Comparison of healthcare resource utilization and costs in patients hospitalized for acute coronary syndrome managed with percutaneous coronary intervention and receiving prasugrel or ticagrelor.

Journal of Medical Economics

ISSN: 1369-6998 (Print) 1941-837X (Online) Journal homepage: http://www.tandfonline.com/loi/ijme20

Comparison of healthcare resource utilization and costs in patients hospitalized for acute coronary syndrome managed with percutaneous coronary intervention and receiving prasugrel or ticagrelor Cliff Molife, Feride Frech-Tamas, Mitch DeKoven, Mark B. Effron, Swapna Karkare, Yajun Zhu, Cynthia Larmore, Jingsong Lu, Patrick McCollam, Elizabeth Marrett & George W. Vetrovec To cite this article: Cliff Molife, Feride Frech-Tamas, Mitch DeKoven, Mark B. Effron, Swapna Karkare, Yajun Zhu, Cynthia Larmore, Jingsong Lu, Patrick McCollam, Elizabeth Marrett & George W. Vetrovec (2015): Comparison of healthcare resource utilization and costs in patients hospitalized for acute coronary syndrome managed with percutaneous coronary intervention and receiving prasugrel or ticagrelor, Journal of Medical Economics To link to this article: http://dx.doi.org/10.3111/13696998.2015.1060979

Accepted online: 18 Jun 2015.Published online: 10 Jul 2015.

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1369-6998 doi:10.3111/13696998.2015.1060979

2015, 1–11

Article 0050.R1/1060979 All rights reserved: reproduction in whole or part not permitted

Original article Comparison of healthcare resource utilization and costs in patients hospitalized for acute coronary syndrome managed with percutaneous coronary intervention and receiving prasugrel or ticagrelor Cliff Molife

Abstract

Eli Lilly & Co. Inc., Indianapolis, IN, USA

Feride Frech-Tamas Daiichi Sankyo, Parsipanny, NJ, USA

Mitch DeKoven

Objective: To compare healthcare resource utilization (HCRU) and healthcare costs in patients with acute coronary syndrome (ACS) managed with percutaneous coronary intervention (PCI) and treated with prasugrel or ticagrelor.

IMS Health, Fairfax, VA, USA

Mark B. Effron Eli Lilly & Co. Inc., Indianapolis, IN, USA

Swapna Karkare IMS Health, Fairfax, VA, USA

Yajun Zhu Cynthia Larmore Eli Lilly & Co. Inc., Indianapolis, IN, USA

Jingsong Lu IMS Health, Fairfax, VA, USA

Patrick McCollam Eli Lilly & Co. Inc., Indianapolis, IN, USA

Elizabeth Marrett Daiichi Sankyo, Parsipanny, NJ, USA

George W. Vetrovec VCU Pauley Heart Ctr., Richmond, VA, USA Address for correspondence: Cliff Molife, PhD, MPH, Lilly Corporate Center, Drop Code 5022, Indianapolis, IN 46285. Tel: 317-220-7074; [email protected] Keywords: Acute coronary syndrome – Prasugrel – Ticagrelor – Healthcare utilization – Costs

Methods: Hospital charge master data were used to identify ACS-PCI patients aged 18 years with 1 in-hospital claim for prasugrel or ticagrelor between August 1, 2011–April 30, 2013. Treatment groups were propensity matched for baseline and index hospitalization characteristics. HCRU and costs were assessed through 90-days post-discharge. Costs were determined based on hospital-specific costto-charge ratios and adjusted to 2013 US dollars. Results: Before matching, ticagrelor patients were older, more-often female, and had increased cardiovascular (CV) and bleeding risks compared with prasugrel patients. Propensity-matched length of index hospital stay (4.7 vs 4.9 days, p ¼ 0.23) and risk for all-cause [30-day: relative risk (RR) ¼ 0.86; 95% CI ¼ 0.73–1.0; 90day: RR ¼ 0.90; 95% CI ¼ 0.80–1.0, and CV-related (30-day: RR ¼ 0.77; 95% CI ¼ 0.59–1.0; 90-day: RR ¼ 0.89; 95% CI ¼ 0.73–1.1) re-hospitalizations did not significantly differ between prasugrel and ticagrelor, respectively. Compared to ticagrelor, the propensity-matched risk of re-hospitalization for myocardial infarction (MI) (30-day: RR ¼ 0.39; 95% CI ¼ 0.21–0.75; 90-day: RR ¼ 0.53; 95% CI ¼ 0.34–0.81) and an outpatient medical encounter for dyspnea (30-day: RR ¼ 0.49; 95% CI ¼ 0.33– 0.74; 90-day: RR ¼ 0.60; 95% CI ¼ 0.46–0.80) were significantly lower for prasugrel patients, with no significant differences in bleeding encounters between groups (30-day: RR ¼ 0.87; 95% CI ¼ 0.54–1.40; 90-day: RR ¼ 1.0; 95% CI ¼ 0.71–1.50). Matched total healthcare costs were not significantly different between groups during the index hospitalization ($36,011 vs $37,247, p ¼ 0.21), 30-days post-discharge ($2007 vs $2522, p ¼ 0.48), 90-days post-discharge ($4564 vs $5242, p ¼ 0.49), and aggregate of the index hospitalization through 90-day follow-up ($40,576 vs $42,494, p ¼ 0.09) timeframes. Conclusions: Re-hospitalization for MI and outpatient encounters for dyspnea were lower in prasugrel treated than in ticagrelor treated ACS-PCI patients up to 90-days post-index hospitalization discharge, with no difference in bleeding encounters or healthcare costs between the two populations. This data supports the utility of prasugrel in routine clinical practice. These findings should be considered within limitations of observational research.

Accepted: 8 June 2015; published online: 10 July 2015 Citation: J Med Econ 2015; 1–11

! 2015 Informa UK Ltd www.informahealthcare.com/jme

Healthcare resource use and costs: prasugrel vs ticagrelor Molife et al.

