The Dyssynchrony in Predicting Response to Cardiac Resynchronization Therapy: A Call for Change

Editorial Comment

The Dyssynchrony in Predicting Response to Cardiac Resynchronization Therapy: A Call for Change Brandon K. Fornwalt, MD, PhD, Boston, Massachusetts

A BRIEF HISTORY OF PREDICTING RESPONSE TO CARDIAC RESYNCHRONIZATION THERAPY Thousands of articles have been published on cardiac resynchronization therapy (CRT) in patients with heart failure. Many of these articles focus on refining selection criteria for CRT to improve the rate of individual patient response, and arguably none have succeeded in improving clinical practice. The lack of standardization of both baseline predictors and outcome or ‘‘response criteria’’ is impairing progress in this field and must be addressed. Echocardiographic measures of dyssynchrony should undergo rigorous evaluation and comparison studies before testing their ability to help improve response to CRT. Additionally, a common end point to quantify ‘‘response to CRT’’ should be decided upon, as the many published end points do not agree with one another. The purpose of this editorial is to discuss these issues in the field of CRT research within the framework of an article showing that the oftenignored right ventricle may play a role in improving CRT for patients with heart failure. Much-needed studies to address shortcomings in this field are proposed, and echocardiography remains poised to play a crucial role in the continued development of this exciting field. The dilemma articulated by Claude Bernard1 in 1865 still haunts clinicians today: the response of the ‘‘average’’ patient to a therapy is not necessarily the response of the individual patient standing before the clinician. The ‘‘average’’ response to cardiac resynchronization therapy (CRT) is undeniably favorable for the current criteria by which we select patients. CRT is a class IA recommendation for patients in sinus rhythm with QRS duration > 120 msec, left ventricular (LV) ejection fraction # 35%, and New York Heart Association (NYHA) class III or ambulatory class IV heart failure symptoms despite optimal medical therapy.2 Fourteen randomized controlled trials enrolling 4,420 patients have demonstrated that CRT improves LV ejection fraction, quality of life (QOL), and NYHA class while reducing hospitalizations by 37% and all-cause mortality by 22%.3 However, CRT is invasive, costly,4 and associated with rare but serious complications, including peri-implantation death (0.3%– 0.5%), wound or device infection (2%), and device or lead failure (5%).3 Additionally, the initial application for CRT submitted by Medtronic (Minneapolis, MN) to the US Food and Drug Administration5 showed that 32% to 55% of patients did not respond to CRT according to the primary end points of improved QOL, improved 6-min walking distance (6MWD), and improved NYHA class (Table 16). These factors demanded an attempt to limit CRT to those patients who will truly benefit, or ‘‘respond.’’ Although initial single-center From the Department of Medicine, Children’s Hospital Boston, Boston, Massachusetts; and the Department of Pediatrics, Harvard Medical School, Boston, Massachusetts. Reprint requests: Brandon K. Fornwalt, MD, PhD, Children’s Hospital Boston, Department of Medicine, 300 Longwood Avenue, Boston, MA 02115 (E-mail: bkf@ gatech.edu). 0894-7317/$36.00 doi:10.1016/j.echo.2010.12.015

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studies showed promise in using LV mechanical dyssynchrony (defined using echocardiographic measures) as a baseline predictor of response to CRT,7 multicenter8 and subsequent single-center9,10 studies have not been able to reproduce these results.

