Introduction: Chronic myeloid leukemia (CML) is a hematological malignancy with an excellent prognostic outcome. After the advancements in CML treatment and the introduction of different tyrosine kinase inhibitors (TKIs), the life expectancy of CML patients has become equivalent to that of the general population. As a result, coronary artery disease is anticipated to be the leading cause of death among CML patients. Moreover, TKI use is associated with a risk of endothelial dysfunction, thrombosis, and cardiovascular events, including myocardial infarction. In this study, we compare the outcomes of percutaneous coronary intervention (PCI) in patients with CML to their matched non-CML counterparts. Method: This is a retrospective cohort study using the Nationwide Readmission Database from January 2016 to December 2020. Adults with or without CML hospitalized for acute myocardial infarction and underwent PCI were included. The patients were identified using ICD-10 codes. The primary outcomes were in-hospital mortality and 30-day readmission rates. The secondary outcomes were PCI complications rates. Results: Out of 2,727,619 patients with myocardial infarction, 2,124 CML patients were identified. A total of 888 CML patients underwent PCI. CML patients were significantly older (mean age: 68.34 ± 11.14 vs. 64.40 ± 12.61 years, p < 0.001) than non-CML patients without a difference in sex distribution. Hypertension (85.45% vs. 78.64%), diabetes (45.48% vs. 37.29), stroke (11.84% vs. 7.78) at baseline were significantly higher in the CML group. Prior myocardial infarction events (20.51% vs. 15.17%) and prior PCI procedure (24.47% vs. 16.89%) were significantly higher in the CML group. CML patients had a significantly longer hospital stay (4.66 ± 4.40 vs. 3.75 ± 4.62 days, p = 0.001). The primary outcomes did not differ between the comparison groups. The risk of post-PCI complications did not differ between the comparison groups in the propensity matched analysis except for coronary artery dissection (odds ratio [OR]: 0.10; 95% confidence interval [CI]: 0.02–0.65, p = 0.016) and ischemic stroke (OR: 0.35; 95% CI: 0.14–0.93, p = 0.034) which were lower in the CML group. Conclusion: This analysis showed no statistically significant difference in mortality, 30-day readmission, and post PCI complications rates between CML and non-CML patients. However, interestingly, CML patients may experience lower coronary artery dissection and ischemic stroke events than those without CML diagnosis.

Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm characterized by an excess production of mature granulocytes but has a favorable prognosis. Approximately half of the patients are usually asymptomatic when the disease is detected during routine investigations. Commonly, patients present with abdominal pain and early satiety [1]. Other patients present with priapism, ocular manifestations, or myeloid mass [2‒4]. The life expectancy of CML patients is currently comparable to that of the general population due to improvements in CML therapy, particularly the use of tyrosine kinase inhibitors (TKIs) [5]. It has been reported that patients who achieve complete cytogenetic response after 2 years of imatinib use have no significant difference in survival from the general population [5]. As a result, it is projected that coronary artery disease would be an important reason for mortality among patients with CML. Particular attention was drawn to the link between TKI usage and the risk of both endothelial dysfunction and cardiovascular events, such as acute myocardial infarction [6]. Moreover, only a few TKIs have high selectivity in targeting the relevant kinases, whereas most TKIs block several kinases, hence increasing the risk of toxicities and side effects, including effects on endothelium and atherosclerosis. Additionally, most patients have other risk factors for coronary artery disease, such as diabetes, hypertension, and dyslipidemia which add to their risk of developing myocardial infarction [7]. Acute myocardial infarction can be recognized on electrocardiogram as ST-segment elevation myocardial infarction (STEMI) when there is a complete plaque rupture and occlusion of the coronary arteries or from partial occlusion of the coronary vessels causing non-STEMI (NSTEMI). In this investigation, we compare the baseline characteristics, complications, and clinical outcomes post percutaneous coronary intervention (PCI) between CML patients and their non-CML counterparts who presented with myocardial infarction and underwent PCI.

