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(Circulation. 2005;111:321-327.)
© 2005 American Heart Association, Inc.
Interventional Cardiology |
From the Brigham and Womens Hospital (L.M., E.J.O., R.E.K.), Harvard Medical School (A.J.O., L.M., E.J.O., R.E.K., D.E.C.), and Harvard Clinical Research Institute (L.M., R.E.K., D.E.C., C.S.), Boston, Mass; Lenox Hill Heart and Vascular Institute (J.W.M., M.B.L.), New York, NY; Mayo Clinic (D.R.H.), Rochester, Minn; Scripps Clinic (P.S.T.), La Jolla, Calif; Center for Cardiology and Vascular Intervention (J.S.), Hamburg, Germany; Department of Cardiology and Angiology (G.B.), University Hospital, Münster, Germany; Beth Israel Deaconess Medical Center (D.E.C.), Boston, Mass; Ohio Heart Health Center (D.J.K.), Cincinnati, Ohio; and Cordis Corporation (B.G.F., D.J.D.), Warren, NJ.
Correspondence to Richard E. Kuntz, MD, MSc, BC-3-012N, Brigham and Womens Hospital, 75 Francis St, Boston, MA 02116. E-mail rkuntz{at}partners.org
Received August 2, 2004; revision received September 26, 2004; accepted October 28, 2004.
| Abstract |
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Methods and Results Late loss (postprocedural minimum lumen diameter minus 8-month minimum lumen diameter) was measured in the angiographic cohorts of the SIRIUS (n=703) and E-SIRIUS (n=308) trials. Two techniques, the standard normal approximation and an optimized power transformation, were used to predict binary angiographic restenosis rates and compare them with observed restenosis rates. The mean in-stent late loss observed in the SIRIUS trial was 0.17±0.45 mm (sirolimus) versus 1.00±0.70 mm (control). If a normal distribution was assumed, late loss accurately estimated in-stent binary angiographic restenosis for the control arm (predicted 35.4% versus observed 35.4%) but underestimated it in the sirolimus arm (predicted 0.6% versus observed 3.2%). Power transformation improved the reliability of the estimate in the sirolimus arm (predicted 3.2% [CI 1.0% to 6.7%]) with similar improvements in the E-SIRIUS trial (predicted 4.0% [CI 1.2% to 7.0%] versus observed 3.9%). In the sirolimus-eluting stent arm, in-stent late loss correlated better with target-lesion revascularization than in-segment late loss (c-statistic=0.915 versus 0.665).
Conclusions Because distributions of late loss with a low mean are right-skewed, the use of a transformation improves the accuracy of predicting low binary restenosis rates. Late loss is monotonically correlated with the probability of restenosis and yields a more efficient estimate of the restenosis process in the era of lower binary restenosis rates.
Key Words: angioplasty stents restenosis
| Introduction |
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1000 subjects.59
In contrast, several recent drug-eluting stent (DES) trials have demonstrated a breakthrough in the reduction of late restenosis compared with bare metal stents, with a consistent incidence of BAR and TLR below 10%.10,11 Even with the achieved low rates, which may underestimate the rate in actual practice or in high-risk groups,1217 cost-effectiveness analysis provides economic and quality-of-life incentives to distinguish therapies with restenosis rates below 10%.18 However, the statistical power available to determine superiority (or demonstrate noninferiority) in competing DES treatments is markedly reduced when sample sizes of 2000 subjects or less are used. A reevaluation of continuous restenosis metrics as discriminators between competing DES therapies is necessary, especially for underpowered pilot (50 to 150 subjects) and pivotal (
1000 subjects) trials. The traditional angiographic variables, late MLD and percent diameter stenosis, are powerful continuous measures, but late loss (postprocedural MLD minus 8-month MLD) has the unique ability to distinguish the magnitude of late intimal renarrowing from baseline and procedural variables (reference vessel diameter and residual stenosis). We sought to evaluate the reliability of late loss in providing a monotonic (nondecreasing) metric of antirestenosis effect and its ability to predict relative measures of restenosis in the DES era.
| Methods |
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The first 850 patient observations from the SIRIUS trial, the 8-month angiographic follow-up cohort, were used to develop the late-loss models (prediction cohort; complete follow-up in 703 patients). The 353-patient E-SIRIUS trial required 8-month follow-up in all subjects (completed in 308 subjects) and was used as the test cohort for the late-loss models generated from the SIRIUS study. Further predictions of relative restenosis based on late-loss estimates were made for the TAXUS (TAXUS Express Paclitaxel-Eluting Stent for Treatment of De Novo Lesions) IV trial.11
Angiographic Analysis
Standard image acquisition was performed at the clinical sites as described previously.10,19 Cineangiograms for both trials were forwarded to the Brigham and Womens Hospital Angiographic Core Laboratory for review by observers blinded to the treatment assignment.
