Clinical Trial Details
— Status: Completed
Administrative data
NCT number |
NCT01166685 |
Other study ID # |
BPII |
Secondary ID |
|
Status |
Completed |
Phase |
Phase 4
|
First received |
July 19, 2010 |
Last updated |
June 4, 2014 |
Start date |
April 2010 |
Est. completion date |
May 2014 |
Study information
Verified date |
June 2014 |
Source |
University Hospital, Basel, Switzerland |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
Switzerland: Ethikkommission |
Study type |
Interventional
|
Clinical Trial Summary
Background:
Retrospective analyses of long-term BASKET findings identified patients with large
drug-eluting stents (DES) (>2.5mm Stents) as patients at risk for late cardiac
death/nonfatal myocardial infarction. In view of new DES with absorbable polymers and new
bare metal stents BMS) with thin struts and biocompatible polymers, BP-II will be launched
to test their comparative clinical safety up to 12 years if treated with an
aspirin/prasugrel combination, since prasugrel halved stent thrombosis rates compared to
clopidogrel in a large ACS trial.
The primary objective is to demonstrate non-inferiority of the Nobori DES stent compared to
the Xience Prime DES stent on safety and e cacy in patients requiring stents >=3.0mm in
diameter on the background of contemporary dual antiplatelet therapy (DAPT) with prasugrel
and aspirin
Set-up:
Multicenter open-label randomized trial.
Patient inclusion:
Unselected series of patients in need of large (>3mm) stents only in native vessels
irrespective of clinical indication.
Patient exclusion:
In-stent restenosis, Left-main disease, cardiogenic shock, planned surgery <12months,
increased bleeding risk, no compliance expected, History of stroke or transient ischemic
attack (TIA).
Randomization:
By centre using sealed envelopes 1:1:1: Nobori:Xience Prime:Prokinetik-stent.
Description:
Background and Study Design
The study is a multicentre, prospective, randomized, open-label trial comparing safety and
efficacy of the NoboriĀ® drug-eluting stent (DES), the Xience PrimeĀ® DES, and the ProKineticĀ®
bare-metal stent (BMS) in patients at low risk of restenosis, i.e. receiving stents >=3.0mm
diameter only, on the background of contemporary antiplatelet therapy.
2289 patients were recruited at 8 centres in 5 countries and randomized 2:1 to DES or BMS,
and 1:1 to either DES subgroup. Randomization was stratified according to centre.
Analysis Datasets
The full analysis set (FAS) will include all randomized patients of whom written informed
consent was obtained. Patients needing an urgent PCI were asked for oral consent prior to
the percutaneous coronary intervention (PCI) and for written informed consent afterwards.
This means that some randomized patients gave oral but not written informed consent.
Patients who gave oral informed consent and died before written informed consent could be
obtained will be included in the FAS. All other patients without signed informed consent
will be excluded regardless of oral informed consent. In accordance with the
intention-to-treat principle all patients will be analysed according to the allocated
treatment group.
The per-protocol set (PPS) will include only those patients from the FAS who did not have
one of the following major protocol violations:
- inclusion criteria not met
- exclusion criteria met
- procedures performed that were not approved by Institutional Review Board (IRB)/Ethics
Committee (EC)
- no study stent (Nobori,Xience Prime or ProKinetic) received
- only stents < 3mm in nominal size, provided that the maximum vessel size measured
during the procedure was <2.75mm
- undergoing multiple step procedure with a different stent received than randomised for
the second or subsequent step.
Inclusion of patients older than 75 years was not approved by the local ethics committee of
the Canton St.Gallen, Switzerland, and consequently, age > 75 years was added to the
exclusion criteria for the center Cantonal Hospital St. Gallen. Patients who did not receive
the randomly allocated stent, but another study stent according to the study protocol, will
be included and analysed according to the stent received (per protocol analysis).
Demographic and Baseline Characteristics
Demographic and baseline data will be presented for each treatment arm using the FAS.
Continuous variables will be presented as mean, standard deviation, median, 1st and 3rd
quartile. Categorical variables will be presented as frequencies and percentages.
Comparisons of continuous data will be done using a non-parametric Kruskal-Wallis rank sum
test. Comparisons of categorical data will be done using a chi-squared test if the expected
number of observations in each cell exceeds 5 - otherwise Fisher's exact test will be
applied.
Primary Objective
The primary objective is to demonstrate non-inferiority of the Nobori DES stent compared to
the Xience Prime DES stent on safety and efficacy in patients requiring stents >=3.0mm in
diameter on the background of contemporary dual antiplatelet therapy (DAPT) with prasugrel
and aspirin.
