Symptomatic burden as an endpoint to evaluate interventions in patients with atrial fibrillation

CREATIVE CONCEPTS

Symptomatic burden as an endpoint to evaluate interventions in patients with atrial fibrillation Dawood Darbar, MD, Dan M. Roden, MD From the Divisions of Clinical Pharmacology and Cardiovascular Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee. Management of patients with atrial fibrillation (AF) is clinically challenging and has led to the development of new pharmacologic and nonpharmacologic therapies. However, no clear consensus on optimal endpoints for defining responses to therapy exists. This paradox arises largely because symptoms, often used to gauge efficacy of interventions, have not been well correlated with long-term “hard” endpoints such as stroke and death. One widely used symptom-based metric is “time to first symptomatic AF episode,” but this correlates poorly with frequency of symptomatic episodes. Similarly, although quality-of-life (QOL) measures have been used, the precise and unbiased assessment of QOL is difficult to define and measure. The availability of implantable devices capable of monitoring and recording all AF episodes has made the accurate determination of total time in AF (“burden”) possible. However, QOL tools and formal measures of AF burden do not correlate well, suggesting that measures of subjective well-being are important adjunct measures to conventional measures of disease severity when evaluating the therapeutic efficacy of treatments for AF. Although measurement of total AF burden requires invasive monitoring, symptomatic AF burden (defined by frequency, duration and severity of symptoms) can be determined in all patients with symptomatic AF and may serve as a valid endpoint, as elimination of symptoms is a common and realistic therapeutic goal. Therefore, we propose an algorithm to quantify symptomatic AF burden as an endpoint in clinical trials. KEYWORDS Atrial fibrillation; Therapies; Endpoints; Burden (Heart Rhythm 2005;2:544 –549) © 2005 Heart Rhythm Society. All rights reserved.

Introduction Atrial fibrillation (AF), the most common arrhythmia in clinical practice, is associated with significant morbidity and mortality and with consumption of health care resources. Management of patients with AF is a significant challenge that is being met with the development of new pharmacologic and nonpharmacologic therapies. Recent randomized trials in minimally symptomatic patients, comparing strategies for rate control versus those for maintenance of rhythm for the management of AF, argued against vigorous attempts to maintain sinus rhythm.1–3 However, in such trials, patients maintaining sinus rhythm have improved outcomes, and many patients are highly symptom-

This work was supported by NIH Grant HL-65962 to Dr. Roden. Address reprint requests and correspondence: Dr. Dawood Darbar, Division of Cardiovascular Medicine, Vanderbilt University School of Medicine, Room 383, Preston Research Building, Nashville, Tennessee 37323-6602. E-mail address: [email protected]. (Received November 1, 2004; accepted January 14, 2005.)

atic with AF.4 Thus, identifying patients in whom therapy is likely to be effective is highly desirable. Recent advances in our understanding of the molecular mechanisms in AF support the notion that variability in response to drug therapy may reflect differences in disease mechanisms, that is, it is possible that response to AF is highly heterogeneous because the arrhythmia itself is not a single pathophysiologic entity but rather represents a final arrhythmia response to a variety of disease pathways that culminate in AF. Indeed, work from our group and others increasingly support the idea that AF is a heterogeneous disorder with a significant genetic component.5–9 Furthermore, increasing evidence indicates activation of pathways not traditionally linked with arrhythmias may be intimately involved in the development of AF. For example, markers of inflammation, such as C-reactive protein, have been associated with increased risk of AF.10 Another “nontraditional” AF risk factor is renin-angiotensin-aldosterone activation. Retrospective as well as placebo-controlled trials of angiotensin-converting enzyme inhibitors and the angiotensin-receptor blocker irbesartan have been associated with a lower incidence of AF.11–13 A recent case-control study of

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doi:10.1016/j.hrthm.2005.01.028

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Symptomatic AF Burden as Endpoint

250 subjects with AF and 250 controls identified polymorphisms in this pathway as risk factors for AF.14 Hence, it is entirely possible that polymorphisms in these nontraditional pathways, implicated in the development of AF, may predict response to drug therapy. However, a key resource for testing hypotheses related to genetic heterogeneity in AF is a valid objective measure of the arrhythmia and its response to interventions.

