Abstract
Background
Long‐term use of antiplatelet agents after acute coronary syndrome in diabetic patients is not well known. Here, we describe antiplatelet use and outcomes in such patients enrolled in the EPICOR Asia (Long‐Term Follow‐up of Antithrombotic Management Patterns in Acute Coronary Syndrome Patients in Asia) registry.
Methods and Results
EPICOR Asia is a prospective, observational study of 12 922 patients with acute coronary syndrome surviving to discharge, from 8 countries/regions in Asia. The present analysis included 3162 patients with diabetes mellitus (DM) and 9602 patients without DM. The impact of DM on use of antiplatelet agents and events (composite of death, myocardial infarction, and stroke, with or without any revascularization; individual components, and bleeding) was evaluated. Significant baseline differences were seen between patients with DM and patients without DM for age, sex, body mass index, cardiovascular history, angiographic findings, and use of percutaneous coronary intervention. At discharge, ≈90% of patients in each group received dual antiplatelet therapy. At 2‐year follow‐up, more patients with DM tended to still receive dual antiplatelet therapy (60% versus 56%). DM was associated with increased risk from ischemic but not major bleeding events. Independent predictors of the composite end point of death, myocardial infarction, and stroke in patients with DM were age ≥65 years and use of diuretics at discharge.
Conclusions
Antiplatelet agent use is broadly comparable in patients with DM and patients without DM, although patients with DM are more likely to be on dual antiplatelet therapy at 2 years. Patients with DM are at increased risk of ischemic events, suggesting an unmet need for improved antithrombotic treatment.
Registration
URL: https://www.clinicaltrials.gov; Unique identifier: NCT01361386.
Keywords: acute coronary syndrome, antiplatelet agents, diabetes mellitus
Subject Categories: Mortality/Survival, Quality and Outcomes, Acute Coronary Syndromes, Angina
Nonstandard Abbreviations and Acronyms
- DAPT
dual antiplatelet therapy
- DM
diabetes mellitus
- EPICOR
Long‐Term Follow‐up of Antithrombotic Management Patterns in Acute Coronary Syndrome Patients
- PoCE
patient‐oriented composite end point
Clinical Perspective
What Is New?
Among patients surviving an acute coronary syndrome, ≈90% of both patients with diabetes mellitus (DM) and patients without DM were discharged on dual antiplatelet therapy, but somewhat more patients with DM than patients without DM were on dual antiplatelet therapy at 2 years after discharge (60% versus 56%).
Although DM was associated with increased risk of ischemic events during follow‐up, there was minimal impact on risk of major bleeding.
Multivariable analysis showed that independent predictors of the composite end point of death, myocardial infarction, and stroke in patients with DM were older age (≥65 years) and use of diuretics at discharge.
What Are the Clinical Implications?
Despite a higher rate of dual antiplatelet therapy use in patients with DM than patients without DM at 2 years after an acute coronary syndrome, patients with DM were at increased risk of ischemic but not bleeding events, suggesting an unmet need for improved antithrombotic treatment.
According to the International Diabetes Federation, in 2015, there were ≈415 million patients worldwide aged 20 to 79 with diabetes mellitus (DM), along with a further 193 million undiagnosed cases. 1 Type 2 DM accounts for up to 90% of all cases, and the prevalence is increasing globally. 1 About half of all deaths in patients with DM are due to cardiovascular disease, 1 the majority resulting from thrombotic events. 2 In addition, patients with DM have a 2‐ to 4‐fold higher risk of recurrent atherothrombotic events and vascular complications than those without DM. 2 Along with oxidative stress, inflammation, and endothelial dysfunction, platelet hyperactivity plays a major role in the progression of thrombotic and cardiovascular events, and type 2 DM is characterized by altered platelet metabolism with increased platelet reactivity and aggregation, which contribute to atherothrombotic complications. 2 , 3 Furthermore, DM is associated with an impaired response to the antiplatelet drug clopidogrel, leading to high on‐treatment platelet reactivity and increased cardiovascular risk. 4 , 5 The use of effective antiplatelet agents could reduce thrombotic complications by inhibiting adenosine diphosphate–induced platelet reactivity. 6
As DM is directly related to both early and late mortality in patients with acute coronary syndrome (ACS), 7 the appropriate management of DM can effectively reduce overall mortality and improve quality of life of patients with ACS. 8 While it is recommended that patients with DM receive antiplatelet agents after ACS, 9 , 10 the long‐term efficacy and safety of antiplatelet agents in this setting is not well known.
The large‐scale prospective EPICOR Asia (Long‐Term Follow‐up of Antithrombotic Management Patterns in Acute Coronary Syndrome Patients in Asia) study (NCT01361386) 11 enrolled patients surviving an ACS, and provided important information regarding clinical management as well as antithrombotic management patterns for patients with ACS in Asia. We analyzed the EPICOR Asia database to compare antithrombotic management patterns and outcomes in patients with ACS, both with and without DM, including overall and propensity score‐matched cohorts.
Methods
Data underlying the findings described in this manuscript may be obtained in accordance with AstraZeneca's data‐sharing policy described at https://astrazenecagrouptrials.pharmacm.com/ST/Submission/Disclosure.