RIGHT VENTRICULAR ASSESSMENT AND CARDIAC RESYNCHRONIZATION THERAPY The search for better selection criteria for CRT has largely been dominated by LV indices of dyssynchrony or function. Baseline right ventricular (RV) dysfunction prior to CRT increases mortality11 and reduces the likelihood of both clinical11 and echocardiographic12 response after CRT. Additionally, CRT improves RVejection fraction13 and peak systolic myocardial velocities in the RV free wall.14 A recent study even suggested that a subset of patients with exaggerated LV-RV interaction show a reduced pulmonary artery pressure after CRT without LV remodeling.15 Thus, the assessment of RV function is emerging as an important aspect of CRT that has been mostly overlooked. In this issue of JASE, Szulik et al16 report that the addition of RV dyssynchrony parameters at baseline improved the ability to predict clinical response to CRT. The authors generated a multivariate model of baseline predictors, including parameters of both LV and RV morphology and LV, RV, and interventricular dyssynchrony. The model showed that the addition of RV dyssynchrony parameters improved the power of their model to predict response to CRT, with an area under the receiver operating characteristic curve equal to 1. Interestingly, no LV dyssynchrony measures were helpful in predicting response to CRT, but this may be because the authors required baseline interventricular or intra-LV dyssynchrony for inclusion in the study. The report by Szulik et al16 provides evidence that, as the authors say, ‘‘it might be useful to consider an analysis of baseline RV function and dyssynchrony’’ in the search for refined CRT selection criteria. However, several limitations deserve mention. These limitations are in fact limitations of the entire field of CRT research; the work of Szulik et al provides a nice framework for a much-needed discussion.

THE DYS-SYNCHRONY AMONG DYSSYNCHRONY PARAMETERS Szulik et al16 investigated 13 different dyssynchrony parameters in their study. This large number is not surprising; anyone reading the literature on predicting response to CRT will likely be overwhelmed by the number of different dyssynchrony parameters.17 Some questions an investigator is faced with when deciding how to quantify dyssynchrony include the following: 1. Which imaging modality should be used (echocardiography, computed tomography, magnetic resonance imaging, nuclear medicine)?

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Abbreviations

CARE-HF = Cardiac Resynchronization-Heart Failure trial CRT = Cardiac resynchronization therapy LV = Left ventricular LVESV = Left ventricular endsystolic volume

MIRACLE = Multicenter InSync Randomized Clinical Evaluation

NNT = Number needed to treat

NYHA = New York Heart Association

QOL = Quality of life RV = Right ventricular 6MWD = 6-min walking distance

TsSD = Standard deviation of times to peak systolic velocity

2. If echocardiography is used, which type should be used (M mode, pulsed Doppler, tissue Doppler velocity, strain, strain rate or displacement, speckle tracking, three-dimensional)? 3. Which industrial platform should be used (Philips, GE Healthcare, etc)? 4. Should radial, longitudinal, or circumferential motion be examined? 5. How many segments or locations should be analyzed (two, four, six, 12, or 16 segments)? 6. Should time to onset or time to peak be measured, or should more data be used? 7. Should the analysis be limited to systole or isovolumic periods or include both? 8. Should the standard deviation or the maximum difference among timings be assessed?

Although studies have addressed some of these issues, many are contradictory, and none have made a good case for which methodology best quantifies dyssynchrony with both high accuracy and good reproducibility. Additionally, multiple studies have shown significant differences both in the diagnosis and the magnitude of dyssynchrony among the different published dyssynchrony parameters.18-21

ASSESSING THE ACCURACY OF DYSSYNCHRONY PARAMETERS Response to CRT should not be the gold standard by which we determine the accuracy of a dyssynchrony parameter. Perhaps the major reason we do not have a gold standard dyssynchrony parameter is because we are using response to CRT as a metric for determining the accuracy of a parameter. A patient’s individual response is affected by too many other variables, including the total scar burden22 and location,23 the region of latest activation,24 RV function as noted by Szulik et al,16 and comorbidities such as diabetes, renal failure, and atrial fibrillation.25 We need to document and compare the accuracy of dyssynchrony parameters in well-controlled studies such as acute pacing-induced dyssynchrony, for which subjects can serve as their own controls.26

QUANTIFYING THE REPRODUCIBILITY OF DYSSYNCHRONY PARAMETERS Reproducibility was either overlooked or grossly inaccurate in many initial publications on dyssynchrony parameters. Unfortunately, overlooking reproducibility led to problems in future studies.8,27 For example, the dyssynchrony parameter with arguably the most

