Abstract
Aims
Chronic myeloid leukemia (CML) patients are at high risk for developing cardiovascular (CV) diseases due to adverse effects of BCR-ABL tyrosine kinase inhibitors.
Objectives
The purpose of this study was to compare patient characteristics and in-hospital mortality between CML patients and non-CML patients, who were hospitalized for ischemic heart disease (IHD).
Methods and results
This study was based on the Japanese Registry of All Cardiac and Vascular Diseases and the Diagnosis Procedure Combination (JROAD-DPC) database. All patients who were first hospitalized for IHD and received percutaneous coronary intervention from April 2012 to March 2021 were extracted. Propensity score matching was used to reduce confounding effects related to differences in patient background. A total of 766 385 patients, in which 371 CML patients were included, were analyzed. CML patients were more likely to be male and less likely to have obesity, hypertension, and dyslipidemia. The number of modifiable CV risk factors (obesity, smoking, hypertension, dyslipidemia, and diabetes mellitus) in CML patients was smaller than in non-CML patients. There was no difference in in-hospital mortality, whether considering all cases or only acute myocardial infarction cases. This was also statistically non-significant after propensity score matching.
Conclusion
CML patients were hospitalized for IHD with fewer CV risk factors than non-CML patients, and in-hospital mortality was comparable between CML and non-CML patients. These findings emphasize the need for more stringent management of modifiable CV risk factors for CML patients.
Keywords: BCR-ABL tyrosine kinase inhibitor, Cardiovascular risk factor, Chronic myeloid leukemia, Ischemic heart disease, JROAD-DPC
Graphical Abstract
Graphical Abstract.
Introduction
The survival of patients with chronic myeloid leukemia (CML) has greatly improved over the years since the introduction of imatinib, the first BCR-ABL tyrosine kinase inhibitor (TKI),1 and currently, the life expectancy of CML patients is approaching that of healthy individuals.2 However, some patients become resistant or intolerant to imatinib, which led to the development of second-generation (dasatinib, nilotinib, bosutinib) and third-generation (ponatinib) BCR-ABL TKIs.3 The second- and third-generation BCR-ABL TKIs share potent inhibitory activity against ABL1, but had distinct inhibitory activity against other tyrosine kinases such as vascular endothelial growth factor receptors, platelet-derived growth factor receptors, fibroblast growth factor receptors, SRC and TIE-2.4,5 Despite the improved therapeutic efficacy, concerns have been raised about the potential cardiovascular (CV) toxicities due to off-target effects of each BCR-ABL TKI. Increasing evidence has been accumulating that BCR-ABL TKIs are associated with increased risk of arteriothrombotic events such as ischemic heart disease (IHD), ischemic stroke, and peripheral artery occlusive disease.4,6,7 According to an analysis of CML patients receiving frontline BCR-ABL TKIs in different prospective trials, the risk for IHD was higher in CML patients receiving ponatinib and to some extent nilotinib and dasatinib.8 Since traditional CV risk factors, such as age, hypertension, diabetes mellitus, dyslipidemia, and pre-existing IHD, increase the risk of CV adverse events,4,9,10 clinical practice guidelines recommend CV risk-assessment at baseline, and CV surveillance during BCR-ABL TKI therapy scheduled according to the baseline risk and drug choice.11,12 However, it remains undetermined whether strategies of CV prevention and coronary intervention for CML patients should be the same as those for non-CML patients, due to the lack of studies revealing the clinical characteristics at the time of hospitalization and in-hospital prognosis of CML patients who developed IHD. In the present study, we used the JROAD-DPC (Japanese Registry of All Cardiac and Vascular Diseases and the Diagnosis Procedure Combination) database, and compared the baseline characteristics and in-hospital mortality between CML and non-CML patients, who developed IHD and underwent percutaneous coronary intervention (PCI), to search for the specific prevention and treatment strategies tailored to CML patients.
