chaunzwa TL, Williams CL, Rahman R, Kozono DE, Baldini EH, Aerts HJWL, Tamarappoo BK, Hoffmann U, et al. Statin use, heart radiation dose, and survival in locally advanced lung cancer. Pract Radiat Oncol. 2021;11(5):e459–67.

30. Atkins KM, Rawal B, Chaunzwa TL, Lamba N, Bitterman DS, Williams CL, Kozono DE, Baldini EH, Chen AB, Nguyen PL, et al. Cardiac radiation dose, cardiac disease, and mortality in patients with lung cancer. J Am Coll Cardiol. 2019;73(23):2976–87.

31. Yegya-Raman N, Wang K, Kim S, Reyhan M, Deek MP, Sayan M, Li D, Patel M, Malhotra J, Aisner J, et al. Dosimetric predictors of symptomatic cardiac events after conventional-dose chemoradiation therapy for inoperable NSCLC. J Thorac Oncol. 2018;13(10):1508–18.

32. Liao J, Liu T, Zhang H, Cai F, Chen J, Dang J. The role of postoperative radiation therapy for completely resected stage III thymoma and effect of higher heart radiation dose on risk of cardiovascular disease: A retrospective cohort study. Int J Surg. 2018;53:345–9.

33. Sadetzki S, Chetrit A, Boursi B, Luxenburg O, Novikov I, Cohen A. Childhood exposure to low to moderate doses of ionizing radiation and the risk of vascular diseases. Am J Epidemiol. 2021;190(3):423–30.

34. Adams MJ, Fisher SG, Lipshultz SE, Shore RE, Constine LS, Stovall M, Dozier A, Thevenet-Morrison K, Block R, Schwartz RG, Pearson TA. Risk of coronary events 55 years after thymic irradiation in the Hempelmann cohort. Cardio-Oncol. 2018;4:1–3.

35. Tran V, Zablotska LB, Brenner AV, Little MP. Radiation-associated circulatory disease mortality in a pooled analysis of 77,275 patients from the Massachusetts and Canadian tuberculosis fluoroscopy cohorts. Sci Rep. 2017;7:44147.

36. Shrestha S, Bates JE, Liu Q, Smith SA, Oeffinger KC, Chow EJ, Gupta AC, Owens CA, Constine LS, Hoppe BS, et al. Radiation therapy related cardiac disease risk in childhood cancer survivors: Updated dosimetry analysis from the childhood cancer survivor study. Radiother Oncol. 2021;163:199–208.

37. Takahashi I, Cologne J, Haruta D, Yamada M, Takahashi T, Misumi M, Fujiwara S, Matsumoto M, Kihara Y, Hida A, Ohishi W. Association between prevalence of peripheral artery disease and radiation exposure in the atomic bomb survivors. J Am Heart Assoc. 2018;7(23):e008921.

38. Vrijheid M, Cardis E, Ashmore P, Auvinen A, Bae JM, Engels H, Gilbert E, Gulis G, Habib R, Howe G, et al. Mortality from diseases other than cancer following low doses of ionizing radiation: results from the 15-Country Study of nuclear industry workers. Int J Epidemiol. 2007;36(5):1126–35.

39. Gillies M, Richardson DB, Cardis E, Daniels RD, O'Hagan JA, Haylock R, Laurier D, Leuraud K, Moissonnier M, Schubauer-Berigan MK, et al. Mortality from circulatory diseases and other non-cancer outcomes among nuclear workers in France, the United Kingdom and the United States (INWORKS). Radiat Res. 2017;188(3):276–90.

40. Azizova TV, Grigoryeva ES, Haylock RGE, Pikulina MV, Moseeva MB. Ischaemic heart disease incidence and mortality in an extended cohort of Mayak workers first employed in 1948–1982. Br J Radiol. 2015;88(1054):20150169.

41. Azizova TV, Bannikova MV, Grigoryeva ES, Briks KV, Hamada N. Mortality from various diseases of the circulatory system in the Russian Mayak nuclear worker cohort: 1948–2018. J Radiol Prot. 2022;42(2):021511.