Study Protocol
The EPICOR Asia study has been previously described in detail 11 and, in summary, was a prospective, observational study of 12 922 patients with ACS surviving to discharge with 2‐year follow‐up, from 219 centers in 8 countries in Asia. All enrolled patients signed written informed consent forms at discharge. The study was conducted in accordance with the ethical principles that are consistent with the Declaration of Helsinki, the International Conference on Harmonization Good Clinical Practice guidelines, and applicable legislation on noninterventional studies in participating countries and regions. The study protocol was approved by the applicable ethics committees for all participating study sites.
Patients
Patient eligibility has also been thoroughly described previously. 11 In summary, consecutive patients ≥18 years of age were considered for enrollment if they were hospitalized within 48 hours of symptom onset of the index cardiovascular event and had a discharge diagnosis of ST‐segment–elevation myocardial infarction (STEMI), non‐STEMI (NSTEMI), or unstable angina. Principal exclusion criteria included an ACS event secondary to or as a complication of other diseases, such as surgery, trauma, or gastrointestinal bleeding, or after percutaneous coronary intervention, or noncardiac comorbid conditions with limited short‐term life expectancy or that might result in protocol noncompliance.
Treatment
All patients in EPICOR Asia underwent routine clinical assessment and received standard antiplatelet therapy. Their detailed medication regimen, which included choice of antiplatelet drugs, their combinations, dosing, timing, and continuation of use during hospitalization and after discharge, was determined by the treating cardiologist; patients did not receive any experimental intervention or treatment. Follow‐up interviews were prespecified at 6 weeks and 3 months after the index event and every 3 months thereafter for 2 years in all patients.
End Points
The primary end point was defined as the CV composite 12 of all‐cause death, myocardial infarction (MI), and ischemic stroke. Secondary efficacy end points were the patient‐oriented composite end point (PoCE) of all‐cause death, MI, stroke, and revascularization. Safety end points were bleeding, including major and minor bleeding. MI was defined in accordance with the third universal definition proposed in 2013, 13 , 14 and stroke as focal or partial loss of neurologic function caused by either an ischemic or hemorrhagic event. Major bleeding was defined as life‐threatening intracranial, hemodynamic compromised bleeding; bleeding requiring transfusion; or a fall in hemoglobin >5 g/dL, 15 while minor bleeding was defined as bleeding that did not meet the above criteria.
Statistical Analysis
For baseline characteristics, categorical variables were summarized as frequencies and percentages and continuous variables as means (SD). Baseline characteristics between patients with DM and patients without DM were compared using the chi‐square test and t‐test for categorical and continuous variables, respectively.
To reduce imbalances in patient characteristics and confounding factors, patients with DM were matched 1:1 with a non‐DM control based on the patient's propensity score using nearest available neighbor matching with no replacement. Here, caliper width was derived as 0.2×(SD of logit of propensity score). The propensity score for DM (probability of having DM) was estimated by multivariable logistic regression including age, sex, body mass index (≤25, >25), history of smoking, medical history (hypertension, dyslipidemia, prior MI, prior percutaneous coronary intervention, prior stroke/transient ischemic attack, peripheral artery disease, heart failure), renal insufficiency (estimated glomerular filtration rate [eGFR] <60 mL/min per 1.73 m2), index event diagnosis, chronic anemia, and major bleeding within 6 months before index event. Standardized differences were calculated for the propensity score–matched populations.
Time to first cardiovascular event was analyzed on the basis of a univariate Cox proportional hazards model including DM status (DM or non‐DM) using the overall (full) cohort and a propensity score–matched patient cohort to estimate unadjusted and adjusted hazard ratio (HR), respectively, along with its 95% CI and P value. Kaplan–Meier plots for each end point were made for the overall and matched patient cohorts.
Multivariable Cox proportional hazards regression analysis, including medications at discharge, was performed in patients with DM to determine predictors of ischemic events (days to death, MI, stroke, and revascularization) and bleeding events (days to any bleeding and major bleeding) among DM patients. The proportional hazards assumption was initially assessed by inspection of the Kaplan–Meier curves for the 2 groups and confirmed by testing of the correlation between the Schoenfeld residuals from the fitted model with time (all P=NS). Variable selection was done by stepwise procedure with the P value cutoffs for selection at P<0.01 and retention at P<0.20. Results based on the final model are presented as HR with 95% CI and P value.
Results
Study Patients and Baseline Characteristics
The EPICOR Asia study recruited 13 005 patients between June 2011 and May 2012. Of these, 83 were excluded: 19 did not survive to discharge and 64 were excluded due to critical data quality issues. 11 Thus, 12 922 patients met the inclusion/exclusion criteria, of whom 12 764 had known diabetic status (DM, n=3162; non‐DM, n=9602) and were included in the unmatched analysis. In addition, a propensity score–matched non‐DM control was identified for 3079 patients with DM (83 patients unmatched). Demographic and baseline characteristics were generally well balanced between patients with DM and patients without DM (Table 1 and Table S1). Notably, patients with DM tended to be older than patients without DM in the full cohort (61.2 versus 59.5 years; P<0.0001), with fewer patients in the ≤55 years age group (27.9% versus 36.8%); in the matched cohort, however, age was well balanced between patients with DM and patients without DM. Patients with DM also had a higher mean body mass index (25.2 versus 24.5 kg/m2; P<0.0001). Renal insufficiency was significantly more common in patients with DM than patients without DM in the full cohort (P<0.0001), but the difference disappeared in the matched cohort. Patients with DM were less likely to receive government‐provided insurance (67.1% versus 70.9%; P<0.0001) and more likely to have no insurance (19.3% versus 15.1%; P<0.0001), and most patients were treated at a university general hospital, irrespective of DM status (DM, 50.8%; non‐DM, 56.1%), with only 5.7% of patients treated in regional, community, or rural hospitals and with similar results in the matched cohort.
