Anticoagulation and Atrial Fibrillation in the Bradycardia- Tachycardia Syndrome

Pauker, Stephen G.

doi:10.1177/0272989x8100100309

Cited by 36 publications

(4 citation statements)

References 11 publications

(15 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Before this analysis, it was unclear whether the heterogeneity in patients' aversion to stroke and to stroke prophylaxis 12,30,44 -49 would justify the use of preference-based atrial fibrillation guidelines and decisionmaking tools. 20,21,29,30,47,50 This uncertainty led to differences in atrial fibrillation guidelines, with some advocating preference-based therapy, at least in low-risk patients, 13,15,20,21,29,30,47 and others recommending warfarin therapy [51][52][53][54] but sometimes accompanied by the caution that "patients' preferences are of utmost importance." 14 Our analysis confirms the relevance of quality of life in the choice of antithrombotic therapy.…”

Section: Discussionmentioning

confidence: 99%

Cost-Effectiveness of Preference-Based Antithrombotic Therapy for Patients With Nonvalvular Atrial Fibrillation

Gage

Cardinalli

Owens

1998

Stroke

View full text Add to dashboard Cite

Background and Purpose-Recent atrial fibrillation guidelines recommend the incorporation of patient preferences into the selection of antithrombotic therapy. However, no trial has examined how incorporating such preferences would affect quality-adjusted survival or medical expenditure. We compared 10-year projections of quality-adjusted survival and medical expenditure associated with two atrial fibrillation treatment strategies: warfarin-for-all therapy versus preference-based therapy. The preference-based strategy prescribed whichever antithrombotic therapy, warfarin or aspirin, had the greater projected quality-adjusted survival. Methods-We used decision analysis stratified by the number of stroke risk factors (history of stroke, transient ischemic attack, hypertension, diabetes, or heart disease). The base case focused on compliant 65-year-old patients who had nonvalvular atrial fibrillation and no contraindications to antithrombotic therapy. Results-In patients whose only risk factor for stroke was atrial fibrillation, preference-based therapy improved projected quality-adjusted survival by 0.05 quality-adjusted life year (QALY) and saved $670. For patients who had atrial fibrillation and one additional risk factor for stroke, preference-based therapy improved quality-adjusted survival by 0.02 QALY and saved $90. In patients who had atrial fibrillation and multiple additional risk factors for stroke, preference-based therapy increased medical expenditures and did not improve quality-adjusted survival substantially.The benefits of preference-flexible therapy arose from the minority of patients who would have had a longer quality-adjusted survival if they had been prescribed aspirin rather than warfarin. Conclusions-As do risks of stroke and of hemorrhage, patients' preferences help to determine which antithrombotic therapy is optimal. Preference-based treatment should improve quality-adjusted survival and reduce medical expenditure in patients who have nonvalvular atrial fibrillation and not more than one additional risk factor for stroke. (Stroke.

show abstract

Section: Discussionmentioning

confidence: 99%

Cost-Effectiveness of Preference-Based Antithrombotic Therapy for Patients With Nonvalvular Atrial Fibrillation

Gage

Cardinalli

Owens

1998

Stroke

View full text Add to dashboard Cite

show abstract

“…Mean quality-adjusted duration has seen widespread application. For example, Weinstein and Stason [1976] model hypertension treatment; Beck and Pauker [1981] examine anticoagulation therapy; Hillner, Hollenberg and Pauker [1986] investigate estrogen for the prevention of osteoporosis; Plante, Piccirillo and Sofferman [1987] model cancer treatment; Mooney, Mushlin and Phelps [1990] study magnetic resonance imaging for multiple sclerosis.…”

