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13-01-2016 | Original Article - ICIN | Uitgave 2/2016 Open Access

Netherlands Heart Journal 2/2016

Treatment variation in stent choice in patients with stable or unstable coronary artery disease

Tijdschrift:
Netherlands Heart Journal > Uitgave 2/2016
Auteurs:
L. T. Burgers, E. A. McClellan, I. E. Hoefer, G. Pasterkamp, J. W. Jukema, S. Horsman, N. H. J. Pijls, J. Waltenberger, M. A. Hillaert, A. C. Stubbs, J. L. Severens, W. K. Redekop

Introduction

Despite improvement in the prognosis of patients with cardiovascular disease (CVD) it still remains the second leading cause of death across the Western world and one of the major causes of disability [ 1]. For many years patients with coronary artery disease (CAD), the most frequent type of CVD, were treated mainly with percutaneous coronary intervention (PCI), coronary artery bypass grafting (CABG) or medication only. Both revascularisations reduce the incidence of death and myocardial infarction (MI) in CAD patients compared with no treatment, but most patients are now treated with PCI. In 2012 approximately 39,000 PCIs were performed in the Netherlands [ 2]. Originally a PCI was performed with an expanding balloon; however, nowadays patients are often treated with a bare-metal stent (BMS) or drug-eluting stent (DES). DES reduces restenosis compared with BMS (8.4 versus 20.9 %) [ 3]. However, patients treated with DES, especially the early-generation, might have a higher chance of developing very late stent thrombosis (0.7 versus 0.1 %) [ 3]. Both types of stents have pros and cons; decisions should be based on what is considered appropriate for a patient since the choice of stent type may have impact on long-term outcomes. Variations in treatment are the result of differences in patient characteristics and clinical factors (e.g. anatomy) but previous studies have shown that physician and hospital factors may contribute to treatment variation. In the UK, stent choice was associated with the operator and the treating hospital [ 4]. Tu et al. [ 5] have shown that the physician performing the diagnostic catheterisation and the treating hospital were strong independent predictors of the type of revascularisation (CABG versus PCI) in Canada. Furthermore, the type of stent was also determined by the type of payer (e.g. Medicaid, private insurance) [ 6]. Of course, these results may be expected to be healthcare system specific and do not apply for Dutch patients, since the Netherlands has a centrally publicly funded healthcare system.
This study will explore the associations with stent choice (DES or BMS) for Dutch patients diagnosed with stable or unstable CAD focusing on variation due to clinical factors and treating hospital.

Methods

Study design

Treatment variation of patients with stable or unstable CAD was explored through analysing data from the Circulating Cells prospective cohort study, which has the aim of discovering markers that identify patients who are at an increased risk of developing a cardiovascular event. In this multicentre study, patients undergoing coronary angiography were included if they had known or suspected stable or unstable CAD; specific diagnoses included unstable angina and non-ST-elevation MI (NSTEMI) [ 7].

Treatment

Patients undergoing coronary angiography were asked to participate in the study. Data were collected regarding patient characteristics, test results and treatment decisions. Patients who were treated with a PCI received a BMS, DES, drug-eluting balloon angioplasty or standard balloon angioplasty. The aim of this study is to examine the factors that are associated with stent choice (DES vs. BMS), meaning that patients treated solely with drug-eluting balloon angioplasty or standard balloon angioplasty are excluded from the analyses. Stent choice for DES was defined as a PCI with at least one DES, including patients treated with only DES but also patients treated with DES in combination with BMS, drug-eluting balloon angioplasty or standard balloon angioplasty. Stent choice for BMS was defined as a PCI with only BMS such that patients treated with BMS in combination with balloon angioplasty or DES are excluded.