Table 1.
Parameters | Patients With DM | Patients Without DM | P Value | ||
---|---|---|---|---|---|
N | n (%)/Mean (SD) | N | n (%)/Mean (SD) | ||
Age, y, mean (SD) | 3162 | 62.1 (10.7) | 9602 | 59.5 (11.8) | <0.0001 |
Age group, y | <0.0001 | ||||
≤55 | 883 (27.9) | 3529 (36.8) | |||
56 to 64 | 958 (30.3) | 2807 (29.2) | |||
65 to 74 | 894 (28.3) | 2192 (22.8) | |||
≥75 | 427 (13.5) | 1074 (11.2) | |||
Male | 3162 | 2210 (69.9) | 9602 | 7527 (78.4) | <0.0001 |
BMI, kg/m2, mean (SD) | 2866 | 25.2 (3.5) | 8853 | 24.5 (3.6) | <0.0001 |
BMI group, kg/m2 | <0.0001 | ||||
≤25 | 1496 (52.2) | 5304 (59.9) | |||
>25 | 1370 (47.8) | 3549 (40.1) | |||
Place of residence | <0.0001 | ||||
Rural | 3162 | 1034 (32.7) | 9602 | 3633 (37.8) | |
Metropolitan | 2128 (67.3) | 5969 (62.2) | |||
Insurance type | 3162 | 9602 | |||
Government | 2121 (67.1) | 6811 (71.0) | <0.0001 | ||
Private | 322 (10.2) | 995 (10.4) | 0.77 | ||
Employer provided | 46 (1.5) | 166 (1.7) | 0.30 | ||
Other | 117 (3.7) | 368 (3.8) | 0.74 | ||
None | 609 (19.3) | 1447 (15.1) | <0.0001 | ||
Hospital type | 3162 | 9602 | <0.0001 | ||
Reg/comm/rural | 181 (5.7) | 546 (5.7) | |||
Non–university general | 736 (23.3) | 2403 (25.0) | |||
University general | 1607 (50.8) | 5383 (56.1) | |||
Other | 638 (20.2) | 1270 (13.2) | |||
Medical history | |||||
Hypertension | 3156 | 2227 (70.6) | 9595 | 4545 (47.4) | <0.0001 |
Hypercholesterolemia | 3007 | 792 (26.3) | 9384 | 1381 (14.7) | <0.0001 |
Current smoker | 2933 | 802 (27.3) | 8999 | 3516 (39.1) | <0.0001 |
Prior MI | 3057 | 447 (14.6) | 9380 | 765 (8.2) | <0.0001 |
Prior PCI | 3063 | 340 (11.1) | 9410 | 625 (6.6) | <0.0001 |
TIA/stroke | 3056 | 196 (6.4) | 9396 | 368 (3.9) | <0.0001 |
PVD | 3047 | 42 (1.4) | 9384 | 58 (0.6) | <0.0001 |
Chronic anemia | 3074 | 50 (1.6) | 9405 | 54 (0.6) | <0.0001 |
Major bleeding | 3097 | 19 (0.6) | 9491 | 33 (0.4) | <0.05 |
In‐hospital events | |||||
Myocardial infarction | 3124 | 142 (4.6) | 9529 | 244 (2.6) | <0.0001 |
Stroke | 3135 | 6 (0.2) | 9541 | 18 (0.2) | 0.98 |
Heart failure | 3133 | 207 (6.6) | 9529 | 448 (4.7) | <0.0001 |
Severe arrhythmias | 3110 | 140 (4.5) | 9516 | 431 (4.5) | 0.95 |
TVR | 3162 | 2042 (64.6) | 9602 | 6701 (69.8) | <0.0001 |
Bleeding | |||||
Major | 3162 | 14 (0.4) | 9602 | 49 (0.5) | 0.64 |
Minor | 3162 | 46 (1.5) | 9602 | 164 (1.7) | <0.0001 |
Clinical presentation | 3162 | 9602 | |||
STEMI | 1439 (45.5) | 5089 (53.0) | <0.0001 | ||
NSTEMI | 770 (24.4) | 1770 (18.4) | |||
Unstable angina | 953 (30.1) | 2743 (28.6) | |||
Renal function, eGFR, mL/min per 1.73 m2, mean (SD) | 3162 | 88.1 (35.8) | 9602 | 95.1 (34.7) | <0.0001 |
Renal function group, eGFR, mL/min per 1.73 m2 | <0.0001 | ||||
<30 | 127 (4.0) | 103 (1.1) | |||
30–59 | 509 (16.1) | 934 (9.7) | |||
60–89 | 1123 (35.5) | 3480 (36.2) | |||
≥90 | 1403 (44.4) | 5085 (53.0) | |||
Laboratory tests | |||||
Hemoglobin, g/dL, mean (SD) | 3018 | 13.2 (2.0) | 9172 | 13.7 (1.9) | <0.0001 |
Peak Cr, mg/dL, mean (SD) | 2790 | 1.2 (0.9) | 8686 | 1.0 (0.6) | <0.0001 |
Positive cardiac markers | 3103 | 2207 (71.1) | 9458 | 6851 (72.4) | 0.16 |
Medications at discharge | |||||
Beta‐blocker | 3145 | 2220 (70.6) | 9581 | 6552 (68.4) | <0.05 |
Calcium channel blocker | 3122 | 475 (15.2) | 9560 | 1060 (11.1) | <0.0001 |
ACEi/ARB | 3144 | 2046 (65.1) | 9578 | 5880 (61.4) | <0.001 |
Any LLT | 3162 | 2835 (89.7) | 9602 | 8727 (90.9) | <0.05 |
Atorvastatin | 1678 (53.1) | 4858 (50.6) | <0.001 | ||
Fluvastatin | 45 (1.4) | 144 (1.5) | |||
Pravastatin | 23 (0.7) | 85 (0.9) | |||
Rosuvastatin | 635 (20.1) | 2185 (22.8) | |||
Simvastatin | 379 (12.0) | 1298 (13.5) | |||
