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

Cost-effectiveness of Surgical Treatment Pathways for Prolapse

OBJECTIVE

To evaluate the cost-effectiveness of surgical treatment pathways for apical prolapse.

STUDY DESIGN

We constructed a stochastic Markov model to assess the cost-effectiveness of vaginal apical suspension, laparoscopic sacrocolpopexy, and robotic sacrocolpopexy. We modeled over 5 and 10 years, with 9 pathways accounting for up to 2 separate surgical repairs, recurrence of symptomatic apical prolapse, reoperation, and complications, including mesh excision. We calculated costs from the health care system's perspective.

RESULTS

Over 5 years, compared with expectant management, all surgical treatment pathways cost less than the willingness-to-pay threshold of US $50,000 per quality adjusted life-years. However, among surgical treatments, all but 2 pathways were dominated. Of the remaining 2, laparoscopic sacrocolpopexy followed by vaginal repair for apical recurrence was not cost-effective compared with the vaginal-only approach (incremental cost-effectiveness ratio [ICER], >$500,000). Over 10 years, all but the same 2 pathways were dominated. However, starting with the laparoscopic approach in this case was more cost-effective with an ICER of US $6,176. If the laparoscopic approach was not available, starting with the robotic approach similarly became more cost-effective at 10 years (ICER, US $35,479).

CONCLUSIONS

All minimally invasive surgical approaches for apical prolapse repair are cost-effective when compared with expectant management. Among surgical treatments, the vaginal-only approach is the only cost-effective option over 5 years. However, over a longer period, starting with a laparoscopic (or robotic) approach becomes cost-effective. These results help inform discussions regarding the surgical approach for prolapse.

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.

METHODS

This article introduces a decision-tree methodology that analyzes a patient's dilemma: to accept a kidney offer now or reject it. The methodology calculates the survival benefit of accepting a kidney given a certain quality now and the survival benefit of rejecting it. Survival benefit calculation accounts for patients' and donors' characteristics and transplant centers' and organ procurement organizations' performances and incorporates patients' perceived transplant and dialysis utilities. Valuations of rejecting an offer are contingent on future opportunities and subject to uncertainty in the timing of successive kidney offers and their quality and donor characteristics.

RESULTS

The decision tree was applied to a realistic patient profile as a demonstration. The tool was tested on 1000 deceased-donor kidney offers in 2016. Evaluating up to 1 year of future offers, the tool attains 61% accuracy, with transplant utility of 1.0 and dialysis utility of 0.5. The accuracy reveals potential bias in kidney offer acceptance/rejection at transplant centers.

CONCLUSIONS

The decision-tree tool presented could aid personalized transplant decision-making in the future by providing patients with calculated, individualized survival benefits between accepting and rejecting a kidney offer.

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. They improve on standard approaches to probabilistic sensitivity analysis by allowing a proper accounting for heterogeneity across studies as well as dependence between control and treatment parameters, while still being simple enough to be carried out on a spreadsheet. The authors apply these methods to conduct a probabilistic sensitivity analysis for a recently published analysis of zidovudine prophylaxis following rapid HIV testing in labor to prevent vertical HIV transmission in pregnant women.

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. In this article, the authors examine methods for including extrinsic goals in medical decision and cost-effectiveness analyses. As illustrations, they revisit 2 previously published analyses, the management of unruptured intracranial arteriovenous malformations (AVMs) and the evaluation of preventive strategies for BRCA + women.

A conceptual framework for evaluating information technologies and decision support systems for bioterrorism preparedness and response

OBJECTIVES

The authors sought to develop a conceptual framework for evaluating whether existing information technologies and decision support systems (IT/DSSs) would assist the key decisions faced by clinicians and public health officials preparing for and responding to bioterrorism.

METHODS

They reviewed reports of natural and bioterrorism related infectious outbreaks, bioterrorism preparedness exercises, and advice from experts to identify the key decisions, tasks, and information needs of clinicians and public health officials during a bioterrorism response. The authors used task decomposition to identify the subtasks and data requirements of IT/DSSs designed to facilitate a bioterrorism response. They used the results of the task decomposition to develop evaluation criteria for IT/DSSs for bioterrorism preparedness. They then applied these evaluation criteria to 341 reports of 217 existing IT/DSSs that could be used to support a bioterrorism response.

MAIN RESULTS

In response to bioterrorism, clinicians must make decisions in 4 critical domains (diagnosis, management, prevention, and reporting to public health), and public health officials must make decisions in 4 other domains (interpretation of bioterrorism surveillance data, outbreak investigation, outbreak control, and communication). The time horizons and utility functions for these decisions differ. From the task decomposition, the authors identified critical subtasks for each of the 8 decisions. For example, interpretation of diagnostic tests is an important subtask of diagnostic decision making that requires an understanding of the tests' sensitivity and specificity. Therefore, an evaluation criterion applied to reports of diagnostic IT/DSSs for bioterrorism asked whether the reports described the systems' sensitivity and specificity. Of the 217 existing IT/DSSs that could be used to respond to bioterrorism, 79 studies evaluated 58 systems for at least 1 performance metric.

CONCLUSIONS

The authors identified 8 key decisions that clinicians and public health officials must make in response to bioterrorism. When applying the evaluation system to 217 currently available IT/DSSs that could potentially support the decisions of clinicians and public health officials, the authors found that the literature provides little information about the accuracy of these systems.