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QUARTERLY FOCUS ISSUE: HEART RHYTHM DISORDERS: STATE-OF-THE-ART PAPER

Indications for Implantable Cardioverter-Defibrillators Based on Evidence and Judgment

Division of Cardiology, University of Miami Miller School of Medicine, Miami, Florida

Manuscript received December 29, 2008; revised manuscript received March 20, 2009, accepted March 24, 2009.

^_* Reprint requests and correspondence: Dr. Robert J. Myerburg, Professor of Medicine and Physiology, Division of Cardiology (D-39), University of Miami Miller School of Medicine, P.O. Box 016960, Miami, Florida 33101 (Email: rmyerbur{at}med.miami.edu).

	Abstract

Top Abstract Evolution of the ICD Randomized Trial Support for... Secondary Prevention Trials Primary Prevention of SCD... ICDs for Prevention of... ICD Indications in Less... Limitations of Clinical Trial... The Low Risk-High Number... New Risk Markers and... Risk Stratification and Economic... Conclusions References

 
Implantable cardioverter-defibrillators (ICDs) are generally reliable medical devices that have the potential to add quality years of life for appropriate candidates. Indications for ICDs have emerged from a series of randomized clinical trials, observational data from cohorts of high-risk patients with less common diseases, and expert opinion based on limited data in uncommon disorders. The randomized trials are limited by inadequate stratification designs that resulted from insufficient funding availability. The result was outcomes that led to uneven applications, based in part on post-implant experience of device utilization. In this document, we explore the basis for the features of the evidence available to support ICD use, the role of clinical judgment in circumstances in which data are limited or lacking, and the need for additional research to improve the specificity of indications. Directions for new research initiatives are considered. In addition, a general overview of a clinical research paradigm is presented, in which the research and health care delivery arms of the health care enterprise combine in research design and funding, as the latter bears the impact of the outcomes of the former. Impact estimates during the design of trials, considering reasonable contingencies for outcomes, are suggested as a means of justifying the size, scope, and appropriate costs of studies. If we who are involved in clinical research and health care delivery do not resolve this problem, for both ICDs and other new therapies that appear in the future, society will do it for us.

Key Words: implantable cardioverter-defibrillators • indications • review

Abbreviations and Acronyms   CAD = coronary artery disease   CMS = Center for Medicare and Medicaid Services   EF = ejection fraction   HCM = hypertrophic cardiomyopathy   ICD = implantable cardioverter-defibrillator   MI = myocardial infarction   NYHA = New York Heart Association   PVC = premature ventricular complex   SCD = sudden cardiac death   VF = ventricular fibrillation   VT = ventricular tachycardia

Categories of disease that have achieved confirmation of ICD benefit from randomized trials, primarily coronary artery disease (CAD) with a prior myocardial infarction (MI), nonischemic cardiomyopathy, and cardiac arrest survivors generally, have done so within the restrictions of clinical trial designs that provide broad sweeps of statistical benefit. The clinical trial data are hampered by the uncertainties of risk-benefit impact for subgroups within study populations and for individual patients. This is, at least in part, a consequence of funding available for the trials. The purpose of this document is to explore the current scientific basis for clearly defined indications, as well as uncertainties based on limitations of data from randomized clinical trials, observational data, and expert opinions. Opportunities for improving risk prediction and therapeutic efficacy and efficiency by means of new investigative strategies are also explored.

	Evolution of the ICD

Top Abstract Evolution of the ICD Randomized Trial Support for... Secondary Prevention Trials Primary Prevention of SCD... ICDs for Prevention of... ICD Indications in Less... Limitations of Clinical Trial... The Low Risk-High Number... New Risk Markers and... Risk Stratification and Economic... Conclusions References

 
Nearly 4 decades elapsed between the original notion that an ICD might be a useful clinical strategy, its subsequent development, and its current acceptance in various clinical settings based on randomized trial data (Fig. 1). Each decade played a distinctive role in the evolution of ICD therapy. From the late 1960s until the first patient implant in 1980 (1), Mirowski's concept of a "standby automatic defibrillator" (2,3) met with skepticism (4) and concern about the practical difficulties in designing and manufacturing such a device (5,6). After the first human device implant in 1980, clinical acceptance of the concept was initially slow, but began to accelerate after Food and Drug Administration approval in 1985 and Medicare coverage for limited indications in 1986.

View larger version (37K): [in this window] [in a new window] [Download PPT slide]   Figure 1 Timeline of Evolution of ICDs From Original Concept to Present The concept of an implantable cardioverter-defibrillator (ICD) originated in the late 1960s, and the development of the technology and proof of concept leading to the first clinical implant extended to 1980. From 1980 until late 1996, data supporting ICD benefit were largely observational, or based on small high-risk cohorts or case-control studies. The first true randomized trials were designed in the late 1980s and early 1990s, and all of the major trials for both primary and secondary indications were published during an interval of <10 years between late 1996 and early 2005. Additional studies since then have aided in the interpretation of the outcomes from the clinical trials, but there remains a need for consolidation and clarification and for additional data to better define efficiency of therapy and targeted selection of individual candidates who have a high likelihood of benefit. AVID = Antiarrhythmic Versus Implantable Defibrillator; CABG-Patch = Coronary Artery Bypass Graft-Patch; CASH = Cardiac Arrest Study of Hamburg; CAST = Cardiac Arrhythmia Suppression Trial; CIDS = Canadian Implantable Defibrillator Study; DEFINITE = Defibrillators In Non-Ischemic Cardiomyopathy Treatment Evaluation; DINAMIT = Defibrillator In Acute Myocardial Infarction Trial; FDA = Food and Drug Administration; MADIT = Multicenter Automatic Defibrillator Implantation Trial; MUSTT = Multicenter Unsustained Tachycardia Trial; SCD-HeFT = Sudden Cardiac Death-Heart Failure Trial.