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Introduction

Patients and methods

Acute coronary syndrome (ACS) is a continuum of acute ischemic cardiac conditions which include unstable angina (UA), non-ST-segment elevation myocardial infarction (NSTEMI), and ST-segment elevation MI (STEMI). Acute Coronary Syndrome is managed either invasively with percutaneous coronary intervention (PCI) with or without a stent, surgically with coronary artery bypass graft (CABG), or medically without re-vascularization. Current treatment guidelines in the US recommend the use of a P2Y12 receptor inhibitor as a standard component of an antiplatelet regimen, in combination with low-dose aspirin, for the secondary prevention of cardiovascular (CV) events1,2. Effient (prasugrel), a P2Y12 receptor inhibitor, was approved by the US Food and Drug Administration (FDA) in July 2009 for the reduction of thrombotic CV events (including stent thrombosis) in patients with ACS managed with PCI (ACS-PCI). The Trial to Assess Improvement in Therapeutic Outcomes by Optimizing Platelet Inhibition With Prasugrel– Thrombolysis in Myocardial Infarction 38 (TRITON-TIMI 38) found that, among 13,608 moderate-to-high-risk patients with ACS-PCI, prasugrel was more efficacious over a 15-month period at preventing ischemic events than clopidogrel, but with an increased risk of non-CABG-related bleeding3. More recently, Brilinta (ticagrelor) was approved by the FDA in July 2011 for the reduction of thrombotic CV events in patients with ACS. The Platelet Inhibition and Patient Outcomes (PLATO) trial, a randomized controlled trial (RCT) of 18,624 patients admitted to the hospital with ACS, with or without ST-segment elevation, demonstrated that patients receiving ticagrelor (in addition to aspirin) had a lower observed risk for the primary end-point (a composite of death from vascular causes, MI, or stroke) relative to patients receiving clopidogrel and aspirin4. The improved efficacy with ticagrelor was accompanied by an increased risk of non-CABG related bleeding. While results from these RCTs suggest a superior anti-thrombotic efficacy of prasugrel or ticagrelor in combination with aspirin over clopidogrel plus aspirin, no RCTs or observational studies have directly compared clinical or economic outcomes between these two drugs. As such, this retrospective, observational study used data from a hospital charge data master to compare healthcare resource utilization and costs in a population of patients with ACS-PCI and treated with either prasugrel or ticagrelor.

Data source

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IMS Health’s Hospital Charge Data Master (CDM) was used for the analysis. The CDM records are drawn from hospital operational files and other reference sources from over 650 hospitals, covering 7 million annual inpatient stays and 60 million annual outpatient visits. Data elements include all inpatient and outpatient encounters within a facility, linked to individual departments, with detailed drug, procedure, diagnosis, and associated charge data. Within the CDM, patients from 213 hospitals met the criteria for inclusion in this study. In compliance with the Health Insurance Portability and Accountability Act (HIPAA), patient data included in the analysis were de-identified; therefore, this study was exempt from Institutional Review Board (IRB) review.

Patient selection Patients who were 18 years of age having a hospital admission and discharge for ACS-PCI (index hospitalization) between August 1, 2011 and April 30, 2013 were identified. Patients were required to have at least one hospital claim for prasugrel or ticagrelor, but not both, during the selected hospitalization. The pre-index period spanned from January 1, 2008 until the day before the index date (date of hospital admission), while the post-index period spanned the 90-day period following the discharge date of the index hospitalization. Patients with a diagnosis of ACS who were managed with PCI were the Primary population for this study. For this analysis, a sub-group of the Primary population was analyzed as guided by the prasugrel prescribing information. The Label sub-group excluded patients with a history of transient ischemic attack (TIA) or stroke as these patients are contraindicated for treatment with prasugrel5. The contraindication for the presence of a prior TIA or stroke was applied to both the prasugrel and ticagrelor treated populations, even though it is not a contraindication for use of ticagrelor. As the database could not identify patients with severe hepatic dysfunction, this contraindication for ticagrelor was not applied to this sub-group. Likewise, the presence of active bleeding or hypersensitivity to drug, both of which are contraindications for both drugs, could not be determined from this database and were not applied.

Baseline patient characteristics Baseline demographics and clinical characteristics (including evidence of prior bleeding, CV events,

www.informahealthcare.com/jme ! 2015 Informa UK Ltd


comorbidities, and medications of interest) were collected over the pre-index period. Additional baseline information was collected during the index hospitalization including hospital characteristics, ACS diagnosis, and chronic comorbidities (e.g., diabetes mellitus).


Healthcare resource utilization and costs Healthcare resource utilization and costs were assessed for the index hospitalization (admission through discharge), for all additional inpatient or outpatient hospital services for the time periods between index hospitalization discharge through 30–90-days, and for the aggregate of the index hospitalization through 90-days follow-up. Length of stay (LOS) was defined as the number of days from index hospital admission to discharge. Rates of re-hospitalization, defined as admission to any hospital within the IMS Health CDM database, were examined within 30and 90-days post-index hospitalization discharge for any cause (all-cause), any CV-event, and individually for MI or re-vascularization, based on primary International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis, and/or procedure codes. Any CV-event was defined as a composite of TIA, stroke, MI (STEMI and NSTEMI), UA, congestive heart failure (CHF), re-vascularization (PCI, CABG, or unspecified coronary revascularization), or sub-acute stent thrombosis (based on evidence of death or MI within 30 days of stenting6) during the follow-up period. In addition, primary and secondary ICD-9-CM diagnosis and procedure codes were used to identify 30- and 90-day re-hospitalization rates for bradyarrhythmia, dyspnea, and bleeding (denoted by the presence of either a primary or secondary diagnosis ICD-9 code of bleeding or transfusion procedure codes). For dyspnea and bleeding, rates of hospital outpatient medical encounters (including emergency department visits) were also quantified over the same time periods, as were the aggregates of re-hospitalization and outpatient medical encounter rates. Total costs were the sum of medical costs, including laboratory and diagnostic tests, and pharmacy costs during hospitalizations. Because the CDM data provides billed charges, hospital-specific cost-to-charge ratios were used to determine hospitalization costs. All-cause costs included hospitalization costs for any reason. If a component of any CV-event was the primary diagnosis for any hospitalization, all costs from that hospitalization were attributed to that CV event and used in the calculation of CV-related costs. Costs were adjusted for inflation to


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2013 prices using the Medical Care component of the US Consumer Price Index for All Urban Consumers.

Statistical analysis Baseline characteristics and unadjusted healthcare resource utilization and costs were compared using Pearson’s Chi-square or Fisher’s exact test for categorical variables and t-test for continuous variables. To minimize the potential for selection bias, a greedy nearest-neighbor 1:1 matching algorithm was used based on propensity scores. The propensity score for each patient was defined as the probability of being in the prasugrel cohort and estimated using logistic regression with covariates including baseline patient demographics, clinical characteristics, hospital characteristics, healthcare utilization, and costs (Supplementary Table S1). Additional covariates included those from the index hospitalization such as ACS diagnosis type, procedural characteristics, and index hospital characteristics. The Primary population and the Label sub-group were propensity-matched separately. All outcomes were analyzed before and after propensity matching. The McNemar’s test was used to compare rates of medical encounters between propensity-matched treatment groups. The relative risk (RR) and its 95% confidence intervals (CIs) were calculated. Costs were reported on a per patient (cohort member) basis. Generalized linear models were used to compare propensity-matched costs during the index hospitalization and aggregate of the index hospitalization through 90day follow-up timeframes (with gamma distribution and log link function) and LOS (with negative binomial distribution and log link function). Generalized estimating equations were used to accommodate the correlation between matched pairs. Comparison of 30- and 90-day re-hospitalization costs between cohorts was conducted using non-parametric bootstrapping to account for the large number of zero-cost values. The 95% CIs were constructed and compared. Two-sided p values were computed for all comparisons and p50.05 was considered statistically significant. All statistical analyses were conducted using SAS version 9.2 (Cary, NC) and were performed by IMS Health.