This is an observational cohort study that used a Nationwide Readmission Database (NRD) from January 2016 to December 2020 to screen for the study population. Eligible patients were adults aged 18 years or above with or without CML diagnosis and hospital admission with a primary diagnosis of acute myocardial infarction, STEMI, or NSTEMI who underwent PCI. The patients were identified by using the related ICD-10 codes (I21.9, I21.3, and I21.4, respectively).

The primary outcomes were in-hospital mortality and 30-day readmission rates. The secondary outcomes were the complications rates post PCI including cardiac arrest, shock, ventricular tachycardia, deep venous thrombosis, pulmonary embolism, cardiac tamponade, coronary artery dissection, ischemic stroke, bleeding, acute kidney injury, respiratory failure, and mechanical ventilation use.

The weighting of patient-level observations was implemented to obtain national estimates. Multivariate regression analysis models were built by including all confounders significantly associated with the outcome on univariable analysis with a cutoff p value of 0.2. Variables deemed important determinants of the outcomes based on the literature were forced into the models. Binary outcomes such as index hospitalization mortality and complications were compared by logistic regression. For readmission comparison, we used the time-to-event Cox regression analysis. Propensity matching was done using the greedy method. Proportions were compared using the Mantel-Haenszel χ2 test or Fisher’s exact test. Continuous variables were compared using Student’s t test. All p values were two-sided, with 0.05 as the threshold for statistical significance. Percentages and means with standard deviation (±SD) were computed for categorical and continuous variables, respectively. Odds ratios (ORs) and their 95% confidence intervals (95% CIs) were used to report the regression analysis results. All statistical analyses were performed using Stata (Version 16.1; StataCorp, Stata Statistical Software: Release 16. 2019, College Station, TX: StataCorp LLC).

Baseline Characteristics

Out of 2,727,619 patients with myocardial infarction, 2,124 CML patients were identified. A total of 888 CML patients underwent PCI. Patients’ baseline characteristics are presented in Table 1. CML patients were significantly older than non-CML patients (mean age: 68.34 ± 11.14 vs. 64.40 ± 12.61 years, p < 0.001) without a difference in sex distribution. All CML patients had a Charlson comorbidity index score of 3, while the scores in non-CML patients ranged between 1 and 3. CML patients stayed in hospital for a significantly longer time than non-CML patients (4.66 ± 4.40 vs. 3.75 ± 4.62 days, p = 0.001) with significantly more patients who stayed for more than 3 days (40.93% vs. 29.49%, p < 0.001). Hypertension (85.45% vs. 78.64%, p < 0.001), diabetes (45.48% vs. 37.29, p < 0.001), stroke (11.84% vs. 7.78, p = 0.002) at baseline were significantly higher in the CML group. Prior myocardial infarction events (20.51% vs. 15.17%, p = 0.002) and prior PCI procedure (24.47% vs. 16.89%, p < 0.001) were significantly higher in the CML group as well.

Table 1.