Treatment objectives for AF and endpoint selection The traditional objectives for treatment of AF are restoration and maintenance of sinus rhythm; prevention of thromboembolic events, particularly stroke; prevention of deterioration of left ventricular function;15 and alleviation of symptoms. One of the key principles of endpoint selection is that the endpoint chosen should be directly connected to the objectives of therapy. In AF studies, this may include clinical events, such as death or stroke, ventricular function, and symptoms.16 Patient selection also has a profound impact on the choice of endpoints. For example, when studying AF in young patients with otherwise relatively healthy hearts who have no stroke risk factors, choosing death or stroke as an endpoint seems inappropriate. Although associations between AF and increased mortality have been described,17,18 the impact of AF itself (as opposed to concomitant disease) on mortality appears small.19 Therefore, endpoints beyond mortality are desirable. On the other hand, many therapies for AF can cause potentially fatal adverse effects, and the reported associations between AF and increased mortality may partly result from the therapies. Thus, mortality is an endpoint that should be tracked in any AF study. One of the principal clinical goals of therapy for AF management is improvement of patient symptoms. Although this can be accomplished by restoring sinus rhythm or by controlling the rapid and irregular ventricular response, objective data measuring such symptoms have been difficult to accumulate in clinical trials.1 To evaluate the efficacy of various interventions in AF, it is important to assess the symptom severity with a definable set of measures that can be reliably, reproducibly, and validly quantitated. This need to quantify AF symptoms is at the crux of evaluating treatments to control arrhythmia recurrence in patients with AF. However, there is a dearth of information about how to assess quantitatively or semi-quantitatively the degree of symptoms resulting from AF. Furthermore, there is no widely accepted clinical classification scheme as there is for anginal chest pain (e.g., Canadian Cardiovascular Society) or for dyspnea of congestive heart failure (e.g., New York Heart Association). Because many new therapies are being developed for AF, the need to develop a scheme for quantification of the symptoms that could be used for bedside management of patients and as a study endpoint is

545 becoming urgent, as was underscored by the participants of a recent symposium devoted to evaluating endpoints in AF trials.20

Clinical endpoints in AF studies “Hard” endpoints used in AF trials include mortality, stroke, heart failure, and hospitalization.16 Clearly, these endpoints impact the lives of AF patients, and a therapy’s capability to modify these endpoints is clinically useful. However, clinical endpoints have two drawbacks: (1) no measure of symptoms, which is what patients have, and (2) low frequency. Therefore, very large numbers of patients followed over many years must be studied to show a significant therapy-induced change. Furthermore, if too long a time is required to complete a study, the outcome must be evaluated in the context of newer therapies introduced after initiation of the trial. These limitations have led to interest in meaningful, so-called “surrogate” endpoints in AF trials. A surrogate endpoint is a “measurement that is used in therapeutic trials as a substitute for a clinically meaningful endpoint that is a direct measure of how a patient feels, functions, or survives and is expected to predict the effect of the therapy.”21 However, there are many examples, notably in cardiovascular medicine (e.g., Cardiac Arrhythmia Suppression Trial [CAST]22), where improvement in a surrogate endpoint was accompanied by worsening of clinical endpoint. The Atrial Fibrillation Follow-up Investigation of Rhythm Management (AFFIRM) study provides a more recent example where a surrogate for successful rhythm control (serial ECGs and patient symptoms) may have led to an increased risk of stroke in the rhythm control arm because of discontinuation of warfarin (Coumadin).1 A recent study similarly found that success rates for AF ablation would be overestimated if judged simply by symptomatic recurrence.23

Endpoints in rhythm control AF studies Time to first AF episode If maintenance of sinus rhythm is the ultimate therapeutic goal, then it might be valid to use an endpoint related to the recurrence of AF events during follow-up. One popular endpoint used is the “time to first symptomatic AF episode.”24 This endpoint initially was used in studies of the efficacy of antiarrhythmic drugs for paroxysmal supraventricular tachycardia.24,25 These studies observed that the distribution of successive recurrences of tachycardia (supraventricular/atrial fibrillation) followed a Poisson distribution, indicating each attack was independent of the previous one. This observation indicates the time to first recurrence starting at any period of time is an unbiased measure of arrhythmia frequency and may be a valid end-