All procedural and follow-up angiograms were reviewed with standard morphological criteria.2022 Quantitative angiographic analysis was performed with a validated automated edge-detection algorithm (Medis CMS).23 A 5-mm segment of reference diameter proximal and distal to the stenosis was used to calculate the average reference vessel diameter. MLDs were measured within the stent (in-stent analysis) and within the segment including 5 mm proximal and distal to the stent margins (in-segment analysis).23a
Definitions
Late loss was defined as the MLD immediately after the procedure minus the MLD at 8-month follow-up. Percent diameter stenosis was defined as [1(MLD/reference vessel diameter)x100]. BAR was defined as a >50% diameter stenosis at follow-up. Lesion length was defined as the axial extent of the lesion that contained a shoulder-to-shoulder lumen reduction by
20%. TLR was defined as clinically driven revascularization of the target lesion by 9 months of follow-up and was adjudicated by an independent Clinical Events Committee.
Statistical Analysis
Ordinal variables are expressed as frequencies, and continuous variables are expressed as mean±SD. Binary variables were compared with
2 analysis, and continuous variables were evaluated with the Students t test. A 2-sided probability value
0.05 was considered significant. Statistical analyses were performed in SAS (version 8.2) unless otherwise noted.
Prediction of Angiographic Restenosis Rate From Late Loss
The normality of the distributions of late loss (in-stent and in-segment) were tested in each arm (active and control) of the SIRIUS trial with the Kolmogorov-Smirnov test. The fit of other parametric distributions (Gamma, Weibull) and the following transformations of late loss were examined systematically: log, square root, log normal, log-logistic, and power. The power-transformation procedure was the most flexible in transforming the late-loss distribution. The BOXCOX procedure (STATA) was used to screen the fit of the power transformation, then the optimum power (ranging from 0 to 1) was selected to predict the BAR rate observed in each arm of the SIRIUS trial (prediction cohort). The new transformed mean and SD were computed to correct for the rightward skew of the data (see online-only Data Supplement Appendix).
Predicted BAR rates were computed for the standard (normal assumption with the expected value of late loss required to result in a >50% diameter stenosis) and transformed methods and compared with the observed BAR rates for SIRIUS and E-SIRIUS (the test cohort) trials. Confidence intervals (2-sided, 95%) were obtained by simulating 1000 bootstrap samples.24 Percent error was defined as 100 times the difference between the observed rate and the predicted rate divided by the observed rate. Finally, we applied a simple interpolation of the published in-stent late-loss result in the active arm of the TAXUS IV trial11 between the active and control arms of the SIRIUS trial to yield a power-transformation value for TAXUS IV.
Correlation of Late Loss With Clinical Restenosis
The ability of late loss to predict clinical restenosis in the SIRIUS trial was examined with logistic regression models of TLR as the outcome variable and either in-stent or in-segment late loss as the dependent variable. The c-statistic was measured and compared for each (1.0 signifying perfect accuracy).
| Results |
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Late Loss Is Not Normally Distributed
The distribution of both in-stent and in-segment late loss was not normal for either arm of the trial (in-segment late loss: P<0.01 sirolimus, P<0.01 control; in-stent late loss: P<0.01 sirolimus, P=0.047 control), and the magnitude of right skewness (from a normal distribution where skew=0) was greatest in the sirolimus arm (in-segment late-loss skewness: 0.89 sirolimus, 0.43 control, in-stent: 1.23 sirolimus, 0.32 control; Figures 1 and 2
). Power transformation of in-stent late loss is the optimum method to predict BAR rates from mean late loss.
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Compared with other transformations and nonnormal distributions, the 0.13 power transformation, ie, (late loss)0.13, was the optimum for restoring normality of the right tail of in-segment late loss in the active arm, and the 0.52 power transformation, ie, (late loss)0.52, was the optimum for the control arm. For in-stent late loss, the optimum powers were 0.13 for the active arm and 0.99 for the control arm. The in-segment and in-stent late-loss power transformations were then applied to predict BAR rates. The transformed and nontransformed predictions for both SIRIUS (prediction set) and E-SIRIUS (test set) were compared with the observed rates (Table 2).
