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Background: We compared the relative benefits, harms and cost-effectiveness of hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery ± systemic chemotherapy versus cytoreductive surgery ± systemic chemotherapy or systemic chemotherapy alone in people with peritoneal metastases from colorectal, gastric or ovarian cancers by a systematic review, meta-analysis and model-based cost-utility analysis. Methods: We searched MEDLINE, EMBASE, Cochrane Library and the Science Citation Index, ClinicalTrials.gov and WHO ICTRP trial registers until 14 April 2022. We included only randomised controlled trials addressing the research objectives. We used the Cochrane risk of bias tool version 2 to assess the risk of bias in randomised controlled trials. We used the random-effects model for data synthesis when applicable. For the cost-effectiveness analysis, we performed a model-based cost-utility analysis using methods recommended by The National Institute for Health and Care Excellence. Results: The systematic review included a total of eight randomised controlled trials (seven randomised controlled trials, 955 participants included in the quantitative analysis). All comparisons other than those for stage III or greater epithelial ovarian cancer contained only one trial, indicating the paucity of randomised controlled trials that provided data. For colorectal cancer, hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy probably results in little to no difference in all-cause mortality (60.6% vs. 60.6%; hazard ratio 1.00, 95% confidence interval 0.63 to 1.58) and may increase the serious adverse event proportions compared to cytoreductive surgery ± systemic chemotherapy (25.6% vs. 15.2%; risk ratio 1.69, 95% confidence interval 1.03 to 2.77). Hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy probably decreases all-cause mortality compared to fluorouracil-based systemic chemotherapy alone (40.8% vs. 60.8%; hazard ratio 0.55, 95% confidence interval 0.32 to 0.95). For gastric cancer, there is high uncertainty about the effects of hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy versus cytoreductive surgery + systemic chemotherapy or systemic chemotherapy alone on all-cause mortality. For stage III or greater epithelial ovarian cancer undergoing interval cytoreductive surgery, hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy probably decreases all-cause mortality compared to cytoreductive surgery + systemic chemotherapy (46.3% vs. 57.4%; hazard ratio 0.73, 95% confidence interval 0.57 to 0.93). Hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy may not be cost-effective versus cytoreductive surgery + systemic chemotherapy for colorectal cancer but may be cost-effective for the remaining comparisons. Limitations: We were unable to obtain individual participant data as planned. The limited number of randomised controlled trials for each comparison and the paucity of data on health-related quality of life mean that the recommendations may change as new evidence (from trials with a low risk of bias) emerges. Conclusions: In people with peritoneal metastases from colorectal cancer with limited peritoneal metastases and who are likely to withstand major surgery, hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy should not be used in routine clinical practice (strong recommendation). There is considerable uncertainty as to whether hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy or cytoreductive surgery + systemic chemotherapy should be offered to patients with gastric cancer and peritoneal metastases (no recommendation). Hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy should be offered routinely to women with stage III or greater epithelial ovarian cancer and metastases confined to the abdomen requiring and likely to withstand interval cytoreductive surgery after chemotherapy (strong recommendation). Future work: More randomised controlled trials are necessary. Study registration: This study is registered as PROSPERO CRD42019130504. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 17/135/02) and is published in full in Health Technology Assessment; Vol. 28, No. 51. See the NIHR Funding and Awards website for further award information.

Cancers of the bowel, ovary or stomach can spread to the lining of the abdomen ('peritoneal metastases'). Chemotherapy (the use of drugs that aim to kill cancer cells) given by injection or tablets ('systemic chemotherapy') is one of the main treatment options. There is uncertainty about whether adding cytoreductive surgery (cytoreductive surgery; an operation to remove the cancer) and 'hyperthermic intraoperative peritoneal chemotherapy' (warm chemotherapy delivered into the lining of the abdomen during cytoreductive surgery) are beneficial. We reviewed all the information from medical literature published until 14 April 2022, to answer the above uncertainty. We found the following from eight trials, including about 1000 participants. In people with peritoneal metastases from bowel cancer, hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy probably does not provide any benefits and increases harm compared to cytoreductive surgery + systemic chemotherapy, while cytoreductive surgery + systemic chemotherapy appears to increase survival compared to systemic chemotherapy alone. There is uncertainty about the best treatment for people with peritoneal metastases from stomach cancer. In women with peritoneal metastases from ovarian cancer who require systemic chemotherapy before cytoreductive surgery to shrink the cancer to allow surgery ('advanced ovarian cancer'), hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy probably increases survival compared to cytoreductive surgery + systemic chemotherapy. In people who can withstand a major operation and in whom cancer can be removed, cytoreductive surgery + systemic chemotherapy should be offered to people with peritoneal metastases from bowel cancer, while hyperthermic intraoperative peritoneal chemotherapy + cytoreductive surgery + systemic chemotherapy should be offered to women with peritoneal metastases from 'advanced ovarian cancer'. Uncertainty in treatment continues for gastric cancer. This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 17/135/02) and is published in full in Health Technology Assessment; Vol. 28, No. 51. See the NIHR Funding and Awards website for further award information.