Results The database contained 157,479 patients who were hospitalized and discharged for ACS, of whom 59,118 were managed with PCI. After applying age (18 years) and treatment (prasugrel or ticagrelor) criteria, the Primary


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Figure 1. Patient selection flow chart. ACS-PCI ¼ acute coronary syndrome managed with percutaneous coronary intervention.

population was composed of 13,134 prasugrel and 2964 ticagrelor patients (Figure 1).

Baseline demographic and clinical characteristics Prior to propensity matching, ticagrelor patients in the Primary population were older (64.1 years vs 58.6 years; p50.0001), more likely to be female (33.4% vs 26.7%; p50.0001), and were more frequently treated at a teaching hospital (54.2% vs 42.6%; p50.0001) compared with prasugrel patients (Table 1). Higher rates of co-morbid conditions were seen in ticagrelor-treated patients, placing them at greater risk for an ischemic or bleeding event compared with those receiving prasugrel. During the index ACS hospitalization, the admission diagnosis of UA was more frequent in prasugrel patients compared with ticagrelor patients. In contrast, the proportions of STEMI and NSTEMI patients were similar between prasugrel- and ticagrelor-treated patients. 4


Utilization and cost outcomes in unmatched patients were lower in prasugrel treated patients than in ticagrelor treated patients (Supplementary Tables S2 and S3). After propensity score matching, the majority (490%) of ticagrelor patients were matched with prasugrel patients and 2661 patients remained in each treatment cohort. There were no statistically significant differences in measured baseline characteristics between matched treatment groups (Table 1).

Index hospitalization length of stay and costs During the index hospitalization, there were no significant differences between prasugrel-treated and ticagrelor-treated patients for hospital length of stay (mean LOS ¼ 4.7 vs 4.9 days; p ¼ 0.23) (Table 5) or associated total costs ($36,011 vs $37,247; p ¼ 0.21), medical costs ($32,947 vs $34,098; p ¼ 0.20), or pharmacy costs ($3064 vs $3149; p ¼ 0.42), although costs appeared lower with prasugrel (Table 4).



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Table 1. Baseline patient demographics and clinical characteristics: unmatched and propensity score matched Primary population.


Characteristics

Age, years (mean SD) Female (%) Hospital Type: (%) Teaching Non-teaching Unknown Index ACS event (%) STEMI NSTEMI UA Unspecified ACS Prior history/comorbidities (%) Anemia Cerebrovascular disease CHF CKD COPD Diabetes Dyslipidemia Dyspnea Hypertension Ischemic heart disease Peripheral vascular disease Prior CABG Prior MI Prior PCI Prior TIA/Stroke CCI score (mean SD) Pre-index medications (%) ACE inhibitor ADP receptor inhibitor Diabetes Medication

Unmatched

Matched

Prasugrel (n ¼ 13,134)

Ticagrelor (n ¼ 2964)

p value

Prasugrel (n ¼ 2661)


p value

58.6 10.8 26.7

64.1 12.4 33.4

50.0001 50.0001 50.0001

62.5 11.5 32.4

62.4 11.7 32.0

0.76 0.79 0.83

42.6 46.5 10.9

54.2 38.3 7.5

38.6 36.4 21.6 3.4

39.6 37.1 18.5 4.8

54.1 39.4 6.5

53.9 39.2 6.9

40.6 35.9 19.0 4.5

39.3 36.9 18.9 4.9

0.71

50.0001

8.9 4.8 6.9 8.4 12.9 37.3 77.9 8.3 35.4 26.2 11.4 1.5 7.7 10.2 2.0 1.4 1.8 15.6 16.0 12.2

13.0 9.7 10.2 12.9 15.8 35.9 74.3 10.5 41.1 29.9 16.3 1.6 8.4 10.0 5.4 1.7 2.2 19.0 17.7 15.1

50.0001 50.0001 50.0001 50.0001 50.0001 0.15 50.0001 50.0001 50.0001 50.0001 50.0001 0.70 0.22 0.67 50.001 50.0001

11.4 8.2 9.4 10.8 16.7 35.5 74.3 9.9 39.2 28.5 14.9 1.8 8.3 10.0 4.2 1.6 2.0

50.001 0.02 50.001

17.7 17.2 13.8

12.1 8.3 9.5 11.7 15.3 35.9 74.4 10.1 39.6 28.6 14.7 1.8 8.1 9.8 4.6 1.7 2.1 18.4 17.0 14.3

0.44 0.84 0.85 0.26 0.16 0.77 0.95 0.75 0.74 0.95 0.79 1.00 0.73 0.82 0.55 0.70 0.54 0.86 0.61

ACE, angiotensin-converting-enzyme; ACS, acute coronary syndrome; ADP, adenosine diphosphate; CABG, coronary artery bypass graft surgery; CCI, Charlson Comorbidity Index; CHF, congestive heart failure; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; MI, myocardial infarction; NSTEMI, non ST-elevation MI; PCI, percutaneous coronary intervention; STEMI, ST-elevation MI; TIA, transient ischemic attack; UA, unstable angina.

30-Day healthcare resource utilization and costs

90-Day healthcare resource utilization and costs

The risk of 30-day re-hospitalization for MI (RR ¼ 0.39; 95% CI ¼ 0.21–0.75) was significantly lower for prasugrel-treated patients compared with ticagrelor-treated patients (Tables 3 and 5). Although re-hospitalizations for dyspnea did not differ between treatment groups, the risk of an outpatient medical encounters for dyspnea was significantly lower for prasugrel compared with ticagrelor (RR ¼ 0.49; 95% CI ¼ 0.33–0.74). Prasugrel-treated patients had lower rates of all-cause re-hospitalizations, re-hospitalizations due to any CVevent, re-vascularization, bradyarrhythmia and bleeding within 30 days compared with ticagrelor-treated patients; however, the differences were not statistically significant. Similar results were noted for total all-cause costs ($2007 vs $2522, p ¼ 0.48) and CV-related costs ($878 vs $1272; p ¼ 0.47) within 30-days post-discharge (Table 4).

