NCA - Cardiac Pacemakers: Single-Chamber and Dual-Chamber Permanent Cardiac Pacemakers (CAG-00063R3) - Decision Memo

Documented non-reversible symptomatic bradycardia due to sinus node dysfunction.Documented non-reversible symptomatic bradycardia due to second degree and/or third degree atrioventricular block.The following indications are non-covered since there is insufficient evidence to conclude that implanted permanent cardiac pacemakers, single chamber or dual chamber, are reasonable and necessary:Reversible causes of bradycardia such as electrolyte abnormalities, medications or drugs, and hypothermia.Asymptomatic first degree atrioventricular block.Asymptomatic sinus bradycardia.Asymptomatic sino-atrial block or asymptomatic sinus arrest.Ineffective atrial contractions (e.g., chronic atrial fibrillation or flutter, or giant left atrium) without symptomatic bradycardia.Asymptomatic second degree atrioventricular block of Mobitz Type I unless the QRS complexes are prolonged or electrophysiological studies have demonstrated that the block is at or beyond the level of the His Bundle (a component of the electrical conduction system of the heart).Syncope of undetermined cause.Bradycardia during sleep.Right bundle branch block with left axis deviation (and other forms of fascicular or bundle branch block) without syncope or other symptoms of intermittent atrioventricular block.Asymptomatic bradycardia in post-myocardial infarction patients about to initiate long-term beta-blocker drug therapy.Frequent or persistent supraventricular tachycardias, except where the pacemaker is specifically for the control of the tachycardia.A clinical condition in which pacing takes place only intermittently and briefly, and which is not associated with a reasonable likelihood that pacing needs will become prolonged.Medicare Administrative Contractors will determine coverage under section 1862(a)(1)(A) of the Social Security Act for any other indications for the implantation and use of single chamber or dual chamber cardiac pacemakers that are not specifically addressed in this national coverage determination.Appendix AGeneral Methodological Principles of Study DesignWhen making national coverage determinations, CMS evaluates relevant clinical evidence to determine whether or not the evidence is of sufficient quality to support a finding that an item or service falling within a benefit category is reasonable and necessary for the diagnosis or treatment of an illness or injury or to improve the functioning of a malformed body member. The overall objective for the critical appraisal of the evidence is to determine to what degree we are confident that: 1) the specific assessment questions can be answered conclusively; and 2) the intervention will improve health outcomes for patients.We divide the assessment of clinical evidence into three stages: 1) the quality of the individual studies; 2) the generalizability of findings from individual studies to the Medicare population; and 3) overarching conclusions that can be drawn from the body of the evidence on the direction and magnitude of the interventions potential risks and benefits.The methodological principles described below represent a broad discussion of the issues we consider when reviewing clinical evidence. However, it should be noted that each coverage determination has its unique methodological aspects.Assessing Individual StudiesMethodologists have developed criteria to determine weaknesses and strengths of clinical research. Strength of evidence generally refers to: 1) the scientific validity underlying study findings regarding causal relationships between health care interventions and health outcomes; and 2) the reduction of bias. In general, some of the methodological attributes associated with stronger evidence include those listed below.Use randomization (allocation of patients to either intervention or control group) in order to minimize bias.Use contemporaneous control groups (rather than historical controls) in order to ensure comparability between the intervention and control groups.Use prospective (rather than retrospective) studies to ensure a more thorough and systematical assessment of factors related to outcomes.Use larger sample sizes in studies to help ensure adequate numbers of patients are enrolled to demonstrate both statistically significant as well as clinically significant outcomes that can be extrapolated to the Medicare population. Sample size should be large enough to make chance an unlikely explanation for what was found.Use masking (blinding) to ensure patients and investigators do not know to which group patients were assigned (intervention or control). This is important especially in subjective outcomes, such as pain or quality of life, where enthusiasm and psychological factors may lead to an improved perceived outcome by either the patient or assessor.Regardless of whether the design of a study is a randomized controlled trial, a non-randomized controlled trial,  a cohort study or a case-control study, the primary criterion for methodological strength or quality is the extent to which differences between intervention and control groups can be attributed to the intervention studied. This is known as internal validity. Various types of bias can undermine internal validity. These include:Different characteristics between patients participating and those theoretically eligible for study but not participating (selection bias),Co-interventions or provision of care apart from the intervention under evaluation (performance bias),Differential assessment of outcome (detection bias), andOccurrence and reporting of patients who do not complete the study (attrition bias).In principle, rankings of research design have been based on the ability of each study design category to minimize these biases. A randomized controlled trial minimizes systematic bias (in theory) by selecting a sample of participants from a particular population and allocating them randomly to the intervention and control groups. Thus, in general, randomized controlled studies have been typically assigned the greatest strength, followed by non-RCTs and controlled observational studies. The design, conduct and analysis of trials are important factors as well. For example, a well designed and conducted observational study with a large sample size may provide stronger evidence than a poorly designed and conducted randomized controlled trial with a small sample size. The following is a representative list of study designs (some of which have alternative names) ranked from most to least methodologically rigorous in their potential ability to minimize systematic bias.Randomized controlled trialsNon-randomized controlled trialsProspective cohort studiesRetrospective case control studiesCross-sectional studiesSurveillance studies (e.g., using registries or surveys)Consecutive case seriesSingle case reportsWhen there are merely associations but not causal relationships between a studys variables and outcomes, it is important not to draw causal inferences. Confounding refers to independent variables that systematically vary with the causal variable. This distorts measurement of the outcome of interest because its effect size is mixed with the effects of other extraneous factors.  