Primary Endpoint
The primary endpoint is the time to the first major adverse cardiac event (MACE) observed
within 24 months. MACE is a composite endpoint including cardiac death, myocardial
infarction (MI) and target-vessel revascularization (TVR).
Statistical Hypothesis, Model and Method of Analysis
Statistical Hypothesis
The statistical null-hypothesis is that Nobori DES is inferior to Xience Prime DES regarding
the MACE rate (pi) at 24 months when using a prespecified non-inferiority margin (delta), in
terms of absolute risk difference:
H0 : pi_Nobori - pi_XiencePrime >= delta
The alternate hypothesis is that the e ect of Nobori DES is non-inferior to Xience Prime DES
using the same non-inferiority margin as above.
alternate hypothesis (HA) : pi_Nobori - pi_XiencePrime < delta
We will use a non-inferiority margin of 3.8 % absolute risk difference. The sample size
calculation was based on delta = 3.8 %, assuming a MACE rate in the Xience Prime arm of 7.6
%, as observed in the BASKET-PROVE (BP) trial, for both DES (Kaiser et al., 2010). The
stated non-inferiority margin considers a 50 % relative excess of events or more in the
Nobori DES arm as inferior. This threshold is similar to that of the LEADERS trial
(Windecker et al., 2008).
Statistical Model and Method of Analysis
The absolute risk difference of MACE at 24 months between the Nobori DES and the Xience
Prime DES will be compared to the non-inferiority margin, using a two-sided 95 % confidence
interval (CI) applying a continuity-corrected modification of the Wilson's score method
(Newcombe, 1998). Non-inferiority will be declared if the upper limit of the 95 % CI of the
absolute risk difference does not exceed delta. The probability of MACE within 24 months
will be calculated and graphically visualized using the Kaplan-Meier estimator.
We will estimate the hazard ratio of the Nobori DES versus the Xience Prime DES using Cox
proportional hazards (PH) survival analysis, allowing to test for superiority if
non-inferiority can be established. The model will contain the factor "stent type" (Nobori
DES vs. Xience Prime DES) and be stratified according to the variable "centre". Hazard
ratios will be presented with the corresponding 95 % CI.
The proportional hazards assumption will be assessed in two steps: 1) Visually through
log-log curves and 2) Testing Schoenfeld's residuals for time-dependency. In case of
non-proportional hazards a time-independent logistic regression model will be used to
analyze the incidence of the primary endpoint within 24 months as binary variable.
An additional landmark analysis will be performed for the time-intervals 0-12 months and
12-24 months. We will t a time-strati ed Cox PH model, including an interaction term between
the factor "stent type" and time-interval (0-12 vs. 12-24 months). The interaction term will
be compared to the null hypothesis of no-interaction using a log-likelihood ratio test.
The analyses are performed on the PPS (but see sensitivity analyses). All tests will have a
two-sided significance level, alpha, of 0.05.
Handling of Data and Missing Values
Data will be analysed for potential extreme outliers. If present, each outlier will be
investigated. However, outliers will be included in the analysis, except if a clinical cause
can be excluded. There will be no missing values for the primary endpoint since losses to
follow-up can be incorporated in the Cox proportional hazards models by censoring the time
observed at the last follow-up/last contact date (right censoring).
Sensitivity Analyses
S1: All analyses will be repeated for the FAS. It is important to note that for
non-inferiority analyses, estimates from intention-to-treat analyses are less conservative,
i.e., more likely to establish non-inferiority than those from per-protocol analyses, since
differences may be blurred by including patients with major protocol violations.
S2: In the Cox PH model described for the primary endpoint, we will test for an interaction
between "stent type" and "centre" using a log-likelihood ratio test. A significant
interaction means differences in treatment-effect across centres. This will determine
whether the treatment-effect was homogeneous, which is important for the interpretation of
results.
S3: In case of non-proportional hazards, time-independent analyses using logistic regression
will be performed for the prespecified time-periods 0-12 months and 0-24 months.
Subgroup Analyses
We will investigate the effect of Nobori DES versus Xience Prime DES across the following
prespecified subgroups:
1. Diabetes (yes vs. no).
2. Acute coronary syndrome (ACS, ACS vs. stable coronary artery disease).
3. Stent length per segment.
4. At least one stent <3.0mm received (yes vs. no).
5. More than one stented segment (yes vs. no).
6. Prior myocardial infarction (yes vs. no).
7. Smoking current (yes vs. no).
8. Gender (female vs. male)
Interaction terms between the factor "stent type" and each of the above factors will be
included in the Cox regression model, together with the main effects of "stent type" and the
respective factor, and compared to the null hypothesis of no-interaction using a
log-likelihood ratio test. A significant interaction means that the effect of treatment
differs between subgroups.