546 point. As discussed later, however, other studies find different distributions with other implications for trial design. Advantages: One of the main advantages of this endpoint is that it is a continuous variable, making it easy to measure central tendency and variance and to compare two treatment groups statistically. Its popularity as a measure of drug efficacy in patients with AF also stems from ease of measurement, efficiency, and practicality. Disadvantages: For time to first recurrence to be a valid endpoint, a number of assumptions must be correct. It must not only correlate with the frequency of symptomatic AF episodes, but also a change in the frequency of symptomatic episodes should equate with net improvements in symptoms and quality of life (QOL). The latter, however, remains to be determined. It is possible that a patient’s QOL is not related to the frequency of symptomatic episodes but to the total duration and severity of symptoms during AF episodes. The second assumption is that the time to first symptomatic recurrence is a valid representation of the frequency of the episodes. For this assumption to be valid, symptomatic AF must arise independently and according to a Poisson distribution. However, some investigators have observed that AF events frequently occur in clusters, and most recent studies suggest that time to first symptomatic AF recurrence is not a valid representation of the frequency of all AF episodes.26 –28 In addition, data from atrial remodeling in AF suggest that episodes of persistent AF are more dependent on the time from the previous event.29 Therefore, while time to first symptomatic AF episode may be useful in paroxysmal AF, it seems less likely to be a valid endpoint for persistent AF. Furthermore, relying solely on time to first recurrence may fail to capture other important endpoints: a 7-day episode of AF as a first event after initiating an intervention may be more deleterious (in terms of symptoms, stroke, and heart failure risk) than a 1-hour episode. Although clustering of AF episodes questions the validity of time to first recurrence as an endpoint in AF studies, it may provide insight into mechanisms of early recurrences in AF. A recent study showed that recurrence of AF after electrical cardioversion clusters in the first few weeks with a mode at day 5 and the degree of AF clustering was predictive of cardioversion success.30 The AF ablation literature also suggests that early recurrence of AF is not always predictive of long-term recurrence of AF after ablation.31 Therefore, utility of time to first symptomatic recurrence not only may enhance our understanding of the molecular mechanisms underlying early recurrence of AF but also may identify novel therapeutic strategies for the prevention and treatment of persistent AF.

Device-based measurements Recent technologic advances in pacemaker telemetry have made possible an accurate determination of the proportion of time a patient with paroxysmal AF is in AF and have led to the concept of AF burden. Total AF burden is defined as

Heart Rhythm, Vol 2, No 5, May 2005 the total duration of all atrial tachyarrhythmias divided by total follow-up time.32 Advantages: The measurement of total AF burden includes symptomatic and asymptomatic episodes. Because some reports place the ratio of asymptomatic to symptomatic episodes as high as 12:1 in patients with symptomatic paroxysmal AF, the assessment of symptomatic episodes alone would greatly underestimate the total burden.33 Another advantage of measurement of total AF burden over other endpoints is that it is objective and not subject to investigator bias. Furthermore, the sampling error introduced by relying on patient symptoms or episodic monitoring is eliminated. A clinical trial using AF burden as an endpoint likely would also require a smaller sample size and shorter follow-up time compared to a trial with clinical endpoints of mortality or stroke. Disadvantages: AF burden is a surrogate and as such needs to be calibrated carefully against clinically important endpoints. It is important to recognize that, similar to time to first recurrence, AF burden is most likely to be a helpful measurement in patients with paroxysmal AF rather than persistent AF. Another drawback is that pacemaker telemetry data are biased by patient selection and thus will not apply to patients who do not have a bradycardia indication for pacing. In the Vanderbilt AF Registry, 12% of patients (54/458) have a device implanted capable of determining AF burden. Nonimplantable external recorders that can be worn for 1 week to 1 month and have the capability to diagnose and store AF information are being developed and could play an important role in evaluating efficacy of drug therapy for AF in the future.