Data and statistical analyses

Choice of stent type (DES or BMS) was compared between patient subgroups, determined by diagnosis. The following baseline characteristics were also collected during the study: age, gender, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), thrombolysis in myocardial infarction (TIMI) score for unstable CAD patients, New York Heart Association (NYHA) class, number of diseased vessels (50–99 % stenosis), cardiac history (previous heart failure, previous MI, previous PCI, and previous CABG), non-cardiac history (cerebrovascular accident (CVA) or transient ischaemic attack (TIA), pulmonary disease, peripheral vessel disease (PVD), and renal failure), and CVD risk factors (diabetes mellitus, hypertension, hyperlipidaemia, smoking, and pack-years (tobacco)).
Multiple imputation was used to prevent patients from being excluded from the analyses due to missing values. Baseline characteristics (SBP, DBP, BMI, NYHA class, previous heart failure, previous MI, CVA or TIA, pulmonary disease, PVD, renal failure, diabetes mellitus, hypertension, hyperlipidaemia, current smoker and pack-years) were missing for less than 2 % of all cases except pack-years, which was missing for 14 % of all cases. These characteristics were imputed using predictive mean matching for scale variables. Five imputation sets were created with ten iterations, each using fully conditional specification in SPSS 22 (IBM Corp. Released 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp). Age, gender, previous PCI, previous CABG, and diagnosis were only used as predictors and not imputed since there were no missing values for these variables.
Differences between groups were tested using Chi-squared analysis for categorical variables. Bivariate analyses using logistic regression were performed to identify variables that were associated with stent type; stable and unstable CAD patients were analysed separately. Backwards selection was used to create the final multivariate model(s). P values lower than 0.05 were considered statistically significant, although a higher threshold of 0.1 was used to select variables for the multivariate analysis. Associations were discussed with clinical experts in order to see if the results make sense (face validity).

Results

In total, 714 patients were included in the Circulating Cells cohort, 22 of whom were excluded from the analyses since they did not have significant coronary atherosclerosis. The remaining 692 patients were included in three teaching hospitals and one general hospital, and 477 patients were treated with PCI. Of those patients, 442 patients were treated with BMS or DES. Others were treated with a combination of BMS and balloon angioplasty ( n = 4), drug-eluting balloon angioplasty or standard balloon angioplasty ( n = 18) or missing ( n = 13) and are excluded from the analysis. The number of patients treated per hospital (I–IV) was 130, 98, 81, and 133, respectively. Table  1 presents the baseline demographic and angiographic characteristics of the included patients. The mean age of the cohort was 63 years and 72 % were male. The majority (81 %) of the patients were diagnosed with stable CAD (including silent ischaemia) after the coronary angiography. There were three significant differences in characteristics of stable CAD ( n = 358) and unstable CAD patients ( n = 84). Stable CAD patients more often had a lower NYHA class, were less often current smokers and had less often experienced a CVA/TIA compared with unstable CAD patients.
Table 1
Baseline characteristics
 
All patients after imputation
Patients with stable CAD
Patients with unstable CAD
 
 
Mean
SD
N b
Mean
SD
N b
Mean
SD
N b
p value a
Baseline characteristics
Age
62.72
10
442
62.96
10
358
61.71
11
84
0.319
Male (%)
72 %
 
442
73 %
 
358
68 %
 
84
0.354
SBP (mmHg)
135
19
442
135
19
358
134
21
84
0.748
DBP (mmHg)
77
11
442
77
11
358
79
11
84
0.273
BMI (kg/m 2)
28
4
442
28
4
358
27
4
84
0.266
TIMI score c
1
8 %
 
83
     
8 %
 
83
 
2
18 %
 
83
     
18 %
 
83
 
3
30 %
 
83
     
30 %
 
83
 
4
28 %
 
83
     
28 %
 
83
 
5
12 %
 
83
     
12 %
 
83
 
6 + 7
4 %
 
83
     
4 %
 
83
 
Number of diseased vessels (50–99 %)
                 