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OBJECTIVES: Probabilistic sensitivity analysis (PSA) is conducted to account for the uncertainty in cost and effect of decision options under consideration. PSA involves obtaining a large sample of input parameter values (N) to estimate the expected cost and effect of each alternative in the presence of parameter uncertainty. When the analysis involves using stochastic models (eg, individual-level models), the model is further replicated P times for each sampled parameter set. We study how N and P should be determined. METHODS: We show that PSA could be structured such that P can be an arbitrary number (say, P=1). To determine N, we derive a formula based on Chebyshev's inequality such that the error in estimating the incremental cost-effectiveness ratio (ICER) of alternatives (or equivalently, the willingness-to-pay value at which the optimal decision option changes) is within a desired level of accuracy. We described 2 methods to confirm, visually and quantitatively, that the N informed by this method results in ICER estimates within the specified level of accuracy. RESULTS: When N is arbitrarily selected, the estimated ICERs could be substantially different from the true ICER (even as P increases), which could lead to misleading conclusions. Using a simple resource allocation model, we demonstrate that the proposed approach can minimize the potential for this error. CONCLUSIONS: The number of parameter samples in probabilistic cost-effectiveness analyses should not be arbitrarily selected. We describe 3 methods to ensure that enough parameter samples are used in probabilistic cost-effectiveness analyses.

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BACKGROUND: Methods to present the result of cost-effectiveness analyses under parameter uncertainty include cost-effectiveness planes (CEPs), cost-effectiveness acceptability curves/frontier (CEACs/CEAF), expected loss curves (ELCs), and net monetary benefit (NMB) lines. We describe how NMB lines can be augmented to present NMB values that could be achieved by reducing or resolving parameter uncertainty. We evaluated the ability of these methods to correctly 1) identify the alternative with the highest expected NMB and 2) communicate the magnitude of parameter and decision uncertainty. METHODS: We considered 4 hypothetical decision problems representing scenarios with high variance or correlated cost and effect estimates and alternatives with similar cost-effectiveness ratios. We used these decision problems to demonstrate the limitations of existing methods and the potential of augmented NMB lines to resolve these issues. RESULTS: CEPs and CEACs/CEAF could falsely imply the lack of sufficient evidence to identify the optimal option if cost and effect estimates have high variance, are correlated across alternatives, or when alternatives have similar cost-effectiveness ratios. The augmented NMB lines and ELCs can correctly identify the option with the highest expected NMB and communicate the potential benefit of resolving uncertainties. Like ELCs, the augmented NMB lines provide information about the value of resolving parameter uncertainties, but augmented NMB lines may be easier to interpret for decision makers. CONCLUSIONS: Our analysis supports recommending the augment NMB lines as an important method to present the results of economic evaluation studies under parameter uncertainty. HIGHLIGHTS: The results of cost-effectiveness analyses (CEAs) when the cost and effect estimates of alternatives are uncertain are commonly presented using cost-effectiveness planes (CEPs), cost-effectiveness acceptability curves/frontier (CEACs/CEAF), and expected loss curves (ELCs).Although currently not often used, net monetary benefit (NMB) lines could present the results of cost-effectiveness to identify the alternative with the highest expected NMB values given the current level of uncertainty. Furthermore, NMB lines can be augmented to 1) show metrics of value of information, which measure the value of additional research to reduce or eliminate the decision uncertainty, and 2) display the confidence intervals along the NMB lines to ensure that NMB values are estimated accurately using a sufficiently large number of parameter samples.Using several decision problems, we demonstrate the limitation of existing methods to present the results of CEAs under parameter uncertainty and how augmented NMB lines could resolve these issues.Our analysis supports recommending augmented NMB lines as an important method to present the results of CEA under uncertainty since they 1) correctly identify the alternative with the highest expected NMB value given the current evidence, 2) provide information about the potential value of additional research to improve the decision by reducing or resolving uncertainty in model parameters, 3) assist the analysis to visually ensure that enough parameter samples are used to estimate the expected NMB of alternatives, and 4) are easier to interpret for decision makers compared with other methods.