The risk of re-hospitalization for MI at 90-days (RR ¼ 0.53; 95% CI ¼ 0.34–0.81), and the risk of an outpatient medical encounter for dyspnea (RR ¼ 0.60; 95% CI ¼ 0.46– 0.80) were significantly lower with prasugrel (Tables 3 and 5). All other 90-day resource utilization measures were consistent with the 30 day results (Tables 3 and 5). Similarly, mean total all-cause and CV-related 90-day costs reflected the 30-day measures, as well as total allcause and CV related costs during the aggregate period from index hospitalization through 90-days post discharge (all-cause: $40,576 vs $42,494, p ¼ 0.09; CV-related: $38,016 vs $39,526, p ¼ 0.15) (Table 4).


Label sub-group Demographics and baseline clinical characteristics for the unmatched Label population were generally similar Healthcare resource use and costs: prasugrel vs ticagrelor Molife et al.

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Table 2. Baseline patient demographics and clinical characteristics: unmatched and propensity score matched Label sub-group.


Characteristics

Age, years (mean SD) Female (%) Hospital type (%) Teaching Non-teaching Unknown Index ACS event (%) STEMI NSTEMI UA Unspecified ACS Prior history/comorbidities (%) Anemia Cerebrovascular disease CHF CKD COPD Diabetes Dyslipidemia Dyspnea Hypertension Ischemic heart disease Peripheral vascular disease Prior CABG Prior MI Prior PCI CCI Score (mean SD) Pre-index medications (%) ACE inhibitor ADP receptor inhibitor Diabetes medication

Unmatched

Matched

Prasugrel (n ¼ 12,872)


p value



p value

58.5 10.8 26.4

63.8 12.3 33.0

50.0001 50.0001 50.0001

62.1 11.6 30.4

62.3 11.7 31.5

0.54 0.41 0.88

42.6 46.6 10.8

54.0 38.6 7.4

38.9 36.4 21.4 3.3

40.2 36.8 18.1 4.9

54.1 39.5 6.5

53.8 39.4 6.8

40.3 36.1 19.2 4.4

40.5 36.4 18.7 4.4

0.98

50.0001

8.3 3.8 6.5 7.9 12.6 36.9 77.8 7.9 34.3 25.3 10.9 1.5 7.4 9.8 1.3 1.7 14.8 15.3 11.5

11.38 6.6 8.9 11.5 15.0 34.8 73.5 9.6 38.4 27.6 15.0 1.6 7.7 9.4 1.6 2.0 16.8 15.8 13.3

50.0001 50.0001 50.0001 50.0001 0.0005 0.03 50.0001 0.002 50.0001 0.01 50.0001 0.66 0.59 0.48 50.0001 0.007 0.52 0.01

10.8 5.9 8.6 10.4 14.7 34.4 72.5 9.3 36.6 26.2 13.4 1.4 7.8 9.4 1.5 1.9 15.5 15.0 12.2

11.0 5.7 8.1 10.3 14.7 34.6 73.9 9.2 37.7 26.2 13.6 1.7 7.5 9.4 1.5 1.9

0.79 0.72 0.58 0.96 1.00 0.88 0.25 0.88 0.40 1.00 0.77 0.36 0.63 0.92 0.81

16.00 15.4 12.5

0.62 0.72 0.70

ACE, angiotensin-converting-enzyme; ACS, acute coronary syndrome; ADP, adenosine diphosphate; CABG, coronary artery bypass graft surgery; CCI, Charlson Comorbidity Index; CHF, congestive heart failure; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease; MI, myocardial infarction; NSTEMI, non ST-elevation MI; PCI, percutaneous coronary intervention; STEMI, ST-elevation MI; TIA, transient ischemic attack; UA, unstable angina.

to those observed in the Primary population, although patients in the Label population appeared to have slightly lower rates of comorbidities (Table 2). After matching, 2531 patients remained in each cohort (Figure 1). Overall, outcomes results for the matched Label subgroup were consistent with the Primary population in terms of both the directionality of the findings and the size of the point estimates (Tables 3–5). As with the Primary population, prasugrel-treated patients in the Label sub-group, compared with ticagrelor-treated patients, were associated with significantly lower 30and 90-day rates of re-hospitalization for MI (30-day: RR ¼ 0.39; 95% CI ¼ 0.21–0.75; 90-day: RR ¼ 0.53; 95% CI ¼ 0.34–0.82) and outpatient dyspnea encounters (30-day: RR ¼ 0.53; 95% CI ¼ 0.35–0.80; 90-day: RR ¼ 0.74; 95% CI ¼ 0.56–0.97), with no significant differences in bleeding encounters (30-day: RR ¼ 0.82; 95% CI ¼ 0.59–1.1; 90-day: RR ¼ 0.98; 95% CI ¼ 0.76– 1.2) (Tables 3 and 5). In contrast with the Primary 6


population, however, prasugrel-treated patients had a significantly lower 90-day all-cause re-hospitalization rate (RR ¼ 0.83, 95% CI ¼ 0.74–0.94) and lower 30and 90-day CV-related re-hospitalization rates (30-day: RR ¼ 0.71; 95% CI ¼ 0.54–0.94; 90-day: RR ¼ 0.76; 95% CI ¼ 0.61–0.93) compared with ticagrelor-treated patients in the Label sub-group (Tables 3 and 5). As with the Primary population, the cost differences between prasugrel and ticagrelor during 30 days and 90 days post-discharge did not reach statistical significance in the Label sub-group (30-day: $2198 vs $2534, p ¼ 0.52, 90-day: $4741 vs $5260, p ¼ 0.52) (Table 4). However, in the Label sub-group, all-cause total costs were significantly less with prasugrel for the index hospitalization ($35,185 vs $37,213, p ¼ 0.03) and the aggregate period from index hospitalization through 90-days follow-up ($39,926 vs $42,480; p ¼ 0.03). Similar results were observed for all-cause medical costs and total CV related costs in the Label sub-group (Table 4). www.informahealthcare.com/jme ! 2015 Informa UK Ltd


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Table 3. Propensity score matched relative risk of medical encounters for 30-/90-day follow-up periods: Primary population and Label sub-group. Prasugrel vs Ticagrelor

Primary population


Relative risk

30-day follow-up Re-hospitalizations All-cause Any CV-event* Myocardial infarction Re-vascularization Bradyarrhythmia Bleeding Dyspnea Outpatient medical encounters Bleeding Dyspnea Composite re-hospitalization/outpatient encounters Bleeding Dyspnea 90-day follow-up Re-hospitalizations All-cause Any CV-event* Myocardial Infarction Revascularization Bradyarrhythmia Bleeding Dyspnea Outpatient medical encounters Bleeding Dyspnea Composite re-hospitalization/outpatient encounters Bleeding Dyspnea