Patients’ baseline characteristics

VariableCML group (n = 888), n (%)Non-CML group (n = 1,422,659), n (%)p value
Age, mean±SD, years 68.34±11.14 64.40±12.61 <0.001 
 <65 years 333 (37.54) 761,976 (53.56) <0.001 
 >65 years 555 (62.46) 660,683 (46.44) <0.001 
Female 282 (31.79) 451,410 (31.73) 0.982 
Urban location 705 (79.44) 1,114,795 (78.36) 0.592 
Teaching hospitals 658 (74.14) 1,027,871 (72.25) 0.396 
Hospital stay, mean±SD, days 4.66±4.40 3.75±4.62 0.001 
 ≤3 days 524 (59.07) 1,003,117 (70.51) <0.001 
 >3 days 363 (40.93) 419,542 (29.49) <0.001 
Smoking 29.21 24.74 0.034 
Alcohol use 0.53 03.21 <0.001 
Drug use 2.10 3.85 0.044 
CCI score   <0.001 
 1 436,329 (30.67)  
 2 394,788 (27.75)  
 3 888 (100.0) 591,399 (41.57)  
Chronic comorbidities  
 Hypertension 759 (85.45) 1,118,779 (78.64) <0.001 
 Dyslipidemia 667 (75.10) 1,012,506 (71.17) 0.073 
 Diabetes 404 (45.48) 530,509 (37.29) <0.001 
 Obesity 157 (17.64) 302,742 (21.28) 0.074 
 Sleep apnea 115 (12.95) 117,369 (8.25) 0.001 
 Prior MI 182 (20.51) 215,817 (15.17) 0.002 
 Prior PCI 217 (24.47) 240,287 (16.89) <0.001 
 Prior CABG 121 (13.61) 111,394 (7.83) <0.001 
 Atrial fibrillation 182 (20.52) 187,080 (13.15) <0.001 
 Prior stroke 105 (11.84) 110,683 (7.78) 0.002 
 PVD 151 (16.99) 140,559 (9.88) <0.001 
 CHF 425 (47.90) 499,069 (35.08) <0.001 
 VHD 176 (19.84) 156,492 (11.0) <0.001 
 CKD 279 (31.45) 203,156 (14.28) <0.001 
 Anemia 277 (31.16) 199,741 (14.04) <0.001 
 Chronic lung disease 186 (20.99) 256,221 (18.01) 0.096 
 Coagulation disease 96 (10.80) 59,183 (4.16) <0.001 
 Hypothyroidism 148 (16.68) 148,952 (10.47) <0.001 
VariableCML group (n = 888), n (%)Non-CML group (n = 1,422,659), n (%)p value
Age, mean±SD, years 68.34±11.14 64.40±12.61 <0.001 
 <65 years 333 (37.54) 761,976 (53.56) <0.001 
 >65 years 555 (62.46) 660,683 (46.44) <0.001 
Female 282 (31.79) 451,410 (31.73) 0.982 
Urban location 705 (79.44) 1,114,795 (78.36) 0.592 
Teaching hospitals 658 (74.14) 1,027,871 (72.25) 0.396 
Hospital stay, mean±SD, days 4.66±4.40 3.75±4.62 0.001 
 ≤3 days 524 (59.07) 1,003,117 (70.51) <0.001 
 >3 days 363 (40.93) 419,542 (29.49) <0.001 
Smoking 29.21 24.74 0.034 
Alcohol use 0.53 03.21 <0.001 
Drug use 2.10 3.85 0.044 
CCI score   <0.001 
 1 436,329 (30.67)  
 2 394,788 (27.75)  
 3 888 (100.0) 591,399 (41.57)  
Chronic comorbidities  
 Hypertension 759 (85.45) 1,118,779 (78.64) <0.001 
 Dyslipidemia 667 (75.10) 1,012,506 (71.17) 0.073 
 Diabetes 404 (45.48) 530,509 (37.29) <0.001 
 Obesity 157 (17.64) 302,742 (21.28) 0.074 
 Sleep apnea 115 (12.95) 117,369 (8.25) 0.001 
 Prior MI 182 (20.51) 215,817 (15.17) 0.002 
 Prior PCI 217 (24.47) 240,287 (16.89) <0.001 
 Prior CABG 121 (13.61) 111,394 (7.83) <0.001 
 Atrial fibrillation 182 (20.52) 187,080 (13.15) <0.001 
 Prior stroke 105 (11.84) 110,683 (7.78) 0.002 
 PVD 151 (16.99) 140,559 (9.88) <0.001 
 CHF 425 (47.90) 499,069 (35.08) <0.001 
 VHD 176 (19.84) 156,492 (11.0) <0.001 
 CKD 279 (31.45) 203,156 (14.28) <0.001 
 Anemia 277 (31.16) 199,741 (14.04) <0.001 
 Chronic lung disease 186 (20.99) 256,221 (18.01) 0.096 
 Coagulation disease 96 (10.80) 59,183 (4.16) <0.001 
 Hypothyroidism 148 (16.68) 148,952 (10.47) <0.001 

CABG, coronary artery bypass grafting; CCI, Charlson comorbidity index; CHF, congestive heart failure; CKD, chronic kidney disease; CML, chronic myeloid leukemia; MI, myocardial infarction; PCI, percutaneous coronary intervention; PVD, peripheral vascular disease; SD, standard deviation; VHD, valvular heart disease.

