Applying the win ratio method in clinical trials of orphan drugs: an analysis of data from the COMET trial of avalglucosidase alfa in patients with late-onset Pompe disease.

BACKGROUND: Clinical trials for rare diseases often include multiple endpoints that capture the effects of treatment on different disease domains. In many rare diseases, the primary endpoint is not standardized across trials. The win ratio approach was designed to analyze multiple endpoints of interest in clinical trials and has mostly been applied in cardiovascular trials. Here, we applied the win ratio approach to data from COMET, a phase 3 trial in late-onset Pompe disease, to illustrate how this approach can be used to analyze multiple endpoints in the orphan drug context. METHODS: All possible participant pairings from both arms of COMET were compared sequentially on changes at week 49 in upright forced vital capacity (FVC) % predicted and six-minute walk test (6MWT). Each participant's response for the two endpoints was first classified as a meaningful improvement, no meaningful change, or a meaningful decline using thresholds based on published minimal clinically important differences (FVC ± 4% predicted, 6MWT ± 39 m). Each comparison assessed whether the outcome with avalglucosidase alfa (AVA) was better than (win), worse than (loss), or equivalent to (tie) the outcome with alglucosidase alfa (ALG). If tied on FVC, 6MWT was compared. In this approach, the treatment effect is the ratio of wins to losses ("win ratio"), with ties excluded. RESULTS: In the 2499 possible pairings (51 receiving AVA × 49 receiving ALG), the win ratio was 2.37 (95% confidence interval [CI], 1.30-4.29, p = 0.005) when FVC was compared before 6MWT. When the order was reversed, the win ratio was 2.02 (95% CI, 1.13-3.62, p = 0.018). CONCLUSION: The win ratio approach can be used in clinical trials of rare diseases to provide meaningful insight on treatment benefits from multiple endpoints and across disease domains.

Correction: Chua et al. Cost-Effectiveness Analysis of HPV Extended versus Partial Genotyping for Cervical Cancer Screening in Singapore. Cancers 2023, 15, 1812.

The authors wish to revise two words in Table 1 row 3, and the first paragraph of Section 2 [...].

Cost-Effectiveness Analysis of HPV Extended versus Partial Genotyping for Cervical Cancer Screening in Singapore.

Human papillomavirus (HPV) partial genotyping (PGT) identifies HPV16 and HPV18 individually, alongside 12 other high-risk HPV genotypes (hrHPV) collectively. HPV extended genotyping (XGT) identifies four additional hrHPV individually (HPV31, 45, 51, and 52), and reports the remaining eight in three groups (HPV33|58; 56|59|66; 35|39|68). Quality-adjusted life years (QALY), health care resource use, and costs of XGT were compared to PGT for cervical cancer screening in Singapore using DICE simulation. Women with one of the three hrHPV identified by XGT (HPV35|39|68; 56|59|66; 51), and atypical squamous cells of undetermined significance (ASCUS) on cytology, are recalled for a repeat screening in one year, instead of undergoing an immediate colposcopy with PGT. At the repeat screening, the colposcopy is performed only for persistent same-genotype infections in XGT, while with PGT, all the women with persistent HPV have a colposcopy. Screening 500,122 women, aged 30-69, with XGT, provided an incremental cost-effectiveness ratio (ICER) versus PGT of SGD 16,370/QALY, with 7130 (19.4%) fewer colposcopies, 6027 (7.0%) fewer cytology tests, 9787 (1.6%) fewer clinic consultations, yet 2446 (0.5%) more HPV tests. The XGT ICER remains well below SGD 100,000 in sensitivity analyses, (-SGD 17,736/QALY to SGD 50,474/QALY). XGT is cost-effective compared to PGT, utilizes fewer resources, and provides a risk-based approach as the primary cervical cancer screening method.

The Impact of Restrictive Transfusion Practices on Hemodynamically Stable Critically Ill Children Without Heart Disease: A Secondary Analysis of the Age of Blood in Children in the PICU Trial.