0.077
1
44 %
 
442
46 %
 
358
36 %
 
84
 
> 1
56 %
 
442
54 %
 
358
64 %
 
84
 
NYHA
                 
p< 0.001
NYHA I
73 %
 
442
73 %
 
358
76 %
 
84
 
NYHA II
18 %
 
442
20 %
 
358
7 %
 
84
 
NYHA III
6 %
 
442
7 %
 
358
4 %
 
84
 
NYHA IV
2 %
 
442
0 %
 
358
13 %
 
84
 
Cardiac history (%)
Previous heart failure
2 %
 
442
2 %
 
358
1 %
 
84
0.542
Previous MI
31 %
 
442
33 %
 
358
23 %
 
84
0.066
Previous PTCA
33 %
 
442
35 %
 
358
26 %
 
84
0.116
Previous CABG
7 %
 
442
8 %
 
358
5 %
 
84
0.369
Non-cardiac history (%)
CVA/TIA
8 %
 
442
6 %
 
358
14 %
 
84
0.017
Pulmonary disease
11 %
 
442
10 %
 
358
14 %
 
84
0.242
Peripheral vessel disease
13 %
 
442
13 %
 
358
14 %
 
84
0.684
Renal failure
3 %
 
442
4 %
 
358
1 %
 
84
0.25
Risk factors (%)
Diabetes mellitus
21 %
 
442
22 %
 
358
20 %
 
84
0.764
Hypertension
66 %
 
442
67 %
 
358
60 %
 
84
0.189
Hyperlipidaemia
68 %
 
442
70 %
 
358
60 %
 
84
0.057
Current smokers
19 %
 
442
16 %
 
358
32 %
 
84
0.001
Pack years d
19.7
18
442
19.2
18.1
358
21.9
22.1
84
0.302
Diagnosis (%)
Stable angina
81 %
 
442
             
Unstable angina
10 %
 
442
             
NSTEMI
9 %
 
442
             
Treatment/stent choice
                 
0.736
DES
66 %
 
442
66 %
 
358
68 %
 
84
 
BMS
34 %
 
442
34 %
 
358
32 %
 
84
 
Hospital
I
29 %
 
442
28 %
 
358
37 %
 
84
 
II
22 %
 
442
24 %
 
358
13 %
 
84
 
III
18 %
 
442
14 %
 
358
37 %
 
84
 
IV
30 %
 
442
34 %
 
358
13 %
 
84
 
BMI body mass index, CABG coronary artery bypass graft, CVA cerebrovascular accident, DBP diastolic blood pressure, MI myocardial infarction, NA not applicable, NSTEMI non ST elevation myocardial infarction, NYHA New York heart association, PTCA percutaneous transluminal coronary angioplasty, SBP systolic blood pressure, TIA transient ischaemic attack, TIMI thrombolysis in myocardial infarction.
aStable versus unstable.
bNumber of patients on which the analyses were based.
cOnly reported for unstable angina and NSTEMI.
dNumber of packs per day multiplied with years of smoking.
In total 771 stents were used to treat 442 patients with 612 target lesions. On average 1.385 target lesions were stented per patient (range 1–3), where 1.260 stents were used per lesion and 1.744 stents (range 1–6) per patient were used. Of the 442 patients, 66 % were treated with one or more DES. Bivariate analyses (Table  2) showed that NYHA class, number of diseased vessels, previous PCI, smoking, diabetes and the treating hospital were significantly associated with stent choice for a patient. The frequency of DES use varied widely (50–99 %) between the four hospitals, considering the total population. The variation in stent choice was larger in the unstable patient group (45–100 %).
Table 2
Associations with therapeutic decision (DES vs BMS)
 
All patients
Patients with stable CAD
Patients with unstable CAD
 
DES (%)/ OR
N
p value
DES (%)/ OR
N
p value
DES (%)/ OR
N
p value
Overall
66 %
442
 