QOL as an endpoint for AF trials QOL measures have often been used as an endpoint to assess efficacy of therapeutic interventions on symptomatic conditions, as has been done in AF trials. These measures relate to patients’ subjective perception of illness and incorporate treatment factors, such as drug-related side effects, biologic factors (severity and symptoms), and psychological and social factors, all of which impact perceived well-being and QOL. QOL scales can be generic, such as the ShortForm-36 (SF-36), or disease specific. The only AF diseasespecific scales for which there is any validation are those designed for assessing symptoms. The Symptom Checklist, shortened to eight AF-specific symptoms, has been validated in two studies.34,35 The University of Toronto AF Symptom Scale attempts to measure AF burden (based on frequency, duration, and severity) and some measures of QOL and health utilization.36 Advantages: QOL data attempt to provide not only a measure of the effect of an illness on a patient’s perception of his/her QOL but also morbidity associated with therapeutic interventions. However, traditional endpoints are insensitive to these effects and thus may be limited. Because one of the principal goals of therapy of AF management is improvement of patient symptoms, QOL is an important

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Symptomatic AF Burden as Endpoint

and potentially quantifiable endpoint for efficacy in AF studies. QOL tools are generally self-administered questionnaires that can be optically scanned directly into databases, enhancing efficiency and decreasing data entry sources of error. Although few data evaluating the comparative efficacy of drug therapy on QOL outcomes in AF are available, a substudy of the Canadian Trial of Atrial Fibrillation (CTAF) did assess the effect of antiarrhythmic treatment (amiodarone vs sotalol or propafenone) on patient-perceived QOL (as assessed by SF-36, Symptom Checklist, and AF Severity Score).36 This study found that all patients got better over time, and those patients who had recurrence of AF fared worse on measures of global well-being and symptom checklist frequency regardless of assigned therapy.36 Thus, measures of subjective well-being appear to be important adjunct measures, in addition to conventional measures of disease severity, such as frequency or duration of AF attacks, when assessing therapeutic efficacy of treatments of AF. Disadvantages: Interview-administered approaches decrease the amount of missing data but at the cost of creating respondent bias. The precise and unbiased assessment of QOL is very difficult, difficult both to define and to measure. Other concerns with the use of QOL as an endpoint in AF studies are related to the distinction of generic vs specific QOL scales. Generic scales allow comparison across different disease states and generally have more robust normative datasets available. Diseasespecific scales may enhance the sensitivity of the measure but often lack adequate assessment of the validity of the instrument. For scales to be useful, they must be valid, reliable, and responsive. Many validated generic QOL instruments are available,37 but the Symptom Checklist and the AF Severity Scale are the only validated AF disease-specific scales.34,35,38 Another drawback to using QOL as an endpoint for AF studies is that the correlation of QOL measures and formal measures of AF burden is either poor or unknown. QOL tools, although relevant, may not be as precise as traditional outcomes measures, such as time to first symptomatic recurrence of AF. There is a need to use validated instruments that are sensitive to any intervention under study.

Is symptomatic AF burden an appropriate endpoint for evaluating interventions to control arrhythmia recurrence in AF patients? In the current ACC/AHA/ESC guidelines for management of AF, “disabling” symptoms are the criterion for the initial choice of rhythm control approach over the rate control approach.39 Therefore, symptomatic AF burden (defined by frequency, duration, and severity of symptoms) may serve as a valid endpoint, as elimination of symptoms is a common and realistic goal in this patient population. However,

547 Table 1 burden*

Algorithm for scoring atrial fibrillation symptomatic

Severity parameter AF frequency (higher scores denote more frequent AF)

AF duration (higher scores denote AF of longer duration)

AF severity (of most recent episode)

Scoring Less than once a year 1 About once a year 2 About 2– 4 times a year 3 About once a month 4 About twice a month 5 About once a week 6 About 2–3 times a week 7 About 4 –5 times a week 8 Daily or almost daily 9 More than once a day 10 A few minutes 1 ⬍30 minutes 2 30 – 45 minutes 3 About ⬍1 hour 4 About 1– 4 hours 5 About 5–12 hours 6 About 13–24 hours 7 About 1–3 days 8 About 4 –7 days 9 ⬎7 days 10 1 ⫽ not at all severe 1–10 10 ⫽ extremely severe

AF ⫽ atrial fibrillation.