Methods
Study population
The study population was composed of hospitalized patients from April 2012 to March 2021 in the JROAD-DPC database. The JROAD was launched by the Japanese Circulation Society to assess the clinical activities of institutions nationwide that have a dedicated CV subspeciality inpatient services.13 The JROAD-DPC database was constructed by linking the accumulated information from JROAD-participating institutions to the DPC data, which include patient characteristics and clinical data (diagnosis at admission, discharge outcomes, clinical examinations, and treatments), collected from DPC-participating institutions.13,14 The JROAD-DPC database covers the majority of CV inpatients nationwide (11 298 644 cases in 1119 hospitals between April 2012 and March 2021). The identification of IHD and CML was based on the International Classification of Diseases Tenth Revision (ICD-10) diagnosis codes related to angina pectoris (I20), acute myocardial infarction (AMI) (I21), subsequent myocardial infarction (I22), certain current complications following AMI (I23), other acute ischemic heart diseases (I24), and chronic IHD (I25); and CML (C92.1). For comparison of baseline characteristics, patient age and sex, height, weight, body mass index, main diagnosis, comorbidities at admission, length of hospitalization, drugs, therapeutic procedures, and discharge status were extracted from the database. For CML patients, types of BCR-ABL TKIs (imatinib, dasatinib, nilotinib, bosutinib, and ponatinib) used at admission were also extracted. Patients who were 20 years or older and underwent PCI were extracted, and then readmission cases were excluded. We included 890 028 patients first hospitalized for IHD and received PCI (Figure 1). Diagnosis of IHD was defined as the main diagnosis, admission-precipitating diagnosis, or most resource-consuming diagnosis. Medical resources were determined by the cost of examinations and treatments during hospitalization. Most resource-consuming diagnosis was defined by the doctor’s discretion based on medical resources and the main diagnosis disease.
Figure 1.
Flowchart of this study. CML, chronic myeloid leukemia; IHD, ischemic heart disease; JROAD-DPC, The Japanese Registry of All Cardiac and Vascular Diseases and the Diagnosis Procedure Combination; PCI, percutaneous coronary intervention.
The study protocol conformed to the Declaration of Helsinki, and was reviewed and approved by the Institutional Review Board of the University of Tokyo (approval number 2022025NI) and the Japanese Circulation Society (approval number 2021-09). Waiver of individual informed consent was granted by the institutional review board.
Clinical outcomes
The main outcome was in-hospital mortality (total number of deaths ≤ 7 days and 30 days after admission, and total number of deaths during hospitalization). Patients were censored at discharge, and were not followed thereafter.
Sample matching
Propensity score (PS) matching was used to reduce confounding effects related to differences in patient background. PS was estimated with a logistic regression model, with the following clinically relevant covariates: age, sex, obesity, smoking, hypertension, diabetes mellitus, dyslipidemia, stroke, peripheral vascular disease, congestive heart failure, renal disease, liver failure, chronic obstructive pulmonary disease, dementia. Matching was performed with greedy nearest neighbor matching algorithm (ratio = 1:1 without replacement), with a caliper of width 0.2 of the standard deviation of the logistic of the estimated PS. We used the standardized difference to examine the balance of covariates, whereby an absolute value of standardized differences <0.1 was considered to be statistically non-significant.
Statistical analysis
Categorical variables were expressed as proportion (%). The Shapiro-Wilk test was used to assess the normal distribution of continuous data. Continuous variables were expressed as mean ± SD for parameters with normal distribution, as median (IQR) for parameters with skewed distribution. Continuous variables were compared using standardized differences and a two-sample t test or the Mann–Whitney U test according to the data distribution. Differences between proportions were assessed using standardized differences and chi-square test. Absolute value of standardized differences <0.1 was considered to be statistically non-significant. We estimated the odds ratio (OR) and 95% confidence interval (CI) with CML for in-hospital mortality (within 7 days, 30 days, and total) by matched logistic regression analysis adjusted for hospitalization days before and after PS matching. We also conducted subgroup analysis specifically on AMI cases. Statistical analysis was performed using JMP Pro V.16.0.