66 %
358
 
68 %
84
 
Diagnosis
   
0.558
           
Stable CAD
66 %
358
             
Unstable angina
63 %
46
             
NSTEMI
74 %
38
             
Hospital
   
p< 0.001
   
p< 0.001
   
p< 0.001
1
50 %
130
 
52 %
99
 
45 %
31
 
2
64 %
98
 
66 %
87
 
55 %
11
 
3
99 %
81
 
98 %
50
 
100 %
31
 
4
64 %
133
 
65 %
122
 
55 %
11
 
Baseline characteristics
Age (years)
1.008
442
0.387
1.005
358
0.682
1.023
84
0.272
Gender
   
0.474
   
0.46
   
0.872
Male
67 %
318
 
67 %
261
 
68 %
57
 
Female
64 %
124
 
63 %
97
 
67 %
27
 
SBP (mmHg)
1.007
442
0.188
1.003
358
0.598
1.022
84
0.074
DBP (mmHg)
0.998
442
0.815
0.997
358
0.767
1.001
84
0.968
BMI (kg/m 2)
1.038
442
0.128
1.049
358
0.08
0.994
84
0.912
TIMI score a
   
0.085
         
0.085
1
71 %
7
       
71 %
7
 
2
80 %
15
       
80 %
15
 
3
48 %
25
       
48 %
25
 
4
83 %
23
       
83 %
23
 
5
60 %
10
       
60 %
10
 
6 + 7
100 %
3
       
100 %
3
 
NYHA
   
p< 0.01
   
0.036
   
0.011
NYHA I
62 %
324
 
63 %
260
 
59 %
64
 
NYHA II
71 %
79
 
69 %
73
 
100 %
6
 
NYHA III & IV
90 %
39
 
88 %
25
 
93 %
14
 
Number of diseased vessels
   
p< 0.01
   
p< 0.01
   
0.102
1
58 %
196
 
58 %
166
 
57 %
30
 
> 1
73 %
246
 
72 %
192
 
74 %
54
 
Cardiac history
Previous heart failure
   
0.981
   
0.836
   
0.489
Yes
67 %
9
 
63 %
8
 
100 %
1
 
No
66 %
433
 
66 %
350
 
67 %
83
 
Previous MI
   
0.077
   
0.090
   
0.536
Yes
72 %
137
 
72 %
118
 
74 %
19
 
No
64 %
305
 
63 %
240
 
66 %
65
 
Previous PTCA
   
p< 0.01
   
p< 0.01
   
0.271
Yes
76 %
148
 
76 %
126
 
77 %
22
 
No
61 %
294
 
60 %
232
 
65 %
62
 
Previous CABG
   
0.541
   
0.736
   
0.433
Yes
61 %
31
 
63 %
27
 
50 %
4
 
No
67 %
411
 
66 %
331
 
69 %
80
 
Non-cardiac history
CVA/TIA
   
0.748
   
0.682
   
0.924
Yes
69 %
35
 
70 %
23
 
67 %
12
 
No
66 %
407
 
66 %
335
 
68 %
72
 
Pulmonary disease
   
0.103
   
0.142
   
0.445
Yes
56 %
47
 
55 %
35
 
58 %
12
 
No
68 %
395
 
36 %
323
 
69 %
72
 
PVD
   
0.086
   
0.124
   
0.445
Yes
56 %
57
 
56 %
45
 
58 %
12
 
No
68 %
385
 
67 %
313
 
69 %
72
 
Renal failure
   
0.059
   
0.126
   
0.144
Yes
43 %
14
 
46 %
13
 
0 %
1
 
No
67 %
428
 
67 %
345
 
69 %
83
 
Risk factors
                 
Diabetes mellitus
   
p< 0.001
   
p< 0.001
   
0.009
Yes
93 %
95
 
92 %
78
 
94 %
17
 
No
59 %
347
 
59 %
280
 
61 %
67
 
Hypertension
   
0.306
   
0.498
   
0.324
Yes
68 %
290
 
67 %
240
 
72 %
50
 
No
63 %
152
 
63 %
118
 
62 %
34
 
Hyperlipidaemia
   
0.943
   
0.427
   
0.144
Yes
66 %
302
 
65 %
252
 
74 %
50
 
No
67 %
140
 
69 %
106
 
59 %
34
 
Current smokers
   
0.037
   
0.066
   
0.246
Yes
57 %
85
 
55 %
58
 
59 %
27
 
No
69 %
357
 
68 %
300
 
72 %
57
 
Pack years b
1.001
442
0.898
1.000
358
0.974
1.002
84
0.877