Multiple statins | 20 (0.6) | 47 (0.5) | |||
Other LLT only | 55 (1.7) | 110 (1.2) | |||
Diuretic | 3128 | 624 (20.0) | 9564 | 1055 (11.0) | <0.0001 |
Nitrate | 2971 | 280 (9.4) | 9036 | 712 (7.9) | <0.01 |
Any PPI | 3162 | 1168 (36.9) | 9602 | 3333 (34.7) | <0.05 |
Results are unadjusted. P values from chi‐square test or t‐test as appropriate. ACEi indicates angiotensin‐converting enzyme inhibitor; ARB, angiotensin II receptor blocker; BMI, body mass index; Cr, creatinine; CVD, cardiovascular disease; DM, diabetes mellitus; eGFR, estimated glomerular filtration rate; LLT, lipid‐lowering therapy; NSTEMI, non–ST‐segment–elevation myocardial infarction; PCI, percutaneous coronary intervention; PPI, proton pump inhibitor; PVD, peripheral vascular disease; Reg/comm/rural, regional/community/rural; STEMI, ST‐segment–elevation myocardial infarction; TIA, transient ischemic attack; and TVR, target vessel revascularization.
More patients without DM than patients with DM underwent any cardiac catheterization (82.7% versus 80.1%; P<0.001), and the rate of multivessel disease at the index event was higher in the DM than in the non‐DM group (51.0% versus 44.3%; P<0.0001), with a greater percentage of patients with DM having 3 target vessels (40.5% versus 29.9%), and more than 2 stents implanted (16.8% versus 13.0%), with similar findings in the matched cohort (Table 2 and Table S2). Following discharge, there were no significant differences between the groups in terms of cardiovascular interventions in the unmatched or matched cohorts. In‐hospital MI was more frequently reported in patients with DM than patients without DM (4.6% versus 2.6%; P<0.0001), and patients with DM were more often prescribed diuretics at discharge (20.0% versus 11.0%; P<0.0001) (Table 1). Similar findings were observed in the matched cohort (Table S1). Notably, in‐hospital hemoglobin level was measured less frequently in the DM group.
Table 2.
Parameters | Patients With DM | Patients Without DM | P Value | ||
---|---|---|---|---|---|
N | n (%) | N | n (%) | ||
Cardiac catheterization during the index hospitalization | 3119 | 2498 (80.1) | 9513 | 7868 (82.7) | <0.001 |
Multivessel disease | 3162 | 1612 (51.0) | 9602 | 4256 (44.3) | <0.0001 |
PCI | 3080 | 2013 (65.4) | 9457 | 6638 (70.2) | <0.0001 |
Emergency PCI | 3080 | 937 (30.4) | 9457 | 3281 (34.7) | <0.0001 |
Target vessel | 2146 | 7685 | <0.05 | ||
Arterial bypass graft | 1 (0) | 2 (0) | |||
LAD | 1361 (56.3) | 4510 (58.7) | |||
LCX | 355 (14.7) | 939 (12.2) | |||
Left main | 54 (2.2) | 188 (2.5) | |||
RCA | 642 (26.6) | 2041 (26.6) | |||
Vein bypass graft(s) | 3 (0.1) | 5 (0.1) | |||
Number of target vessels | 2256 | 7175 | <0.0001 | ||
1 | 668 (29.6) | 2941 (41.0) | |||
2 | 675 (29.9) | 2086 (29.1) | |||
3 | 913 (40.5) | 2148 (29.9) | |||
Any stent | 3080 | 1971 (64.0) | 9457 | 6505 (68.8) | <0.0001 |
Number of stents | 1971 | 6506 | <0.0001 | ||
1 | 1076 (54.6) | 4010 (61.6 | |||
2 | 564 (28.6) | 1651 (25.4) | |||
>2 | 331 (16.8) | 845 (13.0) | |||
Postdischarge interventions | |||||
Cardiac catheterization | 3162 | 262 (8.3) | 9602 | 779 (8.1) | 0.76 |
Angiography | 3162 | 146 (4.6) | 9602 | 460 (4.8) | 0.69 |
Balloon PCI | 3162 | 32 (1.0) | 9602 | 86 (0.9) | 0.55 |
Any stent | 3162 | 140 (4.4) | 9602 | 387 (4.0) | 0.33 |
Bare metal stent | 3162 | 14 (0.4) | 9602 | 44 (0.5) | 0.91 |
Drug‐eluting stent | 3162 | 126 (4.0) | 9602 | 346 (3.6) | 0.32 |
Results are unadjusted. P values from chi‐square test or t‐test as appropriate. DM indicates diabetes mellitus; LAD, left anterior descending; LCX, left circumflex; PCI, percutaneous coronary intervention; and RCA, right coronary artery.