Secondary Objectives
A1: To demonstrate superiority of the Nobori DES over the ProKinetic BMS in terms of MACE
within 24 months. This comparison will also act as an internal control for the
non-inferiority analysis (primary objective), with the ProKinetic BMS as a putative placebo.
A2: To compare the Nobori DES to the ProKinetic BMS, and the Nobori DES to the Xience Prime
DES in terms of late harm (cardiac death, MI and stent thrombosis from month 12-24).
B: To compare the Nobori DES to the Xience Prime DES, and the Nobori DES to the ProKinetic
BMS in terms of additional secondary endpoints.
C: To investigate the safety - or possible harm - of DAPT with prasugrel and aspirin in
patients with stable coronary artery disease (CAD) versus acute coronary syndromes (ACS)
regarding bleeding events.
D: To assess the effect of DAPT with aspirin plus prasugrel versus aspirin plus clopidogrel
as used in a historical comparator cohort with BASKET-PROVE (BP).
Secondary Endpoints
1. Components of the primary endpoint.
- Cardiac death
- Myocardial infarction (MI)
- Any MI
- Non-fatal MI
- Target vessel revascularization (TVR)
- Any TVR
- Non-MI related TVR
2. Composite safety endpoint of cardiac death and non-fatal MI.
3. Stent thrombosis according to ARC definitions.
- Definite
- Definite or probable
- Definite, probable or possible
4. Major bleeding including fatal bleeding, i.e., BARC >=3.
5. All cause death.
6. Net clinical benefit = Primary endpoint plus major bleeding.
Statistical Hypothesis, Model and Method of Analysis
[A1] Nobori DES versus ProKinetic BMS: MACE within 24 months
The statistical null hypothesis is that there is no difference between Nobori DES and
ProKinetic BMS in terms of MACE. The Cox PH model described for the primary end-point which
includes the factor "stent type" now compares Nobori DES to ProKinetic BMS. In case of
non-proportional hazards a logistic regression model will be used to analyze the incidence
of MACE within 24 months.
[A2] Nobori DES versus ProKinetic BMS, and Nobori DES versus Xience Prime DES: Late harm
The statistical null hypothesis is that there is no difference between Nobori DES and
Prokinetic BMS, and no difference between Nobori DES versus Xience Prime DES in terms of
late harm. We will use a Cox PH model, landmark analysis and a time-strati ed Cox PH model
(for the time-intervals 0-12 months and 12-24 months), as described in for the primary
objective, for the endpoints cardiac death, non-fatal MI and stent thrombosis. Assessment of
the proportional hazards assumption will be performed in accordance to the method described
for the primary endpoint. In case of non-proportional hazards, logistic regression models
will be used to analyze the incidence of events.
[B] Nobori DES versus ProKinetic BMS, and Nobori DES versus Xience Prime DES: Other
secondary endpoints
The statistical null hypothesis is that there is no difference between Nobori DES and
ProKinetic BMS, and Nobori DES and Xience Prime DES in terms of secondary endpoints. All
secondary endpoints 1-6 will be analysed using Cox PH models including the factor "stent
type" and strati ed according to "centre" for events within 24 months - as specified for the
primary endpoint. Assessment of the proportional hazards assumption will be performed in
accordance to the method described for the primary endpoint. In case of non-proportional
hazards, logistic regression models will be used to analyze the incidence of events.
Landmark analyses at 0-12 and 12-4 months will be performed. Absolute probabilities of the
event of interest will be calculated and graphically visualized using the Kaplan-Meier
estimator. Subgroup analyses as specified for the primary endpoint will be performed for all
secondary endpoints.
[C] Safety of DAPT with prasugrel and aspirin in patients with stable CAD regarding bleeding
events
For this analysis we will generate four subgroups based on stent type (DES vs. BMS) and
indication: 1) DES+Stable CAD, 2) DES+ACS, 3) BMS+Stable CAD, and 4) BMS+ACS. The endpoints
major bleeding (BARC >=3), MACE (including its components), and stent thrombosis (see
definitions in Section 5.1) will be analysed using Kaplan-Meier curves and a Cox PH model
including the above groups as the 4-level factor "indication-by-stent type" and the
stratifying factor "centre". Thereby, we will make the following comparisons: a) DES-ACS vs.
DES-stable CAD, b) BMS-ACS vs. BMS-stable CAD, and c) DES-stable CAD vs. BMS-stable CAD. In
case of non-proportional hazards, the survival analysis will be complemented by a
time-independent logistic regression analysis on major bleeding events at 24 months as well
as at a cut-o point of 12 months.