BMI body mass index, CABG coronary artery bypass graft, CAD coronary artery disease, CVA cerebrovascular accident, DBP diastolic blood pressure, MI myocardial infarction, NA not applicable, NSTEMI non ST elevation myocardial infarction, NYHA New York heart association, PTCA percutaneous transluminal coronary angioplasty, PVD peripheral vessel disease, SBP systolic blood pressure, TIA transient ischaemic attack, TIMI thrombolysis in myocardial infarction.
aonly for unstable angina and NSTEMI.
bNumber of packs per day multiplied with years of smoking.
All multivariate analyses (Table  3) showed that patients with diabetes had a significantly higher chance of receiving DES. The use of DES versus BMS in the stable CAD population was not only associated with diabetes but also with the treating hospital, smoking status, and previous PCI. Patients treated in hospital II or III, patients having diabetes, and patients with a previous PCI had a higher chance of being treated with DES. Patients treated in hospital I and patients who were current smokers had a lower chance of being treated with DES.
Table 3
Multivariate analyses therapeutic decision (BMS vs DES)
 
Bivariate analyses (OR)
Multivariate analyses (OR)
p value*
Total population ( n  = 442)
Number of diseased vessels
1
0.520
0.560
0.006
> 1
Ref
   
NYHA class
NYHA class I
Ref
   
NYHA class II
1.478
   
NYHA class III + IV
5.311
   
Hospital
1
0.565
   
2
1.016
   
3
45.176
   
4
Ref
   
Diabetes (yes vs no)
8.680
8.318
p < 0.001
Renal artery disease (yes vs no)
0.368
   
Current smoker (yes vs no)
0.599
   
Previous MI (yes vs no)
1.486
   
PVD (yes vs no)
1.017
   
Previous PTCA (yes vs no)
2.045
   
TIMI score a
1
Ref
   
2
1.20
   
3
0.37
   
4
2.000
   
5
0.600
   
6 + 7
646189937
   
Constant
 
1.911
p < 0.001
Nagelkerke R 2
 
16 %
 
Stable CAD ( n  = 358)
Bivariate analyses (OR)
Multivariate analyses (OR)
p  value*
BMI (kg/m 2)
1.049
   
Hospital
1
0.578
0.466
0.013
2
1.034
1.047
0.884
3
26.671
29.381
0.001
4
Ref
Ref
 
Previous MI (yes vs no)
1.513
   
NYHA class
NYHA class I
Ref
   
NYHA class II
1.280
   
NYHA class III + IV
4.319
   
Number of diseased vessels
1
0.536
   
> 1
Ref
   
Current smoker (yes vs no)
0.588
0.404
0.014
Diabetes (yes vs no)
8.454
12.001
p < 0.001
Previous PTCA (yes vs no)
2.103
2.284
0.003
Constant
 
1.207
0.397
Nagelkerke R 2
 
33 %
 
Unstable CAD ( n= 84)
Bivariate analyses (OR)
Multivariate analyses (OR)
p  value*
Hospital
1
0.686
   
2
1.000
   
3
1346229036
   
4
Ref
   
NYHA class
NYHA class I
Ref
   
NYHA class II
1105324892
   
NYHA class III + IV
8.895
   
Diabetes (yes vs no)
10.146
10.146
0.029
TIMI score a
1
Ref
   
2
1.600
   
3
0.369
   
4
1.900
   
5
0.600
   
6 + 7
646189937
   
SBP (mmHg)
1.007
   
Constant
 
1.577
0.069
Nagelkerke R 2
 
13 %
 
SBP systolic blood pressure, BMI body mass index, NYHA New York heart association, PTCA percutaneous transluminal coronary angioplasty, TIMI Thrombolysis In Myocardial Infarction.
aP value of multivariate analyses.
* p = 0.05