Label sub-group

95% CI

Relative risk

Lower limit

Upper limit

0.86 0.77 0.39 0.78 0.72 0.73 0.86

0.73 0.59 0.21 0.54 0.42 0.47 0.29

1.0 1.0 0.75 1.1 1.2 1.1 2.5

0.87 0.49

0.54 0.33

0.77 0.51

95% CI Lower limit

Upper limit

0.89 0.71 0.39 0.77 0.90 0.79 0.50

0.75 0.54 0.21 0.53 0.54 0.51 0.15

1.0 0.94 0.75 1.1 1.5 1.2 1.7

1.4 0.74

0.82 0.53

0.49 0.35

1.4 0.80

0.56 0.35

1.1 0.75

0.82 0.53

0.59 0.36

1.1 0.77

0.90 0.89 0.53 0.89 0.74 0.93 0.91

0.80 0.73 0.34 0.69 0.50 0.70 0.39

1.0 1.1 0.81 1.2 1.1 1.3 2.1

0.83 0.76 0.53 0.81 0.87 0.98 0.67

0.74 0.61 0.34 0.61 0.60 0.72 0.27

0.94 0.93 0.82 1.1 1.28 1.3 1.6

1.0 0.60

0.71 0.46

1.5 0.80

0.94 0.74

0.63 0.56

1.4 0.97

0.95 0.61

0.75 0.47

1.2 0.80

0.98 0.72

0.76 0.56

1.2 0.94

*Any CV-event: transient ischemic attack, stroke, myocardial infarction, unstable angina, congestive heart failure, re-vascularization, or stent thrombosis.

Discussion This retrospective observational study from a healthcare administrative database presents the first large-scale analysis directly comparing utilization and expenditures of patients with ACS managed with PCI and treated with prasugrel or ticagrelor in routine clinical practice. Across all propensity score matched measures up to 90 days postindex hospital discharge, patients treated with prasugrel had lower rates of healthcare resource utilization and lower mean costs compared to patients treated with ticagrelor, although the majority of these differences were marginal and not statistically significant. However, the rates of re-hospitalization for MI and outpatient encounters for dyspnea at 30- and 90-days were significantly lower for prasugrel-treated patients, with no significant differences in bleeding between the treatment groups. Unlike the Primary population, 90-day all-cause rehospitalization rates, 30- and 90-day rates of re-hospitalization for any CV event, and aggregate 90-day costs were found to be significantly lower for prasugrel patients in the Label sub-group. These findings may be relevant for healthcare decisionmakers given that the National Quality Forum (NQF) ! 2015 Informa UK Ltd www.informahealthcare.com/jme

has endorsed and the Centers for Medicare and Medicaid Services (CMS) have implemented the rate of 30-day all-cause re-hospitalization after acute MI as an important measure of hospital quality of care7–9. The baseline characteristics of patients receiving prasugrel differed considerably from patients receiving ticagrelor. This finding suggests physician-directed differential use of these drugs in routine clinical practice as guided by the drugs’ prescribing information or a perception of a difference in the net safety to efficacy profiles between the two agents. However, in real-world settings, treatment selection may be influenced by other factors including individual patient characteristics, hospital formularies, and current treatment guidelines. In order to minimize channeling bias, treatment groups were successfully matched based on propensity scores. Where possible, comparison of study results to the published literature is helpful to evaluate generalizability. In this study, the average index hospitalization LOS and 30-day all-cause re-hospitalization rates are generally within the range reported by prior retrospective claims database studies10. Consistent with Meadows et al.11 and Curtis et al.12, the present study found that the majority of Healthcare resource use and costs: prasugrel vs ticagrelor Molife et al.

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39,365–41,786 36,966–39,067 40,576 38,016

*Costs are per-patient, based on the full treatment cohort, and are expressed in 2013 USD. Total costs are inclusive of both medical and pharmacy charges. Costs during the follow-up period are inclusive of re-hospitalizations, outpatient hospital services, and emergency department visits. yCV-related costs: based on any medical encounter for transient ischemic attack, stroke, myocardial infarction, unstable angina, congestive heart failure, re-vascularization, or stent thrombosis. zAggregate costs for the index hospitalization through 90-days post-discharge.

0.03 0.02 40,522–44,437 37,672–41,337 42,480 39,505 38,713–41,139 36,024–38,031 39,926 37,027 0.09 0.15 40,603–44,386 37,758–41,295

3939–5235 1617–2420 4564 2003

42 494 39 526

0.52 0.49 4499–6162 1814–2882 5260 2288 4026–5505 1431–2316 4741 1845 0.49 0.53 4476–6114 1820–2860

1652–2388 642–1145 2007 878

5242 2279

0.52 0.47 2001–3203 921–1838 2534 1311 1768–2633 614–1106 2198 848 0.48 0.47 2002–3182 904–1792

0.21 0.20 0.42 35,561–38,932 32,523–35,672 2986–3312 37,247 34,098 3149 35,061–36,961 32,084–33,810 2933–3195 36,011 32,947 3064

Index hospitalization Total costs Medical Pharmacy Follow-up period 30 days post-discharge Total all-cause costs Total CV-related costsy 90 days post-discharge Total all-cause costs Total CV-related costsy Aggregatez Total all-cause costs Total CV-Related Costs

95% CI Mean 95% CI Mean

2522 1272

34,341–36,029 31,397–32,932 2895–3146

37,213 34,109 3 104

35,466–38,959 32,472–35,746 2 944–3264

0.03 0.03 0.41

2015

35,185 32,164 3021

95% CI Mean 95% CI Mean

Ticagrelor (n ¼ 2531) Prasugrel (n ¼ 2531) p value Ticagrelor (n ¼ 2661)

Primary population

Prasugrel (n ¼ 2661) Healthcare costs*

Table 4. Propensity score matched healthcare costs ($) for index hospitalization and 30-/90-day follow-up periods: Primary population and Label sub-group.