42. Azizova TV, Haylock RGE, Moseeva MB, Bannikova MV, Grigoryeva ES. Cerebrovascular diseases incidence and mortality in an extended Mayak worker cohort 1948–1982. Radiat Res. 2014;182(5):529–44.
43. Azizova TV, Moseeva MB, Grigoryeva ES, Hamada N. Incidence risks for cerebrovascular diseases and types of stroke in a cohort of Mayak PA workers. Radiat Environ Biophys. 2022;61(1):5–16.

44. Azizova TV, Grigorieva ES, Hunter N, Pikulina MV, Moseeva MB. Risk of mortality from circulatory diseases in Mayak workers cohort following occupational radiation exposure. J Radiol Prot. 2015;35(3):517–38.

45. Azizova TV, Bannikova MV, Grigorieva ES, Bagaeva YP, Azizova EV. Risk of lower extremity arterial disease in a cohort of workers occupationally exposed to ionizing radiation over a prolonged period. Radiat Environ Biophys. 2016;55(2):147–59.

46. Azizova T, Briks K, Bannikova M, Grigoryeva E. Hypertension incidence risk in a cohort of Russian workers exposed to radiation at the Mayak Production Association over prolonged periods. Hypertension. 2019;73(6):1174–84.

47. Bouet S, Davesne E, Samson E, Jovanovic I, Blanchardon E, Challeton-de Vathaire C, Richardson DB, Leuraud K, Laurier D, Laurent O. Analysis of the association between ionizing radiation and mortality in uranium workers from five plants involved in the nuclear fuel production cycle in France. Int Arch Occup Environ Health. 2019;92(2):249–62.

48. Drubay D, Caër-Lorho S, Laroche P, Laurier D, Rage E. Mortality from circulatory system diseases among French uranium miners: a nested case-control study. Radiat Res. 2015;183(5):550–62.

49. Boice JD Jr, Cohen SS, Mumma MT, Hagemeyer DA, Chen H, Golden AP, Yoder RC, Dauer LT. Mortality from leukemia, cancer and heart disease among U.S. nuclear power plant workers, 1957–2011. Int J Radiat Biol. 2022;98(4):657–78.

50. Elgart SR, Little MP, Chappell LJ, Milder CM, Shavers MR, Huff JL, Patel ZS. Radiation exposure and mortality from cardiovascular disease and cancer in early NASA astronauts. Sci Rep. 2018;8(1):8480.

51. Cha ES, Zablotska LB, Bang YJ, Lee WJ. Occupational radiation exposure and morbidity of circulatory disease among diagnostic medical radiation workers in South Korea. Occup Environ Med. 2020;77(11):752–60.

52. Park S, Lee DN, Jin YW, Cha ES, Jang W-I, Park S, Seo S. Non-cancer disease prevalence and association with occupational radiation exposure among Korean radiation workers. Sci Rep. 2021;11(1):22415.

53. Markabayeva A, Bauer S, Pivina L, Bjorklund G, Chirumbolo S, Kerimkulova A, Semenova Y, Belikhina T. Increased prevalence of essential hypertension in areas previously exposed to fallout due to nuclear weapons testing at the Semipalatinsk Test Site, Kazakhstan. Environ Res. 2018;167:129–35.

54. Krestinina LY, Silkin SS, Degteva M, Akleyev AV. Risk of death from circulatory system diseases in a Ural population cohort exposed to accidental radiation between 1950 and 2015. Radiatsionnaya Gygiena. 2019;12(1):52–61.

55. Mueller S, Fullerton HJ, Stratton K, Leisenring W, Weathers RE, Stovall M, Armstrong GT, Goldsby RE, Packer RJ, Sklar CA, et al. Radiation, atherosclerotic risk factors, and stroke risk in survivors of pediatric cancer: a report from the Childhood Cancer Survivor Study. Int J Radiat Oncol Biol Phys. 2013;86(4):649–55.

56. Fullerton HJ, Stratton K, Mueller S, Leisenring WW, Armstrong GT, Weathers RE, Stovall M, Sklar CA, Goldsby RE, Robison LL, Krull KR. Recurrent stroke in childhood cancer survivors. Neurology. 2015;85(12):1056–64.

57. Mulrooney DA, Armstrong GT, Huang S, Ness KK, Ehrhardt MJ, Joshi VM, Plana JC, Soliman EZ, Green DM, Srivastava D, et al. Cardiac outcomes in adult survivors of childhood cancer exposed to cardiotoxic therapy: a cross-sectional Study. Ann Intern Med. 2016;164(2):93–101.