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OBJECTIVES: Health economic (HE) models are often considered as "black boxes" because they are not publicly available and lack transparency, which prevents independent scrutiny of HE models. Additionally, validation efforts and validation status of HE models are not systematically reported. Methods to validate HE models in absence of their full underlying code are therefore urgently needed to improve health policy making. This study aimed to develop and test a generic dashboard to systematically explore the workings of HE models and validate their model parameters and outcomes. METHODS: The Probabilistic Analysis Check dashBOARD (PACBOARD) was developed using insights from literature, health economists, and a data scientist. Functionalities of PACBOARD are (1) exploring and validating model parameters and outcomes using standardized validation tests and interactive plots, (2) visualizing and investigating the relationship between model parameters and outcomes using metamodeling, and (3) predicting HE outcomes using the fitted metamodel. To test PACBOARD, 2 mock HE models were developed, and errors were introduced in these models, eg, negative costs inputs, utility values exceeding 1. PACBOARD metamodeling predictions of incremental net monetary benefit were validated against the original model's outcomes. RESULTS: PACBOARD automatically identified all errors introduced in the erroneous HE models. Metamodel predictions were accurate compared with the original model outcomes. CONCLUSIONS: PACBOARD is a unique dashboard aiming at improving the feasibility and transparency of validation efforts of HE models. PACBOARD allows users to explore the working of HE models using metamodeling based on HE models' parameters and outcomes.

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BACKGROUND: There is uncertainty in the relative benefits and harms of hyperthermic intraoperative peritoneal chemotherapy (HIPEC) when added to cytoreductive surgery (CRS) +/- systemic chemotherapy or systemic chemotherapy alone in people with peritoneal metastases from colorectal, gastric, or ovarian cancers. METHODS: We searched randomized controlled trials (RCTs) in the medical literature until April 14, 2022 and applied methods used for high-quality systematic reviews. FINDINGS: We included a total of eight RCTs (seven RCTs included in quantitative analysis as one RCT did not provide data in an analyzable format). All comparisons other than ovarian cancer contained only one trial. For gastric cancer, there is high uncertainty about the effect of CRS + HIPEC + systemic chemotherapy. For stage III or greater epithelial ovarian cancer undergoing interval cytoreductive surgery, CRS + HIPEC + systemic chemotherapy probably decreases all-cause mortality compared to CRS + systemic chemotherapy. For colorectal cancer, CRS + HIPEC + systemic chemotherapy probably results in little to no difference in all-cause mortality and may increase the serious adverse events proportions compared to CRS +/- systemic chemotherapy, but probably decreases all-cause mortality compared to fluorouracil-based systemic chemotherapy alone. INTERPRETATION: The role of CRS + HIPEC in gastric peritoneal metastases is uncertain. CRS + HIPEC should be standard of care in women with stage III or greater epithelial ovarian cancer undergoing interval CRS. CRS + systemic chemotherapy should be standard of care for people with colorectal peritoneal metastases, with HIPEC given only as part of a RCT focusing on subgroups and regimes. PROSPERO REGISTRATION: CRD42019130504.