	Randomized Trial Support for ICD Therapy

Top Abstract Evolution of the ICD Randomized Trial Support for... Secondary Prevention Trials Primary Prevention of SCD... ICDs for Prevention of... ICD Indications in Less... Limitations of Clinical Trial... The Low Risk-High Number... New Risk Markers and... Risk Stratification and Economic... Conclusions References

 
The randomized clinical trials of ICD benefit are classified into 2 categories: primary and secondary prevention strategies. Primary prevention of SCD has been interpreted, by common usage, to mean a reduction in mortality among a category of patients known to be at high risk for cardiac arrest due to defined pre-existing disease, but without clinical expression of potentially fatal arrhythmias. Secondary prevention has been used to refer to reduction of mortality risk in patients who have survived cardiac arrests due to ventricular tachyarrhythmias. Although these classifications, as used in the electrophysiological literature, are not conventional epidemiological definitions (19) (Table 1), they have become ingrained in the ICD literature and will therefore be applied in this document.

	Secondary Prevention Trials

Top Abstract Evolution of the ICD Randomized Trial Support for... Secondary Prevention Trials Primary Prevention of SCD... ICDs for Prevention of... ICD Indications in Less... Limitations of Clinical Trial... The Low Risk-High Number... New Risk Markers and... Risk Stratification and Economic... Conclusions References

 
The secondary prevention strategy emerged from observational data recognizing that survivors of documented life-threatening ventricular tachyarrhythmias (ventricular fibrillation [VF], pulseless ventricular tachycardia [VT]) are at high risk for recurrent arrhythmic events and death (20,21). This category has been extended to include patients with unexplained syncope suspected to be due to high-risk tachyarrhythmic mechanisms in the presence of advanced structural heart disease. High recurrence rates were likely when a cardiac arrest was associated with uncontrollable arrhythmogenic pathophysiology or recurring triggers.

The cumulative results of 3 randomized trials have led to the general acceptance of ICD therapy for survivors of cardiac arrest when the arrhythmia was not due to transient and/or reversible factors, such as acute MI, proarrhythmic drug effects, or electrolyte disturbances. The occurrence of cardiac arrest during the acute phase of MI, defined as from the onset of symptoms to 24 to 48 h, is not an indication for an ICD and does not contribute to the decision of whether an ICD is indicated, based upon post-MI risk markers. While this statement is generally accepted and incorporated into the guidelines documents addressing management of ventricular arrhythmias and SCD (22), limited data have begun to question the validity of this conclusion (23). Until further data are forthcoming, this generally accepted exclusion still stands.

The 3 secondary prevention trials, the AVID (Antiarrhythmic Versus Implantable Defibrillator) trial in the U.S. (11), CIDS (Canadian Implantable Defibrillator Study) in Canada (13), and CASH (Cardiac Arrest Study of Hamburg) in Germany (14), were initiated between the late 1980s and early 1990s (Table 2). The AVID trial was the first to be completed and demonstrated a statistically significant survival benefit of the ICD over antiarrhythmic drug therapy (primarily amiodarone), with a 2-year relative risk reduction of 27%, corresponding to an absolute risk reduction of 7% (Table 2). Because of the similarities between the AVID and CIDS trials, the latter was terminated after the AVID trial was reported. Although the CIDS trial did not achieve a statistically significant all-cause mortality benefit, possibly because it was stopped early, it did demonstrate a similar trend toward benefit, with a 2-year relative risk reduction of 30%, corresponding to an absolute risk reduction of 6%. The CASH study, which was smaller and had some intervening design changes because 1 of the arms in the study suggested an adverse outcome, was started before the AVID and CIDS trials and were reported later (14). It too failed to achieve statistically significant benefit, but showed magnitudes of relative and absolute risk reduction similar to the other 2 studies. Thus, only 1 of the 3 secondary prevention trials achieved independent statistical significance, but that 1 has dominated opinion because of its larger size and clarity of outcome. Moreover, a meta-analysis of the pooled data from the 3 trials did demonstrate statistical significance (24).

	Primary Prevention of SCD in Patients With Coronary Artery Disease and Prior Myocardial Infarction

Top Abstract Evolution of the ICD Randomized Trial Support for... Secondary Prevention Trials Primary Prevention of SCD... ICDs for Prevention of... ICD Indications in Less... Limitations of Clinical Trial... The Low Risk-High Number... New Risk Markers and... Risk Stratification and Economic... Conclusions References

 
During the 1980s and early 1990s, there was intense interest in the use of programmed electrical stimulation techniques for determining whether inducibility of life-threatening arrhythmias (VT or VF) was a reliable method for profiling risk of SCD in patients with CAD who have survived an MI (27–29). In addition to risk profiling, the questions of suppression of inducibility of ventricular arrhythmias in the electrophysiology laboratory and of suppressibility of ambient arrhythmias were also explored for their potential as indicators of protection against spontaneous life-threatening arrhythmias by antiarrhythmic drugs. The combination of the emergence of ICDs as a practical therapy, concern about adverse effects of antiarrhythmic drugs based in part upon the CAST study (7,8), and insufficient data on efficacy of device or pharmacological therapies for protection against SCD, led to the design of randomized trials testing defibrillator therapy against "conventional" therapy, the latter including antiarrhythmic drugs in many of the studies. The first of the randomized primary prevention ICD trials was MADIT (Multicenter Automatic Defibrillator Implantation Trial) (Table 3). MADIT compared ICD therapy to antiarrhythmic drugs (75% amiodarone) in a population of post-MI patients with EFs <35%, nonsustained VT on ambulatory monitoring, inducible VT by programmed stimulation, and failure of intravenous procainamide to prevent inducibility. The study was small, but a 59% difference in the relative risk of death was observed between the ICD group and the active controls at 2 years of follow-up (13% versus 32%) (9). Another study, MUSTT (Multicenter Unsustained Tachycardia Trial) (12), was designed to determine whether inducibility of VT identified SCD risk in patients with CAD, 95% of whom had a prior MI, documented nonsustained VT 4 days after the most recent MI, and an EF 40%. The MUSTT trial did not randomize ICD therapy, but patients failing suppression of inducibility received ICDs at the option of treating physicians. The ICD subgroup achieved a 58% reduction in relative risk of death (24% vs. 55%) over 5 years of observation (12). The MADIT and MUSTT results were interpreted to indicate that electrophysiological inducibility in patients with low EFs and nonsustained VT was a predictor of SCD, with improvement in outcome by implantation of ICDs compared with antiarrhythmic drugs. The lack of survival benefits attributable to antiarrhythmic drugs in these studies were reinforced by 2 other randomized, placebo-controlled post-MI amiodarone trials that showed no survival benefit, EMIAT (European Myocardial Infarct Amiodarone Trial) (30) and CAMIAT (Canadian Amiodarone Myocardial Infarction Arrhythmia Trial) (31).