Section: Stochastic Treesmentioning

confidence: 99%

Stochastic-Tree Models in Medical Decision Making

Hazen

Pellissier²,

Sounderpandian

1998

Interfaces

View full text Add to dashboard Cite

Abstract:The stochastic tree is a recently introduced generalization of the decision tree which allows the explicit depiction of temporal uncertainty, while still employing the familiar rollback procedure for decision trees. We offer in this paper an introduction to stochastic tree modeling and techniques involved in their application to medical treatment decisions. We also describe an application of these tools to the analysis of the decision to undergo a total hip replacement from the perspectives of an individual patient (via utility analysis) and of society (via cost-effectiveness analysis). For medical analyses, the most commonly used method for the formulation and display of discrete-time Markov chains is the Markov cycle tree developed by Hollenberg [1984]. Hazen [1992] introduced a continuous-time analog of the Markov-cycle tree, the stochastic tree, which combines features of decision trees [Raiffa 1968] and stochasticprocess transition diagrams. Stochastic tree diagrams not only can depict continuously distributed temporal uncertainties, but, like decision trees, can be rolled back to determine optimal decisions. This rollback procedure is an instance of the method of successive approximations from stochastic dynamic programming (Denardo [1982], Ross [1970]). It can be applied not only for risk-neutral objective functions, such as mean quality adjusted lifetime [Hazen 1992], but also for the calculation of expected utility .One of the first applications of stochastic tree modeling in medical decision making was an investigation of total hip replacement surgery for patients with severe osteoarthritis 4 (OA) of the hip. An estimated 120,000 hip replacements are performed per year in North America [Harris and Sledge 1990]. This decision is interesting from a number of points of view. Although total hip replacement surgery (total hip arthroplasty, THA) is the most successful procedure for patients with advanced arthritis of the hip, the treatment decision for an individual patient with this condition can be difficult. While the surgery offers the potential of increased quality of life, it carries additional risk of mortality and morbidity.From a societal perspective, given the increasing incidence of severe osteoarthritis of the hip, the growing demand for THA, and the high costs associated with the procedure, there is concern that a larger share of health care resources will be spent on THA in the future.Rising costs and attempts to improve the efficiency of health care delivery have stimulated the need for analyses that objectively examine the trade-offs between therapeutic benefits and expenditures. If the economic consequences of surgical interventions are included, procedures such as THA are particularly vulnerable to scrutiny for several reasons. First, it is an elective procedure. Second, its target population is largely geriatric. Third, it is an expensive, high-technology procedure. Finally, in terms of short-term costs alone, medical management would appear to represent a less expensive treatment...

show abstract

“…Note that total lifetime and total time spent in a particular state are instances of quality-adjusted duration with v(x) = 1 for the appropriate set of states x and v(x) = 0 for the complementary set, so a broad range of conventional measures is subsumed. For models using mean quality-adjusted duration, see for example Weinstein and Stason (1976), Beck and Pauker (1981), Hillner, Hollenberg and Pauker (1986), Plante, Piccirillo and Sofferman (1987), Roach et al (1988), Mooney, Mushlin and Phelps (1990).…”

Section: Transformation Of Stochastic Treesmentioning

confidence: 99%

Recursive Utility for Stochastic Trees

Hazen

Pellissier

1996

Operations Research

View full text Add to dashboard Cite

This work is important for several reasons. It is the first contribution to the literature on preference over risky time streams in which the utility structure is linked to specific and frequently used stochastic models (stochastic trees), and in which the utility structure is specifically designed to permit tractable methods of expected utility calculation (dynamic programming recursion). The stochastic tree structure with utility recursion is important because it extends the convenient graphical features of decision trees to the modeling of risky time streams. Such features include ease and clarity in model formulation and presentation, as well as a visual structure which suggests a computational method of solution (rollback). In the near term, this provides graphically intuitive model construction and evaluation capabilities for users who may be less familiar with stochastic modeling and algorithms, especially including users those in the medical community, for whom this tool was developed. The results of the paper characterize all possible recursive utility functions over stochastic trees, providing in the long term a basis for devising useful utility structures beyond what are discussed in the paper.

show abstract

Anticoagulation and Atrial Fibrillation in the Bradycardia- Tachycardia Syndrome

Cited by 36 publications

References 11 publications

Cost-Effectiveness of Preference-Based Antithrombotic Therapy for Patients With Nonvalvular Atrial Fibrillation

Cost-Effectiveness of Preference-Based Antithrombotic Therapy for Patients With Nonvalvular Atrial Fibrillation

Stochastic-Tree Models in Medical Decision Making

Recursive Utility for Stochastic Trees

Contact Info

Product

Resources

About