*Modified from University of Toronto Atrial Fibrillation Severity Scale.36 it must be emphasized that symptomatic AF burden is not just a “surrogate” for some other clinical outcome, such as stroke or death; it is, per se, an important outcome measure by itself. We propose measuring symptomatic AF burden using an algorithm for scoring the frequency, duration, and severity of symptoms (Table 1). The algorithm is a modification of the University of Toronto AF Severity Scale.36,40 The AF burden scale has been modified by combining the three measures of severity (each of which contributes equally to the AF burden score [each measure ranging from 1–10]) to yield scores ranging from 3 to 30. The relationship of symptomatic burden defined in this fashion to the total AF burden is unknown and should be the subject of further study, as should be weighting among the three contributing measures of severity. We believe this approach holds some promise as a reasonable index of endpoint that is realistic from a design and from a patient symptom point of view. It may serve as a suitable measure of drug efficacy and may be used to classify clinical phenotypes, including response to antiarrhythmic drug therapy, in patients with AF. Advantages: A major advantage of using symptomatic AF burden as an endpoint is that it is easy to measure, it is objective, and it can be measured in every patient. A substudy of the CTAF showed that symptomatic AF burden (defined slightly differently) was associated with different rates of arrhythmia recurrence than in the parent study.41 We and others have used symptomatic AF burden as an endpoint to assess response to antiarrhythmic therapy after catheter ablation of AF.42-44 The ACC/AHA Clinical Data

548 Standards for AF published in 2004 also have advocated evaluating symptomatic AF burden using a similar scoring system based on frequency, duration, and severity of symptoms during AF.45 In the AFFIRM study, response to antiarrhythmic drug therapy also was evaluated based on the frequency and duration of AF episodes.1 Limitations of symptomatic AF burden: Measurement of symptomatic AF burden requires that the patient keep records of (1) when the symptoms begin and end and (2) symptom severity; hence, the method is prone to patient sampling error. Although asymptomatic episodes of AF are not measured when evaluating symptomatic burden, antiarrhythmic drugs may decrease the occurrence of asymptomatic AF.46 The correlation between symptomatic and asymptomatic episodes and its relationship with total AF burden remains to be determined. The dangers of using symptomatic AF burden as a surrogate for “hard” endpoints, such as stroke, were discussed earlier.1,23 Although the proposed algorithm for scoring symptomatic AF burden has not been formally assessed, it is based on the validated University of Toronto AF Severity Scale.36,40 Our modification of the AF Severity Scale is simple and easy to use. An AF burden score can be readily obtained at each outpatient clinic visit from all patients treated with interventions aimed at preventing recurrences of AF. However, its applicability to an “ablate and pace” strategy for management of AF remains uncertain, although many studies have shown that this approach consistently improves symptoms.47,48 Ultimately, however, whether the proposed algorithm will be used at the bedside by busy clinicians for evaluating response to antiarrhythmic therapy remains to be determined.

Conclusion Development of meaningful endpoints is imperative to evaluate and compare the therapeutic efficacy of new interventions used for treatment of AF. The paradigm for the design of most recent AF trials evaluating treatments to control arrhythmia recurrence has been measurement of time to first recurrence. However, this is a somewhat artificial measure that correlates poorly with the frequency of AF episodes. Although advances in pacemaker telemetry technology now permit measurement of total AF burden, validation with clinical endpoints still is required. Accordingly, we advocate assessing the severity of arrhythmia recurrence in AF trials by measurement of symptomatic AF burden (as calculated by a composite, equally weighted measure of average AF frequency, duration, and severity). The score is easy to use and objective. Therefore, an AF burden score may serve as a valid and meaningful endpoint for evaluating treatments for control of arrhythmia recurrence in patients with AF.