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INTRODUCTION: Emicizumab is the initial subcutaneously administered bispecific antibody approved as a prophylactic treatment for patients with haemophilia A (PwHA). AIM: This study assessed the economic evaluation of emicizumab treatment for non-inhibitor severe haemophilia A (HA) patients in India. METHODS: A Markov model evaluated the cost-effectiveness of emicizumab prophylaxis compared to on-demand therapy (ODT), low-dose prophylaxis (LDP; 1565 IU/kg/year), intermediate-dose prophylaxis (IDP; 3915 IU/kg/year) and high-dose prophylaxis (HDP; 7125 IU/kg/year) for HA patients without factor VIII inhibitors. Inputs from HAVEN-1 and HAVEN-3 trials included transition probabilities of different bleeding types. Costs and benefits were discounted at a 3.5% annual rate. RESULTS: In the base-case analysis, emicizumab was cost-effective compared to HDP, with an incremental cost-effectiveness ratio (ICER) per quality-adjusted life-years (QALY) of Indian rupees (INR) 27,869. Compared to IDP, ODT and LDP, emicizumab prophylaxis could be considered a cost-effective option if the paying threshold is >1 per capita gross domestic product (GDP) with ICER/QALY values of INR 264,592, INR 255,876 and INR 305,398, respectively. One-way sensitivity analysis (OWSA) highlighted emicizumab cost as the parameter with the greatest impact on ICERs. Probabilistic sensitivity analysis (PSA) indicated that emicizumab had a 94.7% and 49.4% probability of being cost-effective at willingness-to-pay (WTP) thresholds of three and two-times per capita GDP. CONCLUSION: Emicizumab prophylaxis is cost-effective compared to HDP and provides value for money compared to ODT, IDP, and LDP for severe non-inhibitor PwHA in India. Its long-term humanistic, clinical and economic benefits outweigh alternative options, making it a valuable choice in resource-constrained settings.

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OBJECTIVES: Probabilistic sensitivity analysis (PSA) has been shown to reduce bias in outcomes of health economic models. However, only 1 existing study has been identified that incorporates PSA within a resource-constrained discrete event simulation (DES) model. This article aims to assess whether it is feasible and appropriate to use PSA to characterize parameter uncertainty in DES models that are primarily constructed to explore the impact of constrained resources. METHODS: PSA is incorporated into a new case study of an Emergency Department DES. Structured expert elicitation is used to derive the variability and uncertainty input distributions associated with length of time taken to complete key activities within the Emergency Department. Potential challenges of implementation and analysis are explored. RESULTS: The results of a trial of the model, which used the best estimates of the elicited means and variability around the time taken to complete activities, provided a reasonable fit to the data for length of time within the Emergency Department. However, there was substantial and skewed uncertainty around the activity times estimated from the elicitation exercise. This led to patients taking almost 3 weeks to leave the Emergency Department in some PSA runs, which would not occur in practice. CONCLUSIONS: Structured expert elicitation can be used to derive plausible estimates of activity times and their variability, but experts' uncertainty can be substantial. For parameters that have an impact on interactions within a resource-constrained simulation model, PSA can lead to implausible model outputs; hence, other methods may be needed.

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INTRODUCTION: Unmeasured confounding can lead to biased interpretations of empirical findings. This paper aimed to assess the magnitude of suspected unmeasured confounding due to driving mileage and simulate the statistical power required to detect a discrepancy in the effect of polypharmacy on road traffic crashes (RTCs) among older adults. METHODS: Based on Monte Carlo Simulation (MCS) approach, we estimated 1) the magnitude of confounding of driving mileage on the association of polypharmacy and RTCs and 2) the statistical power of to detect a discrepancy from no adjusted effect. A total of 1000 studies, each of 500000 observations, were simulated. RESULTS: Under the assumption of a modest adjusted exposure-outcome odds ratio of 1.35, the magnitude of confounding bias by driving mileage was estimated to be 16% higher with a statistical power of 50%. Only an adjusted odds ratio of at least 1.60 would be associated with a statistical power of about 80% CONCLUSION: This applied probabilistic bias analysis showed that not adjusting for driving mileage as a confounder can lead to an overestimation of the effect of polypharmacy on RTCs in older adults. Even considering a large sample, small to moderate adjusted exposure effects were difficult to be detected.