Whereas the MADIT, MUSTT, and MADIT II studies enrolled patients many months after the qualifying MI on average, the DINAMIT (Defibrillator In Acute Myocardial Infarction Trial) study was designed to evaluate the potential for ICD benefit when implanted early after a MI in patients with EFs 35% (16). Even though both old (32,33) and recent (34,35) data suggest a higher risk for SCD early after MI, the DINAMIT study suggested no overall survival benefit attributable to early implantation of ICDs in patients randomly allocated at 6 to 40 days after MI (mean 18 days), despite a reduced arrhythmic mortality. In addition, there was an unexplained increase in nonarrhythmic mortality compared with conventional therapy that needs to be explored in future studies. The inconsistency between early SCD risk and absence of early ICD benefit observed in the DINAMIT study has led some to call for further studies of this question.

	ICDs for Prevention of SCD in Nonischemic Cardiomyopathy

Top Abstract Evolution of the ICD Randomized Trial Support for... Secondary Prevention Trials Primary Prevention of SCD... ICDs for Prevention of... ICD Indications in Less... Limitations of Clinical Trial... The Low Risk-High Number... New Risk Markers and... Risk Stratification and Economic... Conclusions References

 
Several small randomized trials carried out to evaluate the potential for ICD benefit among patients with nonischemic cardiomyopathy were inconclusive. Another study, the DEFINITE (Defibrillators In Non-Ischemic Cardiomyopathy Treatment Evaluation), was designed to test ICD benefit in a cohort of 458 patients with nonischemic cardiomyopathy, a history of heart failure, EFs 35%, and PVCs or nonsustained VT (17) (Table 3). The study compared ICD therapy to conventional therapy and demonstrated a strong trend (p = 0.08) toward ICD benefit, with a 2-year mortality of 7.9% in the ICD group compared with 14.1% with standard therapy. Although a threshold of significance for total survival benefit was not reached, likely because of insufficient numbers, certain subgroups, such as those with prolonged QRS durations, EF >20%, and New York Heart Association (NYHA) functional class III heart failure performed better with ICD therapy.

The SCD-HeFT (Sudden Cardiac Death-Heart Failure Trial) study (18) enrolled patients with both nonischemic and ischemic cardiomyopathies with EFs 35%, and required stable NYHA functional class II or III heart failure. The study was unique in design in that it had an ICD arm, a drug arm (amiodarone), and a usual-therapy control group. The study was nearly equally balanced between patients with nonischemic cardiomyopathy and those with ischemic cardiomyopathy, 85% of whom had a prior MI (G. Bardy, personal communication, previously unpublished data from SCD-HeFT, May 2008). Both groups were large enough to do meaningful subgroup analyses of benefit. The study was underpowered for a 3-way analysis, so the ICD and amiodarone groups were compared with the control group independently. There was no difference between usual therapy and amiodarone, whereas an ICD survival benefit became apparent after the first 2 years and continued to increase at 5 years. The magnitude of absolute benefit was relatively small at 1.4% per year (cumulative 7% over 5 years), but there was a relative risk reduction of 23% (29% vs. 36%). Although there remains some uncertainty regarding ICD benefit for nonischemic cardiomyopathy patients without heart failure, regardless of EF (Table 3), the cumulative information available from clinical trials and observational data, in conjunction with opinions of experts in the field, supports prophylactic ICD therapy among the subgroup of patients with nonischemic cardiomyopathy who remain in NYHA functional class II or III heart failure on optimal medical therapy. Subgroup analysis suggested that NYHA functional class II patients benefited more, in contrast to the observation in the DEFINITE study that class III heart failure patients performed better (17).

	ICD Indications in Less Common and Rare Disorders

Top Abstract Evolution of the ICD Randomized Trial Support for... Secondary Prevention Trials Primary Prevention of SCD... ICDs for Prevention of... ICD Indications in Less... Limitations of Clinical Trial... The Low Risk-High Number... New Risk Markers and... Risk Stratification and Economic... Conclusions References

 
The major categories of cardiovascular diseases, which generate cohorts large enough to accommodate randomized clinical trial designs, dominate the cumulative number of indications for ICDs. Nonetheless, physicians must also evaluate patients with less common disorders about which available data on ICD benefit are less robust. The less common diseases associated with SCD risk are a heterogeneous group of clinical entities, none of which is large enough to support a randomized clinical trial. Thus, the decision-making process for ICD indications is derived from registry and small cohort data, and interpreted by expert opinion provided in practice guideline documents (22,36) (Table 4). In the absence of sufficient data to generate uniformly agreed-upon expert opinions, decision making defaults to physician judgment. Under such circumstances, it is incumbent upon the physician to explain the limits of knowledge to the potential candidates, so that they can make informed decisions.