OBJECTIVES: Guidelines recommend against RBC transfusion in hemodynamically stable (HDS) children without cardiac disease, if hemoglobin is greater than or equal to 7 g/dL. We sought to assess the clinical and economic impact of compliance with RBC transfusion guidelines. DESIGN: A nonprespecified secondary analysis of noncardiac, HDS patients in the randomized trial Age of Blood in Children (NCT01977547) in PICUs. Costs analyzed included ICU stay and physician fees. Stabilized inverse propensity for treatment weighting was used to create a cohort balanced with respect to potential confounding variables. Weighted regression models were fit to evaluate outcomes based on guideline compliance. SETTING: Fifty international tertiary care centers. PATIENTS: Critically ill children 3 days to 16 years old transfused RBCs at less than or equal to 7 days of ICU admission. Six-hundred eighty-seven subjects who met eligibility criteria were included in the analysis. INTERVENTIONS: Initial RBC transfusions administered when hemoglobin was less than 7 g/dL were considered "compliant" or "non-compliant" if hemoglobin was greater than or equal to 7 g/dL. MEASUREMENTS AND MAIN RESULTS: Frequency of new or progressive multiple organ system dysfunction (NPMODS), ICU survival, and associated costs. The hypothesis was formulated after data collection but exposure groups were masked until completion of planned analyses. Forty-nine percent of patients (338/687) received a noncompliant initial transfusion. Weighted cohorts were balanced with respect to confounding variables (absolute standardized differences < 0.1). No differences were noted in NPMODS frequency (relative risk, 0.86; 95% CI, 0.61-1.22; p = 0.4). Patients receiving compliant transfusions had more ICU-free days (mean difference, 1.73; 95% CI, 0.57-2.88; p = 0.003). Compliance reduced mean costs in ICU by $38,845 U.S. dollars per patient (95% CI, $65,048-$12,641). CONCLUSIONS: Deferring transfusion until hemoglobin is less than 7 g/dL is not associated with increased organ dysfunction in this population but is independently associated with increased likelihood of live ICU discharge and lower ICU costs.

A Framework for Integrating Continuous Glucose Monitor-Derived Metrics into Economic Evaluations in Type 1 Diabetes.

Economic models in type 1 diabetes have relied on a change in haemoglobin A1c as the link between the blood glucose trajectory and long-term clinical outcomes, including microvascular and macrovascular disease. The landscape has changed in the past decade with the availability of regulatory approved, accurate and convenient continuous glucose monitoring devices and their ability to track patients' glucose levels over time. The data emerging from continuous glucose monitoring have enriched the clinical understanding of the disease and indirectly of patients' behaviour. This has triggered the development of new measures proposed to better define the quality of glycaemic control, beyond haemoglobin A1c. The objective of this paper is to review recent developments in clinical knowledge brought into focus with the application of continuous glucose monitoring devices, and to discuss potential approaches to incorporate the concepts into economic models in type 1 diabetes. Based on a targeted review and a series of multidisciplinary workshops, an influence diagram was developed that captures newer concepts (e.g. continuous glucose monitoring metrics) that can be integrated into economic models and illustrates their association with more established concepts. How the additional continuous glucose monitoring-based indicators of glycaemic control may contribute to economic modelling beyond haemoglobin A1c, and more accurately reflect the economic value of novel type 1 diabetes treatments, is discussed.

Prediction of Recurrent Ischemic Stroke Using Registry Data and Machine Learning Methods: The Erlangen Stroke Registry.

BACKGROUND: There have been multiple efforts toward individual prediction of recurrent strokes based on structured clinical and imaging data using machine learning algorithms. Some of these efforts resulted in relatively accurate prediction models. However, acquiring clinical and imaging data is typically possible at provider sites only and is associated with additional costs. Therefore, we developed recurrent stroke prediction models based solely on data easily obtained from the patient at home. METHODS: Data from 384 patients with ischemic stroke were obtained from the Erlangen Stroke Registry. Patients were followed at 3 and 12 months after first stroke and then annually, for about 2 years on average. Multiple machine learning algorithms were applied to train predictive models for estimating individual risk of recurrent stroke within 1 year. Double nested cross-validation was utilized for conservative performance estimation and models' learning capabilities were assessed by learning curves. Predicted probabilities were calibrated, and relative variable importance was assessed using explainable artificial intelligence techniques. RESULTS: The best model achieved the area under the curve of 0.70 (95% CI, 0.64-0.76) and relatively good probability calibration. The most predictive factors included patient's family and housing circumstances, rehabilitative measures, age, high calorie diet, systolic and diastolic blood pressures, percutaneous endoscopic gastrotomy, number of family doctor's home visits, and patient's mental state. CONCLUSIONS: Developing fairly accurate models for individual risk prediction of recurrent ischemic stroke within 1 year solely based on registry data is feasible. Such models could be applied in a home setting to provide an initial risk assessment and identify high-risk patients early.

Predicting Hospital Resource Use During COVID-19 Surges: A Simple but Flexible Discretely Integrated Condition Event Simulation of Individual Patient-Hospital Trajectories.