58. Haddy N, Mousannif A, Tukenova M, Guibout C, Grill J, Dhermain F, Pacquement H, Oberlin O, El-Fayech C, Rubino C, et al. Relationship between the brain radiation dose for the treatment of childhood cancer and the risk of long-term cerebrovascular mortality. Brain. 2011;134(Pt 5):1362–72.

59. El-Fayech C, Haddy N, Allodji RS, Veres C, Diop F, Kahlouche A, Llanas D, Jackson A, Rubino C, Guibout C, et al. Cerebrovascular diseases in childhood cancer survivors: role of the radiation dose to Willis circle arteries. Int J Radiat Oncol Biol Phys. 2017;97(2):278–86.

60. Cutter DJ, Schaapveld M, Darby SC, Hauptmann M, van Nimwegen FA, Krol ADG, Janus CPM, van Leeuwen FE, Aleman BMP. Risk of valvular heart disease after treatment for Hodgkin lymphoma. J Natl Cancer Inst. 2015;107(4):djv008.

61. Hahn E, Jiang H, Ng A, Bashir S, Ahmed S, Tsang R, Sun A, Gospodarowicz M, Hodgson D. Late cardiac toxicity after mediastinal radiation therapy for Hodgkin lymphoma: contributions of coronary artery and whole heart dose-volume variables to risk prediction. Int J Radiat Oncol Biol Phys. 2017;98(5):1116–23.

62. Moignier A, Broggio D, Derreumaux S, Beaudre A, Girinsky T, Paul JF, Drubay D, Lefkopoulos D, Franck D, Aubert B, et al. Coronary stenosis risk analysis following Hodgkin lymphoma radiotherapy: A study based on patient specific artery segments dose calculation. Radiother Oncol. 2015;117(3):467–72.

63. Killander F, Wieslander E, Karlsson P, Holmberg E, Lundstedt D, Holmberg L, Werner L, Koul S, Haghanegi M, Kjellen E, et al. No increased cardiac mortality or morbidity of radiation therapy in breast cancer patients after breast-conserving surgery: 20-year follow-up of the randomized SWEBCGRT Trial. Int J Radiat Oncol Biol Phys. 2020;107(4):701–9.

64. Abraham A, Sanghera KP, Gheisari F, Koumna S, Riauka T, Ghosh S, Warkentin H, Gabos Z, Chafe S, Tankel K, et al. Is radiation-induced cardiac toxicity reversible? Prospective evaluation of patients with breast cancer enrolled in a phase 3 randomized controlled trial. Int J Radiat Oncol Biol Phys. 2022;113(1):125–34.

65. Errahmani MY, Locquet M, Spoor D, Jimenez G, Camilleri J, Bernier M-O, Broggio D, Monceau V, Ferrières J, Thariat J, et al. Association between cardiac radiation exposure and the risk of arrhythmia in breast cancer patients treated with radiotherapy: a case-control study. Front Oncol. 2022;12:892882.

66. Zureick AH, Grzywacz VP, Almhariq MF, Silverman BR, Vayntraub A, Chen PY, Gustafson GS, Jawad MS, Dilworth JT. Dose to the left anterior descending artery correlates with cardiac events after irradiation for breast cancer. Int J Radiat Oncol Biol Phys. 2022;114(1):130–9.

67. Tagami T, Almhariq MF, Balanescu DV, Quinn TJ, Dilworth JT, Franklin BA, Bilolikar A. Usefulness of coronary computed tomographic angiography to evaluate coronary artery disease in radiotherapy-treated breast cancer survivors. Am J Cardiol. 2021;143:14–20.

68. Wang K, Eblan MJ, Deal AM, Lipner M, Zagar TM, Wang Y, Mavroidis P, Lee CB, Jensen BC, Rosenman JG, et al. Cardiac toxicity after radiotherapy for stage III non-small-cell lung cancer: Pooled analysis of dose-escalation trials delivering 70 to 90 Gy. J Clin Oncol. 2017;35(13):1387–94.