Results
Patient characteristics
After excluding patients with incomplete data, we analyzed 766 385 patients, in which 371 CML patients were included. Baseline characteristics of the entire cohort are presented in Table 1. The percentage of male in CML patients was higher than that in non-CML patients [81.9% in CML patients vs. 75.2% in non-CML patients; P = 0.0026; standardized difference (Std diff) = 0.16]. CML patients had less prevalence of obesity (28.8% vs. 36.7%; P = 0.0018; Std diff = −0.17), hypertension (52.6% vs. 62.5%; P < 0.0001; Std diff = −0.20), and dyslipidemia (48.3% vs. 63.4%; P < 0.0001; Std diff = − 0.31) than non-CML patients. The number of modifiable CV risk factors (obesity, smoking, hypertension, diabetes mellitus, dyslipidemia) in CML patients was smaller than that in non-CML patients (2.1 ± 1.2 vs. 2.5 ± 1.2, mean ± SD; P < 0.0001; Std diff = − 0.32). In contrast, the medication rate of antihypertensive drugs, lipid-lowering drugs, antidiabetic drugs, antiplatelet drugs, and anticoagulant drugs in CML patients before admission was significantly higher than those in non-CML patients (see Supplementary material online, Table S1).
Table 1.
Baseline characteristics of patients with or without CML before propensity score matching
| All (n = 766 385) |
CML (n = 371) |
Non-CML (n = 766 014) |
P value | Std diff | |
|---|---|---|---|---|---|
| Demographics | |||||
| Age, median (IQR) | 71 (63–78) | 70 (64–78) | 71 (63–78) | 0.33 | −0.03 |
| Male, % | 75.2 | 81.9 | 75.2 | 0.0026 | 0.16 |
| BMI, median (IQR) | 23.9 (21.7–26.2) | 23.5 (21.5–25.6) | 23.9 (21.7–26.2) | 0.043 | −0.10 |
| BMI ≥ 25, % | 36.6 | 28.8 | 36.7 | 0.0018 | −0.17 |
| Smoking, % | 52.2 | 50.4 | 52.2 | 0.49 | −0.04 |
| Comorbidities, % | |||||
| Hypertension | 62.5 | 52.6 | 62.5 | < 0.0001 | −0.20 |
| Diabetes mellitus | 35.3 | 31.3 | 35.3 | 0.10 | −0.09 |
| Dyslipidemia | 63.4 | 48.3 | 63.4 | < 0.0001 | −0.31 |
| Congestive heart failure | 27.1 | 31.0 | 27.2 | 0.096 | 0.08 |
| Stroke | 5.3 | 6.2 | 5.3 | 0.45 | 0.04 |
| Peripheral vascular disease | 6.9 | 6.7 | 6.9 | 0.92 | −0.01 |
| Chronic kidney disease | 7.8 | 9.7 | 7.8 | 0.17 | 0.07 |
| Liver failure | 0.0 | 0.0 | 0.0 | 0.77 | 0.00 |
| Chronic obstructive pulmonary disease | 2.7 | 2.2 | 2.7 | 0.51 | −0.04 |
| Dementia | 1.3 | 0.5 | 1.3 | 0.19 | −0.08 |
| Number of CV risk factorsa, mean ± SD | 2.5 ± 1.2 | 2.1 ± 1.2 | 2.5 ± 1.2 | < 0.0001 | −0.32 |
| 0 | 5.3 | 9.4 | 5.3 | ||
| 1 | 15.9 | 22.9 | 15.9 | ||
| 2 | 28.1 | 29.1 | 28.1 | ||
| 3 | 29.3 | 25.9 | 29.3 | ||
| 4 | 17.0 | 10.8 | 17.0 | ||
| 5 | 4.4 | 1.9 | 4.4 |
Data are presented as number (%), mean ± SD, or median (IQR; interquartile range) where appropriate. P value for continuous variables were compared using Mann–Whitney U test. P value for differences between proportions were assessed using chi-square test.