Label sub-group

p value



all-cause re-hospitalizations were associated with a re-vascularization procedure. The finding that rehospitalizations for MI were significantly lower with prasugrel compared with ticagrelor is directionally consistent with evidence from recent meta-analyses which showed that prasugrel was associated with lower, but insignificant, rates of MI compared with ticagrelor13,14. Additionally, the overall non-fatal MI reduction with prasugrel in the TRITON-TIMI 38 trial (24%)3 was greater than that with ticagrelor in the PLATO trial (16%)4, and the timing of ischemic outcome benefit with prasugrel in the TRITONTIMI 38 trial was earlier than that with ticagrelor in the PLATO trial. However, any comparison between these trials regarding early ischemic outcomes should be performed with caution due to considerable differences in study design, particularly the adjudication of MI events. There were no significant differences between the treatment groups in 30- and 90-day bleeding-related medical encounter rates, although the rates appeared higher with ticagrelor. This finding is plausible from a pharmacodynamic perspective15,16 and consistent with evidence from some indirect comparisons suggesting no difference in bleeding between prasugrel and ticagrelor13,14,17,18. However, these indirect comparisons may be confounded by irreconcilable cross-trial differences in study protocols (e.g., timing, dosing, duration of study drugs, definitions of bleeding) and populations13,14,17,18. The consistency with the few meta-analyses provides some support for the findings from the direct comparison of bleeding encounters in this real-world study in the absence of a randomized comparison of prasugrel to ticagrelor. Based on these results, there would not be an expected difference in healthcare resource utilization or cost between these two drugs related to bleeding. While bleeding is the most common side-effect of both ticagrelor4 and prasugrel3, ticagrelor has also been shown to be associated with significantly higher rates of ticagrelor-induced mild-to-moderate dyspnea and predominantly asymptomatic bradyarrhythmia compared with clopidogrel21. These side-effects are likely due to ticagrelorinduced elevations in adenosine concentrations, which are not seen with prasugrel22. Patients with ACS presenting with new onset or worsening dyspnea may require additional medical attention and monitoring resulting in higher medical resource utilization and costs. A prior analysis of patients with a history of ACS reported a mean per patient cost estimate for a dyspnea medical encounter of $695823. Our study, which captures dyspnea episodes in the inpatient and outpatient settings at 30 and 90 days, showed significantly lower rates of dyspnea-related encounters after adjustment with prasugrel compared to ticagrelor. This finding was primarily driven by an increased risk for dyspnea outpatient encounters with ticagrelor compared with prasugrel. Real-world adherence and persistence of ticagrelor may be challenging as a result of www.informahealthcare.com/jme ! 2015 Informa UK Ltd


2015

Table 5. Propensity score matched healthcare resource utilization for index hospitalization and 30-/90-day follow-up periods: Primary population and Label sub-group.


Characteristics

Index hospitalization, mean (SD) Length of stay, mean SD 30-day medical encounter rates, n (%) All-cause re-hospitalization Re-hospitalization for any CV-event* Re-hospitalization for Myocardial infarction Re-vascularization Bradyarrhythmia Bleeding Dyspnea Other outpatient medical encounters Bleeding Dyspnea 90-day medical encounter rates, n (%) All-cause re-hospitalization Re-hospitalization for any CV-event* Re-hospitalization for Myocardial infarction Revascularization Bradyarrhythmia Bleeding Dyspnea Other outpatient medical encounters Bleeding Dyspnea

Primary population Prasugrel (n ¼ 2661)


4.7 4.1

Label sub-group p value



p value

4.9 4.1

0.23

4.6 3.6

4.8 3.9

0.11

239 (9.0) 91 (3.4)

278 (10.5) 118 (4.4)

0.07 0.05

9.3 3.3

10.5 4.6

0.16 0.01

13 (0.5) 50 (1.9) 23 (0.9) 35 (1.3) 6 (0.2)

33 (1.2) 64 (2.4) 32 (1.2) 48 (1.8) 7 (0.3)

0.003 0.19 0.22 0.15 0.78

0.5 1.9 1.1 1.5 0.2

1.3 2.4 1.2 1.9 0.3

0.003 0.18 0.70 0.26 0.25

32 (1.2) 35 (1.3)

37 (1.4) 71 (2.7)

0.55 0.0005

1.1 1.4

1.3 2.6

0.44 0.002

431 (16.2) 177 (6.7)

478 (18.0) 199 (7.5)

0.09 0.24

15.1 5.7

18.1 7.5

0.004 0.009

31 (1.2) 101 (3.8) 42 (1.6) 83 (3.1) 10 (0.4)

59 (2.2) 113 (4.3) 57 (2.1) 89 (3.3) 11 (0.4)

0.003 0.41 0.13 0.65 0.83

1.2 3.5 1.9 3.2 0.3

2.2 4.3 2.2 3.3 0.5

0.004 0.13 0.49 0.87 0.37

59 (2.2) 76 (2.9)

58 (2.2) 126 (4.7)

0.9257 0.0004

1.9 3.4

2.0 4.7

0.76 0.03

*Any CV-event: transient ischemic attack, stroke, myocardial infarction, unstable angina, congestive heart failure, re-vascularization, or stent thrombosis.

non-hemorrhagic side-effects including bradyarrythmia and dyspnea24. Additionally, considering that ticagrelor is a twice-daily agent, whereas prasugrel is administered once daily, patients receiving once-daily dosing may be more adherent than those receiving twice-daily dosing25. From a cost perspective, prasugrel was associated with lower average total and medical healthcare costs compared with ticagrelor, although these cost differences were not statistically significant. As hospitalizations are a key healthcare cost driver for payers, this finding is in line with the results showing that prasugrel patients had fewer cardiovascular re-hospitalizations and outpatient encounters for dyspnea compared with ticagrelor treated patients. For both treatment cohorts, medical costs were the major driver of total costs and pharmacy costs accounted for510% of the total costs during all examined timeframes. Additionally, the majority of costs incurred during the aggregate of the index hospitalization through 90-day follow-up timeframe were primarily driven by index hospitalization. These trends and average medical costs for the index hospitalization in this study are consistent with results from earlier studies19,20,26,27. In pre-specified sub-group analyses, findings for the Label sub-group were directionally similar to the Primary ! 2015 Informa UK Ltd www.informahealthcare.com/jme

population and the point estimates did not vary considerably. This is likely due to the substantial overlap between the Primary population and the Label sub-group. In some instances, however, the same measure differed statistically across populations. It is possible that these variations were due to differences in baseline risks between the populations under study or may have been due to chance. Of note, ACS-PCI patients with prior TIA or stroke (excluded from the Label sub-group) are known to be at a higher risk for bleeding and recurrent ischemic events28 and associated utilization29. No formal tests of interaction were conducted. Taken together, the direction of the present study findings on financial implications associated with treatment with prasugrel compared with ticagrelor was consistent across all utilization and cost measures and examined populations; however, the absolute values of the calculated costs should not be taken for granted due to a number of reasons. First, there was no statistical significance in any of the cost comparisons with the exception of index hospitalization and aggregate 90 day costs among the Label sub-group. This finding in the Label sub-group is reflective of significantly fewer CV-related re-hospitalizations and 90 day all-cause reHealthcare resource use and costs: prasugrel vs ticagrelor Molife et al.