69. Wang K, Pearlstein KA, Patchett ND, Deal AM, Mavroidis P, Jensen BC, Lipner MB, Zagar TM, Wang Y, Lee CB, et al. Heart dosimetric analysis of three types of cardiac toxicity in patients treated on dose-escalation trials for Stage III non-small-cell lung cancer. Radiother Oncol. 2017;125(2):293–300.

70. Lee CC, Zheng H, Soon YY, Foo LL, Koh WY, Leong CN, Vellayappan B, Tey JCS, Tham IWK. Association between radiation heart dosimetric parameters, myocardial infarct and overall survival in stage 3 non-small cell lung cancer treated with definitive thoracic radiotherapy. Lung Cancer. 2018;120:54–9.

71. Borkenhagen JF, Bergom C, Rapp CT, Klawikowski SJ, Rein LE, Gore EM. Dosimetric predictors of cardiotoxicity in thoracic radiotherapy for lung cancer. Clin Lung Cancer. 2019;20(6):435–41.

72. Chen L, Ta S, Wu W, Wang C, Zhang Q. Prognostic and added value of echocardiographic strain for prediction of adverse outcomes in patients with locally advanced non-small cell lung cancer after radiotherapy. Ultrasound Med Biol. 2019;45(1):98–107.

73. Cho S-G, Kim Y-H, Park H, Park KS, Kim J, Ahn S-J, Bom H-S. Prediction of cardiac events following concurrent chemoradiation therapy for non-small-cell lung cancer using FDG PET. Ann Nucl Med. 2022;36(5):439–49.

74. Ni L, Koshy M, Connell P, Pitroda S, Golden DW, Al-Hallaq H, Hubert G, Kauffman G, McCall A, Malik R. Heart V5 predicts cardiac events in unresectable lung cancer patients undergoing chemoradiation. J Thorac Dis. 2019;11(6):2229–39.

75. Wang X, Palaskas NL, Yusuf SW, Abe JI, Lopez-Mattei J, Banchs J, Gladish GW, Lee P, Liao Z, Deswal A, Lin SH. Incidence and onset of severe cardiac events after radiotherapy for esophageal cancer. J Thorac Oncol. 2020;15(10):1682–90.

76. Cai G, Li C, Yu J, Meng X. Heart dosimetric parameters were associated with cardiac events and overall survival for patients with locally advanced esophageal cancer receiving definitive radiotherapy. Front Oncol. 2020;10:153.
77. Dorth JA, Patel PR, Broadwater G, Brizel DM. Incidence and risk factors of significant carotid artery stenosis in asymptomatic survivors of head and neck cancer after radiotherapy. Head Neck. 2014;36(2):215-9.

78. van Aken ESM, van der Laan HP, Bijl HP, van den Bosch L, van den Hoek JGM, Dieters M, Steenbakkers RJHM, Langendijk JA. Risk of ischaemic cerebrovascular events in head and neck cancer patients is associated with carotid artery radiation dose. Radiother Oncol. 2021;157:182-7.

79. Little MP, Kleinerman RA, Stovall M, Smith SA, Mabuchi K. Analysis of dose response for circulatory disease after radiotherapy for benign disease. Int J Radiat Oncol Biol Phys. 2012;84(5):1101-9.

80. Green DM, Grigoriev YA, Nan B, Takashima JR, Norkool PA, D'Angio GJ, Breslow NE. Congestive heart failure after treatment for Wilms' tumor: A report from the National Wilms' Tumor Study Group. J Clin Oncol. 2001;19(7):1926-34.

81. Maraldo MV, Giusti F, Vogelius IR, Lundemann M, van der Kaaij MA, Ramadan S, Meulemans B, Henry-Amar M, Aleman BM, Raemaekers J, et al. Cardiovascular disease after treatment for Hodgkin's lymphoma: an analysis of nine collaborative EORTC-LYSA trials. Lancet Haematol. 2015;2(11):e492-502.

82. Lorenzen EL, Rehammar JC, Jensen M-B, Ewertz M, Brink C. Radiation-induced risk of ischemic heart disease following breast cancer radiotherapy in Denmark, 1977-2005. Radiother Oncol. 2020;152:103-10.

83. Nakashima E, Akahoshi M, Nerishi K, Fujiwara S. Systolic blood pressure and systolic hypertension in adolescence of atomic bomb survivors exposed in utero. Radiat Res. 2007;168(5):593-9.