For observational, and in some cases randomized controlled trials, the method in which confounding factors are handled (either through stratification or appropriate statistical modeling) are of particular concern. For example, in order to interpret and generalize conclusions to our population of Medicare patients, it may be necessary for studies to match or stratify their intervention and control groups by patient age or co-morbidities.Methodological strength is, therefore, a multidimensional concept that relates to the design, implementation and analysis of a clinical study. In addition, thorough documentation of the conduct of the research, particularly study selection criteria, rate of attrition and process for data collection, is essential for CMS to adequately assess and consider the evidence.Generalizability of Clinical Evidence to the Medicare PopulationThe applicability of the results of a study to other populations, settings, treatment regimens and outcomes assessed is known as external validity. Even well-designed and well-conducted trials may not supply the evidence needed if the results of a study are not applicable to the Medicare population. Evidence that provides accurate information about a population or setting not well represented in the Medicare program would be considered but would suffer from limited generalizability.The extent to which the results of a trial are applicable to other circumstances is often a matter of judgment that depends on specific study characteristics, primarily the patient population studied (age, sex, severity of disease and presence of co-morbidities) and the care setting (primary to tertiary level of care, as well as the experience and specialization of the care provider).  Additional relevant variables are treatment regimens (dosage, timing and route of administration), co-interventions or concomitant therapies, and type of outcome and length of follow-up.The level of care and the experience of the providers in the study are other crucial elements in assessing a studys external validity. Trial participants in an academic medical center may receive more or different attention than is typically available in non-tertiary settings. For example, an investigators lengthy and detailed explanations of the potential benefits of the intervention and/or the use of new equipment provided to the academic center by the study sponsor may raise doubts about the applicability of study findings to community practice.  Given the evidence available in the research literature, some degree of generalization about an interventions potential benefits and harms is invariably required in making coverage determinations for the Medicare population. Conditions that assist us in making reasonable generalizations are biologic plausibility, similarities between the populations studied and Medicare patients (age, sex, ethnicity and clinical presentation) and similarities of the intervention studied to those that would be routinely available in community practice.A studys selected outcomes are an important consideration in generalizing available clinical evidence to Medicare coverage determinations. One of the goals of our determination process is to assess health outcomes. We are interested in the results of changed patient management not just altered management. These outcomes include resultant risks and benefits such as increased or decreased morbidity and mortality. In order to make this determination, it is often necessary to evaluate whether the strength of the evidence is adequate to draw conclusions about the direction and magnitude of each individual outcome relevant to the intervention under study. In addition, it is important that an interventions benefits are clinically significant and durable, rather than marginal or short-lived. Generally, an intervention is not reasonable and necessary if its risks outweigh its benefits.If key health outcomes have not been studied or the direction of clinical effect is inconclusive, we may also evaluate the strength and adequacy of indirect evidence linking intermediate or surrogate outcomes to our outcomes of interest.Assessing the Relative Magnitude of Risks and BenefitsGenerally, an intervention is not reasonable and necessary if its risks outweigh its benefits. Health outcomes are one of several considerations in determining whether an item or service is reasonable and necessary. For most determinations, CMS evaluates whether reported benefits translate into improved health outcomes. CMS places greater emphasis on health outcomes actually experienced by patients, such as quality of life, functional status, duration of disability, morbidity and mortality, and less emphasis on outcomes that patients do not directly experience, such as intermediate outcomes, surrogate outcomes, and laboratory or radiographic responses. The direction, magnitude and consistency of the risks and benefits across studies are also important considerations.Based on the analysis of the strength of the evidence, CMS assesses the relative magnitude of an intervention or technologys benefits and risk of harm to Medicare beneficiaries.Appendix BTable of TrialsAuthor, YearBaselinePrimary OutcomeSecondary OutcomesComplicationsConnolly, 2000Canadian Trial of Physiologic Pacing Investigators (CTOPP)single ventricular pacing (n = 1474) vs physiologic pacing [dual or atrial (5.2%), n = 1094]mean age = 73 years;59% men;sinoatrial node disease = 40%;AV block = 60%stroke or cv death;annual rate of stroke or cv death was 5.5% vs 4.9% respectively;RRR 9.5% 95% CI -10.5-25.7%; p = 0.33.mean follow-up=3 years.annual rate of all cause death 6.6% vs 6.3% respectively; RRR 0.9% 95%CI -18.1-16.8%; p=0.92.annual rate of atrial fib 6.6% vs 5.3%  respectively;RRR 18% 95% CI 0.3-32.6%; p = 0.05.any perioperative 3.8% vs 9.0% respectively; p < 0.001.Lamas, 1998Pacemaker Selection in the Elderly  (PASE)single vent chamber (n = 204) vs dual chamber programming (n = 203)mean age=76 years;60% men;sinus node 43%;AV block 49%health related QOL SF-36;improved significantly after pacemaker implantation (P < 0.001), but there were no differences between the two pacing modes in either the quality of lifedeath all causes 17% vs 16%; p = 0.95.stroke or death 19% vs 17%; p = 0.75.atrial fib 19% vs 17%; p = 0.80.complications not reported.Lamas, 2002Mode Selection Trial in Sinus Node Dysfunction (MOST)dual chamber (n = 1014) vs programming (ventricular n = 996)median age=74 years;52% men;sinus node dysfunctiondeath any cause or nonfatal stroke; 21.5% vs 23%, respectively;HR 0.93 95% CI 0.78-1.13; p = 0.48.median follow-up = 33 months.all death 19.7% vs 20.5% respectively, HR 0.97 95% CI 0.8-1.18.atrial fibrillation 21.4% vs 27.1% respectively, HR 0.79; 95% CI 0.66-0.94; p = 0.008.perioperative 30d complication rate 4.8% (all patients received dual chamber).