OBJECTIVES: To assist with planning hospital resources, including critical care (CC) beds, for managing patients with COVID-19. METHODS: An individual simulation was implemented in Microsoft Excel using a discretely integrated condition event simulation. Expected daily cases presented to the emergency department were modeled in terms of transitions to and from ward and CC and to discharge or death. The duration of stay in each location was selected from trajectory-specific distributions. Daily ward and CC bed occupancy and the number of discharges according to care needs were forecast for the period of interest. Face validity was ascertained by local experts and, for the case study, by comparing forecasts with actual data. RESULTS: To illustrate the use of the model, a case study was developed for Guy's and St Thomas' Trust. They provided inputs for January 2020 to early April 2020, and local observed case numbers were fit to provide estimates of emergency department arrivals. A peak demand of 467 ward and 135 CC beds was forecast, with diminishing numbers through July. The model tended to predict higher occupancy in Level 1 than what was eventually observed, but the timing of peaks was quite close, especially for CC, where the model predicted at least 120 beds would be occupied from April 9, 2020, to April 17, 2020, compared with April 7, 2020, to April 19, 2020, in reality. The care needs on discharge varied greatly from day to day. CONCLUSIONS: The DICE simulation of hospital trajectories of patients with COVID-19 provides forecasts of resources needed with only a few local inputs. This should help planners understand their expected resource needs.

Evaluating Montréal's harm reduction interventions for people who inject drugs: protocol for observational study and cost-effectiveness analysis.

INTRODUCTION: The main harm reduction interventions for people who inject drugs (PWID) are supervised injection facilities, needle and syringe programmes and opioid agonist treatment. Current evidence supporting their implementation and operation underestimates their usefulness by excluding skin, soft tissue and vascular infections (SSTVIs) and anoxic/toxicity-related brain injury from cost-effectiveness analyses (CEA). Our goal is to conduct a comprehensive CEA of harm reduction interventions in a setting with a large, dispersed, heterogeneous population of PWID, and include prevention of SSTVIs and anoxic/toxicity-related brain injury as measures of benefit in addition to HIV, hepatitis C and overdose morbidity and mortalities averted. METHODS AND ANALYSIS: This protocol describes how we will develop an open, retrospective cohort of adult PWID living in Québec between 1 January 2009 and 31 December 2020 using administrative health record data. By complementing this data with non-linkable paramedic dispatch records, regional monthly needle and syringe dispensation counts and repeated cross-sectional biobehavioural surveys, we will estimate the hazards of occurrence and the impact of Montréal's harm reduction interventions on the incidence of drug-use-related injuries, infections and deaths. We will synthesise results from our empirical analyses with published evidence to simulate infections and injuries in a hypothetical population of PWID in Montréal under different intervention scenarios including current levels of use and scale-up, and assess the cost-effectiveness of each intervention from the public healthcare payer's perspective. ETHICS AND DISSEMINATION: This study was approved by McGill University's Institutional Review Board (Study Number: A08-E53-19B). We will work with community partners to disseminate results to the public and scientific community via scientific conferences, a publicly accessible report, op-ed articles and open access peer-reviewed journals.

Risk factors in adolescents as predictors of arterial hypertension in adults: Protocol for a systematic review.

This is a protocol of a review paper, and there is no abstract. This review is part of a doctoral project that aims to develop a discrete event simulation model to predict how many adolescents may become hypertensive in adulthood. We will use data from the Brazilian study of cardiovascular risks in adolescents, called ERICA (Portuguese acronym). This study may help promote adherence to disease prevention protocols.

Economic evaluation of betibeglogene autotemcel (Beti-cel) gene addition therapy in transfusion-dependent ß-thalassemia.

Background: Standard of care (SoC) for transfusion-dependent ß-thalassemia (TDT) requires lifelong, regular blood transfusions as well as chelation to reduce iron accumulation. Objective: This study investigates the cost-effectiveness of betibeglogene autotemcel ('beti-cel'; LentiGlobin for ß-thalassemia) one-time, gene addition therapy compared to lifelong SoC for TDT. Study design: Microsimulation model simulated the lifetime course of TDT based on a causal sequence in which transfusion requirements determine tissue iron levels, which in turn determine risk of iron overload complications that increase mortality. Clinical trial data informed beti-cel clinical parameters; effects of SoC on iron levels came from real-world studies; iron overload complication rates and mortality were based on published literature. Setting: USA; commercial payer perspective Participants: TDT patients age 2-50 Interventions: Beti-cel is compared to SoC. Main outcome measure: Incremental cost-effectiveness ratio (ICER) utilizing quality-adjusted life-years (QALYs) Results: The model predicts beti-cel adds 3.8 discounted life years (LYs) or 6.9 QALYs versus SoC. Discounted lifetime costs were $2.28 M for beti-cel ($572,107 if excluding beti-cel cost) and $2.04 M for SoC, with a resulting ICER of $34,833 per QALY gained. Conclusion: Beti-cel is cost-effective for TDT patients compared to SoC. This is due to longer survival and cost offset of lifelong SoC.

Using Discretely Integrated Condition Event Simulation To Construct Quantitative Benefit-Risk Models: The Example of Rotavirus Vaccination in France.