BMI, body mass index; CML, chronic myeloid leukemia; CV, cardiovascular; Std diff, standardized difference.
aObesity (BMI ≥ 25), smoking, hypertension, diabetes mellitus, dyslipidemia.
We further compared baseline characteristics of CML patients who were treated with individual BCR-ABL TKIs. However, we could identify the use of individual BCR-ABL TKIs only in 248 of CML patients; imatinib for 49 patients, dasatinib for 40 patients, nilotinib for 107 patients, bosutinib for 38 patients, and ponatinib for 14 patients. There were no significant differences in the demographics or the number of modifiable CV risk factors among individual BCR-ABL TKIs, except for the younger age of patients treated with bosutinib (see Supplementary material online, Table S2).
The logistic regression analysis was performed to estimate propensity scores using the variables in Table 2. The baseline characteristics of 371 matched pairs are summarized in Table 2. In the matched cohort, the modifiable CV risk factors and comorbidities were well balanced (Table 2, Supplementary material online, Figure S1).
Table 2.
Baseline characteristics of patients with or without CML after propensity score matching
| CML (n = 371) |
Non-CML (n = 371) |
P value | Std diff | |
|---|---|---|---|---|
| Demographics | ||||
| Age, median (IQR) | 70 (64–78) | 70 (64–77) | 0.99 | −0.00 |
| Male, % | 81.9 | 81.7 | 0.92 | 0.01 |
| BMI, median (IQR) | 23.5 (21.5–25.6) | 23.5 (21.6 −25.5) | 0.99 | 0.09 |
| BMI ≥ 25, % | 28.8 | 29.4 | 0.87 | −0.01 |
| Smoking, % | 50.4 | 49.3 | 0.77 | 0.02 |
| Comorbidities, % | ||||
| Hypertension | 52.6 | 52.3 | 0.94 | 0.01 |
| Diabetes mellitus | 31.3 | 31.3 | 1.0 | 0 |
| Dyslipidemia | 48.3 | 48.8 | 0.88 | −0.01 |
| Congestive heart failure | 31.0 | 31.3 | 0.94 | 0.01 |
| Stroke | 6.2 | 5.7 | 0.76 | 0.02 |
| Peripheral vascular disease | 6.7 | 6.7 | 1.0 | 0.00 |
| Chronic kidney disease | 9.7 | 9.4 | 0.90 | 0.01 |
| Liver failure | 0.0 | 0.0 | — | 0 |
| Chronic obstructive pulmonary disease | 2.2 | 1.6 | 0.59 | 0.04 |
| Dementia | 0.5 | 0.3 | 0.56 | 0.04 |
| Number of CV risk factorsa, mean ± SD | 2.1 ± 1.2 | 2.1 ± 1.2 | 0.98 | 0.00 |
| 0 | 9.4 | 9.4 | ||
| 1 | 22.9 | 23.5 | ||
| 2 | 29.1 | 28.6 | ||
| 3 | 25.9 | 25.6 | ||
| 4 | 10.8 | 11.1 | ||
| 5 | 1.9 | 1.9 |
Data are presented as number (%), mean ± SD, or median (IQR; interquartile range) where appropriate. P value for continuous variables were compared using Mann–Whitney U test. P value for differences between proportions were assessed using chi-square test.
BMI, body mass index; CML, chronic myeloid leukemia; CV, cardiovascular; Std diff, standardized difference.
aObesity (BMI ≥ 25), smoking, hypertension, diabetes mellitus, dyslipidemia.
