Author + information
- Yasuhiro Honda, MD⁎ ( and )
- Peter J. Fitzgerald, MD, PHD
- ↵⁎Reprint requests and correspondence:
Dr. Yasuhiro Honda, Division of Cardiovascular Medicine, Stanford University Medical Center, 300 Pasteur Drive, Room H3554, Stanford, California 94305-5637
Over the past decades, a number of studies have searched the determinants of adverse events following stent implantation. Among several clinical, angiographic, and intravascular ultrasound (IVUS) variables identified in those reports, minimum stent area (MSA) as measured by IVUS is a consistent and powerful predictor for both angiographic and clinical restenosis (1). In fact, multiple clinical trials in the bare-metal stent (BMS) era have shown that IVUS-guided stent placement improves clinical outcomes as compared with angiographic guidance alone, primarily by achieving larger acute lumen gain while avoiding increased complications (1). However, controversial results were also reported in a few other BMS studies (2,3), presumably due to differing criteria for IVUS-guided optimal stenting as well as various adjunctive treatment strategies that were used in these trials in response to suboptimal results. Currently, there is a growing clinical demand for clarifying whether this paradigm learned from BMS remains important in the contemporary percutaneous coronary interventions, and, if so, whether an optimal procedural end point exists to achieve the best clinical outcomes following drug-eluting stent (DES) implantation.
Rationale for the Bigger-Is-Better Paradigm
In-stent restenosis is primarily due to excessive biological response within a stented artery—namely neointimal proliferation (4,5). This leads to the question, “Why is MSA, as a mechanical stent parameter, a strong determinant of restenosis?” It is easy to understand that stent underexpansion can result in flow-limiting lumen compromise even with minimal neointimal hyperplasia. However, this explanation does not fully clarify why achieving even larger stent area can further reduce the restenosis rate in BMS—the so-called bigger-is-better paradigm. To elucidate this mechanism, it is essential to understand the principle of this optimization strategy based upon the statistical profile of in-stent biologic response.
In statistical analysis of a given population, neointimal volume within BMS generally follows a near-Gaussian, bell-shaped frequency distribution around a mean value of 30% to 35% (Fig. 1). On its histogram, the mean value represents the overall biologic response to the stent, whereas the width of the distribution curve indicates the degree of lesion-to-lesion variation in arterial response to acute and/or chronic vessel injury (6). Restenosis, measured as a binary variable, corresponds to the area under the right end of the distribution curve beyond a threshold of neointimal proliferation. Mathematically, stents with larger MSA can afford a greater amount of neointima until reaching a flow-limiting stenosis. Therefore, any type of adjunctive mechanical strategy to achieve larger acute lumen gain reduces restenosis simply by raising this threshold (shifting the threshold toward the right) rather than changing the shape or location of the distribution curve itself. As a result, even in a range of adequate stent expansion, obtaining larger MSA continues to reduce restenosis until the threshold passes beyond the right tail end of the frequency curve of neointima.
Is Bigger-Is-Better Also Applicable to DES?
Apparently from the statistical model discussed above, the applicability of the conventional bigger-is-better strategy to a specific new stent device depends on the shape of the right tail end of the frequency distribution of neointima. For example, the bigger-is-better strategy (shifting the threshold toward the right) would continue to help reduce the restenosis rate (the area of the right tail end above the threshold) of stents with a relatively long tail-end distribution (i.e., large individual variation of neointimal proliferation). On the contrary, if a particular stent shows a skewed or deformed frequency distribution curve of neointima with a short right tail end (i.e., small individual variation), the benefit of achieving a larger acute gain beyond a certain point would be steeply diminished. It is important to note that, unlike BMS, significant biologic modification properties of current DES often result in a non-Gaussian frequency distribution (6). In such DES, the shape and width of the tail end may not be accurately predicted from the mean or median value of overall neointimal volume. Therefore, the applicability and relative benefit of the bigger-is-better optimization strategy needs to be judged individually in each DES, based upon its whole profile of biological response, rather than the representative antiproliferative effect expressed as the mean value of neointima (or late loss by angiography) reported in the literature.
Diagnostic Accuracy of MSA for Follow-Up Patency in DES Versus BMS
In this issue of JACC: Cardiovascular Interventions, Doi et al. (7) has extended our insights from an earlier series of IVUS studies with BMS and/or sirolimus-eluting stents (8–11) to patients treated with paclitaxel-eluting stents (PES). Using one of the largest-ever reported datasets of PES with IVUS interrogation, the study investigated the predictive value of post-intervention MSA on 9-month patency of PES versus BMS. As consistently observed in other stent studies, multivariate logistic regression analysis identified post-intervention MSA as the independent predictor of subsequent in-stent restenosis in both PES and BMS. With receiver-operator characteristic analysis, the optimal threshold of MSA that best predicted 9-month stent patency was reported as 5.7 mm2 for PES and 6.4 mm2 for BMS.