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References 1. Wyse DG, Waldo AL, DiMarco JP, Domanski MJ, Rosenberg Y, Schron EB, Kellen JC, Greene HL, Mickel MC, Dalquist JE, Corley SD. A comparison of rate control and rhythm control in patients with atrial fibrillation. N Engl J Med 2002;347:1825–1833. 2. Hohnloser SH, Kuck KH, Lilienthal J. Rhythm or rate control in atrial fibrillation—Pharmacological Intervention in Atrial Fibrillation (PIAF): a randomised trial. Lancet 2000;356:1789 –1794. 3. Van Gelder IC, Hagens VE, Bosker HA, Kingma JH, Kamp O, Kingma T, Said SA, Darmanata JI, Timmermans AJ, Tijssen JG, Crijns HJ. A comparison of rate control and rhythm control in patients with recurrent persistent atrial fibrillation. N Engl J Med 2002;347: 1834 –1840. 4. Corley SD, Epstein AE, DiMarco JP, Domanski MJ, Geller N, Greene HL, Josephson RA, Kellen JC, Klein RC, Krahn AD, Mickel M, Mitchell LB, Nelson JD, Rosenberg Y, Schron E, Shemanski L, Waldo AL, Wyse DG. Relationships between sinus rhythm, treatment, and survival in the Atrial Fibrillation Follow-Up Investigation of Rhythm Management (AFFIRM) Study. Circulation 2004;109:1509 –1513. 5. Darbar D, Herron KJ, Ballew JD, Jahangir A, Gersh BJ, Shen WK, Hammill SC, Packer DL, Olson TM. Familial atrial fibrillation is a genetically heterogeneous disorder. J Am Coll Cardiol 2003;41:2185– 2192. 6. Ellinor PT, Shin JT, Moore RK, Yoerger DM, MacRae CA. Locus for atrial fibrillation maps to chromosome 6q14 –16. Circulation 2003; 107:2880 –2883. 7. Brugada R, Tapscott T, Czernuszewicz GZ, Marian AJ, Iglesias A, Mont L, Brugada J, Girona J, Domingo A, Bachinski LL, Roberts R. Identification of a genetic locus for familial atrial fibrillation. N Engl J Med 1997;336:905–911. 8. Fox CS, Parise H, D’Agostino RB Sr, Lloyd-Jones DM, Vasan RS, Wang TJ, Levy D, Wolf PA, Benjamin EJ. Parental atrial fibrillation as a risk factor for atrial fibrillation in offspring. JAMA 2004;291: 2851–2855. 9. Oberti C, Wang L, Li L, Dong J, Rao S, Du W, Wang Q. Genomewide linkage scan identifies a novel genetic locus on chromosome 5p13 for neonatal atrial fibrillation associated with sudden death and variable cardiomyopathy. Circulation 2004;110:3753–3759. 10. Aviles RJ, Martin DO, Apperson-Hansen C, Houghtaling PL, Rautaharju P, Kronmal RA, Tracy RP, Van Wagoner DR, Psaty BM, Lauer MS, Chung MK. Inflammation as a risk factor for atrial fibrillation. Circulation 2003;108:3006 –3010. 11. Madrid AH, Bueno MG, Rebollo JM, Marin I, Pena G, Bernal E, Rodriguez A, Cano L, Cano JM, Cabeza P, Moro C. Use of irbesartan to maintain sinus rhythm in patients with long-lasting persistent atrial fibrillation: a prospective and randomized study. Circulation 2002;106: 331–336. 12. Pedersen OD, Bagger H, Kober L, Torp-Pedersen C. Trandolapril reduces the incidence of atrial fibrillation after acute myocardial infarction in patients with left ventricular dysfunction. Circulation 1999; 100:376 –380. 13. Vermes E, Tardif JC, Bourassa MG, Racine N, Levesque S, White M, Guerra PG, Ducharme A. Enalapril decreases the incidence of atrial fibrillation in patients with left ventricular dysfunction: insight from the Studies Of Left Ventricular Dysfunction (SOLVD) trials. Circulation 2003;107:2926 –2931. 14. Tsai CT, Lai LP, Lin JL, Chiang FT, Hwang JJ, Ritchie MD, Moore JH, Hsu KL, Tseng CD, Liau CS, Tseng YZ. Renin-angiotensin system gene polymorphisms and atrial fibrillation. Circulation 2004; 109:1640 –1646. 15. Hsu LF, Jais P, Sanders P, Garrigue S, Hocini M, Sacher F, Takahashi Y, Rotter M, Pasquie JL, Scavee C, Bordachar P, Clementy J, Haissaguerre M. Catheter ablation for atrial fibrillation in congestive heart failure. N Engl J Med 2004;351:2373–2383. 16. Wyse DG. Selection of endpoints in atrial fibrillation studies. J Cardiovasc Electrophysiol 2002;13:S47–S52.

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Symptomatic AF Burden as Endpoint