Myocarditis.   Cardiac arrest is a well-established complication of acute viral myocarditis (38,39). Its incidence appears to be very low, although the precise frequency of cardiac arrest or symptomatic sustained VT among those affected with myocarditis is unknown. Although arrhythmias during the acute phase of myocarditis are generally not considered decisive for immediate ICD indications, the determination of whether, and under what circumstances, the post-myocarditis patient should receive an ICD remains challenging (22). Despite limited data, recurrent or persistent life-threatening arrhythmias (sustained VT, and possibly long runs of nonsustained VT, especially if polymorphic) after healing are commonly considered indications, regardless of EF, based on pathological data on unanticipated SCDs in minimally symptomatic or unrecognized myocarditis (39). It is generally agreed that post-myocarditis cardiomyopathy that meets ICD criteria for nonischemic cardiomyopathy is an ICD indication, but ICDs are not generally recommended for patients whose EFs return to normal or near-normal, and who are free of arrhythmias other than PVCs after healing, regardless of prior acute phase arrhythmias. The middle ground—patients with EFs in the range of 35% to 45% and ambient nonsustained arrhythmias—remains uncertain because of an absence of data.

Infiltrative disorders.   Cardiac sarcoidosis is a generally accepted indication when accompanied by VT (sustained and possibly nonsustained), regardless of EF (40). The other infiltrative disorders have indication criteria that are variable and not well defined, as outlined in the guideline documents (22,37). However, the data are not extensive, and to a significant degree, indications are determined by life expectancy based on multiorgan involvement, as in amyloidosis.

Inherited disorders.   The inherited disorders that may be indications for ICDs are a heterogeneous group characterized by primary expressions that are either structural substrate-based or arrhythmic. An example of the former is hypertrophic cardiomyopathy (HCM) for which categorically defined SCD risk has been recognized for many years (41). Unfortunately, although HCM is relatively more common among the less common disorders, it is not sufficiently common to support a reasonably sized randomized clinical trial. Thus, the data favoring the use of ICDs for at-risk patients in this category are derived from retrospective analysis of observational data from a registry of patients with HCM who received ICDs (42) (Table 4). In the absence of randomized controls, outcomes were measured as rates of appropriate ICD discharges, rather than survival benefit. Despite the limitations of such an approach, and the fact that an ICD shock is not a surrogate for death (43), it is generally accepted that ICDs are indicated for specific subgroups within the HCM cohort.

The ICD strategies for HCM are separated into primary and secondary indications. Among patients who received ICDs for secondary indications after surviving a documented or strongly suspected life-threatening arrhythmia, the end point of appropriate ICD discharges occurred at an annualized rate of 10.6%, or a cumulative rate of 39% over 5 years (44). Primary prevention indications are based upon risk profiling, also derived largely from retrospective data and expert opinion. The ICD utilization rate of 3.6% per year (cumulative 5-year rate of 17%) suggests a less dramatic benefit, but nonetheless supports the use of ICDs in patients with the defined risk markers. The major risk markers for primary prevention include one or more of the following: LV wall thickness 30 mm, syncope, family history of SCD, and nonsustained VT. A high LV outflow gradient and blunted blood pressure response to exercise have also been suggested as risk markers for primary prevention (42,45).

A second structurally based inherited condition is arrhythmogenic right ventricular dysplasia, which has attracted a great deal of interest in recent years because of recognition that it is more common than previously thought, although it still remains properly classified among the less common disorders. SCD is commonly the first clinical manifestation, particularly in association with exercise triggers. While accurate diagnosis can be difficult (46), early recognition offers the potential for improved SCD prevention strategies. To this end, ICD therapy has become accepted for patients arrhythmogenic right ventricular dysplasia who have symptomatic arrhythmias (Table 4), as well as for those with documented disease thought to be at high risk, although the cut-point for ICD indications for primary prevention is not yet clearly defined (47,48). As with other entities in this category, the secondary prevention strategy for ICDs is clear, but criteria for ICDs for primary prevention use of ICDs are less well defined.

The inherited disorders that express as primary arrhythmias include congenital long-QT interval syndrome, Brugada syndrome, and very rare conditions such as catecholaminergic polymorphic VT (49), short-QT interval syndrome (50), and a recently described variant of early repolarization (51). These uncommon disorders may have extremely variable clinical expression, and reliable cohort data are also difficult to acquire, further defaulting to expert opinion that is based on limited data. For each of these entities, it is generally accepted that ICDs are indicated for high-risk subgroups that can be identified with varying degrees of confidence.

Among patients with congenital long-QT syndrome, ICDs are generally accepted as secondary prevention therapy for those who have had cardiac arrest or documented symptomatic ventricular tachyarrhythmias, based largely upon experiences from a sizable international registry (52) (Table 4). Beta-blockers are generally recommended as the first choice of therapy for patients who are asymptomatic or have syncope without beta-blocker therapy. For patients who experience syncope while on beta-blocker therapy, particularly if suspected to be due to ventricular tachyarrhythmias, ICDs are generally recommended (53). However, an ICD may be recommended in other circumstances, based on the judgment of the physician.

A more difficult decision-making process in the congenital long-QT syndrome population regards management of asymptomatic family members who carry the mutation identified in a related proband who has expressed life-threatening arrhythmias or SCD. Beta-blockers are generally advised as first-line therapy. However, while it has been thought in the past that a family history of SCD, cardiac arrest, or symptomatic ventricular tachyarrhythmias suggested increased risk of such events in asymptomatic relatives who are mutation carriers, the magnitude of risk is lower than in probands, and the power of the carrier state as an independent predictor for individual risk has recently been questioned (54,55). Variability of risk in individual carriers within a family may be based upon modifier genes migrating in a parallel but separate inheritance patterns, random environmental factors, or even a statistical aberration due to selection bias or limited numbers observed over time (Fig. 2) (56). Individual variability creates a dilemma for treating physicians, and it is now suggested that individual risk profiles be considered in related carriers. One of the potential limiting factors is the observation that among the clinical expressions of long-QT syndrome, syncope is by far the more common, and mortality rates, while large enough to warrant concern, are statistically lower than nonfatal events. New strategies for risk profiling, both clinical and genetic, will be needed to unravel these uncertainties.