Antithrombotic Medication
No statistically significant difference was evident between patients with DM and patients without DM in terms of prehospital chronic treatment with aspirin or P2Y12 inhibitors (Table 3 and Table S3). In‐hospital antithrombotic treatment was also similar in the 2 groups, with the exception that patients with DM were less likely to receive aspirin or clopidogrel loading doses. Use of antiplatelet agents at discharge was also broadly comparable in each group. Most patients received dual antiplatelet therapy (DAPT) at discharge, with somewhat lower use in patients with DM than patients without DM (88.3% versus 90.0%), although the difference disappeared in the matched cohort (88.3% versus 89.8%). At 2‐year follow‐up, however, patients with DM showed a modestly greater use of DAPT (60.0% versus 57.0%) and were also more likely to be receiving a P2Y12 inhibitor (66.4% versus 62.3%). The unmatched cohort showed similar results.
Table 3.
Parameters | Patients With DM | Patients Without DM | Standardized Difference | ||
---|---|---|---|---|---|
N | n (%) | N | n (%) | ||
In‐hospital treatment | |||||
Aspirin | 3079 | 2861 (92.9) | 3079 | 2867 (93.1) | −0.0076 |
Loading | 3079 | 1140 (37.0) | 3079 | 1195 (38.8) | −0.0368 |
Any P2Y12 inhibitor | 3079 | 2875 (93.4) | 3079 | 2849 (92.5) | 0.0330 |
Clopidogrel | 3079 | 2811 (91.3) | 3079 | 2794 (90.7) | 0.0193 |
Loading | 3079 | 1387 (45.1) | 3079 | 1464 (47.6) | −0.0502 |
Ticagrelor | 3079 | 2 (0.1) | 3079 | 3 (0.1) | −0.0114 |
Prasugrel | 3079 | 87 (2.8) | 3079 | 71 (2.3) | 0.0329 |
Ticlopidine | 3079 | 10 (0.3) | 3079 | 9 (0.3) | 0.0059 |
Cilostazol | 3079 | 81 (2.6) | 3079 | 55 (1.8) | 0.0575 |
LMW heparin | 3079 | 1657 (53.8) | 3079 | 1717 (55.8) | −0.0392 |
Fondaparinux | 3079 | 310 (10.1) | 3079 | 318 (10.3) | −0.0086 |
GPIIb/IIIa inhibitor | 3079 | 502 (16.3) | 3079 | 512 (16.6) | −0.0088 |
Warfarin/NOAC | 3079 | 22 (0.7) | 3079 | 23 (0.8) | −0.0038 |
Thrombolytics | 3079 | 176 (5.7) | 3079 | 178 (5.8) | −0.0028 |
At discharge | |||||
Aspirin | 3036 | 2895 (95.4) | 3052 | 2934 (96.1) | −0.0385 |
Any P2Y12 inhibitor | 3033 | 2866 (94.5) | 3050 | 2873 (94.2) | 0.0129 |
Aspirin alone | 3036 | 162 (5.3) | 3052 | 167 (5.5) | −0.0060 |
P2Y12 inhibitor alone | 3033 | 122 (4.0) | 3050 | 92 (3.0) | 0.0546 |
DAPT | 3079 | 2720 (88.3) | 3079 | 2765 (89.8) | −0.0469 |
Cilostazol | 3033 | 78 (2.6) | 3050 | 55 (1.8) | 0.0526 |
Warfarin/NOAC | 3079 | 30 (1.0) | 3079 | 33 (1.1) | −0.0097 |
At 2 y | |||||
Aspirin | 2432 | 2166 (89.1) | 2481 | 2183 (88.0) | 0.0337 |
Any P2Y12 inhibitor | 2430 | 1613 (66.4) | 2481 | 1546 (62.3) | 0.0849 |
Aspirin alone | 2432 | 699 (28.7) | 2482 | 767 (30.9) | −0.0472 |
P2Y12 inhibitor alone | 2430 | 148 (6.1) | 2481 | 125 (5.0) | 0.0459 |
DAPT | 2432 | 1460 (60.0) | 2481 | 1413 (57.0) | 0.0625 |
Cilostazol | 2430 | 28 (1.2) | 2480 | 27 (1.1) | 0.0060 |
Warfarin/NOAC | 2437 | 19 (0.8) | 2488 | 19 (0.8) | 0.0018 |
DAPT indicates dual antiplatelet therapy; DM, diabetes mellitus; GP, glycoprotein; LMW, low‐molecular‐weight; and NOAC, novel oral anticoagulant.