9



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hospitalizations observed with prasugrel-treated patients in this sub-group. Second, as noted as a potential limitation below, there may have been some under-reporting of utilization and costs data in this study. Third, although hospital-specific cost-to-charge ratios were available and used to estimate costs from billed charges in the CDM, it should be noted that cost-to-charge ratios may vary across hospital departments. The current study has several strengths including the use of a large database which allowed for a diverse crosssection of patient types and hospital settings (including teaching and non-teaching institutions) and the ability to capture healthcare records for patients independent of their participation in a specific health plan or payer type, both of which support generalizability of the findings. It should be noted, however, that 64% of hospitals were located in the southern geographic region (data not shown), and any resulting bias is unknown. There was access to procedural and hospital characteristics that allowed for propensity score matching on important known confounding variables. However, as is a common limitation with retrospective database studies, residual confounding may still remain as potential unknown and unmeasured known confounders (e.g., under-reporting of pre-existing conditions, patient weight, aspirin use, hospital formulary and provider characteristics, training of the physician and the potential bias of trainers, and physician prescribing decision) could not be fully accounted for. Thus, cause and effect relationships cannot be established from this study. Since unique ICD-9 diagnosis codes do not exist to allow discrimination between drug-induced vs other causes of dyspnea and bradyarrhythmia, the sensitivity and specificity of the algorithm used to identify these outcomes is unknown. Data on outpatient pharmacy claims, physician visits, and their associated costs were not available, therefore adherence and persistence of the index drug during follow-up could not be assessed. Re-hospitalizations that occurred outside of IMS data capture were not recorded, although any missing data is likely to be non-differential. The index period for this study began shortly after the FDA approval of ticagrelor. It is possible that concerns of practitioners with the side-effects of ticagrelor at the time of its introduction may have contributed to longer hospital LOS or increased re-hospitalization rates among patients with an ACS event occurring early in the study timeframe. However, a sensitivity analysis that reduced the beginning of the index period by 3 months did not alter the results meaningfully. While the present study represents the first direct comparison of prasugrel with ticagrelor in respect to healthcare resource utilization and costs, the results need to be tempered due to the limitations applied to interpreting observational research. 10


Conclusion In this retrospective observational study, re-hospitalization for MI and outpatient encounters for dyspnea within 90-days post-index hospital discharge for ACS-PCI patients were lower with prasugrel use than with ticagrelor use, with no significant differences noted in bleedingrelated utilization or other measures of healthcare utilization or costs. The results of this study need to be considered within the limitations of observational research; however, US healthcare decision-makers may find these results helpful to inform coverage and access decisions for these treatments.

Transparency Declaration of funding This study was funded by Daiichi Sankyo Inc., Parsippany, NJ, USA and Eli Lilly and Company, Indianapolis, IN, USA. Declaration of financial/other relationships CM, CL, YZ, PM, and MBE are employees of Eli Lilly and Company. FF and EM are employees of Daiichi Sankyo, Inc. GV is an unpaid consultant to Daiichi Sankyo and Eli Lilly. MD, SK, JL were employees of IMS Health at the time of the study. IMS Health received research funding from Daiichi Sankyo Inc. and Eli Lilly and Company to conduct this study and prepare this manuscript. Acknowledgments The authors thank Doug Faries, PhD, Hsiao Lieu, MD, William Malatestinic, PharmD, and Nayan Acharya, MD, at Eli Lilly and Company; Qiaoyi Zhang, PhD, Brian Baker, PharmD, and Howard Rutman, MD, at Daiichi Sankyo Inc.; and Won Chan Lee at IMS, for valuable contributions to this study and manuscript. Molly Tomlin, MS, at Eli Lilly and Company assisted in the preparation of this manuscript. Previous presentation Some material contained in this paper was previously presented at the American Heart Association: Quality of Care and Outcomes Research in Cardiovascular Disease and Stroke Scientific Sessions; Baltimore, MD, USA; June 2–4, 2014.

References 1. Jneid H, Anderson JL, Wright RS, et al. 2012 ACCF/AHA focused update of the guideline for the management of patients with unstable angina/non–STelevation myocardial infarction (updating the 2007 guideline and replacing the 2011 focused update): a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol 2012;60:654-90 2. O’Gara PT, Kushner FG, Ascheim DD, et al. 2013 ACCF/AHA guideline for the management of ST-elevation myocardial infarction: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation 2013;127:e362-425 3. Wiviott SD, Braunwald E, McCabe CH, et al; TRITON-TIMI 38 (Investigators). Prasugrel versus clopidogrel in patients with acute coronary syndromes. N Engl J Med 2007;357:2001-15




4. Wallentin L, Becker RC, Budaj A. Ticagrelor versus clopidogrel in patients with acute coronary syndromes. N Engl J Med 2009;361:1045-57 5. Effient [package insert]. Indianapolis, IN: Eli Lilly and Company, 2013 6. Malenka DJ, Kaplan AV, Sharp SM, et al. Postmarketing surveillance of medical devices using Medicare claims. Health Affairs 2005;24:928-37 7. National Quality Measures Clearinghouse. Acute myocardial infarction: hospital 30-day, all cause, risk-standardized readmission rate (RSMR) following AMI hospitalization. Rockville, MD: Agency for Healthcare Research and Quality (AHRQ), 2014. Available at: http://www.qualitymeasures.ahrq.gov/ content.aspx?id=46498 [Last accessed 6 January 2015] 8. Joynt KE, Jha AK. A Path Forward on Medicare Readmissions. New Engl J Med 2013;368:1175-7 9. Rau J. Armed with bigger fines, Medicare to punish 2,225 hospitals for excess readmissions. Washington, DC: Kaiser Health News, 2013. Available at: http://kaiserhealthnews.org/news/readmission-penaltiesmedicare-hospitals-year-two/ [Last accessed 6 January 2015] 10. Chastek B, Riedel AA, Wygant G, et al. Evaluation of hospitalization and followup costs among patients hospitalized with ACS treated with a stent and clopidogrel. Curr Med Res Opin 2009;25:2845-52 11. Meadows E, Bae J, Zagar A, et al. Rehospitalization following percutaneous coronary intervention for commercially insured patients with acute coronary syndrome: a retrospective analysis. BMC Res Notes 2012;5:342 12. Curtis JP, Schreiner G, Wang Y, et al. All-cause readmission and repeat revascularization after percutaneous coronary intervention in a cohort of Medicare patients. J Am Coll Cardiol 2009;54:903-7 13. Biondi-Zoccai G, Lotrionte M, Agostoni P, et al. Adjusted indirect comparison meta-analysis of prasugrel versus ticagrelor for patients with acute coronary syndromes. Int J Cardiol 2011;150:325-31 14. Steiner S, Moertl D, Chen L, et al. Network meta-analysis of prasugrel, ticagrelor, high- and standard-dose clopidogrel in patients scheduled for percutaneous coronary interventions. Thromb Haemost 2012;108:318-27 15. Deharo P, Bassez C, Bonnet G, et al. Prasugrel versus ticagrelor in acute coronary syndrome: a randomized comparison. Int J Cardiol 2013;170:e21-2 16. Alexopoulos D, Stavrou K, Koniari I, et al. Ticagrelor vs prasugrel one-month maintenance therapy: impact on platelet reactivity and bleeding events. Thromb Haemost. 2014;112:551-7