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Predictions based on the normal assumption underestimated restenosis rates in the active arms of SIRIUS and E-SIRIUS trials because of the lack of compensation for right-skewed late-loss distributions. For the SIRIUS trial, the active arm in-stent binary restenosis rate was underestimated by 81% (0.6% predicted rate compared with 3.2% observed rate), and the active in-segment binary restenosis rate was underestimated by 38% (5.5% predicted rate compared with 8.9% observed rate). Similarly, in the test cohort (E-SIRIUS), the transformed active-arm predictions matched better with the observed rates (Table 2). Transformed in-stent late loss was the most predictive of the E-SIRIUS observed BAR rates compared with in-segment transformed late loss and both in-stent and in-segment nontransformed late loss.
In-Stent Late Loss Is Correlated With TLR
We compared predictive models of TLR using in-stent and in-segment late loss. In the active arm, in-stent late loss was a more reliable predictor of TLR (c-statistic 0.915, versus 0.665 for in-segment), whereas TLR from the control arm was similarly predicted from in-stent or in-segment late loss (c-statistic 0.897 versus 0.916, respectively).
Predicting Restenosis Rates for Other DES Systems With In-Stent Late Loss
The optimum transformation power for prediction of BAR from late loss depends on the mean late loss, which varied from 0.13 mm in the active SIRIUS arm to 0.99 mm in the control arm. Interpolation of an in-stent late loss of 0.39 mm observed in the active arm of the TAXUS IV trial11 yielded a power-transformation parameter of 0.36. The published mean reference vessel diameter of 2.75 mm and postprocedural MLD of 2.66 mm in-stent were then used to predict the in-stent BAR rate. With the in-stent late-loss normal approximation (standard method), the predicted in-stent BAR was 3.7%, an underestimate of 39% compared with the observed in-stent BAR rate of 5.5%. The in-stent late-loss transformation approximation, on the other hand, predicted an in-stent BAR rate of 6.1%, an overestimate of only 10% (Figure 3).
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| Discussion |
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The evaluation of restenosis in the DES era is more complex. In the SIRIUS and TAXUS experience, binary angiographic and clinical restenosis rates are below 10%,10,11 which makes comparisons between competing DES treatments more difficult with sample sizes below 1000 to 2000 subjects. Moreover, the initial evaluation of future candidate DES will likely rely on smaller dose-finding studies of fewer than 100 subjects per test group, in which the infrequent binary restenosis end points will be too insensitive to be effective discriminators.
In the present study, we have evaluated late loss as a potential gauge of restenosis in the DES era. First, in the DES era, in which mean late loss is often a fraction of its SD, right skewness can be overcome with power transformation to allow accurate approximation of BAR rates. Second, late loss is correlated with restenosis: The models in the present study show a monotonic (nondecreasing) relationship between higher late loss and higher restenosis rates in the 2 SIRIUS trials studied, as well as the indirect prediction of the TAXUS IV restenosis rate. Third, in-stent late loss showed a better correlation with TLR than in-segment late loss for the DESs studied. With these robust features, in-stent late loss is a sensitive indicator of restenosis propensity.
Late loss was initially developed as a tool to compare the mechanisms of restenosis between different coronary interventions such as balloon angioplasty, stenting, and atherectomy.28 Within stents, late loss is an absolute measure of neointimal renarrowing, with vascular contraction being prevented by the stent framework.29,30 In-stent neointimal renarrowing, however, is still only 1 factor that determines the probability of restenosis, which is also influenced by the vessel diameter. Commonly reported measures of relative restenosis include percent diameter stenosis and BAR rates. In the pre-DES era, among coronary devices, stents had the lowest relative restenosis but, paradoxically, also had the highest late loss.25 As a result, comparisons of different mechanical percutaneous interventions (angioplasty, stents, atherectomy) relied on relative measures of restenosis. In the case of similar mechanical interventions, however, such as stents with similar acute gains, the need for relative adjustments is reduced, and late loss may be a valuable tool to gauge antirestenosis effect.
Late Loss and Its Skewed Distribution for DESs
With bare metal stenting, late loss has been observed to follow a near-normal distribution.1,31 Bare metal stent trials and registries have demonstrated mean late losses varying from 0.6 to 1.2 mm.5,6,26,27,3235 The RAVEL trial of the sirolimus-eluting Bx Velocity stent was the first randomized trial to report a stent with an average late loss well below the expected historical range, as well as its own control arm (in-stent late loss 0.01 mm active versus 0.80 mm control), which corresponded to a BAR rate of 0% for the active arm versus 26% in the control arm.36
As the positive mean of any normal distribution is reduced enough so that its spread becomes significantly bounded by zero, it becomes right-skewed. The distribution of late loss for bare metal stents is only marginally skewed by zero. In the case of the sirolimus-eluting stent, however, for which the mean late loss has ranged between 0.01 and 0.24 mm, the late-loss distributions studied are markedly deviated from normal and skewed to the right. In such skewed distributions, the variance, as estimated from the sample SD, no longer accurately denotes the deviation from the mean. If the calculated SD is used to predict binary event rates in this right tail, the predicted binary rates will be underestimated (Figure 4). To accurately study the behavior of such a distribution, either transformation or selection of a distribution that more closely resembles the skewed data becomes necessary rather than reliance on traditional normal methods. The power transformation used in the present study restored a more predictable normal distribution and demonstrated a monotonic relationship between late loss and restenosis.