Death and Ischemic Events
Overall, DM was an independent predictor of events on univariate analysis of the propensity score–matched and –unmatched cohorts (Table 4 and Table S4, respectively). The primary end point (all‐cause death, MI, or stroke) occurred significantly more often in the DM group than in the non‐DM group in the matched cohort (11.8% versus 8.5%; HR [95% CI], 1.41 [1.20–1.64]; P<0.0001), as did all components including all‐cause death (7.0% versus 5.6%; HR [95% CI], 1.26 [1.03–1.53]; P<0.05); MI (4.4% versus 2.8%; HR [95% CI], 1.59 [1.21–2.08]; P<0.001), and stroke (1.9% versus 1.2%; HR [95% CI], 1.56 [1.04–2.36]; P<0.05), and the differences were somewhat more marked in the unmatched cohort (Table 4 and Table S4). The incidence of PoCE was also significantly higher in patients with DM as compared with patients without DM (21.2% versus 18.2%; HR [95% CI], 1.18 [1.06–1.32]; P<0.01), with similar results in the unmatched cohort. However, while the rate of revascularization alone was higher in patients with DM in the full cohort (12.0% versus 10.6%; HR [95% CI], 1.17 [1.04–1.31]; P=0.01) (Table S4), it was similar in the 2 matched groups (11.8% versus 11.5%; HR [95% CI]; 1.04 [0.90–1.20]; P=0.62) (Table 4). Time‐to‐event curves comparing cardiovascular events, PoCE, and mortality between patients with DM and patients without DM are shown in the Figure—Panels A through C and Figure S1A through S1C, respectively.
Table 4.
Parameter | Patients With DM | Patients Without DM | HR (95% CI*) | P Value* | ||
---|---|---|---|---|---|---|
N | n (%) | N | n (%) | |||
Composite end point (death, MI, and stroke) | 3079 | 362 (11.8) | 3079 | 263 (8.5) | 1.41 (1.20–1.64) | <0.0001 |
All‐cause death | 3079 | 215 (7.0) | 3079 | 173 (5.6) | 1.26 (1.03–1.53) | <0.05 |
MI | 3079 | 136 (4.4) | 3079 | 87 (2.8) | 1.59 (1.21–2.08) | <0.001 |
Stroke | 3079 | 57 (1.9) | 3079 | 37 (1.2) | 1.56 (1.04–2.36) | <0.05 |
Any revascularization | 3079 | 364 (11.8) | 3079 | 354 (11.5) | 1.04 (0.90–1.20) | 0.61 |
PoCE | 3079 | 652 (21.2) | 3079 | 560 (18.2) | 1.18 (1.06–1.32) | <0.01 |
Bleeding | 3079 | 202 (6.6) | 3079 | 184 (6.0) | 1.11 (0.91–1.36) | 0.30 |
Major | 3079 | 9 (0.3) | 3079 | 13 (0.4) | 0.70 (0.30–1.64) | 0.41 |
Minor | 3079 | 197 (6.4) | 3079 | 177 (5.7) | 1.13 (0.92–1.38) | 0.24 |
DM indicates diabetes mellitus; HR, hazard ratio; MI, myocardial infarction; and PoCE, patient‐oriented composite end point.
From univariate Cox proportional hazards model with robust standard error for the parameter estimates.
Bleeding Events
The incidence of predefined major bleeding was not significantly different between the full DM and non‐DM groups (0.3% versus 0.3%; HR [95% CI], 1.00 [0.49–2.04]) (Table S4), nor in the matched cohort (Table 4). The incidence of minor and overall bleeding was higher in patients with DM in the full cohort (6.5% versus 5.6%; HR [95% CI], 1.19 [1.02–1.40]; P<0.05; and 6.7% versus 5.9%; HR [95% CI], 1.18 [1.01–1.38]; P<0.05), but the difference disappeared in the matched cohort. Time‐to‐event curves comparing bleeding between patients with DM and patients without DM are shown in the Figure—Panel D and Figure S1D.
Predictors of Events in Patients With DM
Covariates simultaneously adjusted for in the multivariable regression were age, sex, medical history, chronic DM therapy, place of residence (rural or metropolitan), country, eGFR, index diagnosis, discharge medications, and invasive cardiac catheterization. Multivariable regression showed that the independent predictors of increased cardiovascular events (composite of death, MI, and stroke) in patients with DM were age ≥65 years and use of diuretics at discharge (Table 5). Lower rates of cardiovascular events were associated with in‐hospital cardiac catheterization, residency in India or Hong Kong/Singapore/South Korea versus China, eGFR ≥30 mL/min per 1.73 m2, and index diagnosis of unstable angina (versus STEMI).
Table 5.