17. Dries DL, Exner DV, Gersh BJ, Domanski MJ, Waclawiw MA, Stevenson LW. Atrial fibrillation is associated with an increased risk for mortality and heart failure progression in patients with asymptomatic and symptomatic left ventricular systolic dysfunction: a retrospective analysis of the SOLVD trials. Studies of Left Ventricular Dysfunction. J Am Coll Cardiol 1998;32:695–703. 18. Wyse DG, Love JC, Yao Q, Carlson MD, Cassidy P, Greene LH, Martins JB, Ocampo C, Raitt MH, Schron E, Stamato NJ, Olarte A. Atrial fibrillation: a risk factor for increased mortality—An AVID registry analysis. J Interv Card Electrophysiol 2001;5:267–273. 19. Beyerbach DM, Zipes DP. Mortality as an endpoint in atrial fibrillation. Heart Rhythm 2004;1:8 –19. 20. Mehra R, Wyse GD. Overview of symposium: outcomes in AF trials. Heart Rhythm 2004;1:1–2. 21. Temple R. Are surrogate markers adequate to assess cardiovascular disease drugs? JAMA 1999;282:790 –795. 22. Echt DS, Liebson PR, Mitchell LB, Peters RW, Obias-Manno D, Barker AH, Arensberg D, Baker A, Friedman L, Greene HL. Mortality and morbidity in patients receiving encainide, flecainide, or placebo. The Cardiac Arrhythmia Suppression Trial. N Engl J Med 1991;324: 781–788. 23. Karch MR, Zrenner B, Deisenhofer I, Schreieck J, Schmitt C. Difference between symptom-free and recurrence-free survival after either circumferential or segmental pulmonary vein ablation of atrial fibrillation (abstr). Circulation 2004;110:SIII-459. 24. Pritchett EL, Smith MS, McCarthy EA, Lee KL. The spontaneous occurrence of paroxysmal supraventricular tachycardia. Circulation 1984;70:1– 6. 25. Greer GS, Wilkinson WE, McCarthy EA, Pritchett EL. Random and nonrandom behavior of symptomatic paroxysmal atrial fibrillation. Am J Cardiol 1989;64:339 –342. 26. Rose MS, Gillis AM, Sheldon RS. Evaluation of the bias in using the time to the first event when the inter-event intervals have a Weibull distribution. Stat Med 1999;18:139 –154. 27. Kaemmerer WF, Rose MS, Mehra R. Distribution of patients’ paroxysmal atrial tachyarrhythmia episodes: implications for detection of treatment efficacy. J Cardiovasc Electrophysiol 2001;12:121–130. 28. Shehadeh LA, Liebovitch LS, Wood MA. Temporal patterns of atrial arrhythmia recurrences in patients with implantable defibrillators: implications for assessing antiarrhythmic therapies. J Cardiovasc Electrophysiol 2002;13:303–309. 29. Nattel S, Li D. Ionic remodelling in the heart: pathophysiological significance and new therapeutic opportunities for atrial fibrillation. Circ Res 2000;87:440 – 447. 30. Van Den Berg MP, Van Noord T, Brouwer J, Haaksma J, Van Veldhuisen DJ, Crijns HJ, Van Gelder IC. Clustering of RR intervals predicts effective electrical cardioversion for atrial fibrillation. J Cardiovasc Electrophysiol 2004;15:1027–1033. 31. Oral H, Knight BP, Ozaydin M, Tada H, Chugh A, Hassan S, Scharf C, Lai SW, Greenstein R, Pelosi F Jr, Strickberger SA, Morady F. Clinical significance of early recurrences of atrial fibrillation after pulmonary vein isolation. J Am Coll Cardiol 2002;40:100 –104. 32. Friedman PA, Ip JH, Jazayeri M, Lobban JH, Olshansky B, Zhou D, Knowles T, Euler DE. The impact of atrial prevention and termination therapies on atrial tachyarrhythmia burden in patients receiving a dual-chamber defibrillator for ventricular arrhythmias. J Interv Card Electrophysiol 2004;10:103–110. 33. Page RL, Wilkinson WE, Clair WK, McCarthy EA, Pritchett EL. Asymptomatic arrhythmias in patients with symptomatic paroxysmal atrial fibrillation and paroxysmal supraventricular tachycardia. Circulation 1994;89:224 –227. 34. Maglio C SJ, Paquette M, Dorian P, Bygrave A, Wood K, Ayers GM. Measuring quality of life and symptom severity in patients with atrial fibrillation. Pacing Clin Electrophysiol 1998;21:839. 35. Newman DM, Dorian P, Paquette M, Sulke N, Gold MR, Schwartzman DS, Schaaf K, Wood K, Johnson L. Effect of an implantable

549

36.

37. 38. 39.

40.

41.

42.

43.

44.

45.

46.

47.