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In-Stent Versus In-Segment Late Loss
Whereas in-stent measurements of follow-up MLD have been relied on for the evaluation of virtually all bare metal stents to date,5,6,37 the observation of an exuberant renarrowing at the margins of stents, despite a therapeutic effect within the stent observed in early brachytherapy trials38 and some pilot DES trials,39 termed "edge effect" or "candy-wrapper restenosis," led to inclusion of the zones proximal and distal to the stent for analysis. When the binary variable angiographic restenosis is used, the more inclusive in-segment analysis has the attractive ability to capture events that occur only at the edges, whereas the in-stent analysis does not.
In the present examination of late loss, we also sought to determine whether the in-stent or in-segment analysis was more reliable. We found that for the control arm, in-stent and in-segment analyses were essentially equivalent, with similar c-statistics for predicting TLR. However, in the sirolimus-eluting stent arm, in-stent late loss was much better correlated with TLR than was in-segment late loss.
Ideally, an angiographic measure of neointimal renarrowing would represent the magnitude of maximum change in lumen diameter from the time of stenting to the follow up angiogram across the treatment site and margins. Such a measurement would require a comparison across the 2 time points slice by slice along the length of the vessel, within matched, fine (
1 mm) increments. Practically, however, standard techniques of measuring late loss have compared MLDs from a specified zone. The in-stent late-loss calculation compares MLDs both from within the stented zone. The in-segment late-loss calculation compares the minimum of the proximal, distal, and stent zone diameters (in-segment MLD) after stenting and at late follow-up, rather than the maximum late loss from these zones. Thus, the in-segment calculation has the possibility of comparing different regions rather than representing the maximum late loss from among the zones evaluated. Because the greatest acute gain and late loss are usually within the stented zone, the in-segment postprocedural MLD will tend to be measured outside of the stented zone and the follow-up MLD within the stented zone, such that in-segment late loss will necessarily underestimate the maximum late loss (within the stent). In the absence of an edge effect,10,19,36 it is not surprising that the in-stent late-loss measurement best reflects the likelihood of clinical restenosis. The difference in c-statistics for in-stent compared with in-segment late loss reflects the better correlation of in-stent late loss with the probability of TLR when sirolimus-eluting stents are used.
Other Continuous Absolute and Relative Angiographic End Points
Two other angiographic variables should be considered as alternatives: an absolute measure of restenosis, late MLD, and a relative measure of restenosis, late percent diameter stenosis. These continuous measures are correlated with restenosis. The unique advantage of late loss is the ability to distinguish the magnitude of late intimal renarrowing from baseline and procedural variables such as reference vessel diameter and residual stenosis. Whereas percent diameter stenosis is directly linked to the likelihood of target-vessel revascularization in a given patient, late loss isolates the neointimal hyperplasia component of the restenosis process for a given DES.
Clinical Implications for In-Stent Late Loss
Proper binary restenosis rate estimation from late loss requires mathematical transformation of the data, because traditional extrapolation will diminish the actual differences in binary restenosis rates for any 2 comparable values of late loss. This underestimation error is most pronounced at low restenosis rates where current DES clinical trials range. This method of transformation will require future validation as additional DES studies are published. Although higher late-loss values correlate positively with higher restenosis rates, to what extent small differences in late loss are clinically meaningful between comparative DES systems may be more difficult to answer. These small differences may have the most important effects in high-restenosis-risk groups.
Study Limitations
Although vessel diameter may have a smaller effect on late loss than on relative measures of restenosis, such as other restenosis end points, late loss is best used to compare stents between groups that have similar acute gain, lesion lengths, and diabetes prevalence, as in a randomized, controlled trial. Finally, although in-stent late loss was most reliable for prediction of angiographic and clinical restenosis in sirolimus-eluting stents, analysis of the proximal and distal zones is still mandatory to detect edge effects when new DESs are studied.
| Conclusions |
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| Footnotes |
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The online-only Data Supplement, which contains an Appendix, can be found with this article at http://www.circulationaha.org.
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