Parameter Predictors | HR (95% CI) | P Value |
---|---|---|
Composite of death, MI and stroke | ||
Age, y, vs ≤55 | <0.0001 | |
56–64 | 1.13 (0.82–1.55) | |
65–74 | 1.40 (1.02–1.91) | |
≥75 | 2.29 (1.64–3.18) | |
Cardiac catheterization for index event | 0.44 (0.35–0.55) | <0.0001 |
Country/region, vs China | <0.01 | |
Hong Kong, Singapore, South Korea | 0.71 (0.48–1.06) | |
India | 0.60 (0.46–0.80) | |
Malaysia, Thailand, Vietnam | 0.91 (0.66–1.25) | |
Discharge medications: diuretics | 1.62 (1.30–2.02) | <0.0001 |
eGFR group, mL/min per 1.73 m2, vs <30 | <0.0001 | |
≥30 to <60 | 0.66 (0.46, 0.96) | |
≥60 to <90 | 0.48 (0.33–0.70) | |
≥90 | 0.39 (0.27–0.58) | |
Final diagnosis of index admission event, vs STEMI | <0.0001 | |
NSTEMI | 1.25 (0.99–1.58) | |
UA | 0.64 (0.48–0.84) | |
Death | ||
Age, y, vs ≤55 | <0.0001 | |
56–64 | 1.57 (0.96–2.56) | |
65–74 | 1.95 (1.21–3.15) | |
≥75 | 4.35 (2.71–6.97) | |
Discharge medications: aldosterone inhibitors | 1.58 (1.10–2.28) | 0.01 |
Cardiac catheterization for index event | 0.40 (0.31–0.53) | <0.0001 |
Discharge medications: diuretics | 1.74 (1.27–2.38) | <0.001 |
eGFR group, mL/min per 1.73 m2, vs <30 | <0.0001 | |
≥30 to <60 | 0.66 (0.43–1.00) | |
≥60 to <90 | 0.36 (0.23–0.56) | |
≥90 | 0.28 (0.18–0.45) | |
Chronic DM therapy: oral agent | 0.69 (0.53–0.91) | <0.01 |
MI | ||
Cardiac catheterization for index event | 0.26 (0.19–0.37) | <0.0001 |
Country/region, vs China | <0.0001 | |
Hong Kong, Singapore, South Korea | 1.08 (0.64–1.83) | |
India | 0.12 (0.06–0.27) | |
Malaysia, Thailand, Vietnam | 0.99 (0.63–1.56) | |
Final diagnosis of index admission event, vs STEMI | <0.0001 | |
NSTEMI | 1.56 (1.08–2.25) | |
UA | 0.34 (0.20–0.57) | |
History: MI | 1.79 (1.22–2.64) | <0.01 |
Stroke | ||
Country/region, vs China | <0.05 | |
Hong Kong, Singapore, South Korea | 0.44 (0.14–1.40) | |
India | 0.22 (0.08–0.60) | |
Malaysia, Thailand, Vietnam | 0.66 (0.26–1.66) | |
Female | 2.46 (1.48–4.06) | <0.001 |
Any bleeding | ||
Chronic anemia | 5.38 (2.92–9.93) | <0.0001 |
Country/region, vs China | <0.0001 | |
Hong Kong, Singapore, South Korea | 0.43 (0.25–0.76) | |
India | 0.04 (0.01–0.13) | |
Malaysia, Thailand, Vietnam | 0.31 (0.16–0.59) |
Variable selection was done by stepwise procedure with the P value cutoffs for selection at P<0.01 and retention at P<0.20. For each outcome, the final model only included the variables shown in this table. DM indicates diabetes mellitus; eGFR, estimated glomerular filtration rate; HR, hazard ratio; MI, myocardial infarction; NSTEMI, non–ST‐segment–elevation myocardial infarction; STEMI, ST‐segment elevation myocardial infarction; and UA, unstable angina.
Predictors of the individual end point of death were age ≥65 years and use of diuretics or aldosterone inhibitors at discharge (Table 5). Lower rates of death were predicted by cardiac catheterization, eGFR ≥30, and chronic oral DM therapy. Increased risk of MI was predicted by a diagnosis of NSTEMI (versus STEMI) and history of MI. Conversely, a diagnosis of unstable angina decreased the risk of death, along with cardiac catheterization, and residency in India versus China. The only independent predictor of stroke was female sex, whereas residency in India versus China was again associated with reduced risk.
Higher rates of PoCE were associated with use of a diuretic at discharge and index diagnosis of NSTEMI (versus STEMI), whereas in‐hospital cardiac catheterization, eGFR ≥60 mL/min per 1.73 m2, index diagnosis of unstable angina (versus STEMI), and residency in India were associated with of a lower rate of PoCE (Table S5). Predictors of the individual end point of revascularization were NSTEMI, use of H2‐receptor antagonists or omeprazole at discharge, and residency in metropolitan areas, whereas residency in India lowered the event rate.
For any bleeding events, chronic anemia was a predictor of increased risk, whereas residency in any country/region versus China lowered the risk (Table 5). Use of an aldosterone inhibitor or nonsteroidal anti‐inflammatory drugs at discharge were predictive of major bleeding (Table S5).
Discussion
The EPICOR Asia study confirms that patients with DM treated for ACS are at increased risk of ischemic events and mortality, and that treatment with antiplatelet agents for up to 2 years after discharge is not associated with a significant increase in major bleeding complications. This is consistent with several clinical trials, despite there being a preponderance of White patients in those studies and a broad multiethnic population in our own study. 16 , 17 , 18 Furthermore, and again in accordance with previous trials and reviews, 19 the present study shows that while clinical outcomes are improved with antiplatelet therapy in patients with ACS, patients with DM experience relatively high rates of ischemic events during follow‐up. Several reasons may account for this. First, patients with DM experience multiple metabolic abnormalities, such as insulin resistance and hyperglycemia. Such comorbidities could contribute to a prothrombotic state and possibly increase procoagulant activity and thrombin generation via several mechanisms, leading to atherosclerosis and thrombosis. Moreover, hyperglycemia per se could exacerbate insulin resistance and promote an altered platelet metabolic milieu, resulting in increased platelet reactivity and potentially contributing to the pathogenesis of atherothrombotic complications. Notably, several abnormal signaling pathways, including receptor and intracellular downstream signaling, have been identified in platelets of patients with DM. 20
On multivariable regression analysis, independent predictors of cardiovascular events during long‐term follow‐up in patients with DM included a number of unsurprising factors, such as age ≥65 years (composite cardiovascular events and death) and index event diagnosis of NSTEMI versus STEMI (PoCE and revascularization). Similarly, predictors of lower cardiovascular event rates in patients with DM included in‐hospital cardiac catheterization or eGFR ≥30 mL/min per 1.73 m2. Other predictors of increased risk of events, such as use of diuretics at discharge, are more difficult to interpret; they may be indicators of patients' overall health status or may simply be attributable to chance in this nonrandomized cohort population or be artefacts of the way some data were collected. The observation that residency in countries/regions other than China was associated with lower risk of cardiovascular events may be interpreted as attributable to variability in access to healthcare facilities (either because of genuine regional variations or because of the specific centers included in the study or issues associated with cost of treatment).