Primary and Secondary Outcomes

The rates of post-PCI complications and clinical outcomes are demonstrated in Table 2. The primary outcomes (i.e., in-hospital mortality and 30-day readmission) did not differ between the comparison groups. However, there was a trend toward an increased risk of 30-day readmission by 41% in the CML patients in propensity matched analysis (OR: 1.41; 95% CI: 0.99–2.01, p = 0.056). The risk of post-PCI complications did not differ between the comparison groups except for cardiac arrest (OR: 0.41; 95% CI: 0.20–0.85; p = 0.017), mechanical circulatory support use (OR: 0.55, 95% CI: 0.35–0.87; p = 0.011), and mechanical ventilation use (OR: 0.59; 95% CI: 0.35–0.98, p = 0.040), which were lower in the CML group. However, analysis with propensity matching did not yield significant findings for the latter three variables but showed statistical significance for coronary artery dissection (OR: 0.10; 95% CI: 0.02–0.65, p = 0.016) and ischemic stroke (OR: 0.35; 95% CI: 0.14–0.93, p = 0.034) which were lower in the CML group (Table 2).

Table 2.

Post procedural complications and clinical outcomes

VariableCML group (n = 888), n (%)Non-CML group (n = 1,422,659), n (%)Multivariate regression analysis
OR (95% CI), p valuepropensity-matched OR (95% CI), p value
Complications 
 Cardiac arrest 14 (1.58) 45,383 (3.19) 0.41 (0.20–0.85), 0.017 1.04 (0.41–2.64), 0.940 
 VT 78 (8.85) 162,468 (11.42) 0.69 (0.47–1.01), 0.056 1.02 (0.64–1.63), 0.925 
 MCS use 54 (6.04) 86,355 (6.07) 0.55 (0.35–0.87), 0.011 0.68 (0.41–1.14), 0.144 
 IABP 35 (3.90) 57,191 (4.02) 0.60 (0.36–1.00), 0.050 0.80 (0.42–1.52), 0.491 
 Impella 22 (2.53) 31,723 (2.23) 0.61 (0.32–1.18), 0.141 0.68 (0.31–1.49), 0.339 
 ECMO 2,845 (0.20) 
 LVAD 569 (0.04) 
 Vasopressor use 21 (2.32) 19,917 (1.40) 1.02 (0.53–1.98), 0.948 1.00 (0.38–2.64), 0.994 
 Septic shock 6 (0.67) 9,531 (0.67) 0.53 (0.14–1.99), 0.348 
 Respiratory failure 122 (13.76) 140,710 (9.89) 0.82 (0.58–1.16), 0.259 0.98 (0.64–1.52), 0.943 
 Mechanical ventilation use 48 (5.47) 79,669 (5.60) 0.59 (0.35–0.98), 0.040 0.90 (0.49–1.66), 0.733 