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BACKGROUND: Digital therapeutic care (DTC) programs are unsupervised app-based treatments that provide video exercises and educational material to patients with nonspecific low back pain during episodes of pain and functional disability. German statutory health insurance can reimburse DTC programs since 2019, but evidence on efficacy and reasonable pricing remains scarce. This paper presents a probabilistic sensitivity analysis (PSA) to evaluate the efficacy and cost-utility of a DTC app against treatment as usual (TAU) in Germany. OBJECTIVE: The aim of this study was to perform a PSA in the form of a Monte Carlo simulation based on the deterministic base case analysis to account for model assumptions and parameter uncertainty. We also intend to explore to what extent the results in this probabilistic analysis differ from the results in the base case analysis and to what extent a shortage of outcome data concerning quality-of-life (QoL) metrics impacts the overall results. METHODS: The PSA builds upon a state-transition Markov chain with a 4-week cycle length over a model time horizon of 3 years from a recently published deterministic cost-utility analysis. A Monte Carlo simulation with 10,000 iterations and a cohort size of 10,000 was employed to evaluate the cost-utility from a societal perspective. Quality-adjusted life years (QALYs) were derived from Veterans RAND 6-Dimension (VR-6D) and Short-Form 6-Dimension (SF-6D) single utility scores. Finally, we also simulated reducing the price for a 3-month app prescription to analyze at which price threshold DTC would result in being the dominant strategy over TAU in Germany. RESULTS: The Monte Carlo simulation yielded on average a €135.97 (a currency exchange rate of EUR €1=US $1.069 is applicable) incremental cost and 0.004 incremental QALYs per person and year for the unsupervised DTC app strategy compared to in-person physiotherapy in Germany. The corresponding incremental cost-utility ratio (ICUR) amounts to an additional €34,315.19 per additional QALY. DTC yielded more QALYs in 54.96% of the iterations. DTC dominates TAU in 24.04% of the iterations for QALYs. Reducing the app price in the simulation from currently €239.96 to €164.61 for a 3-month prescription could yield a negative ICUR and thus make DTC the dominant strategy, even though the estimated probability of DTC being more effective than TAU is only 54.96%. CONCLUSIONS: Decision-makers should be cautious when considering the reimbursement of DTC apps since no significant treatment effect was found, and the probability of cost-effectiveness remains below 60% even for an infinite willingness-to-pay threshold. More app-based studies involving the utilization of QoL outcome parameters are urgently needed to account for the low and limited precision of the available QoL input parameters, which are crucial to making profound recommendations concerning the cost-utility of novel apps.

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OBJECTIVES: This study aimed to develop a microsimulation model to estimate the health effects, costs, and cost-effectiveness of public health and clinical interventions for preventing/managing type 2 diabetes. METHODS: We combined newly developed equations for complications, mortality, risk factor progression, patient utility, and cost-all based on US studies-in a microsimulation model. We performed internal and external validation of the model. To demonstrate the model's utility, we predicted remaining life-years, quality-adjusted life-years (QALYs), and lifetime medical cost for a representative cohort of 10 000 US adults with type 2 diabetes. We then estimated the cost-effectiveness of reducing hemoglobin A1c from 9% to 7% among adults with type 2 diabetes, using low-cost, generic, oral medications. RESULTS: The model performed well in internal validation; the average absolute difference between simulated and observed incidence for 17 complications was < 8%. In external validation, the model was better at predicting outcomes in clinical trials than in observational studies. The cohort of US adults with type 2 diabetes was projected to have an average of 19.95 remaining life-years (from mean age 61), incur $187 729 in discounted medical costs, and accrue 8.79 discounted QALYs. The intervention to reduce hemoglobin A1c increased medical costs by $1256 and QALYs by 0.39, yielding an incremental cost-effectiveness ratio of $9103 per QALY. CONCLUSIONS: Using equations exclusively derived from US studies, this new microsimulation model achieves good prediction accuracy in US populations. The model can be used to estimate the long-term health impact, costs, and cost-effectiveness of interventions for type 2 diabetes in the United States.

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BACKGROUND: Lifestyle Africa is an adapted version of the Diabetes Prevention Program designed for delivery by community health workers to socioeconomically disadvantaged populations in low- and middle-income countries (LMICs). Results from the Lifestyle Africa trial conducted in an under-resourced community in South Africa indicated that the programme had a significant effect on reducing haemoglobin A1c (HbA1c). OBJECTIVE: To estimate the cost of implementation and the cost-effectiveness (in cost per point reduction in HbA1c) of the Lifestyle Africa programme to inform decision-makers of the resources required and the value of this intervention. METHODS: Interviews were held with project administrators to identify the activities and resources required to implement the intervention. A direct-measure micro-costing approach was used to determine the number of units and unit cost for each resource. The incremental cost per one point improvement in HbA1c was calculated. RESULTS: The intervention equated to 71 United States dollars (USD) in implementation costs per participant and a 0.26 improvement in HbA1c per participant. CONCLUSIONS: Lifestyle Africa reduced HbA1c for relatively little cost and holds promise for addressing chronic disease in LMIC. Decision-makers should consider the comparative clinical effectiveness and cost-effectiveness of this intervention when making resource allocation decisions. TRIAL REGISTRATION: Trial registration is at ClinicalTrials.gov (NCT03342274).