84. Tatsukawa Y, Nakashima E, Yamada M, Funamoto S, Hida A, Akahoshi M, Sakata R, Ross NP, Kasagi F, Fujiwara S, Shore RE. Cardiovascular disease risk among atomic bomb survivors exposed in utero, 1978-2003. Radiat Res. 2008;170(3):269-74.

85. Kreuzer M, Dufey F, Sogl M, Schnelzer M, Walsh L. External gamma radiation and mortality from cardiovascular diseases in the German WISMUT uranium miners cohort study, 1946-2008. Radiat Environ Biophys. 2013;52(1):37-46.

86. Tatarenko O. Expert evaluation of cases of myocardial infarction in the Chernobyl clean-up workers with hypertension. Kardiologija v Belarusi. 2018;10(4):470-6.

87. Krasnikova LI, Buzunov VO, Solonovitch SI. Radiation and non-radiation factors impact on development of cerebrovascular diseases in the Chernobyl clean-up workers. The epidemiological study results. Probl Radiats Med Radiobiol. 2013;18:89-101.

88. Semenova Y, Rakhimova I, Nurpeissov T, Alikeyeva G, Khaibullin T, Kovalchuk V, Ainabekova Y, Yurkovskaya O, Glushkova N, Pivina L, et al. Epidemiology of stroke and transient ischemic attacks in the population of the territories adjacent to the former Semipalatinsk Nuclear Test Site, Kazakhstan. Radiat Environ Biophys. 2022;61(1):17-28.

89. Takahashi I, Shimizu Y, Grant EJ, Cologne J, Ozasa K, Kodama K. Heart disease mortality in the Life Span Study, 1950-2008. Radiat Res. 2017;187(3):319-32.

90. Little MP, Pawel D, Misumi M, Hamada N, Cullings HM, Wakeford R, Ozasa K. Lifetime mortality risk from cancer and circulatory disease predicted from the Japanese atomic bomb survivor Life Span Study data taking account of dose measurement error. Radiat Res. 2020;194(3):259-76.

91. Zielinski JM, Ashmore PJ, Band PR, Jiang H, Shilnikova NS, Tait VK. Krewski D. Low dose ionizing radiation exposure and cardiovascular disease mortality: cohort study based on Canadian national dose registry of radiation workers. Int J Occup Med Environ Health. 2009;22(1):27-33.

92. Zhang W, Haylock RGE, Gillies M, Hunter N. Mortality from heart diseases following occupational radiation exposure: analysis of the National Registry for Radiation Workers (NRRW) in the United Kingdom. J Radiol Prot. 2019;39(2):327-53.

93. Hinksman CA, Haylock RGE, Gillies M. Cerebrovascular disease mortality after occupational radiation exposure among the UK national registry for radiation workers cohort. Radiat Res. 2022;197(5):459-70.

94. Zablotska LB, Fenske N, Schnelzer M, Zhivin S, Laurier D, Kreuzer M. Analysis of mortality in a pooled cohort of Canadian and German uranium processing workers with no mining experience. Int Arch Occup Environ Health. 2018;91(1):91-103.

95. Lane RSD, Frost SE, Howe GR, Zablotska LB. Mortality (1950-1999) and cancer incidence (1969-1999) in the cohort of Eldorado uranium workers. Radiat Res. 2010;174(6):773-85.

96. Anderson JL, Bertke SJ, Yiin J, Kelly-Reif K, Daniels RD. Ischaemic heart and cerebrovascular disease mortality in uranium enrichment workers. Occup Environ Med. 2021;78(2):105-11.

97. Golden AP, Ellis ED, Cohen SS, Mumma MT, Leggett RW, Wallace PW, Girardi D, Watkins JP, Shore RE, Boice JD. Updated mortality analysis of the Mallinckrodt uranium processing workers, 1942-2012. Int J Radiat Biol. 2022;98(4):701-21.

98. Boice JD Jr, Cohen SS, Mumma MT, Ellis ED, Cragle DL, Eckerman KF, Wallace PW, Chadda B, Sonderman JS, Wiggs LD, et al. Mortality among mound workers exposed to polonium-210 and other sources of radiation, 1944-1979. Radiat Res. 2014;181(2):208-28.