  <24 h 26 (2.94) 27,030 (1.90) 1.22 (0.64–2.32), 0.541 1.43 (0.64–3.20), 0.382 
  24–96 h 15 (1.69) 34,286 (2.41) 0.43 (0.22–0.83), 0.012 0.73 (0.24–2.28), 0.590 
  >96 h 7 (0.84) 22,336 (1.57) 0.28 (0.09–0.87), 0.027 0.46 (0.04–5.90), 0.546 
 Acute HF 266 (29.97) 288,088 (20.25) 1.17 (0.86–1.59), 0.308 1.17 (0.75–1.81), 0.487 
 Coronary artery dissection 5 (0.53) 13,373 (0.94) 0.54 (0.12–2.50), 0.431 0.10 (0.02–0.65), 0.016 
 Cardiac tamponade 3 (0.36) 2,845 (0.20) 1.01 (0.24–4.32), 0.991 
 Ischemic stroke 6 (0.70) 13,231 (0.93) 0.50 (0.18–1.38), 0.180 0.35 (0.14–0.93), 0.034 
 Hemorrhagic stroke 1 (0.15) 142 (0.01) 
 DVT 3 (0.37) 4,552 (0.32) 0.72 (0.18–2.92), 0.642 
 PE 2 (0.26) 4,268 (0.30) 0.63 (0.09–4.44), 0.639 
 CIED use 16 (1.85) 14,507 (1.09) 1.08 (0.48–2.41), 0.852 0.75 (0.23–2.44), 0.634 
 CHB 22 (2.48) 28,026 (1.97) 0.99 (0.52–1.90), 0.983 0.75 (0.30–1.84), 0.523 
 AKI 201 (22.69) 209,131 (14.70) 0.83 (0.62–1.11), 0.211 0.83 (0.57–1.20), 0.324 
 AKI requiring dialysis 15 (1.74) 12,519 (0.88) 0.80 (0.37–1.75), 0.574 4.53 (0.25–82.76), 0.308 
 Dialysis 53 (5.93) 39,834 (2.80) 1.05 (0.66–1.67), 0.837 1.45 (0.58–2.28), 0.699 
 Major bleed 28 (3.20) 25,181 (1.77) 1.01 (0.59–1.71), 0.982 0.76 (0.36–1.60), 0.460 
 Major bleed requiring transfusion 10 (1.18) 5,691 (0.40) 1.36 (0.62–2.96), 0.445 1.12 (0.24–5.22), 0.889 
 Blood transfusion 59 (6.60) 31,298 (2.20) 1.52 (0.99–2.34), 0.059 1.69 (0.83–3.47), 0.150 
Clinical outcomes 
 In-hospital mortality 40 (4.47) 47,374 (3.33) 0.84 (0.49–1.44), 0.527 0.93 (0.49–1.80), 0.838 
 30-day readmission 130 (14.64) 132,312 (9.30) 1.17 (0.92–1.47), 0.197 1.41 (0.99–2.01), 0.056 
VariableCML group (n = 888), n (%)Non-CML group (n = 1,422,659), n (%)Multivariate regression analysis
OR (95% CI), p valuepropensity-matched OR (95% CI), p value
Complications 
 Cardiac arrest 14 (1.58) 45,383 (3.19) 0.41 (0.20–0.85), 0.017 1.04 (0.41–2.64), 0.940 
 VT 78 (8.85) 162,468 (11.42) 0.69 (0.47–1.01), 0.056 1.02 (0.64–1.63), 0.925 
 MCS use 54 (6.04) 86,355 (6.07) 0.55 (0.35–0.87), 0.011 0.68 (0.41–1.14), 0.144 
 IABP 35 (3.90) 57,191 (4.02) 0.60 (0.36–1.00), 0.050 0.80 (0.42–1.52), 0.491 