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INTRODUCTION: The role of early economic evaluation (EEE) in the development of medical technology has been increasingly recognized; however, data on the use of EEE in surgical technology are sparse. The objective of this review was to explore the use of EEE in the development of surgical technologies, with emphasis on how uncertainty has been addressed. AREAS COVERED: A systematic review was conducted, and original articles employing any form of EEE of surgical technology were selected for review, with 10 studies included in the analysis. These studies demonstrated significant variation in the approach to managing parameter uncertainty, specifically regarding the type of analysis used and the inclusion of effectiveness parameters in sensitivity analysis. The conclusions drawn did not appear to factor in uncertainty in the models. EXPERT OPINION: Approaches to handling parameter uncertainty in previous EEEs of surgical technology have been limited, with some studies failing to address parameter uncertainty. In addition, EEEs do not appear to follow established guidelines with respect to the use of sensitivity analyses. It is important that EEEs of surgical technology address parameter uncertainty in order to draw more robust conclusions from the analysis and allow investors to consider this uncertainty when making investment decisions.

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BACKGROUND: quadrivalent inactivated vaccine (QIV) has replaced trivalent inactivated vaccine (TIV). In Portugal, TIV is free of charge for risk groups, including older adults (≥65 years old). In its turn, QIV-which provides broader protection as it includes an additional lineage B strain-was introduced in Portugal in October 2018; only since the 2019/20 influenza season has it been provided free of charge for risk groups. This study evaluates the cost effectiveness of switching from TIV to QIV, from the National Health Service perspective, in the Portuguese elderly mainland population. METHODS: A decision tree model was developed to compare TIV and QIV, based on Portuguese hospitalization data for the 2015/16 influenza season. The primary health economic outcome under consideration was the incremental cost-effectiveness ratio (ICER). In addition, one-way sensitivity analysis and probabilistic sensitivity analysis were performed. RESULTS: the high cost of QIV (approximately three times the cost of TIV) would lead to a total increment of EUR 5,283,047, and the resulting ICER would be EUR 26,403,007/QALY, above the usual willingness-to-pay threshold. CONCLUSIONS: from the National Health Service perspective, our findings reveal that QIV is not cost effective for the Portuguese elderly population due to the high cost. If the QIV costs were the same as the TIV, then QIV would be cost effective.

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Health economic modeling of novel technology at the early stages of a product lifecycle has been used to identify technologies that are likely to be cost-effective. Such early assessments are challenging due to the potentially limited amount of data. Modelers typically conduct uncertainty analyses to evaluate their effect on decision-relevant outcomes. Current approaches, however, are limited in their scope of application and imposes an unverifiable assumption, that is, uncertainty can be precisely represented by a probability distribution. In the absence of reliable data, an approach that uses the fewest number of assumptions is desirable. This study introduces a generalized approach for quantifying parameter uncertainty, that is, probability bound analysis (PBA), that does not require a precise specification of a probability distribution in the context of early-stage health economic modeling. We introduce the concept of a probability box (p-box) as a measure of uncertainty without necessitating a precise probability distribution. We provide formulas for a p-box given data on summary statistics of a parameter. We describe an approach to propagate p-boxes into a model and provide step-by-step guidance on how to implement PBA. We conduct a case and examine the differences between the status-quo and PBA approaches and their potential implications on decision-making.

