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Purpose: Analyzing and communicating uncertainty is essential in medical decision making. To judge whether risks are acceptable, policy makers require information on the expected outcomes but also on the uncertainty and potential losses related to the chosen strategy. We aimed to compare methods used to represent the impact of uncertainty in decision problems involving many strategies, enhance existing methods, and provide an open-source and easy-to-use tool., Methods: We conducted a systematic literature search to identify methods used to represent the impact of uncertainty in cost-effectiveness analyses comparing multiple strategies. We applied the identified methods to probabilistic sensitivity analysis outputs of 3 published decision-analytic models comparing multiple strategies. Subsequently, we compared the following characteristics: type of information conveyed, use of a fixed or flexible willingness-to-pay threshold, output interpretability, and the graphical discriminatory ability. We further proposed adjustments and integration of methods to overcome identified limitations of existing methods., Results: The literature search resulted in the selection of 9 methods. The 3 methods with the most favorable characteristics to compare many strategies were 1) the cost-effectiveness acceptability curve (CEAC) and cost-effectiveness acceptability frontier (CEAF), 2) the expected loss curve (ELC), and 3) the incremental benefit curve (IBC). The information required to assess confidence in a decision often includes the average loss and the probability of cost-effectiveness associated with each strategy. Therefore, we proposed the integration of information presented in an ELC and CEAC into a single heat map., Conclusions: This article presents an overview of methods presenting uncertainty in multiple-strategy cost-effectiveness analyses, with their strengths and shortcomings. We proposed a heat map as an alternative method that integrates all relevant information required for health policy and medical decision making., Highlights: To assess confidence in a chosen course of action, decision makers require information on both the probability and the consequences of making a wrong decision.This article contains an overview of methods for presenting uncertainty in multiple-strategy cost-effectiveness analyses.We propose a heat map that combines the probability of cost-effectiveness from the cost-effectiveness acceptability curve (CEAC) with the consequences of a wrong decision from the expected loss curve.Collapsing of the CEAC can be reduced by relaxing the CEAC, as proposed in this article.Code in Microsoft Excel and R is provided to easily analyze data using the methods discussed in this article.

Background: Metamodeling may substantially reduce the computational expense of individual-level state transition simulation models (IL-STM) for calibration, uncertainty quantification, and health policy evaluation. However, because of the lack of guidance and readily available computer code, metamodels are still not widely used in health economics and public health. In this study, we provide guidance on how to choose a metamodel for uncertainty quantification., Methods: We built a simulation study to evaluate the prediction accuracy and computational expense of metamodels for uncertainty quantification using life-years gained (LYG) by treatment as the IL-STM outcome. We analyzed how metamodel accuracy changes with the characteristics of the simulation model using a linear model (LM), Gaussian process regression (GP), generalized additive models (GAMs), and artificial neural networks (ANNs). Finally, we tested these metamodels in a case study consisting of a probabilistic analysis of a lung cancer IL-STM., Results: In a scenario with low uncertainty in model parameters (i.e., small confidence interval), sufficient numbers of simulated life histories, and simulation model runs, commonly used metamodels (LM, ANNs, GAMs, and GP) have similar, good accuracy, with errors smaller than 1% for predicting LYG. With a higher level of uncertainty in model parameters, the prediction accuracy of GP and ANN is superior to LM. In the case study, we found that in the worst case, the best metamodel had an error of about 2.1%., Conclusion: To obtain good prediction accuracy, in an efficient way, we recommend starting with LM, and if the resulting accuracy is insufficient, we recommend trying ANNs and eventually also GP regression.