Outcomes
There was no difference in in-hospital mortality (within 7 days, 30 days, and total) between CML patients and non-CML patients (Table 3). The results did not change after PS matching. Since most deaths were documented in patients with the ICD-10 diagnosis code of AMI (all patients; n = 15,864, AMI patients; n = 14 063), we performed an additional analysis focusing on these patients. We identified 259 952 AMI patients, in which 97 CML patients were included. Differences in patient characteristics between CML and non-CML patients in the AMI cohort were comparable to those in the entire cohort (see Supplementary material online, Table S3). There was no difference in in-hospital mortality (7 days, 30 days, and total) between CML patients and non-CML patients (see Supplementary material online, Table S4). After PS matching, in-hospital mortality within 30 days and total in-hospital mortality were relatively higher in non-CML patients, but it was not statistically significant.
Table 3.
In-hospital mortality of patients with CML and without CML before and after propensity score matching
| In-hospital mortality | Non-matching | Matching | |||||||
|---|---|---|---|---|---|---|---|---|---|
| All patients | All (n = 766 385) |
CML (n = 371) |
Non-CML (n = 766 014) |
OR (95% CI) |
P
value |
CML (n = 371) |
Non-CML (n = 371) |
OR (95% CI) | P value |
| 7 days mortality, % | 1.0 | 1.1 | 1.0 | 1.15 (0.43–3.11) | 0.78 | 1.1 | 0.8 | 1.31 (0.29–5.93) | 0.73 |
| 30 days mortality, % | 1.7 | 1.1 | 1.7 | 0.62 (0.23–1.67) | 0.35 | 1.1 | 2.2 | 0.49 (0.15–1.65) | 0.25 |
| Total mortality, % | 2.1 | 1.6 | 2.1 | 0.72 (0.32–1.63) | 0.43 | 1.6 | 3.0 | 0.52 (0.19–1.44) | 0.21 |
Data given as number (%).
CI, confidence interval; CML, chronic myeloid leukemia; OR, odds ratio.
Discussion
The major findings of the present study are as follows: (i) among patients who developed IHD and underwent PCI, CML patients had fewer CV risk factors than non-CML patients, (ii) in-hospital mortality was comparable between CML and non-CML patients (Central Illustration). In our study, inclusion of only patients who underwent PCI allowed comparisons within a relatively homogeneous patient population and avoided biases related to the treatment. In Japan, hospitals capable of performing PCI are distributed throughout the country, and cases of AMI treated with thrombolytic therapy alone are extremely rare, accounting for <5%.15,16 Additionally, the ratio of PCI to coronary artery bypass grafting (CABG) for revascularization is more skewed towards PCI in Japan than in Western countries, and it was reported that PCI is performed ∼15 times more frequently than CABG.13 Therefore, patients with more severe conditions and indications for CABG were excluded in this study, but these cases are few in number and their impact is likely to be limited.
The traditional CV risk factors predispose to BCR-ABL TKI-related CV toxicities.4,9,10 In the phase 2 Ponatinib Ph+ ALL and CML Evaluation (PACE) trial, the risk of serious arterial adverse events was higher in CML patients aged > 65 years [relative risk 1.8, (95% CI: 1.2–2.9)] and in those with underlying diabetes mellitus [relative risk 2.4, (95% CI: 1.5–3.8)], hypertension [relative risk 3.2, (95% CI: 1.8–5.8)], hypercholesterolemia [relative risk 1.6, (95% CI: 1.0–2.7)], or pre-existing IHD [relative risk 2.6, (95% CI: 1.6–4.0)].17 However, it is unclear whether CML patients developing IHD have any clinical characteristics that differ from those of non-CML patients. In the present study using the nationwide JROAD-DPC database, we showed that CML patients had fewer CV risk factors than non-CML patients at hospitalization for IHD. This finding indicates that CML per se and/or BCR-ABL TKI therapy is a causal risk factor for IHD. A previous study comparing a cohort of CML patients (from 2004 to 2009) with a cohort of patients without cancer (from 2003 to 2010) revealed that CML patients had a higher rate of IHD (33.0 vs. 11.9 per 1000 person-years).18 In this study, BCR-ABL TKIs treatment was observed in 15% of CML patients, with 97% of these receiving imatinib, and in the CML cohort, those with BCR-ABL TKI therapy had a similar rate of IHD (30.5 per 1000 person-years), compared with those without BCR-ABL TKI therapy (33.9 per 1000 person-years).18 These results suggested that the higher risk of IHD was driven by underlying factors associated with CML per se, not by imatinib. It remains unclear why CML patients without BCR-ABL TKI therapy are at high risk of IHD, but functional alterations in both blood and endothelial cells with a BCR-ABL fusion gene might contribute to the pathogenesis.19