View larger version (23K): [in this window] [in a new window] [Download PPT slide]   Figure 2 Variable Phenotypic Expression in Gene-Positive LQT Syndrome Patients Variable expression confounds the interpretation of the genetics of the inherited long-QT (LQT) syndrome and can be viewed as a multistage expression algorithm. Expression level I in gene-positive subjects refers to whether and to what extent the corrected QT interval lengthens predictably based on the presence of a genetic variant plus environmental influences. At expression level II, referring to phenotypic expression of clinical events, such as syncope, arrhythmias, cardiac arrest, and sudden cardiac death, variability occurs with both physiological and environmental modifiers. This feature of long-QT syndrome influences the difficulty in the decision-making process for implantable cardioverter-defibrillators in gene-positive carriers of related probands, with and without baseline expression of corrected QT prolongation. No quantitative distribution of the various patterns of electrocardiographic (ECG) phenotype/arrhythmia phenotype is intended because of lack of sufficient data. However, ECG(–)/arrhythmia(+) is likely far less common than ECG(+)/arrhythmia(–). Modified, with permission, from Myerburg and Castellanos (56).

Catecholaminergic polymorphic ventricular tachycardia, the short–QT-interval syndrome, and early repolarization patterns associated with risk of SCD (51) are additional conditions in which ICDs are indicated for secondary prevention. Patients with early repolarization patterns associated with life-threatening arrhythmias have some clinical features similar to those of patients with Brugada syndrome (62). However, the pathophysiological basis for this entity has yet to be defined and, most importantly, our current inability to prospectively differentiate the rare persons at risk from the very large population with "normal" early repolarization confounds attempts at primary prevention with ICDs.

	Limitations of Clinical Trial Designs

Top Abstract Evolution of the ICD Randomized Trial Support for... Secondary Prevention Trials Primary Prevention of SCD... ICDs for Prevention of... ICD Indications in Less... Limitations of Clinical Trial... The Low Risk-High Number... New Risk Markers and... Risk Stratification and Economic... Conclusions References

 
The sources of data for establishing ICD benefits, particularly those for primary prevention strategies, are limited in their ability to identify strata of risk and ICD survival benefits for individual patients or concentrated subgroups. This derives in part from the fact that none of the studies, regardless of the number of entry criteria, stratified the 1 continuous variable common to each—namely, a qualifying EF. By dichotomizing entry based on a single pre-specified value of EF, analyses of the outcomes are limited to cumulative effects on heterogeneous populations. This is further impacted by emergence of qualifying EF as a dominant focus for ICD indications, in a sense minimizing other qualifications or clinical criteria.

Whenever an entry cut-off is used for a continuous variable, it is axiomatic that the enrolled population will have a mean or median value that deviates from the defined threshold value. This variance was especially prominent in the primary prevention ICD trials for post-MI and nonischemic cardiomyopathy patients, in which enrollees had broad ranges of EF values skewed away from the entry threshold (63) (Fig. 3). However, it is the threshold values that are generally linked to recommendations, even though subgroup analyses have generally suggested reduced benefit for patients closer to the entry limits. The effect of failing to stratify the entry criteria such as EF, accumulating patient populations that deviate significantly from the outer limit of qualification, and suggestions of limited benefit in certain defined subgroups is a loss of efficiency in application of the results of these clinical trials as they are applied to the general population (63,64). While conventional analysis of most of the trials demonstrate statistically significant benefit, the actual magnitudes of the benefits among subgroups, and their impact on individual patients, remain uncertain. Without placing a value on a particular length of added life based upon numbers needed to treat, it is sufficient to recognize the need for better stratification so that greater numbers of patients receiving ICDs will achieve benefit and those not reasonably expected to achieve benefit can be excluded from consideration.

View larger version (31K): [in this window] [in a new window] [Download PPT slide]   Figure 3 Entry Criteria for EF and EFs of Subjects Enrolled in ICD Trials Each of these 4 primary prevention trials had a qualifying ejection fraction (EF) cutoff (green circles), above which patients were not enrolled (grey bars). In each study, the EF subgroup that dominated enrollment (solid blue bars) (mean ± SD for MADIT and MADIT II and median and interquartile ranges for MUSTT and SCD-HeFT) received a measurable benefit from implantable cardioverter-defibrillator (ICD) therapy, whereas those with EFs closer to the threshold entry criterion (cross-hatched blue bars) achieved no benefit or an uncertain benefit (see text on ejection fraction data). Used with permission, from Myerburg (63). AM = ambulatory monitor; EPS = electrophysiological study; HF = heart failure; other abbreviations as in Figure 1.

Ejection fraction data from ICD trials.   A pre-specified qualifying EF limit was the 1 categorical entry criterion common to all of the primary prevention ICD trials. Most of the trials set enrollment at an EF 35%, with entry cut-offs ranging from 30 to 40% (Table 3). Although the absolute differences between the EF entry thresholds, and mean or median values of those actually enrolled, ranged from 7% to 14% in these trials (Table 3), the threshold entry criterion is generally linked, directly or indirectly, to treatment recommendations. As an example of the limitations of this approach, the maximum qualifying EF in the SCD-HeFT study was 35%, whereas the enrolled patients had a median EF of 25%, with an interquartile range of 20% to 30% (18). Subgroup analysis of the 17% of study patients enrolled with EFs >30% suggested no ICD benefit. The MADIT and MADIT II study populations had similar trends for EF subgroups close to the upper limit cut-off for entry (9,15,74). While such nonpre-specified subgroup analyses usually lack the power to prove absence of benefit, particularly if apparent differences are trends that do not achieve statistical significance, such trends raise important questions about generalizability of the magnitude of benefit across all strata of the study populations. Consistency of this pattern in multiple ICD trials reinforces the plausibility of this concern (75) and supports the need for additional data.