99. Boice JD, Cohen SS, Mumma MT, Chen H, Golden AP, Beck HL, Till JE. Mortality among U.S. military participants at eight aboveground nuclear weapons test series. Int J Radiat Biol. 2022;98(4):679-700.

100. Boice JD Jr, Cohen SS, Mumma MT, Golden AP, Howard SC, Girardi DJ, Ellis ED, Bellamy MB, Dauer LT, Samuels C, et al. Mortality among workers at the Los Alamos National Laboratory, 1943-2017. Int J Radiat Biol. 2022;98(4):722-49.

101. Gillies M, Haylock RGE. Mortality and cancer incidence 1952-2017 in United Kingdom participants in the United Kingdom's atmospheric nuclear weapon tests and experimental programmes. J Radiol Prot. 2022;42(2):021507.

102. Boice JD Jr, Cohen SS, Mumma MT, Howard SC, Yoder RC, Dauer LT. Mortality among medical radiation workers in the United States, 1965-2016. Int J Radiat Biol. 2023;99(2):183-207.

103. Ivanov VK, Maksioutov MA, Chekin SY, Petrov AV, Biryukov AP, Kruglova ZG, Matyash VA, Tsyb AF, Manton KG, Kravchenko JS. The risk of radiation-induced cerebrovascular disease in Chernobyl emergency workers. Health Phys. 2006;90(3):199-207.

104. Ivanov VK. Late cancer and noncancer risks among Chernobyl emergency workers of Russia. Health Phys. 2007;93(5):470-9.

105. Kashcheev VV, Chekin SY, Maksioutov MA, Tumanov KA, Menyaylo AN, Kochergina EV, Kashcheeva PV, Gorsky AI, Shchukina NV, Karpenko SV, Ivanov VK. Radiation-epidemiological study of cerebrovascular diseases in the cohort of Russian recovery operation workers of the Chernobyl accident. Health Phys. 2016;111(2):192-7.

106. Kashcheev VV, Chekin SY, Karpenko SV, Maksioutov MA, Menyaylo AN, Tumanov KA, Kochergina EV, Kashcheeva PV, Gorsky AI, Shchukina NV, et al. Radiation risk of cardiovascular diseases in the cohort of Russian emergency workers of the Chernobyl accident. Health Phys. 2017;113(1):23-9.

107. Chekin SY, Maksyutov MA, Kashcheyev VV, Karpenko SV, Tumanov KA, Korelo AM, Kochergina YV, Zelenskaya NS, Lashkova OY, Shchukina NV, Ivanov VK. Effect of dose uncertainty on the assessment of the radiation risk of nononcological diseases among Russian workers involved in cleaning up the consequences of the accident at the Chernobyl nuclear power plant (NPP). Radiat Risk. 2022;31:21-35.

108. Shafransky IL, Tukov AR, Sidorin IV, Prokhorova ON, Kalinina MV. Analysis of the risk of death from ischemic heart disease among the liquidators of the consequences of the accident at Chernobyl NPP and workers in the nuclear industry. Radiat Risk. 2020;29(3):129-41.

109. Grosche B, Lackland DT, Land CE, Simon SL, Apsalikov KN, Pivina LM, Bauer S, Gusev BI. Mortality from cardiovascular diseases in the Semipalatinsk historical cohort, 1960-1999, and its relationship to radiation exposure. Radiat Res. 2011;176(5):660-9.

110. Martin S, Ségala C. Epidemiological study of mortality among workers exposed to tritium in France. Radiat Res. 2021;195(3):284-92.

111. Rage E, Caër-Lorho S, Drubay D, Ancelet S, Laroche P, Laurier D. Mortality analyses in the updated French cohort of uranium miners (1946-2007). Int Arch Occup Environ Health. 2015;88(6):717-30.

112. Sridharan V, Johnson KA, Landes RD, Cao M, Singh P, Wagoner G, Hayar A, Sprick ED, Eveld KA, Bhattacharyya A, et al. Sex-dependent effects of genetic upregulation of activated protein C on delayed effects of acute radiation exposure in the mouse heart, small intestine, and skin. PLoS ONE. 2021;16(5):e0252142.