It was reported that nilotinib impaired glucose and lipid metabolism.20–23 Ponatinib was also associated with the development of hypertension.24,25 In the PACE trial, grade 3–4 hypertension occurred in 14% of ponatinib-treated patients with 5 years of follow-up, and up to 68% of patients experienced any increase in blood pressure from baseline.26 Nilotinib and ponatinib may worsen CV risk factors such as diabetes mellitus, dyslipidemia, and hypertension, and thereby promote the progression of coronary atherosclerosis. In addition, nilotinib and ponatinib also exert direct pro-atherogenic effects on endothelial cell function27–29 and potentiates platelet thrombus formation.30 Although the risk for IHD differs according to individual BCR-ABL TKIs (higher from ponatinib and to some extent from nilotinib and dasatinib),8 there was no significant difference in the number of CV risk factors among the group of CML patients subdivided by the use of individual BCR-ABL TKIs. Imatinib is preferentially used in CML patients with high CV risk due to a favorable CV safety profile, which might lead to bias regarding the CV risk of patients who are prescribed BCR-ABL TKIs. We also acknowledge that the relatively small number of each group (imatinib for 49 patients, dasatinib for 40 patients, nilotinib for 107 patients, bosutinib for 38 patients, and ponatinib for 14 patients) might reduce the statistical power and influence the results. A pooled analysis of multinational databases will be required to elucidate whether clinical characteristics of CML patients developing IHD may differ depending on the use of individual BCR-ABL TKIs.
In the present study, imatinib, dasatinib, and nilotinib were used in 19.8%, 16.1%, and 43.1% of CML patients, respectively, and these proportions were different from those of real-world clinical practice. A Japanese registry, enrolling a total of 506 patients from April 2010 to March 2013, showed that 139 (27.9%), 144 (28.9%), and 169 (33.9%) patients were treated with imatinib, dasatinib, and nilotinib, respectively.31 Although the observation periods were different, the proportion of the use of imatinib or dasatinib was lower and that of nilotinib was higher in our study. The metabolic and vascular adverse effects of nilotinib increase the risk for developing IHD.4,20–23,27–30 Since our study included CML patients who developed IHD and underwent PCI, the higher proportion of patients receiving nilotinib in our study may indicate a strong correlation between nilotinib use and the incidence of IHD events.
There was no significant difference in in-hospital mortality between CML patients and non-CML patients in our study. Therefore, specific consideration is not needed for the short-term treatment of IHD, including PCI, in CML patients. The literature is still limited for the long-term outcomes of CML patients after developing IHD. According to a report of survival data in an Italian cohort of 656 CML patients treated dasatinib, nilotinib, bosutinib, or ponatinib, the standard mortality ratio of CML patients after developing IHD was more than 3 times higher than that of Italian population of control.32 Although the life expectancy of CML patients is becoming close to that of healthy individuals,2 long-term survival rates can be decreased by severe adverse events related to BCR-ABL TKI therapy, as well as by comorbid CV diseases.33 Our results indicate no significant difference in short-term outcome compared with non-CML patients, but CML patients, despite having fewer CV risk factors, may develop IHD. At hospitalization for IHD, CML patients had fewer CV risk factors, but paradoxically higher rates of medication for CV risk factors, than non-CML patients (see Supplementary material online, Table S1). We speculate that this might reflect a recently growing recognition of the importance of CV risk management in CML patients, as recommended by clinical practice guidelines.11,12 Therefore, our results suggest that modifiable CV risk factors should be more aggressively and rigorously controlled to prevent IHD in CML patients. The rational approach for prophylaxis requires further understanding of the pathophysiology of accelerated atherosclerosis in CML patients, and development of a specific tool designed to estimate the baseline CV risk in the CML population. CML patients may benefit by lowering target blood pressure and cholesterol levels, or by proactive administration of antiplatelet drugs or anticoagulant drugs. More work will be needed to specify the optimal preventive strategies for CML patients according to their baseline CV risk.