In contrast to the CMS approval values for EF, the ventricular arrhythmias and sudden cardiac death guidelines document (22) uses EF ranges derived from (but not identical to) entry criteria, rather than values observed among the enrolled subjects, to establish recommendations for ICD therapy. The recommended upper limit of EF in post-MI patients ranges from 30% to 35% in the absence of heart failure, and from 30% to 40% with class II or III heart failure. The 2008 update of the 2002 device guidelines links more closely to specific EF limits used in study designs, avoiding ranges, but does not integrate commentary on the potential confounding influence of observed values. The recommendations developed in both documents reinforce the generally accepted principle of inserting clinical judgment into decision making for the individual patient.

Additional limitations of EF data include a lack of a uniform methodology and reliability of EF measurements and of time from infarct to determination of a qualifying EF. In regard to the former, while many large clinical trials establish uniform reading criteria or core centers for analysis of imaging data, giving somewhat more credibility to the reported values, they still allow measurement to be made by multiple modalities which are inherently variable. Of greater concern is the lack of any standard for interpretation of data, particularly echocardiographic EFs, during the general application of the outcomes in the practice communities. Reader variability in interpreting data is a general problem to which ICD decision making is not immune.

Heart failure and ICD benefit.   Because a history of heart failure is among the clinical variables that add dimensions beyond EF for potential benefit of ICD therapy (74,76–78), it is important for the clinician to distinguish cardiomyopathy as an expression of myocardial damage and measured as a reduced EF, from clinical heart failure as the functional consequence of muscle damage, expressed as NYHA functional classification. The role of heart failure as an indicator for ICD benefit enters trial strategies and influences outcomes analyses in 3 different patterns: 1) persistent heart failure on medical therapy as an entry criterion in study design, as exemplified in the SCD-HeFT study; 2) a high prevalence of manifest heart failure at entry in studies in which only a history of heart failure was included in entry criteria, such as in the DEFINITE study; and 3) a high prevalence of either a history of heart failure or manifest heart failure in studies in which neither was an entry criterion, such as in the MADIT II trial. In the latter 2 models, subgroup analyses suggest that a history of heart failure is likely an indicator of potential ICD benefit, exceeding that of the qualifying EF alone.

Although the SCD-HeFT study (18) was designed to determine whether patients with heart failure and an EF 35% benefit from ICD therapy, requiring stable NYHA functional class II and III for enrollment, the MADIT II trial required only a low post-MI EF. Based upon subgroup analysis of EFs dichotomized at 25%, the 33% of subjects with EFs >25% did not appear to achieve the same magnitude of ICD benefit suggested for the cumulative group or for those with EF 25%. Moreover, hospitalization for episodic heart failure was a strong indicator of future ICD use and of mortality among patients enrolled into the MADIT II trial (15). In addition, emergence of heart failure was more common in the ICD group, particularly after ICD therapy (78,79), suggesting (among other possibilities) that the underlying pathophysiology of heart failure predisposes to life-threatening arrhythmias. In the SCD-HeFT study, ICD shocks predicted a higher mortality rate than observed in ICD recipients who did not have shocks (80). At least 30% of the deaths among patients who had appropriate shocks occurred within 24 h of a first appropriate shock, suggesting end-stage pathophysiology in a substantial minority of those with a shock/death relationship.

Subgroup analysis of the MADIT population also suggested that an EF 25% and/or a history of heart failure were better predictors of ICD use and mortality during follow-up than EF 26% without heart failure (73). This general principle appears in other trials as well (12,15,17,18), suggesting interactions between EF and heart failure, with the likelihood that presence or absence of heart failure modulates the implications of risk and benefit attributable to EF (63). An exception is the CABG-Patch study (10), which demonstrated no ICD survival benefit despite a mean EF of 27% and a high prevalence of heart failure history (50%) and functional classification impairments (72% NYHA functional class II or III).

QRS duration.   In the MADIT II study, subgroup analysis indicated that a prolonged QRS duration increased the probability of ICD benefit, with uncertainty if the QRS duration was normal (15). This observation controlled CMS-approved ICD indications based on MADIT II data until the SCD-HeFT study (18), and reassessment of the QRS-duration indicator (81,82), superceded the requirement of a QRS duration 0.12 s (66). Although the QRS duration no longer limits CMS indications for MADIT-II candidates, a prolonged QRS duration may be a modifier supporting ICD use in patients with a marginal EF indication. This role for QRS duration is debated (83).

Time after MI and ICD benefit.   The presence of temporal heterogeneity in most of the studies, both in regard to time from qualifying MI or onset of heart failure to enrollment and to timing of a qualifying EF determination, are confounding influences for interpreting EF significance and outcomes data generally. With the exception of DINAMIT, the qualifying EF may have been recorded as early as within 3 to 4 weeks or as remotely as several years from the qualifying MI or onset of heart failure (Table 3). In those studies in which timing of qualifying EF was defined, it was linked to a time before randomization (e.g., 3 to 6 months before enrollment), rather than to time from the qualifying MI or heart failure onset.

The combined observations of the defined time to enrollment in the post-MI ICD trials (9,12,15,18), and the absence of benefit from earlier ICD implantation in the DINAMIT trial (16), have led to the current recommendations for ICD implants 40 days or more after the qualifying MI. In addition, time after a MI influences decision making for an ICD recommendation, in that it is often necessary to decide whether an indication is durable over a long period after MI in a patient free of recurrent events. That is relevant because subgroup differences in outcomes in the primary prevention trials suggest that ICD benefit increases as the interval from the MI to ICD implant increases (84). Because of such subgroup data on delayed risk and benefit, ICD therapy should be considered for the chronic post-MI patient who fulfills criteria, even when there is a long time interval from the most recent MI.