Background: After curative treatment of primary non-small-cell lung cancer (NSCLC), patients undergo intensive surveillance with the aim to detect recurrences from the primary tumor or metachronous second primary lung cancer as early as possible and improve overall survival. However, the benefit of surveillance is debated. Available evidence is of low quality and conflicting. Microsimulation modeling facilitates the exploration of the impact of different surveillance strategies and provides insight into the cost-effectiveness of surveillance., Methods: A microsimulation model was used to simulate a range of computed tomography (CT)-based surveillance schedules, differing in the frequency and duration of CT surveillance. The impact on survival, quality-adjusted life-years, costs, and cost-effectiveness of each schedule was assessed., Results: Ten of 108 strategies formed the cost-effectiveness frontier; that is, these were the strategies with the optimal cost-health benefit balance. Per person, the discounted QALYs of these strategies varied between 5.72 and 5.81 y, and discounted costs varied between €9892 and €19,259. Below a willingness-to-pay threshold of €50,000/QALY, no scanning is the preferred option. For a willingness-to-pay threshold of €80,000/QALY, surveillance scanning every 2 y starting 1 y after curative treatment becomes the best option, with €11,860 discounted costs and 5.76 discounted QALYs per person. The European Society for Medical Oncology guideline strategy was more expensive and less effective than several other strategies., Conclusion: Model simulations suggest that limited CT surveillance scanning after the treatment of primary NSCLC is cost-effective, but the incremental health-benefit remains marginal. However, model simulations do suggest that the guideline strategy is not cost-effective.

Background: Our aim was to evaluate the cost effectiveness of 3 months' adjuvant chemotherapy versus 6 months in high-risk (T4 stage + microsatellite stable) stage II colon cancer (CC) patients., Methods: Using the validated PATTERN Markov cohort model, which simulates the disease progression of stage II CC patients from diagnosis to death, we first evaluated a reference strategy in which high-risk patients were treated with chemotherapy for 6 months. In the second strategy, treatment duration was shortened to 3 months. Both strategies were evaluated for CAPOX (capecitabine plus oxaliplatin) and FOLFOX (fluorouracil, leucovorin and oxaliplatin). Based on trial data, we assumed that shortened treatment duration compared with a 6-month regimen was equally effective for CAPOX and less effective for FOLFOX. Adverse events were highest in the 6-month strategy. Analyses were conducted from a societal perspective using a lifelong time horizon. Outcomes were number of CC deaths per 1000 patients and total discounted costs and quality-adjusted life-years (QALYs) per patient (pp). Incremental net monetary benefit (iNMB) was calculated using a willingness-to-pay value of €50,000/QALY., Results: For CAPOX, the 6-month strategy resulted in 316 CC deaths per 1000 patients, 6.71 QALYs pp and total costs of €41,257 pp. The 3-month strategy resulted in an equal number of CC deaths, but higher QALYs (6.80 pp) and lower costs (€37,645 pp), leading to a iNMB of €8454 per person for 3 months versus 6 months. For FOLFOX, the 6-month strategy resulted in 316 CC deaths per 1000 patients, 6.71 QALYs pp and total costs of €47,135 pp. The 3-month strategy resulted in more CC deaths (393), lower QALYs (6.19 pp) and lower costs (€44,389 pp). An iNMB of -€23,189 was found for 3 months versus 6 months., Conclusion: Our findings indicate that 3 months' adjuvant chemotherapy should be considered as standard of care in high-risk stage II CC patients for CAPOX, but not for FOLFOX., Competing Interests: Conflict of interest statement: The authors declare that there is no conflict of interest., (© The Author(s), 2020.)

Background: Overlap of depressive and anxiety symptoms is supposedly more common in non-Western populations. This can lead to diagnostic uncertainity and undertreatment., Aims: The aim of this study was to assess cross-cultural differences regarding the comorbidity of anxiety and depressive disorders in a comparative population study., Methods: In a random urban population sample, stratified for descent, in Amsterdam, the Netherlands, diagnostic interviews were held by bilingual interviewers. Diagnoses of anxiety and depressive disorders, based on the Composite International Diagnostic Interview, were obtained for 307 native Dutch subjects, 205 Turkish-Dutch subjects and 186 Moroccan-Dutch subjects., Results: The prevalence rate of comorbid anxiety and depressive disorders was higher in Turkish-Dutch (9.8 %) and Moroccan-Dutch (3.8%) subjects compared to native Dutch subjects (2.3%). However, this could be explained by differences in baseline prevalence rate and level of severity of the separate disorders. The onset order of anxiety disorders and depressive disorders was comparable in each ethnic group., Conclusions: The high prevalence rate of comorbid anxiety and depressive diorders in non-Western immigrants in the Netherlands necessitates assesssment and treatment of both disorders. There was no indication of a - culturally influenced - stronger overlap between anxiety and depressive disorders in non-Western immigrants in the Netherlands.