Discussion

This study explored the factors associated with stent choice for Dutch patients diagnosed with stable or unstable CAD. Various factors are associated with the frequency of DES use, including diabetes, previous PCI, number of diseased vessels, NYHA class, smoking and the treating hospital.
Patients requiring a PCI were in most cases treated with at least one DES (66 %), which is in line with the guidelines that suggest that patients with stable CAD should receive a DES if there is no contraindication of prolonged dual antiplatelet therapy [ 8]. Furthermore, DES is recommended over BMS in NSTEMI or unstable angina patients with diabetes [ 9]. Since patients with diabetes have a higher restenosis risk than patients without diabetes, DES is considered the most optimal treatment for these patients since DES reduces restenosis compared with BMS. Consequently, diabetes was significantly associated with stent choice in this study. Patients who have been treated before with a PCI were also more likely to receive DES (76 %); these patients have a higher risk of developing restenosis and thus DES was preferred. Patients with multi-vessel disease (73 % DES) and patients with a high NYHA class (range I–IV: 62–90 % DES) were significantly more frequently treated with DES. Studies suggest that patients with multi-vessel disease should be treated with CABG or PCI using DES since these interventions have shown to be more effective than BMS [ 10]. Patients currently smoking were less often treated with DES.
These clinical factors can be considered as legitimate leading to variation in stent choice. However, 19 % of the variation in stent choice was explained by these factors in the stable CAD population. Beside clinical factors, other potential reasons for treatment variation could exist due to: (1) the operator, (2) the availability and supply of resources, or (3) patient preferences. Considering operator variation, physicians use different methods to decide which stent is most suited for a particular patient. It is known that some physicians are believers of DES and some do not believe in the added value of DES compared with BMS, while BMS is less expensive. In several randomised clinical trials, DES has shown to be more effective than BMS for several indications (e.g. diabetes, long lesions). Some operators strictly follow the results of these trials and the guidelines while other operators also use DES for other indications with a high restenosis risk since guidelines do not provide recommendations concerning the most optimal stent for every type of patient, although it is probably unrealistic to expect this. In our study, one hospital treated almost all patients with DES (99 %); probably DES was used also for ‘off-label’ indications. A Dutch report concluded that world-wide DES is used off-label in 47–81 % of the patients, leading to differences in safety and clinical effectiveness [ 11]. The second potential reason, availability and supply of resources, focuses on the hospital level. In our analyses, the treating hospital was significantly associated with stent choice even after correcting for clinical factors in the stable CAD group. After adding treating hospital to the regression analysis 33 % of the variation in stent choice could be explained. The analyses showed that the frequency of DES use ranged from 50–99 % of all patients across hospitals. This difference could result from a difference in patient case mix, despite the adjustment for many individual patient characteristics in the analyses. Furthermore, payment arrangements with stent manufacturers and budget constraints may have influenced the stent choice. Another potential reason, patient preference, could have influenced the variation in stent choice. However, we expect this to be minimal since both interventions can be considered to be equally invasive.