As discussed earlier using the statistical model, the diagnostic accuracy of MSA for follow-up lumen patency is a function of neointimal variability, rather than the average power of neointimal suppression. As an extreme theoretical example, if the lesion-to-lesion variation of neointimal proliferation is 0 (i.e., every patient develops the same amount of neointima), post-procedural MSA of this particular stent would predict follow-up lumen dimensions with 100% accuracy, regardless of the mean value of neointima. Conversely, even if a mean (or median) amount of neointima is small, MSA can poorly predict follow-up lumen patency in stents with relatively large lesion-to-lesion variations.
According to the results reported in the study by Doi et al. (7), the current PES—TAXUS Express and TAXUS Liberté (Boston Scientific, Natick, Massachusetts)—appear to have similar diagnostic performance of MSA, as compared with BMS with identical stent platforms. Whereas the overall antiproliferative effect of PES resulted in a smaller optimal threshold of MSA, the C statistic and odds ratio in predicting 9-month restenosis were virtually identical for PES and BMS, possibly indicating comparable degrees of neointimal variation across the lesions treated with PES versus BMS. Of note, the lower positive and higher negative predictive values of PES may have largely derived from the lower incidence of restenosis in the PES population, rather than possibly suppressed neointimal variability of PES versus BMS.
Optimal Diagnostic Threshold Versus Procedural End Point
Several investigator groups, including the authors of this editorial, have used receiver-operator characteristic analysis to evaluate the predictive value of MSA in various stenting devices (7–11). Unfortunately, however, the optimal diagnostic thresholds determined in those studies have often been misinterpreted by readers as optimal “procedural” end points (or criteria for optimal stent deployment). As also pointed out by Doi et al. (7), those terms are not equal, simply because to best predict the outcome is not the same as to predict the best outcome. Technically, a procedural end point cannot be determined using a cross-point of sensitivity and specificity curves, because the importance of those 2 diagnostic variables are not equivalent from a clinical perspective (detecting true restenosis is clinically more important than avoiding false-positive diagnosis). An ideal procedural end point should be a clinically reasonable agreement of MSA in maximizing the probability of long-term stent patency while minimizing increased risk of complications, if any.
There is compelling evidence that stent underexpansion is a significant contributor to the development of adverse events, regardless of the stent type (1,6,12–14). In a range of adequate stent expansion, however, the relative benefit of further obtaining larger MSA may significantly vary among DES, depending on its predictability (or lesion variability) of subsequent neointimal proliferation. Although the study by Doi et al. (7) was not intended to identify the criteria for optimal stent deployment, the current PES appear to benefit from a strategy of achieving larger MSA to ensure a greater “safety margin” for unexpectedly large neointimal proliferation occasionally developed during follow-up. Given the wide variety of clinical backgrounds, patient risk factors, lesion morphologies, and disease complexities that we routinely face in our clinical practice, it is unlikely that a single pre-specified MSA end point could be effectively applied to all target lesions. Nevertheless, the ability of IVUS to assess the result of stent implantation more precisely than angiography can significantly contribute to our clinical judgment for individual patients. A continuing scientific endeavor, as represented by the study by Doi et al. (7), needs to be mounted for better understanding of the biological heterogeneity, ultimately leading to definitive therapies via risk stratification of each target segment.
The authors are indebted to Brian K. Courtney, MD, MSEE, for his scientific and editorial advice.
↵⁎ Editorials published in JACC: Cardiovascular Interventions reflect the views of the authors and do not necessarily represent the views of JACC: Cardiovascular Interventions or the American College of Cardiology.
- American College of Cardiology Foundation
- Honda Y.,
- Fitzgerald P.J.,
- Yock P.G.
- Mudra H.,
- di Mario C.,
- de Jaegere P.,
- et al.
- Hoffmann R.,
- Mintz G.S.,
- Dussaillant G.R.,
- et al.
- Doi H.,
- Maehara A.,
- Mintz G.S.,
- et al.
- Hong M.K.,
- Mintz G.S.,
- Lee C.W.,
- et al.
- Sonoda S.,
- Morino Y.,
- Ako J.,
- et al.
- Fujii K.,
- Mintz G.S.,
- Kobayashi Y.,
- et al.
- Honda Y.,
- Fitzgerald P.J.