48.

cardioverter defibrillator with atrial detection and shock therapies on patient-perceived, health-related quality of life. Am Heart J 2003;145:841– 846. Dorian P, Paquette M, Newman D, Green M, Connolly SJ, Talajic M, Roy D. Quality of life improves with treatment in the Canadian Trial of Atrial Fibrillation. Am Heart J 2002;143:984 –990. Newman D. Quality of life as an endpoint for atrial fibrillation research: pitfalls and practice. Heart Rhythm 2004;1:20 –26. Jenkins LS, Bubien RS. Quality of life in patients with atrial fibrillation. Cardiol Clin 1996;14:597– 606. Fuster V, Ryden LE, Asinger RW, Cannom DS, Crijns HJ, Frye RL, Halperin JL, Kay GN, Klein WW, Levy S, McNamara RL, Prystowsky EN, Wann LS, Wyse DG, Gibbons RJ, Antman EM, Alpert JS, Faxon DP, Gregoratos G, Hiratzka LF, Jacobs AK, Russell RO, Smith SC Jr, Alonso-Garcia A, Blomstrom-Lundqvist C, de Backer G, Flather M, Hradec J, Oto A, Parkhomenko A, Silber S, Torbicki A. ACC/AHA/ ESC Guidelines for the Management of Patients With Atrial Fibrillation: Executive Summary A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and the European Society of Cardiology Committee for Practice Guidelines and Policy Conferences (Committee to Develop Guidelines for the Management of Patients With Atrial Fibrillation) Developed in Collaboration With the North American Society of Pacing and Electrophysiology. Circulation 2001;104:2118 –2150. Dorian PJW, Paquette M, Newman D, Wood K, Ayers GM, Camm J, Akhtar M, Luderitz B. The impairment of health-related quality of life in patients with intermittent atrial fibrillation: implications for the assessment of investigational therapy. J Am Coll Cardiol 2000;36: 1303–1309. Dorian P, Mangat I. Quality of life variables in the selection of rate versus rhythm control in patients with atrial fibrillation: observations from the Canadian Trial of Atrial Fibrillation. Card Electrophysiol Rev 2003;7:276 –279. Oral H, Knight BP, Tada H, Ozaydin M, Chugh A, Hassan S, Scharf C, Lai SW, Greenstein R, Pelosi F Jr, Strickberger SA, Morady F. Pulmonary vein isolation for paroxysmal and persistent atrial fibrillation. Circulation 2002;105:1077–1081. Oral H, Scharf C, Chugh A, Hall B, Cheung P, Good E, Veerareddy S, Pelosi F Jr, Morady F. Catheter ablation for paroxysmal atrial fibrillation: segmental pulmonary vein ostial ablation versus left atrial ablation. Circulation 2003;108:2355–2360. Darbar D, Asirvatham S, Munger TM, Hammill SC, Packer DL. Differential response to antiarrhythmic drug therapy in focal-triggered substrate mediated atrial fibrillation following failed ablation. Pacing Clin Electrophysiol 2001;24:657– 658. McNamara RL, Brass LM, Drozda JP Jr, Go AS, Halperin JL, Kerr CR, Levy S, Malenka DJ, Mittal S, Pelosi F Jr, Rosenberg Y, Stryer D, Wyse DG, Radford MJ, Goff DC Jr, Grover FL, Heidenreich PA, Peterson ED, Redberg RF. ACC/AHA key data elements and definitions for measuring the clinical management and outcomes of patients with atrial fibrillation: a report of the American College of Cardiology/ American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Data Standards on Atrial Fibrillation). Circulation 2004;109:3223–3243. Page RL, Tilsch TW, Connolly SJ, Schnell DJ, Marcello SR, Wilkinson WE, Pritchett EL. Asymptomatic or “silent” atrial fibrillation: frequency in untreated patients and patients receiving azimilide. Circulation 2003;107:1141–1145. Ozcan C, Jahangir A, Friedman PA, Patel PJ, Munger TM, Rea RF, Lloyd MA, Packer DL, Hodge DO, Gersh BJ, Hammill SC, Shen WK. Long-term survival after ablation of the atrioventricular node and implantation of a permanent pacemaker in patients with atrial fibrillation. N Engl J Med 2001;344:1043–1051. Wood MA, Brown-Mahoney C, Kay GN, Ellenbogen KA. Clinical outcomes after ablation and pacing therapy for atrial fibrillation. Circulation 2000;101:1138 –1144.