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evidence supporting its use in predicting response to CRT is the standard deviation of times to peak systolic velocity (TsSD) in the 12 basal and midwall segments of the left ventricle. The initial publications on TsSD did not report reproducibility and instead cited an article28 apparently documenting ‘‘low inter- and intraobserver variability of <5%.’’ The cited article reports that ‘‘the mean difference between observations was <5% of the mean value of the observations for measurement of both amplitudes and durations.’’ There are four problems to note here that apply not only to the example case but to all dyssynchrony parameters in general: 1. Reporting the mean difference is a grossly inaccurate measure of reproducibility, and 95% limits of agreement should be reported at a minimum.29 2. Reproducibility should be determined for the dyssynchrony parameter itself, not just for individual components of a dyssynchrony parameter (such as the time to peak velocity of one of the 12 locations involved in calculating TsSD), because these are not equivalent. 3. If the parameter is to be used in clinical practice as a diagnostic (i.e., to diagnose a patient with dyssynchrony), then good reproducibility of the diagnosis is more important than showing good reproducibility of the magnitude of the parameter. Diagnostic reproducibility should be assessed with k coefficients.30 4. Reproducibility should be documented both between observers and between tests. Test-retest agreement is more relevant, and the few studies that have documented this on dyssynchrony parameters have shown poor results.27,31

THE DYS-SYNCHRONY AMONG RESPONSE CRITERIA Methods to assess response to CRTare nearly as varied and different as the numerous published dyssynchrony parameters. Qualitative lack of agreement among response criteria was apparent from the original Multicenter InSync Randomized Clinical Evaluation (MIRACLE) trial data showing lower numbers of patients who responded to more than one end point (Table 1). The discrepancy was mostly overlooked until a recent study identified 17 different response criteria from the 26 most cited publications on predicting response to CRT.32 The percentage of patients showing a positive response to CRTranged widely from 32% to 91% for the different criteria. Agreement among the methods was strong only 4% of the time and poor 75% of the time. It is therefore impossible to make comparisons across multiple studies that used different response criteria. Szulik et al16 attempted to address this problem by using two different methods in their study to predict response: reverse LV remodeling (> 15% reduction in LV end-systolic volume [LVESV]) and ‘‘clinical response’’ (alive, no hospitalization for decompensation, improved NYHA class $ 1, and 10% decreases in both peak ventilatory oxygen uptake and 6MWD).16 The authors found a different result for each end point, so the reader is left wondering which end point is more important; unfortunately, this question has no good answer. Additionally, their measure of clinical response has not been used before and therefore may end up only adding confusion to the end point conundrum.

THE FALLACY OF OUR ‘‘BEST’’ SURROGATE END POINT More than 150 clinical, hemodynamic, or exercise variables have been identified as predictors of survival in heart failure.33 The major

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Table 1 Response to CRT in the treatment and control groups according to primary end points used in the MIRACLE5 and CARE-HF6 trials Response criterion

Percentage of patients who responded according to the given end point (pacer off)*

Percentage of patients who responded according to the given end point (pacer on)*

NNT

NYHA5 QOL5 6MWD5 6MWD + QOL5 6MWD + NYHA5 QOL + NYHA5 6MWD + QOL + NYHA5 CCS5 Alive at 1 y6 Alive at 2 y6 Alive at 3 y6

38% 44% 27% 18% 15% 26% 12% 39% 87% 75% 63%

68% 58% 45% 33% 38% 47% 30% 65% 90% 83% 77%

3.4 7.4 5.5 6.9 4.4 4.7 5.6 3.9 32.7 13.1 7.4

CCS, improved clinical composite score; NYHA, improvement in NYHA functional class by $ 1 class; QOL, improvement of $ 13 in Minnesota Living with Heart Failure Questionnaire score; 6MWD, improvement of $ 50 m in 6MWD. *Percentages are rounded to the nearest whole number for display, while actual ratios were used to quantify the NNT.

SHOULD WE EVEN BE TRYING TO IMPROVE CARDIAC RESYNCHRONIZATION THERAPY SELECTION CRITERIA?