Study limitations
This study has some limitations. First, our analysis was based on the JROAD-DPC database, and its retrospective and observational nature limits credible causal inferences. Although the number of CML patients (n = 371) in this study was relatively high compared with previous studies, we acknowledge that insufficient sample size may influence the results and reduce the statistical power. Second, the accuracy of the diagnosis is not perfect because these are less validated in the JROAD-DPC database compared with planned prospective studies. However, it was reported that the concordance for the diagnosis of AMI and heart failure was sufficiently acceptable.34 It is expected that accuracy is assured for other diseases. Third, the JROAD-DPC database does not collect numerical data of blood pressure, serum cholesterol, estimated glomerular filtration rate, and glycated hemoglobin, and it was not possible in this study to assess the baseline CV risk by using risk-assessment calculators such as the Framingham Risk Score,35 the SCORE2 (Systematic Coronary Risk Evaluation 2) risk prediction algorithms,36 and the PREVENT (AHA Predicting Risk of CVD EVENTs) risk equations.37 In addition, detailed information on coronary artery lesions, revascularization, and PCI-related adverse events were also unavailable. Fourth, the effect of other BCR-ABL TKIs used in the past could not be adjusted because the type of BCR-ABL TKI was determined based on the drug used at the time of admission. Fifth, the detailed information on clinical course of CML (e.g. time of diagnosis, current stage or phase, and prior treatments) and response to BCR-ABL TKIs was not available in the JROAD-DPC database. Lastly, ponatinib was launched in Japan in November 2016, and there were a relatively small number of CML patients treated with ponatinib.
Conclusions
Our present study demonstrates that CML patients develop IHD with fewer traditional CV risk factors, compared with non-CML patients. Although the short-term prognosis was comparable, CV risk factors should be strictly managed for CML patients.
Lead author biography
Akito Shindo is a postdoctoral fellow at the University of Tokyo Hospital, Japan. He completed cardiology fellowship at NTT Medical Center Tokyo, Japan. He holds a Doctor of Philosophy (PhD) degree in Medicine from the University of Tokyo Graduate School of Medicine. He is interested in clinical and basic research on cardio-oncology.
Supplementary Material
Acknowledgements
The authors thank Dr Michiho Shindo (Tokyo Women’s Medical University) for valuable discussions from the perspective of a practicing hematologist.
Contributor Information
Akito Shindo, Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan.
Hiroshi Akazawa, Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan.
Tomomi Ueda, Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan.
Hiroshi Kadowaki, Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan.
Junichi Ishida, Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan.
Issei Komuro, Department of Frontier Cardiovascular Science, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan; International University of Health and Welfare, 4-1-26 Akasaka, Minato-ku, Tokyo 107-8402, Japan.
Data availability
The data underlying this article were provided by the Japanese Circulation Society under license/permission. Data will be shared on request to the corresponding author with permission of the Japanese Circulation Society.
Supplementary material
Supplementary material is available at European Heart Journal Open online.
Funding
None declared.
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Data Availability Statement
The data underlying this article were provided by the Japanese Circulation Society under license/permission. Data will be shared on request to the corresponding author with permission of the Japanese Circulation Society.