 Impella 22 (2.53) 31,723 (2.23) 0.61 (0.32–1.18), 0.141 0.68 (0.31–1.49), 0.339 
 ECMO 2,845 (0.20) 
 LVAD 569 (0.04) 
 Vasopressor use 21 (2.32) 19,917 (1.40) 1.02 (0.53–1.98), 0.948 1.00 (0.38–2.64), 0.994 
 Septic shock 6 (0.67) 9,531 (0.67) 0.53 (0.14–1.99), 0.348 
 Respiratory failure 122 (13.76) 140,710 (9.89) 0.82 (0.58–1.16), 0.259 0.98 (0.64–1.52), 0.943 
 Mechanical ventilation use 48 (5.47) 79,669 (5.60) 0.59 (0.35–0.98), 0.040 0.90 (0.49–1.66), 0.733 
  <24 h 26 (2.94) 27,030 (1.90) 1.22 (0.64–2.32), 0.541 1.43 (0.64–3.20), 0.382 
  24–96 h 15 (1.69) 34,286 (2.41) 0.43 (0.22–0.83), 0.012 0.73 (0.24–2.28), 0.590 
  >96 h 7 (0.84) 22,336 (1.57) 0.28 (0.09–0.87), 0.027 0.46 (0.04–5.90), 0.546 
 Acute HF 266 (29.97) 288,088 (20.25) 1.17 (0.86–1.59), 0.308 1.17 (0.75–1.81), 0.487 
 Coronary artery dissection 5 (0.53) 13,373 (0.94) 0.54 (0.12–2.50), 0.431 0.10 (0.02–0.65), 0.016 
 Cardiac tamponade 3 (0.36) 2,845 (0.20) 1.01 (0.24–4.32), 0.991 
 Ischemic stroke 6 (0.70) 13,231 (0.93) 0.50 (0.18–1.38), 0.180 0.35 (0.14–0.93), 0.034 
 Hemorrhagic stroke 1 (0.15) 142 (0.01) 
 DVT 3 (0.37) 4,552 (0.32) 0.72 (0.18–2.92), 0.642 
 PE 2 (0.26) 4,268 (0.30) 0.63 (0.09–4.44), 0.639 
 CIED use 16 (1.85) 14,507 (1.09) 1.08 (0.48–2.41), 0.852 0.75 (0.23–2.44), 0.634 
 CHB 22 (2.48) 28,026 (1.97) 0.99 (0.52–1.90), 0.983 0.75 (0.30–1.84), 0.523 
 AKI 201 (22.69) 209,131 (14.70) 0.83 (0.62–1.11), 0.211 0.83 (0.57–1.20), 0.324 
 AKI requiring dialysis 15 (1.74) 12,519 (0.88) 0.80 (0.37–1.75), 0.574 4.53 (0.25–82.76), 0.308 
 Dialysis 53 (5.93) 39,834 (2.80) 1.05 (0.66–1.67), 0.837 1.45 (0.58–2.28), 0.699 
 Major bleed 28 (3.20) 25,181 (1.77) 1.01 (0.59–1.71), 0.982 0.76 (0.36–1.60), 0.460 
 Major bleed requiring transfusion 10 (1.18) 5,691 (0.40) 1.36 (0.62–2.96), 0.445 1.12 (0.24–5.22), 0.889 
 Blood transfusion 59 (6.60) 31,298 (2.20) 1.52 (0.99–2.34), 0.059 1.69 (0.83–3.47), 0.150 
Clinical outcomes 
 In-hospital mortality 40 (4.47) 47,374 (3.33) 0.84 (0.49–1.44), 0.527 0.93 (0.49–1.80), 0.838 
 30-day readmission 130 (14.64) 132,312 (9.30) 1.17 (0.92–1.47), 0.197 1.41 (0.99–2.01), 0.056 