Table 2 LVESV response does not adequately predict cardiovascular mortality (data derived from Yu et al36) Cardiovascular mortality LVESV remodeling

Died

Alive

Sum

<10% (nonresponders) >10% (responders) Sum

15 2 17

38 86 124

53 88 141

motivation for using surrogate end points is to reduce sample size and study duration. The most widely used surrogate in quantifying response to CRT is reduction in LVESV > 15%, for three main reasons: 1. A substudy of the MIRACLE trial showed that the benefits of CRT on 6MWD, NYHA class, and QOL occurred predominantly in patients with objective changes in LV geometry.34 2. The 95% limit of variability in the measurement of LVESV is equal to 615%.35 3. A study by Yu et al36 showed that a reduction of > 10% in LVESV predicted all-cause and cardiovascular mortality, while changes in NYHA class, 6MWD, and QOL did not. However, a closer look at the data suggests that a reduction in LVESV is not a good surrogate at all. Table 2 shows data deduced from the aforementioned study by Yu et al36 on using LVESV response to predict cardiovascular mortality. The authors proposed that these data provided good evidence that LVESV response predicts cardiovascular mortality and could be used as an adequate surrogate end point. Suppose we identify a baseline predictor that has 100% accuracy for predicting LVESV response to CRT. If we limit CRT enrollment criteria to this perfectly accurate LVESV predictor, then, on the basis of data in Table 2, we will exclude 38 of 141 patients (27%) from receiving CRT who have not had cardiovascular death and may have actually benefited from CRT. This is further illustrated by the fact that the k value derived from Table 2 is equal to 0.3, suggesting poor agreement between LVESV response and cardiovascular death.

It is important to remember that CRT is a class IA indication for all patients enrolled in most studies attempting to better predict response to CRT. This means that it is unethical to have a true control group in these studies, and it is important to consider the large documented placebo effect. Table 1 shows that 27% to 44% of patients in the control group (pacer off) ‘‘responded’’ according to the three primary clinical end points from the MIRACLE trial of improved NYHA, 6MWD, and QOL. Thus, when 70% of patients in the treatment group (pacer on) show a ‘‘response’’ according to the primary end point, this does not mean we are actually helping 70% of patients who receive CRT. We are helping only 14% to 29% of patients who receive CRT after accounting for the placebo effect. In other words, for every 3.4 to 7.4 biventricular pacemakers that are implanted, only one patient shows a true benefit (Table 1). This analysis is classically used to assess the magnitude of treatment effect in clinical trials and is referred to as the ‘‘number needed to treat’’ (NNT): NNT ¼

1 Responderstreatment  Respondersplacebo

(1)

where Responderstreatment is the percentage of patients in the treatment group (pacer on) who showed improvement in the primary end point, and Respondersplacebo is the percentage of patients in the placebo group (pacer off) who showed improvement in the primary end point. The data are even more striking when we look at all-cause mortality after 1, 2, and 3 years (Table 1). To save one person’s life in 1 year, we need to treat 32.7 patients with CRT. This number improves dramatically to an NNT of 7.4 for 3-year all-cause mortality. Thus, the true benefit of CRT takes effect long after the typical 6-month follow-up periods for small studies trying to predict ‘‘response to CRT.’’ It is extremely unrealistic to expect that any baseline predictor of a 6-month surrogate end point will predict reliably which patients achieve this documented mortality benefit at 3 years and which do not. Although trying to predict 6-month surrogate end points is unlikely to improve CRT selection criteria, there definitely is potential benefit

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Table 3 Benefit in NNT from refinement of CRT selection criteria (data from MIRACLE5 and CARE-HF6 trials) Assume 80% of patients respond

Assume 90% of patients respond

Response criterion

NNT

NNT

Improvement in NNT

NNT

Improvement in NNT

NYHA5 QOL5 6MWD5 CCS5 Alive at 1 yr6 Alive at 2 y6 Alive at 3 y6

3.4 7.4 5.5 3.9 32.7 13.1 7.4

2.4 2.8 1.9 2.5 * * 5.9

1.0 (29%) 4.6 (62%) 3.6 (65%) 1.4 (37%) * * 1.5 (21%)

1.9 2.2 1.6 2 * 6.8 3.7

1.4 (43%) 5.2 (70%) 3.9 (71%) 1.9 (49%) * 6.4 (49%) 3.7 (50%)