Use of antiplatelet therapy is the fundamental treatment strategy for management of patients with ACS, and guidelines recommend that the majority of patients receive DAPT (aspirin plus a P2Y12 inhibitor) for at least 12 months following an ACS event. Individual duration of DAPT, however, depends on a fundamental trade‐off between ischemic risk and bleeding risk. 9 , 10 , 21 , 22
The recommendation in current guidelines is usually for use of DAPT for at least 6 to 12 months, depending on the setting. 9 , 10 , 22 Our study shows that, although ACS patients with DM are at increased risk of ischemic events and mortality, the number that receive DAPT at 2‐year follow‐up is comparable with patients without DM. While a direct association between DAPT use and cardiovascular events cannot be inferred in this observational study, it is likely that patients with DM were sicker than patients without DM. Given that the EPICOR Asia study was performed largely before the availability of the newer oral antiplatelet agents prasugrel and ticagrelor, it is also possible that more intensive long‐term antithrombotic therapy may be of benefit in patients with DM, particularly given the nonsignificant difference in major bleeding between patients with DM and patients without DM in this study. However, further large‐scale, multicenter, randomized controlled trials are needed to test this hypothesis.
Notably, available guideline recommendations are invariably based on evidence from American and European trials and cannot simply be extrapolated to the Asian population because of ethnic and environmental distinctions. The EPICOR Asia study recruited eligible patients from 219 centers in 8 countries across Asia, while the present analysis mainly focused on the use of antiplatelet agents and outcomes in patients ACS with DM from the EPICOR Asia study. Accordingly, these findings may better guide ACS management in the clinical setting in Asia. A further consideration is that the use of antiplatelet agents reported in EPICOR Asia at 2‐year follow‐up is relatively high, which does not generally accord with routine practice. Interestingly, this is consistent with observations from the EPICOR (Europe and South America) study, where 60.3% of patients with DM and 55.5% of patients without DM remained on DAPT at 2‐year follow‐up. 23 The reasons for this also require further investigation.
Study Limitations
Although prespecified, the present research is a retrospective subgroup analysis that is based on the prospective, observational EPICOR Asia study, with inherent limitations of an observational study based on phone call follow‐up with subsequent event validation from clinical records. Although this approach included 98% of the original full cohort (all patients with known DM or non‐DM status) some reported clinical outcomes were low in absolute number implying underpowering of corresponding comparisons and wider CIs. Hence, some true differences between patients with DM and patients without DM, and some known risk factors, may not have been detected. While underpowering was somewhat larger for the “case‐control” evaluation, in this matched cohort confounding was reduced to facilitate appropriate interpretation of the results. In addition, the DM group was not stratified by type of DM or level of glycemic control, which might have influenced assessment of end point events. As only around 5% to 6% of patients in this study were treated in regional, community, or rural centers, it is also possible that participating sites were weighted toward relatively well‐equipped centers. Finally, and as mentioned above, the study was largely carried out before the availability of the more potent oral antiplatelet agents prasugrel and ticagrelor.
Notwithstanding these limitations, our study clearly shows that the rates of all‐cause death, MI, and stroke in Asian patients with DM who had an ACS were more frequent compared with those in patients without DM. There was no significant difference between the 2 groups in the rates of overall bleeding, major bleeding, and minor bleeding in the matched cohort. In summary, patients with DM are at increased risk of ischemic events, suggesting an unmet need for improved antithrombotic treatment.
Sources of Funding
The EPICOR Asia study was sponsored by AstraZeneca. Being a noninterventional study, no drugs were supplied or funded.
Disclosures
None.
Supporting information
Acknowledgments
All authors contributed to manuscript development and content. AstraZeneca reviewed the manuscript during development; however, final content, opinions, conclusions, and interpretation of the data are the responsibility of the authors. The authors thank Richard Cairns of Worldwide Clinical Trials (Nottingham, UK) for his contributions to the statistical analysis. Editorial support was provided by Carl V Felton, PhD, Paragon (Knutsford, Cheshire, UK), supported by AstraZeneca.
(J Am Heart Assoc. 2020;9:e013476 DOI: 10.1161/JAHA.119.013476.)
Supplementary Material for this article is available at https://www.ahajournals.org/doi/suppl/10.1161/JAHA.119.013476
For Sources of Funding and Disclosures, see page 11.
Contributor Information
Yong Huo, Email: huoyong@263.net.cn.
Yaling Han, Email: hanyaling@263.net.
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