AKI, acute kidney injury; CHB, complete heart block; CI, confidence interval; CIED, cardiovascular implantable electronic device; CML, chronic myeloid leukemia; DVT, deep venous thrombosis; ECMO, extracorporeal membrane oxygenation; HF, heart failure; IABP, intra-aortic balloon pump; LVAD, left ventricular assist device; MCS, mechanical circulatory support; OR, odds ratio; PE, pulmonary embolism; VT, ventricular tachycardia.

This retrospective cohort study investigated the impact of CML diagnosis on the rates of post-PCI complications and clinical outcomes. There was no statistical difference between patients with or without CML in terms of in-hospital mortality, 30-day readmission, and post-PCI complications. However, among CML patients, there was a trend toward an increased risk of 30-day readmission by 41% and significantly lower rates of coronary artery dissection and ischemic stroke in the propensity matched analysis.

CML is not an uncommon cancer and accounts for up to 20% of leukemia in adults [8]. The overall prognosis of CML is favorable. However, the prognosis depends on many factors, with the disease phase at the time of diagnosis being the most reliable predictor of prognosis by far [8]. Patients who are in the chronic phase at the time of diagnosis can control their condition with treatment over the years, but those who are in the accelerated phase or blast crisis have a significantly worse prognosis [9]. The objectives of care for the CML patients are to achieve clinical, cytogenetic, and molecular remission; maintain long-term disease control; prevent progression to advanced disease; and improve quality of life through minimizing treatment-related toxicity and treatment-free remission [10, 11]. The leading cause of death worldwide is cardiovascular disease, followed by cancer. In a cancer patient receiving chemotherapy as an outpatient, the leading cause of death is the progression of cancer, followed by arterial thrombotic events, as shown in a large analysis [12]. With the improvement of cancer treatment, it is anticipated that patients with cancer will have an excellent prognosis and normal life expectancy. The current therapeutic goal for CML patients is to have treatment-free remission and a better quality of life. Patients with CML may have normal life expectancy with the use of various TKI agents. With an improved prognosis, many patients start to question their quality of life and expectations, such as fertility [13, 14], while others wonder about the expected outcome if they experience cardiac events requiring intervention. One study showed no difference in the short-term outcomes between STEMI patients with and without cancer [15]. Interestingly, it was found that primary PCI was underutilized in patients with cancer, including blood, breast, prostate, and colon cancers. On the other hand, a recent meta-analysis showed that cancer did not increase the risk of cardiovascular death, but it increased the risk of all-cause mortality, recurrent myocardial infarction, and significant bleeding in patients presenting with myocardial infarction [16]. An interesting and surprising finding in this study showed that CML diagnosis might be protective against coronary artery dissection and ischemic stroke. However, study limitations should be considered when interpreting this finding.

The use of TKI in CML has been associated with several thrombotic complications. This association is more frequently seen with second-generation (e.g., nilotinib, ponatinib) than with first-generation TKI. TKI inhibits tyrosine kinase activity that stops the uncontrolled production of granulocytes. However, TKIs vary in their specificity in targeting the tyrosine kinase. For example, first-generation TKIs (e.g., imatinib) act by competitively inhibiting the tyrosine kinase at the ATP binding site, which prevents the conformation change to the active form. As opposed to imatinib, less selective broad-spectrum kinase inhibitors such as dasatinib (a second-generation TKI) can block other signaling pathways such as SRC kinases. This broad activity could explain the reason behind the increase in thrombotic events with the use of second-generation TKIs as more broad actions might lead to effects on other cells, including endothelium. Many pathways are affected, especially those which impact multiple signal transduction pathways. The most affected pathways are ubiquitin proteasomal system, lysosomal autophagy pathways [17], cardiotrophin and its receptor gp 130, phosphoinositide 3-kinase, cardiotrophin and its receptor, and AMP-activated protein kinase. Similarly, the development of TKI-induced cardiovascular target-organ damage is frequently linked to the vascular endothelial growth factor [18], which is involved in angiogenesis, microvascular function, and myocardial perfusion.

One of the key factors affecting the health care system is cost. In the USA, a hospital day costs an average of USD 2,883 [19]. The present analysis showed that CML patients have a longer hospital stay by approximately 1 day compared to the non-CML patients. Furthermore, patients with CML may have a trend toward a 40% increase in the 30-day readmission rate (OR: 1.41; 95% CI: 0.99–2.01, p = 0.056). Taken together, the increase in hospital stay and 30-day readmission rate might suggest additional treatment costs for CML patients.

A report generated from the Food and Drug Administration Adverse Event Reporting System (FAERS) showed that TKI may vary in their cardiovascular adverse effects and the related fatality profile, namely, acute coronary syndrome (ACS) and STEMI. As shown in Table 3, imatinib is the most frequently reported TKI that is linked to ACS and related fatality. Imatinib is a first-line treatment of CML and is the most prescribed TKI. It is cheaper, more readily available, and more commonly used than other TKI. Thus, adverse events and fatalities are potentially more likely to be reported with its use than other agents. Nilotinib, a second-generation TKI, is the most frequently reported in association with STEMI events since 2007. Other second-generation TKIs, ponatinib and bosutinib, have also been reported to be associated with STEMI events (Table 3). The second-generation TKIs are more potent and more likely to achieve remission and treatment-free remission than the first-generation agents. However, they are more expensive and probably associated with higher risk of STEMI. Thus, their risk-benefit assessment is warranted. In addition, primary prevention of cardiovascular events should be considered by using preventative medications as appropriate and by controlling risk factors such as hypertension, diabetes, dyslipidemia, and smoking if present.