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OBJECTIVE: This study aimed to investigate the cost-effectiveness of blended cognitive-behavioral therapy (CBT) compared to standard CBT for adult patients suffering from major depressive disorder (MDD). DESIGN: A cost-utility analysis alongside the randomized controlled ENTER trial. SETTING: Center for Telepsychiatry, Mental Health Services in the Region of Southern Denmark, Denmark. PARTICIPANTS: The study included 76 patients suffering from MDD. INTERVENTIONS: The patients in the intervention group received blended CBT treatment comprising a combination of online modules and face-to-face consultations with a psychologist. The patients in the control group received standard CBT treatment, that is, solely face-to-face consultations with a psychologist. The treatment period was 12 weeks. OUTCOME MEASURES: Cost-effectiveness was reported as incremental cost-effectiveness ratio. A micro-costing approach was applied to evaluate the savings derived. Changes in quality-adjusted life-years (QALYs) were estimated using the EuroQol 5-Dimensions 5-Levels questionnaire at the baseline and the six-month follow-up. RESULTS: Data for 74 patients were included in the primary analysis. The adjusted QALY difference between blended CBT and standard CBT was -0.0291 (95% CI: -0.0535 to -0.0047), and the adjusted difference in costs was -£226.32 (95% CI: -300.86 to -151.77). Blended CBT was estimated to have a 6.6% and 3.1% probability of being cost-effective based on thresholds of £20,000 and £30,000. CONCLUSION: Compared to standard CBT, blended CBT represents a cost-saving but also a loss in QALYs for patients suffering from MDD. However, results should be carefully interpreted, given the small sample size. Future research involving larger replication studies focusing on other aspects of blended CBT with more patient involvement is advised. TRIAL REGISTRATION NUMBER: ClinicalTrial.gov: S-20150150.

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This tutorial aims to help make the best available methods for generating and presenting cost-effectiveness results with uncertainty common practice. We believe there is a need for such type of tutorial because some erroneous practices persist (e.g., identifying the cost-effective intervention as the one with the highest probability to be cost-effective), while some of the more advanced methods are hardly used (e.g., the net loss statistic 'NL', expected net loss curves and frontier). The tutorial explains with simple examples the pros and cons of using ICER, incremental net benefit and NL to identify the cost-effective intervention, both with and without uncertainty accounted for probabilistically. A flowchart provides practical guidance on when and how to use ICER, incremental net benefit or NL. Different ways to express and present uncertainty in the results are described, including confidence and credible intervals, the probability that a strategy is cost-effective (as usually shown with cost-effectiveness acceptability curves (CEACs)) and the expected value of perfect information (EVPI). The tutorial clarifies and illustrates why EVPI is the only measure accounting fully for decision uncertainty, and why NL curves and the NL frontier may be preferred over CEACs and other plots for presenting cost-effectiveness results in the context of uncertainty. The easy calculations and a worked-out real-life example will help users to thoroughly understand and correctly interpret key cost-effectiveness results. Examples with mathematical calculations, interpretation, plots and R code are provided.

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BACKGROUND & AIMS: Patients hospitalised because of mental illness often have risk factors for contracting HCV. Scaling-up HCV screening for all psychiatric inpatients as a case-detection strategy for viral elimination is underexplored. This study aimed to evaluate the cost-effectiveness of scaling-up HCV screening and treatment for psychiatry hospital admissions in Switzerland vs. the current standard-of-care risk-based approach, where only those with a history of substance misuse disorder are offered testing. METHODS: HCV prevalence by history of substance misuse disorder was analysed in medical records from inpatient admissions to a Swiss psychiatry department. Cost-effectiveness was analysed from a healthcare provider perspective through a decision-tree screening model, using these HCV prevalence data. Model and parameter uncertainty were assessed using deterministic and probabilistic sensitivity analyses. RESULTS: Prevalence of HCV in psychiatry inpatients with a history of substance misuse disorder (n = 1,013) was 25.7%, compared with 3.5% among the remaining inpatients (n = 3,535). Scaling up HCV screening and treatment for all psychiatry admissions was cost-effective vs. the risk-based approach, with an incremental cost-effectiveness ratio of US$9,188 per quality-adjusted life-year gained. The incremental cost-effectiveness ratio remained cost-effective considering a HCV prevalence as low as 0.07%. The population-level net monetary benefit of the generalised screening approach was US$435,156,348, with 917 additional patients per year detected and treated at a cost of US$3,294 per person (vs. US$2,122 under risk-based screening). CONCLUSIONS: Scaling up HCV screening and treatment at diagnosis with all-oral, interferon-free regimens as a generalised approach for psychiatric admissions was cost-effective and could support reaching World Health Organization targets for HCV elimination by 2030. LAY SUMMARY: Patients hospitalised because of mental illness often have risk factors for HCV. We found that testing all psychiatry patients in hospital for HCV was cost-effective compared with testing only patients who have a history of substance misuse. Scaling up HCV testing and treatment could help to wipe out HCV.

