Cost-effectiveness of lung MRI in lung cancer screening.

Objectives: Recent studies with lung MRI (MRI) have shown high sensitivity (Sn) and specificity (Sp) for lung nodule detection and characterization relative to low-dose CT (LDCT). Using this background data, we sought to compare the potential screening performance of MRI vs. LDCT using a Markov model of lung cancer screening.

Evaluation of Accepting Kidneys of Varying Quality for Transplantation or Expedited Placement With Decision Trees.

Background: Underutilization of marginal-quality kidneys for transplantation produced ideas of expediting kidney placement for populations with decreased opportunities of receiving transplants. Such policies can be less efficacious for specific individuals and should be scrutinized until the decision-making for accepting marginal-quality organs, which has relied on experiential judgment, is better understood at the individual level. There exist rigorous tools promoting personalized decisions with useful and objective information.

Cost-effectiveness of Prophylactic Moisturization for Atopic Dermatitis.

Importance: Emerging evidence suggests that the use of moisturizers on newborns and infants (ie, from birth to 6 months of age) is potentially helpful in preventing the development of atopic dermatitis.

Objective: To investigate the cost-effectiveness of using a daily moisturizer as prevention against atopic dermatitis among high-risk newborns.

Design, Setting, And Participants: In a cost-effectiveness analysis, the average cost of total-body moisturization using 7 common moisturizers from birth to 6 months of age was determined for male and female infants.

A Common Rationale for Global Sensitivity Measures and Their Estimation.

Measures of sensitivity and uncertainty have become an integral part of risk analysis. Many such measures have a conditional probabilistic structure, for which a straightforward Monte Carlo estimation procedure has a double-loop form. Recently, a more efficient single-loop procedure has been introduced, and consistency of this procedure has been demonstrated separately for particular measures, such as those based on variance, density, and information value.

Simulation modeling of the impact of proposed new simultaneous liver and kidney transplantation policies.

Background: Increasing use of kidney grafts for simultaneous liver and kidney (SLK) transplants is causing concern about the most effective utilization of scarce kidney graft resources. This study evaluated the impact of implementing the proposed United Network for Organ Sharing SLK transplant policy on outcomes for end-stage liver disease (ESLD) and end-stage renal disease (ESRD) patients awaiting transplant.

Methods: A Markov model was constructed to simulate a hypothetical cohort of ESLD patients over a 30-year time horizon starting from age 50.

Comparative effectiveness of liver transplant strategies for end-stage liver disease patients on renal replacement therapy.

There are complex risk-benefit tradeoffs with different transplantation strategies for end-stage liver disease patients on renal support. Using a Markov discrete-time state transition model, we compared survival for this group with 3 strategies: simultaneous liver-kidney (SLK) transplantation, liver transplantation alone (LTA) followed by immediate kidney transplantation if renal function did not recover, and LTA followed by placement on the kidney transplant wait list. Patients were followed for 30 years from the age of 50 years.

NUTORC-a transdisciplinary health services and outcomes research team in transplantation.

The field of solid organ transplantation has historically concentrated research efforts on basic science and translational studies. However, there has been increasing interest in health services and outcomes research. The aim was to build an effective and sustainable, inter- and transdisciplinary health services and outcomes research team (NUTORC), that leveraged institutional strengths in social science, engineering, and management disciplines, coupled with an international recognized transplant program.

Comparative effectiveness of donation after cardiac death versus donation after brain death liver transplantation: Recognizing who can benefit.

Due to organ scarcity and wait-list mortality, transplantation of donation after cardiac death (DCD) livers has increased. However, the group of patients benefiting from DCD liver transplantation is unknown. We studied the comparative effectiveness of DCD versus donation after brain death (DBD) liver transplantation.

The value of environmental information without control of subsequent decisions.

The standard value of information approach of decision analysis assumes that the individual or agency that collects the information is also in control of the subsequent decisions based on the information. We refer to this situation as the "value of information with control (VOI-C)." This paradigm leads to powerful results, for example, that the value of information cannot be negative and that it is zero, when the information cannot change subsequent decisions.

Cohort decomposition for Markov cost-effectiveness models.

Cohort analysis is a widespread tool for computing expected costs and quality-adjusted life years (QALYs) in Markov models for medical cost-effectiveness analyses. Although not always explicitly identified, such models commonly have multiple simple factors, or components. In these, a health state consists of a multiple component vector, one component for each factor, and arbitrary combinations of components are possible.

Development of goal-sensitive health-related utility assessment procedures.

Purpose: To measure the degree to which people express willingness to trade life or health for nonmedical goals.

Method: In 3 studies, outpatients provided important life goals. In study 1, patients performed time-tradeoff between life-years and goal achievement and chose between states that varied in goal achievement, life expectancy, and disability; in study 2, patients made choices that traded off health state and goal achievement; in study 3, patients performed time-tradeoff assessments in 3 different goal achievement contexts.

Incorporating extrinsic goals into decision and cost-effectiveness analyses.

It has not been widely recognized that medical patients as individuals may have goals that are not easily expressed in terms of quality-adjusted life years (QALYs). The QALY model deals with ongoing goals such as reducing pain or maintaining mobility, but goals such as completing an important project or seeing a child graduate from college occur at unique points in time and do not lend themselves to easy expression in terms of QALYs. Such extrinsic goals have been posited as explanations for preferences inconsistent with the QALY model, such as unwillingness to trade away time or accept gambles.

Life goals and health decisions: what will people live (or die) for?

Objective: Quality of life may represent not just quality of health but also the degree to which an individual achieves personally meaningful extrinsic goals unrelated to life duration that are not incorporated in the standard quality-adjusted life year model. The objectives of this study are to develop a typology of life goals and explore whether goal type is related to willingness to consider trading life years or health for goals.

Design: .

Large-sample Bayesian posterior distributions for probabilistic sensitivity analysis.

In probabilistic sensitivity analyses, analysts assign probability distributions to uncertain model parameters and use Monte Carlo simulation to estimate the sensitivity of model results to parameter uncertainty. The authors present Bayesian methods for constructing large-sample approximate posterior distributions for probabilities, rates, and relative effect parameters, for both controlled and uncontrolled studies, and discuss how to use these posterior distributions in a probabilistic sensitivity analysis. These results draw on and extend procedures from the literature on large-sample Bayesian posterior distributions and Bayesian random effects meta-analysis.

Stochastic trees and the StoTree modeling environment: models and software for medical decision analysis.

In this paper we present a review of stochastic trees, a convenient modeling approach for medical treatment decision analyses. Stochastic trees are a generalization of decision trees that incorporate useful features from continuous-time Markov chains. We also discuss StoTree, a freely available software tool for the formulation and solution of stochastic trees, implemented in the Excel spreadsheet environment.