113. Stewart FA, Heeneman S, Te Poele J, Kruse J, Russell NS, Gijbels M, Daemen M. Ionizing radiation accelerates the development of atherosclerotic lesions in ApoE-/- mice and predisposes to an inflammatory plaque phenotype prone to hemorrhage. Am J Pathol. 2006;168(2):649-58.

114. Andruska N, Schlaak RA, Frei A, Schottstaedt AM, Lin CY, Fish BL, Gasperetti T, Mpoy C, Pipke JL, Pedersen LN, et al. Differences in
radiation-induced heart dysfunction in male versus female rats. Int J Radiat Biol. 2023;99(7):1096-108.

115. Chmielewski-Stivers N, Petit B, Ollivier J, Monceau V, Tsoutsou P, Quin-tela Pousa A, Lin X, Limoli C, Vozenin M-C. Sex-specific differences in toxicity following systemic paclitaxel treatment and localized cardiac radiotherapy. Cancers. 2021;13(16):3973.

116. Lenarczyk M, Kronenberg A, Mader M, North PE, Komorowski R, Cheng Q, Little MP, Chiang IH, LaTessa C, Jardine J, Baker JE. Age at exposure to radiation determines severity of renal and cardiac disease in rats. Radiat Res. 2019;192(1):63-74.

117. Mitchel REJ, Hasu M, Bugden M, Wyatt H, Hildebrandt G, Chen YX, Priest ND, Whitman SC. Low-dose radiation exposure and protection against atherosclerosis in *ApoE*⁻/⁻ mice: the influence of P53 heterozygosity. Radiat Res. 2013;179(2):190-9.

118. Fajardo LF, Eltringham JR, Steward JR. Combined cardiotoxicity of adriamycin and x-radiation. Lab Invest. 1976;34(1):86-96.

119. Eltringham JR, Fajardo LF, Stewart JR. Adriamycin cardiomyopathy: enhanced cardiac damage in rabbits with combined drug and cardiac irradiation. Radiology. 1975;115(2):471-2.

120. Myers CJ, Lu B. Decreased survival after combining thoracic irradiation and an anti-PD-1 Antibody correlated with increased T-cell infiltration into cardiac and lung tissues. Int J Radiat Oncol Biol Phys. 2017;99(5):1129-36.

121. Yan B, Hooper DC, Yuan Z, Wang C, Chen Y, Lu B. Autoantibodies drive heart damage caused by concomitant radiation and PD-1 Blockade. Cancer Immunol Res. 2023;11(4):546-55.

122. Du S, Zhou L, Alexander GS, Park K, Yang L, Wang N, Zaorsky NG, Ma X, Wang Y, Dicker AP, Lu B. PD-1 modulates radiation-induced cardiac toxicity through cytotoxic T lymphocytes. J Thorac Oncol. 2018;13(4):510-20.

123. Seemann I, te Poele JA, Song JY, Hoving S, Russell NS, Stewart FA. Radiation- and anthracycline-induced cardiac toxicity and the influence of ErbB2 blocking agents. Breast Cancer Res Treat. 2013;141(3):385-95.

124. Sridharan V, Thomas CJ, Cao M, Melnyk SB, Pavliv O, Joseph J, Singh SP, Sharma S, Moros EG, Boerma M. Effects of local irradiation combined with sunitinib on early remodeling, mitochondria, and oxidative stress in the rat heart. Radiother Oncol. 2016;119(2):259-64.

125. Kotla S, Zhang A, Imanishi M, Ko KA, Lin SH, Gi YJ, Moczygemba M, Isgandarova S, Schadler KL, Chung C, et al. Nucleus-mitochondria positive feedback loop formed by ERK5 S496 phosphorylation-mediated poly (ADP-ribose) polymerase activation provokes persistent pro-inflammatory senescent phenotype and accelerates coronary atherosclerosis after chemo-radiation. Redox Biol. 2021;47:102132.

126. Austin PC, Lee DS, Fine JP. Introduction to the analysis of survival data in the presence of competing risks. Circulation. 2016;133(6):601-9.

127. Fine JP, Gray RJ. A proportional hazards model for the subdistribution of a competing risk. J Am Statist Assoc. 1999;94(2):496-509.

**Publisher's Note**

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.