2015

17. Chatterjee S, Ghose A, Sharma A, et al. Comparing newer oral anti-platelets prasugrel and ticagrelor in reduction of ischemic events-evidence from a network meta-analysis. J Thromb Thrombolysis 2013;36:223-32 18. Passaro D, Fadda V, Maratea D, et al. Anti-platelet treatments in acute coronary syndrome: simplified network meta-analysis. Int J Cardiol 2011;150:364-7 19. Zhao Z, Winget M. Economic burden of illness of acute coronary syndromes: medical and productivity costs. BMC Health Serv Res 2011;11:35 20. Etemad LR, McCollam PL. Total first-year costs of acute coronary syndrome in a managed care setting. J Manag Care Pharm 2005;11:300-6 21. Scirica BM, Cannon CP, Emanuelsson H, et al. The Incidence of bradyarrhythmias and clinical bradyarrhythmic events in patients with acute coronary syndromes treated with ticagrelor or clopidogrel in the PLATO (Platelet Inhibition and Patient Outcomes) Trial: results of the Continuous Electrocardiographic Assessment Substudy. J Am Coll Cardiol 2011;57:1908-16 22. Bonello L, Laine M, Kipson N, et al. Ticagrelor increases adenosine plasma concentration in patients with an acute coronary syndrome. J Am Coll Cardiol 2014;63:872-7 23. Bonafede M, Jing Y, Gdovin Bergeson J, et al. Impact of dyspnea on medical utilization and affiliated costs in patients with acute coronary syndrome. Hosp Pract 2011;39:16-22 24. Belchikov YG, Koenig SJ, Dipasquale EM. Potential role of endogenous adenosine in ticagrelor-induced dyspnea. Pharmacotherapy 2013;33:882-7 25. Saini SD, Schoenfeld P, Kaulback K, et al. Effect of medication dosing frequency on adherence in chronic diseases. Am J Manag Care 2009;15:e2233 26. McCollam P, Etemad L. Cost of care for new-onset acute coronary syndrome patients who undergo coronary revascularization. J Invasive Cardiol 2005;17:307-11 27. Menzin J, Wygant G, Hauch O, et al. One-year costs of ischemic heart disease among patients with acute coronary syndromes: findings from a multiemployer claims database. Curr Med Res Opin 2008;24:461-8 28. Ducrocq G, Amarenco P, Labreuche J, et al. A history of stroke/transient ischemic attack indicates high risks of cardiovascular event and hemorrhagic stroke in patients with coronary artery disease. Circulation 2013;127:730-8 29. Berenson K, Ogbonnaya A, Casciano R, et al. Economic consequences of ACS-related rehospitalizations in the US. Curr Med Res Opin 2010;26:329-36


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Clinical effect of ticagrelor administered in acute coronary syndrome patients following percutaneous coronary intervention.

Efficacy and Safety of Prasugrel Compared With Clopidogrel for Patients With Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention.

High Platelet Reactivity in Patients with Acute Coronary Syndromes Undergoing Percutaneous Coronary Intervention: Randomised Controlled Trial Comparing Prasugrel and Clopidogrel.

Spontaneous coronary artery dissection in men presenting with acute coronary syndrome, successfully managed by intravascular ultrasound-guided percutaneous coronary intervention.

Efficacy and safety of prasugrel in acute coronary syndrome patients.

Resource consumption and healthcare costs of acute coronary syndrome: a retrospective observational administrative database analysis.

Rosuvastatin reduces ischemia-reperfusion injury in patients with acute coronary syndrome treated with percutaneous coronary intervention.

Prognostic Analysis for Cardiogenic Shock in Patients with Acute Myocardial Infarction Receiving Percutaneous Coronary Intervention.

Residual Dyslipidemia Leads to Unfavorable Outcomes in Patients with Acute Coronary Syndrome after Percutaneous Coronary Intervention.

Meta-Analysis of Comparison of the Newer Oral P2Y12 Inhibitors (Prasugrel or Ticagrelor) to Clopidogrel in Patients With Non-ST-Elevation Acute Coronary Syndrome.

Comparison of Ticagrelor Versus Prasugrel to Prevent Periprocedural Myonecrosis in Acute Coronary Syndromes.

A comparative study of transulnar and transradial artery access for percutaneous coronary intervention in patients with acute coronary syndrome.

Percutaneous coronary intervention in patients with anomalous origin of coronary artery presenting with acute coronary syndrome: A case series.

Bleeding risk and incidence in real world percutaneous coronary intervention patients with ticagrelor.

Percutaneous coronary intervention in treatment of multivessel coronary artery disease in patients with non-ST-segment elevation acute coronary syndrome.

Relationships of Factors Affecting Self-care Compliance in Acute Coronary Syndrome Patients Following Percutaneous Coronary Intervention.

Effectiveness of switching 'low responders' to prasugrel to ticagrelor after acute coronary syndrome.

Prevalence and prognosis of percutaneous coronary intervention-associated nephropathy in patients with acute coronary syndrome and normal kidney function.

Hematologic complications, healthcare utilization, and costs in commercially insured patients with myelodysplastic syndrome receiving supportive care.

Impact of non-inhibited platelet supplementation on platelet reactivity in patients treated with prasugrel or ticagrelor for an acute coronary syndrome: An ex vivo study.

Percutaneous coronary intervention and inpatient mortality in patients with advanced chronic kidney disease presenting with acute coronary syndrome.

The renoprotective effects of simvastatin and atorvastatin in patients with acute coronary syndrome undergoing percutaneous coronary intervention: An observational study.

Coronary artery bypass grafting-related bleeding complications in real-life acute coronary syndrome patients treated with clopidogrel or ticagrelor.

Bivalirudin versus unfractionated heparin: a meta-analysis of patients receiving percutaneous coronary intervention for acute coronary syndromes.