[D] Comparison between BP II and BP regarding DAPT with prasugrel plus aspirin versus
clopidogrel plus aspirin
Two separate comparisons between trials will be made in terms of major bleeding events (BARC
>=3), MACE (including its components), and stent thrombosis (see definitions in Section
5.1), using the FAS from both trials (BP: as presented in Kaiser et al. (2010)):
Comparison 1
DAPT (12 months duration) with prasugrel and aspirin in DES patients (BP II) versus DAPT (12
months duration) with clopidogrel and aspirin in DES patients (BP).
The statistical null-hypothesis is that there are no differences in rates of major bleeding
events between DAPT treatment with prasugrel plus aspirin (as in BP II) versus clopidogrel
plus aspirin (as in BP) in patients treated with DES. The endpoint major bleeding (BARC >=3)
will be compared between all DES patients in BP II and all DES patients in
BP using a Cox PH model. Because patient populations come from two different trials rather
than from one single randomised trial, a propensity score weighted analysis will be used to
balance the data for confounding effects. The predictors for the calculation of propensity
scores will include potential confounders, i.e., variables that may affect the treatment
(DAPT as determined by trial) as well as the outcome (occurrence of bleeding events) such
as: age, sex, body weight, renal function, hypertension, diabetes, prior MI, etc. We will
use inverse probability weighting (Hernan & Robins, 2006) to estimate the e ect of "DAPT" on
the hazard of bleeding. The Cox PH model will include "DAPT" (prasugrel vs. clopidogrel) and
"indication" (stable CAD vs. ACS) as predictors. In addition, the model will include the
interaction between "DAPT" and "indication", to test whether the difference due to type of
DAPT depends on indication. Hazard ratios along with corresponding 95 % CI will be
presented. If the two DES in BP II (Nobori and Xience Prime) should differ with regard to
bleeding events, MACE and stent thrombosis, we will also include "stent type" as predictor
(Cypher and Xience in BP were very similar).
Comparison 2
DAPT with prasugrel and aspirin (1 month duration) (BP II) versus DAPT with clopidogrel and
aspirin (12 months duration) (BP) in stable CAD patients with BMS.
The statistical null-hypothesis is that there are no differences in rates of major bleeding
events between DAPT treatment with prasugrel plus aspirin (as in BP II) versus clopidogrel
plus aspirin (as in BP) in stable CAD patients treated with BMS. The endpoint major bleeding
(BARC >=3) will be compared between stable CAD patients with BMS from BP II and stable CAD
patients with BMS from BP using a Cox PH model. As for comparison 1 a propensity score
weighted analysis will be performed, and an inverse probability weighting used to estimate
the effect of "DAPT" on the hazard of bleeding. Hazard ratios along with corresponding 95 %
CI will be presented.
General
In case of non-proportional hazards, the survival analysis will be complemented by a
time-independent logistic regression analysis on bleeding events at 12 and 24 months,
estimating odds ratios instead of hazard ratios.
5.3 Handling of Data and Missing Values
Data will be analysed for potential extreme outliers. If present, each outlier will be
investigated. However, outliers will be included in the analysis, except if a clinical cause
can be excluded. In case of missing values for secondary endpoints, all available values
will be used and no imputation of missing values will be performed.
References
Hernan, M. A. & Robins, J. M. 2006: Estimating causal e ects from epidemiological data. J
Epidemiol Community Health 60:578-586.
Kaiser, C.; Galatius, S.; Erne, P.; Eberli, F.; Alber, H.; Rickli, H.; Pedrazzini, G.;
Hornig, B.; Bertel, O.; Bonetti, P.; De Servi, S.; Brunner-La Rocca, H.-P.; Ricard, I. &
Pfisterer, M. 2010: Drug-eluting versus bare-metal stents in large coronary arteries. New
England Journal of Medicine 363:2310-2319.
Newcombe, R. G. 1998: Interval estimation for the difference between independent
pro-portions: Comparison of eleven methods. Statistics in Medicine 17:873-890.
Windecker, S.; Serruys, P. W.; Wandel, S.; Buszman, P.; Trznadel, S.; Linke, A.; Lenk, K.;
Ischinger, T.; Klauss, V.; Eberli, F. et al. 2008: Biolimus-eluting stent with
biodegrad-able polymer versus sirolimus-eluting stent with durable polymer for coronary
revascularisation (leaders): a randomised non-inferiority trial. The Lancet
372(9644):1163-1173.
Clinical Relevance:
The results of BPII will provide evidence for the performance of the newest-generation
stents on the market in daily practice and insights about the efficacy and safety of current
stent designs in an all-comer population. Moreover, BPII will assess the performance of DAPT
with aspirin and prasugrel compared with aspirin plus clopidogrel in terms of ischemic and
bleeding endpoints. - Thus, these findings should have major impact on the current use of
coronary stents, medical antiplatelet therapy regimes and our understanding of possible
reasons for late stent thrombosis.
Other known NCT identifiers