CCS, improved clinical composite score; NYHA, improvement in NYHA functional class by $ 1 class; QOL, improvement of $ 13 in Minnesota Living with Heart Failure Questionnaire score; 6MWD, improvement of $ 50 m in 6MWD. *Cannot be calculated because assumed percentage of responders is lower than current survival rate with CRT at the given follow-up duration.

in continuing to try to improve response to CRT. Table 3 shows the significant improvement in the NNT for several different response criteria, assuming we can improve the percentage of responders to 80% or 90%. Importantly, the fact that 23% of patients who receive CRT die within 3 years suggests that we should continue searching for ways to improve this high mortality rate. However, continuing to attempt to identify better CRT selection criteria may not be the best way to improve response to CRT. REPRODUCIBILITY OF RESPONSE CRITERIA Clearly, the target ‘‘response measure’’ for studies in this field needs to be standardized. As described in the previous section, we cannot continue to rely on 6-month surrogates to predict hard end points. However, hard end points such as mortality are not the only measures patients and their clinicians care about. QOL and symptomatic measures are also important. However, if we choose to target improvement in symptomatic measures, then a reproducibility study must be done documenting the reproducibility of the actual response criteria. For example, the criterion needs to be evaluated both at baseline and at the time of follow-up after CRT by two independent, blinded investigators. Each investigator should then do appropriate calculations and classify each patient as a responder or nonresponder. The agreement among the two investigators should then be compared with a k coefficient. This study has not been done and is critically important to knowing whether we are undertaking a reasonable objective or if we are aiming at a moving target which cannot be reproducibly quantified. FUTURE DIRECTIONS AND CONCLUSIONS Identifying baseline predictors to better select patients who will benefit from CRT is a challenging undertaking. The majority of research published in this field must change focus. Answering the following questions is essential to making progress: 1. Which methodology (described in detail) can be used to accurately and reproducibly (both inter-test and inter-observer diagnostic reproducibility) quantify dyssynchrony in the heart? This must be done with positive and negative controls, such as pacing-induced dyssynchrony, and not by comparing the ability to predict response to CRT. Only after identifying an accurate, reproducible methodology can we then determine the precise

role of dyssynchrony assessment in selecting patients for CRT, which will also help better define the role of RV functional measures proposed by Szulik et al.16 2. Which 6-month surrogate end points, if any, predict the longterm mortality benefit from CRT? If we want to use a predictor of a 6-month surrogate to refine CRT selection criteria, then survival curves based on the response quantified by the surrogate end point are misleading. Agreement between 6-month surrogates and long-term mortality data should be directly assessed with techniques such as Cohen’s k coefficient. Until this study has been done, studies using 6-month surrogates such as a 15% reduction in LVESV are not useful. 3. If the goal of CRT is to improve QOL and clinical symptoms regardless of mortality benefit, then what is the reproducibility of the actual definition of response by any measure we are attempting to predict (NYHA, 6MWD, or QOL)? Until this study has been done, studies predicting ‘‘clinical’’ response at 6 months are not useful. Until these studies are undertaken, what we have been doing in this field can be portrayed using the following analogy: we have been attempting to win an archery contest by hitting a target (curiously, it is moving all over the place) with a highly inaccurate arrow (because we have no bow or other tools to help, we have been throwing the arrow), we are not sure if we have even been aiming at the correct moving target because there are so many archery contests going on today that we got confused and may have shown up at the wrong one, and our current solution is to keep picking up different-looking arrows and chucking them hopelessly at the moving target in the hope that we will still win the contest. I hope readers can appreciate my sense of humor. REFERENCES 1. Bernard C. An introduction to the study of experimental medicine. Reprint of 1865 edition. New York: Dover; 1957. 272. 2. Hunt SA, Abraham WT, Chin MH, Feldman AM, Francis GS, Ganiats TG, et al. ACC/AHA 2005 guideline update for the diagnosis and management of chronic heart failure in the adult: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Writing Committee to Update the 2001 Guidelines for the Evaluation and Management of Heart Failure): developed in collaboration with the American College of Chest Physicians and the International Society for Heart and Lung Transplantation: endorsed by the Heart Rhythm Society. Circulation 2005;112:e154-235.

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