	The Low Risk–High Number Dilemma

Top Abstract Evolution of the ICD Randomized Trial Support for... Secondary Prevention Trials Primary Prevention of SCD... ICDs for Prevention of... ICD Indications in Less... Limitations of Clinical Trial... The Low Risk-High Number... New Risk Markers and... Risk Stratification and Economic... Conclusions References

 
A major population dynamic, the number of SCDs that occur among lower risk subgroups of patients with common disorders, remains a dilemma for reducing the numbers of SCDs. A large majority of the SCDs due to CAD come from the segment of the general population with undiagnosed disease and those who are profiled to be at low absolute risk based on conventional risk markers (85) (Fig. 4). It has been estimated that more than one-third of all SCDs occur among patients with known heart disease, whose EFs are >35%, without other known arrhythmia risk markers. Thus, they are difficult to identify individually based on current ability to profile risk, but generate large numbers among the total SCD population. Another 30% or more are first clinical expressions of unrecognized underlying disease (86) (Fig. 5). At present, the general adult population, those with markers for coronary atherosclerosis and those with low risk profiles after expression of a coronary event, cannot be subgrouped into numbers small enough to warrant ICD therapy. The denominator for the total population class described above is much too large, with event rates too small, to warrant such an approach. New methods of risk profiling will be needed to work within these categories to identify high-risk subgroups among whom primary prevention ICD therapy can be justified (63,71,72,87). Such an approach would have a much greater impact on the public health issue of SCD than does the focus on the small, very high-risk subgroups included in the randomized clinical trials to date (Table 4).

View larger version (34K): [in this window] [in a new window] [Download PPT slide]   Figure 4 Estimates of Incidence and Total Annual Population Burden for General Adult Population and Increasingly High-Risk Subgroups The overall adult population has an estimated sudden death incidence of 0.1% to 0.2% per year, accounting for a total of >300,000 events per year. With the identification of increasingly powerful risk factors, the incidence increases progressively, but it is accomplished by a progressive decrease in the total number of events represented by each group. The inverse relationship between incidence and total number of events occurs because of the progressively smaller denominator pool in the highest subgroup categories. The blue-hatched incidence bars for the higher risk groups represent estimates from the original analysis in the 1990s; the superimposed red-hatched bars reflect more recent estimates based on the effects of newer multimodal therapies. Successful interventions among larger population subgroups require identification of specific markers to increase the ability to identify specific patients who are at particularly high risk for a future event. (Note: The horizontal axis for the incidence figures is not linear.) Modified, with permission, from Myerburg et al. (86). CAD = coronary artery disease; EF = ejection fraction.

View larger version (10K): [in this window] [in a new window] [Download PPT slide]   Figure 5 Distribution of Clinical Status of Victims at Time of SCD Nearly two-thirds of cardiac arrests occur as the first clinically manifest event or in the clinical setting of known disease in the absence of strong risk predictors. Less than 25% of the victims have high-risk markers based on arrhythmic or hemodynamic parameters. Modified, with permission, from Epstein (87). AP = angina pectoris; MI = myocardial infarction; SCD = sudden cardiac death.

	New Risk Markers and Dynamic Risk Profiling

Top Abstract Evolution of the ICD Randomized Trial Support for... Secondary Prevention Trials Primary Prevention of SCD... ICDs for Prevention of... ICD Indications in Less... Limitations of Clinical Trial... The Low Risk-High Number... New Risk Markers and... Risk Stratification and Economic... Conclusions References

The ICD trials incorporated only limited strategies for linking the time interval between the qualifying infarct and EF measurement, or between the qualifying EF and randomization. Neither was there provision for repeated measures of EF or other qualifiers over time. The static nature of these designs does not take into account that the pathophysiologies of ischemic heart disease and nonischemic cardiomyopathy are dynamic, encompassing changes over time that may influence the presence and stability of risk markers. That results in conflicts between entry criteria and outcomes data that can be difficult to resolve for routine clinical applications (63).

Dynamic risk profiling.   The concept of dynamic risk profiling is intended to take into account time-dependent changes in both the presence and the power of risk markers. It is based on the hypothesis that markers such as remodeling after MI, anatomic properties of scarred areas, progression of disease, and variations in hemodynamic and electrophysiological substrates are active processes, and their predictive power for adverse events may change over time. Because of the dynamic nature of post-infarction pathophysiology, a low EF shortly after an acute MI may improve over time (especially if there has been an intervention) (89,90), or an EF >35% may deteriorate over time as a result of remodeling or recurrent ischemic injury. It is, therefore, intuitively treacherous to accept a priori that a single measurement at an ill-defined point in time is necessarily a durable predictor of either low or high long-term risk at some future point in time. Since the stability of risk markers over time has not been systematically studied in the ICD trials, the potential value of repeated measures as a strategy for dynamic risk profiling will require further research.

Additional markers under study.   Reliance on EF as a sole or dominant indicator for ICD implantation has been challenged (88) and debated (91,92), and efforts are under way to identify alternative measures of risk that have independent or added predictive power. These include microvolt T-wave alternans (93), contrast magnetic resonance imaging for imaging the post-infarct anatomy and border zone (94,95), measures of QT variability (96), heart rate variability methods (97–99), familial clustering of SCD as the first expression of CAD (100–102), and the potential for genetic risk profiling (103). None of these have yet worked their way into general clinical applications. For some, available studies have not yet confirmed a generalizable value, and others are still in their infancy.