Implications

In general, patients receive the most optimal stent given their clinical characteristics. However, stent choice is also determined by the treating hospital, probably due to operator variation and availability and supply of resources. Variation should only occur due to demographic and angiographic factors. When variation is due to factors other than demographics or angiography findings it could lead to less optimal stent choices and subsequently differences in long-term outcomes.
Patients receiving DES have a lower risk of target lesion revascularisation than patients treated with BMS [ 3]. However, there is some concern of late stent thrombosis that may occur more frequently after DES than BMS [ 3]. Besides the implications of treatment variation on the effectiveness, it is also important to consider the costs. While BMS is less expensive than DES, BMS leads to more reinterventions than DES. Several studies have estimated the cost-effectiveness of DES versus BMS and many of these studies concluded that initial DES treatment was overall more expensive than the BMS strategy [ 1223]; the reduction in reinterventions did not offset the initial higher stent costs. In most of the studies DES was slightly more effective [ 1223] often leading to an incremental cost-effectiveness ratio that could not be considered cost-effective [ 13, 14, 17, 18, 23]. However, some specific subgroups (diabetes, complex lesions, complex vessels, multi-vessel disease, or a combination of these risk factors) were identified in which DES resulted in a higher health gain in terms of quality-adjusted life-years compared with subgroups that were not at high risk of restenosis and complications. Consequently, in these subgroups, DES was considered more cost-effective. In our study some of these specific subgroups were also associated with a more frequent use of DES.

Limitations

The factors examined in the analyses explained 13–33 % of the variation in treatment decisions. While the treating hospital was associated with stent choice, it is possible that hospital is a proxy for a pre-existing patient case mix. Many clinical factors were included in the regression models but it is possible that factors that are of predictive value were not included. Furthermore, the underlying reason why the treating hospital is associated with stent choice is unknown. This could be due to the operator (e.g. experience), for which data were not available for our analyses, or the availability and supply of resources might explain the association with the treating hospital, even though the Netherlands has a centrally publicly funded healthcare system.
We were not able to compare patients treated solely with BMS and patients treated solely with DES. Stent choice for DES was defined as a PCI with at least one DES which includes patients treated with only DES but also patients treated with DES in combination with BMS, drug-eluting balloon angioplasty or standard balloon angioplasty. Consequently, the associations that we have found actually explain why some patients receive DES and why other patients did not receive DES.
In addition, this study did not take into consideration the differences in stent choice (different types of DES) despite variation in their effectiveness. For example, the newer ultra-thin strut BMS leads to less restenosis than the thicker strut BMS; a study using the SOLSTICE registry showed that ultra-thin strut BMS leads to low 6-month major adverse cardiac event rates (5.8 %), including target lesion revascularisations [ 24]. Furthermore, we made no distinction between the types of drug coating (e.g. paclitaxel, sirolimus, or everolimus) used for DES, even though this may affect clinical outcomes.
Lastly, the latest guideline on myocardial revascularisation [ 25] concluded that the newer generation DES have improved safety outcomes including death, MI and stent thrombosis compared with early-generation DES and BMS. During this study, this guideline was not available and thus it is possible that stent choice might have been somewhat different if the new guidelines had been applicable; DES could be more frequently used. Furthermore, we did not focus on fully bioresorbable stents, which have promising clinical outcomes since they provide desirable transient vessel support without compromising the restoration of normal vessel biology, vessel imaging or treatment options in the long run [ 26]. Consequently, the stents evaluated in the Circulating Cells cohort may not reflect the stent choices that will be made in the near future.

Recommendations

This study showed the existence of treatment variation across hospitals that may have an impact on long-term outcomes. It would be interesting to investigate if the treatment variation seen in this cohort will actually lead to differences in long-term outcomes and costs, which could be achieved by increasing the follow-up period. Van der Sijde et al. [ 27] have also emphasised the role of clinical observations to determine the most appropriate indication for specific types of stents.

Conclusions

This study showed that several clinical factors were associated with stent choice (DES or BMS) for CAD treatment, including diabetes, smoking, NYHA class, multi-vessel disease and previous PCI. In general, it appears that patients receive the most optimal stent given their clinical characteristics. After correcting for the clinical factors, stent choice was also associated with the treating hospital probably due to operator variation and the availability and supply of specific stent types. These differences may lead differences in long term outcomes.
Financial support
This work was supported by unrestricted grants from the Center for Translational Molecular Medicine (CTMM), Circulating Cells project (grant 01C-102) and the Dutch Heart Foundation.

Conflicts of interest

The authors have no conflicts of interest to declare.
Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.

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