Table 3.

ACS and STEMI adverse events in CML patients reported in FAERS (by June 30, 2023)

FDA-approved TKI (approval date)ACSSTEMI
number of adverse eventsnumber of related fatalitiesnumber of adverse eventsnumber of related fatalities
Imatiniba (Oct 2001) 1,257 649 72 34 
Dasatinibb (Jun 2006) 12 40 
Nilotinibc (Oct 2007) 105 11 275 37 
Bosutinibd (Sep 2012) 19 
Ponatinibe (Dec 2012) 18 29 
Asciminbf (Oct 2021) 
FDA-approved TKI (approval date)ACSSTEMI
number of adverse eventsnumber of related fatalitiesnumber of adverse eventsnumber of related fatalities
Imatiniba (Oct 2001) 1,257 649 72 34 
Dasatinibb (Jun 2006) 12 40 
Nilotinibc (Oct 2007) 105 11 275 37 
Bosutinibd (Sep 2012) 19 
Ponatinibe (Dec 2012) 18 29 
Asciminbf (Oct 2021) 

Results were filtered to chronic myeloid leukemia as reason for use, acute coronary syndrome as reaction group, or ST segment elevation or acute myocardial infarction as reaction group.

ACS, acute coronary syndrome; CML, chronic myeloid leukemia; FAERS, Food and Drug Administration Adverse Event Reporting System; FDA, Food and Drug Administration; TKI, tyrosine kinase inhibitor.

aSuspect ingredients were limited to imatinib or imatinib mesylate only.

bSuspect ingredients were limited to dasatinib or dasatinib anhydrous only.

cSuspect ingredients were limited to nilotinib or nilotinib hydrochloride anhydrous or nilotinib hydrochloride monohydrate only.

dSuspect ingredients were limited to bosutinib or bosutinib monohydrate only.

eSuspect ingredients were limited to ponatinib only.

fSuspect ingredients were limited to asciminib, or asciminib hydrochloride only.

The present study has limitations that should be acknowledged when interpreting the findings. Its nonrandomized retrospective observational nature is prone to potential confounding as well as selection and ascertainment bias. Despite using propensity matching method to adjust for the measurable confounders, the unmeasurable ones remain of a concern. The NRD is an administrative database that lacks details on PCI (e.g., access, timing, medications, guidelines used); ACS management; thrombolysis use; risk scores; baseline medications; complications and outcomes definitions; mid- and long-term follow-up; and CML diagnosis duration, phase, and medical therapies. NRD has also the potential for miscoding (e.g., miscoded events) or missed observations. Furthermore, although the FAERS database is a useful tool to examine the safety concerns relating to marketed products, there are significant limitations in drawing significant conclusions from this database. Examples of the related limitations include low-quality reports, duplicate reporting, the absence of death causes, inappropriate estimation of the incidence rates, or drawing evidence about causality.

This analysis showed no statistically significant difference in mortality, 30-day readmission, and post PCI complications rates between CML and non-CML patients. Therefore, the diagnosis of CML should not prevent patients from receiving routine therapy and intervention because of the theoretical risk of thrombosis. Because various TKI agents may have potential differences in their associated risk of STEMI and the rate of achieving treatment-free remission, it is crucial to weigh the risks and benefits associated with each TKI and tailor them according to the patient’s risk.

An ethics statement was not required for this study type as it is based exclusively on data extracted from the Nationwide Readmission Database and FDA reporting system. Written informed patient consent was not required for this study type as it is based exclusively on data extracted from the Nationwide Readmission database and FDA reporting system.

All the authors have no conflict of interest.

This research received no external funding. Open access payment by the Qatar National Library.

Elrazi A Ali: conceptualization, writing, editing, and final approval. Neel Patel: writing, editing, data analysis, and final approval. Mazin Khalid, Jacob Shani, Madhumathi Kalavar, and Mohamed Yassin: writing, editing, and final approval. Rasha Kaddoura: writing, editing, data analysis, and final approval.

All data generated or analyzed during this study are included in this article. Further inquiries can be directed to the corresponding author.

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