	Risk Stratification and Economic Impact

Top Abstract Evolution of the ICD Randomized Trial Support for... Secondary Prevention Trials Primary Prevention of SCD... ICDs for Prevention of... ICD Indications in Less... Limitations of Clinical Trial... The Low Risk-High Number... New Risk Markers and... Risk Stratification and Economic... Conclusions References

 
The funding paradox.   While clinical investigators, practicing physicians, and patients focus primarily on the risk-benefit equation for evaluating the applicability of clinical research to the practice of medicine, other segments of society add a third dimension—cost—to the equation. The expanded equation, risk-benefit-cost, has become increasingly visible to physicians as major trials now commonly include cost-efficacy studies as part of the research design and outcome statements. Such studies, while increasingly important to a financially stressed health care delivery system, appear to have had little impact on health care practice attitudes.

The economic challenges linked to ICD therapy are defined by the facts that ICDs provide reliable therapy, for which the cost is high and the indications are inefficient, as a consequence of limitations of clinical trial designs and observational data. Cost-effectiveness analyses have suggested differing levels of benefit, some falling within accepted ranges for cost-effective medical therapies and others falling outside those ranges (72,104–109). Levels of benefit related to cost are expressed in terms of variables such as length of extended life, complications, need for interim hospitalizations, and most important, the ability to identify the most suitable individual candidates.

The multiplier effect and economic impact.   The impact of ICDs on medical economics is driven by the integration of individual and group efficiencies, which should be adjusted for a multiplier effect based upon prevalence of disease. ICD therapy that is not cost effective by standard criteria, but intended for a rare disorder such as long–QT-interval syndrome, will place a limited economic burden on society because of the infrequency of the disease. In contrast, a common disorder with inefficient guidelines, in which the multiplier effect is large, can have significant economic impact. As an example, the adjustments in CMS approvals after publication of the SCD-HeFT study results (65) for patients in primary prevention categories of ischemic and nonischemic heart disease was estimated to have a potential economic impact of as much as $10 to $15 billion for initial implants only. This was based upon estimates of disease prevalence and then-current costs of ICDs (66). The inefficiencies in ICD prescription, particularly for primary prevention after MI, are reflected in appropriate shock rates of only 20% to 30% and relatively low survival benefits (Fig. 6) (110), as discussed earlier. These limitations derive from restrictions in the designs of clinical trial designs because of funding limitations. The cumulative direct cost (exclusive of ICDs) for the major trials underpinning the primary prevention indications was <$120 million (personal communication with the principle investigators of MADIT, MUSTT, MADIT-II, SCD-HeFT, and DINAMIT, October 2008). Even if the cost of defibrillators are included (estimated cost based on 2,159 patients receiving ICD devices at $30,000 per initial implant = $65 million), and primary prevention indications derived from these study designs were implemented in only one-third of the estimated number of candidates, the initial cost to the health care delivery system would be >25 times the cumulative 1-time expenditure for the clinical trials. Further, additional candidates are added into the health care pool annually.

View larger version (10K): [in this window] [in a new window] [Download PPT slide]   Figure 6 Comparison of Appropriate ICD Discharge Rate and Survival Benefit From MADIT II The survival curve demonstrates the probability of appropriate implantable cardioverter-defibrillator (ICD) therapy at 1, 2, and 3 years of follow-up. The insert demonstrates the excess mortality among control patients without ICDs at the same 3 points in time. These figures demonstrate that appropriate ICD discharges cannot be considered a surrogate for survival, and do not accurately indicate the magnitude of benefit expected from ICD recipients. VT/VF = ventricular tachycardia/fibrillation. Modified, with permission, from Moss AJ et al. (110).

For the future, those of us involved in clinical research and health care delivery, including clinicians and clinical investigators, the insurance industry, funding agencies, and the biomedical manufacturing industries, must work on a resolution of the problem of appropriate funding for clinical research, for both ICDs and other new therapies that are on the horizon. As we learned in the 1980s, failure to consider and address the economic context of our actions will leave us without a meaningful voice as society addresses these issues through other channels (111,112). A societal revolution against perceived excesses or inefficiencies, once started, will be beyond control by any elements of the medical complex (111), and political forces will ultimately prevail.

	Conclusions

Top Abstract Evolution of the ICD Randomized Trial Support for... Secondary Prevention Trials Primary Prevention of SCD... ICDs for Prevention of... ICD Indications in Less... Limitations of Clinical Trial... The Low Risk-High Number... New Risk Markers and... Risk Stratification and Economic... Conclusions References

 
ICDs are reliable medical devices that have the potential to add quality years of life for appropriate candidates. There are scientifically-derived guidelines for their prescription that are limited by the scope of the clinical trials and observational data available. Further studies on risk profiling are needed, but in the interim, practicing physicians should recommend devices to their individual patients based upon available data, which they should interpret in the light of individual patient profiles and their patients' preferences.

	Footnotes

 
Dr. Myerburg is supported in part by a grant from the Leducq Foundation (Network on Sudden Cardiac Death), by the Florida Heart Research Foundation, and by the American Heart Association Chair in Cardiovascular Research at the University of Miami Miller School of Medicine; he has also received consulting fees during the past 24 months from Boston Scientific Corporation, Proctor and Gamble, GlaxoSmithKline Pharmaceuticals, and Sanofi-Aventis, and lecture fees from Boston Scientific Corporation, General Electric Company, and St. Jude Medical Corporation. Dr. Reddy has received consulting fees and grants from St. Jude, and speaker honoraria from Medtronic and Boston Scientific.

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Top Abstract Evolution of the ICD Randomized Trial Support for... Secondary Prevention Trials Primary Prevention of SCD... ICDs for Prevention of... ICD Indications in Less... Limitations of Clinical Trial... The Low Risk-High Number... New Risk Markers and... Risk Stratification and Economic... Conclusions References

 
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