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BACKGROUND: Uncertainty in model-based cost-utility analyses is commonly assessed in a probabilistic sensitivity analysis. Model parameters are implemented as distributions and values are sampled from these distributions in a Monte Carlo simulation. Bootstrapping is an alternative method that requires fewer assumptions and incorporates correlations between model parameters. METHODS: A Markov model-based cost-utility analysis comparing oromucosal spray containing delta-9-tetrahidrocannabinol + cannabidiol (Sativex®, nabiximols) plus standard care versus standard spasticity care alone in the management of multiple sclerosis spasticity was performed over a 5-year time horizon from the Belgian healthcare payer perspective. The probabilistic sensitivity analysis was implemented using a bootstrap approach to ensure that the correlations present in the source clinical trial data were incorporated in the uncertainty estimates. RESULTS: Adding Sativex® spray to standard care was found to dominate standard spasticity care alone, with cost savings of €6,068 and a quality-adjusted life year gain of 0.145 per patient over the 5-year analysis. The probability of dominance increased from 29% in the first year to 94% in the fifth year, with the probability of QALY gains in excess of 99% for all years considered. CONCLUSIONS: Adding Sativex® spray to spasticity care was found to dominate standard spasticity care alone in the Belgian healthcare setting. This study showed the use of bootstrapping techniques in a Markov model probabilistic sensitivity analysis instead of Monte Carlo simulations. Bootstrapping avoided the need to make distributional assumptions and allowed the incorporation of correlating structures present in the original clinical trial data in the uncertainty assessment.

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OBJECTIVES: Because observational studies often use imperfect measurements, results are prone to misclassification errors. We used as a motivating example the possible teratogenic risks of antiemetic agents in pregnancy since a large observational study recently showed that first-trimester exposure to doxylamine-pyridoxine was associated with significantly increased risk of congenital malformations as a whole, as well as central nervous system defects, and previous observational studies did not show such associations. A meta-analysis on this issue was carried out with the aim to illustrate how differential exposure and outcome misclassifications may lead to uncertain conclusions. METHODS: Medline, searched to October 2019 for full text papers in English. Summary Odds Ratios (ORs) with confidence intervals (CIs) were calculated using random-effect models. Probabilistic sensitivity analyses were performed for evaluating the extension of differential misclassification required to account for the exposure-outcome association. RESULTS: Summary ORs were 1.02 (95 % CI, 0.92-1.15), 0.99 (0.82-1.19) and 1.25 (1.08-1.44) for overall congenital, cardiocirculatory, and central nervous system malformations respectively. By assuming exposure and outcome bias factor respectively of 0.95 (i.e., newborns with congenital defects had exposure specificity 5% lower than healthy newborns) and 1.12 (i.e., exposed newborns had outcome sensitivity 12 % higher than unexposed newborns), summary OR of central nervous system defects became 1.13 (95 % CI, 0.99-1.29) and 1.17 (95 % CI, 0.99-1.38). CONCLUSION: Observational investigations and meta-analyses of observational studies need cautious interpretations. Their susceptibility to several, often sneaky, sources of bias should be carefully evaluated.

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BACKGROUND: Results of probabilistic sensitivity analyses (PSA) are frequently visualized as a scatterplot, which is limited through overdrawing and a lack of insight in relative density. To overcome these limitations, we have developed the Relative Density plot (PSA-ReD). METHODS: The PSA-ReD combines a density plot and a contour plot to visualize and quantify PSA results. Relative density, depicted using a color gradient, is transformed to a cumulative probability. Contours are then plotted over regions with a specific cumulative probability. We use two real-world case studies to demonstrate the value of the PSA-ReD plot. RESULTS: The PSA-ReD method demonstrates proof-of-concept and feasibility. In the real-world case-studies, PSA-ReD provided additional visual information that could not be understood from the traditional scatterplot. High density areas were identified by color-coding and the contour plot allowed for quantification of PSA iterations within areas of the cost-effectiveness plane, diminishing overdrawing and putting infrequent iterations in perspective. Critically, the PSA-ReD plot informs modellers about non-linearities within their model. CONCLUSIONS: The PSA-ReD plot is easy to implement, presents more of the information enclosed in PSA data, and prevents inappropriate interpretation of PSA results. It gives modelers additional insight in model functioning and the distribution of uncertainty around the cost-effectiveness estimate.