PURPOSE: Although quantitative benefit-risk models (qBRms) are indisputably valuable tools for gaining comprehensive assessments of health care interventions, they are not systematically used, probably because they lack an integrated framework that provides methodologic structure and harmonization. An alternative that allows all stakeholders to design operational models starting from a standardized framework was recently developed: the discretely integrated condition event (DICE) simulation. The aim of the present work was to assess the feasibility of implementing a qBRm in DICE, using the example of rotavirus vaccination. METHODS: A model of rotavirus vaccination was designed using DICE and implemented in spreadsheet software with 3 worksheets: Conditions, Events, and Outputs. Conditions held the information in the model; this information changed at Events, and Outputs were special Conditions that stored the results collected during the analysis. A hypothetical French birth cohort was simulated for the assessment of rotavirus vaccination over time. The benefits were estimated for up to 5 years, and the risks in the 7 days following rotavirus vaccination versus no vaccination were assessed, with the results expressed as benefit-risk ratios. FINDINGS: This qBRm model required 8 Events, 38 Conditions, and 9 Outputs. Two Events cyclically updated the rates of rotavirus gastroenteritis (RVGE) and intussusception (IS) according to age. Vaccination occurred at 2 additional Events, according to the vaccination scheme applied in France, and affected the occurrence of the other Events. Outputs were the numbers of hospitalizations related to RVGE and to IS, and related deaths. The entire model was specified in a small set of tables contained in a 445-KB electronic workbook. Analyses showed that for each IS-related hospitalization or death caused, 1613 (95% credible interval, 1001-2800) RVGE-related hospitalizations and 787 (95% credible interval, 246-2691) RVGE-related deaths would be prevented by vaccination. These results are consistent with those from a published French study using similar inputs but a very different modeling approach. IMPLICATIONS: A limitation of the DICE approach was the extended run time needed for completing the sensitivity analyses when implemented in the electronic worksheets. DICE provided a user-friendly integrated framework for developing qBRms and should be considered in the development of structured approaches to facilitate benefit-risk assessment.

Leveraging DICE (Discretely-Integrated Condition Event) Simulation to Simplify the Design and Implementation of Hybrid Models.

OBJECTIVES: Using an example of an existing model constructed by the National Institute for Health and Care Excellence (NICE) to inform a real health technology assessment, this study seeks to demonstrate how a discretely integrated condition event (DICE) simulation can improve the implementation of Markov models. METHODS: Using the technical report and spreadsheet, the original model was translated to a standard DICE simulation without making any changes to the design. All original analyses were repeated and the results were compared. Aspects that could have improved the original design were then considered. RESULTS: The original model consisted of 32 copies (8 risk strata × 4 treatments) of the Markov structure, containing more than 6000 Microsoft Excel® formulas (18 MB files). Three aspects (nonadherence, scheduled treatment stop, and end of fracture risk) were handled by incorporating weighted averages into the cycle-specific calculations. The DICE implementation used 3 conditions to represent the states and a single transition event to apply the probabilities; 3 additional events processed the special aspects, and profiles handled the 8 strata (0.12 MB file). One replication took 16 seconds. The original results were reproduced but extensive additional sensitivity analyses, including structural analyses, were enabled. CONCLUSION: Implementing a real Markov model using DICE simulation both preserves the advantages of the approach and expands the available tools, improving transparency and ease of use and review.

Economic Evaluation of Sequences of Biological Treatments for Patients With Moderate-to-Severe Rheumatoid Arthritis and Inadequate Response or Intolerance to Methotrexate in France.

OBJECTIVES: Biologic disease-modifying antirheumatic drugs (bDMARDs) are prescribed sequentially in the treatment of rheumatoid arthritis (RA). Healthcare decision makers continue to debate their use, mainly because of their high costs. Our aim was to perform an economic evaluation for France of bDMARD sequences for treatment of moderate-to-severe RA after inadequate response or intolerance to conventional DMARDs (eg, methotrexate). METHODS: A discretely integrated condition event simulation was developed to track the course of patients from first bDMARD through switches to further lines in a sequence. The model included 11 events, 91 conditions, and 21 controlling equations. Inputs were obtained from a meta-analysis of clinical trials, a French registry, national drug lists, and databases. Survival, time with minimal activity, quality-adjusted life-years (QALYs), and total costs were output. Structural and probabilistic sensitivity analyses were conducted. RESULTS: Sequences starting with etanercept biosimilars (ETB) cost less, with ETB-abatacept-infliximab the least expensive: the mean lifetime discounted total cost was €116 912 per patient, with a mean of 11.166 QALYs. Most other strategies were dominated or led to small QALY gains (0.0008-0.0329). Only ETB-tocilizumab-abatacept made it onto the efficiency frontier, but at €955 778 per QALY gained. These results were confirmed in several scenarios and uncertainty analyses. CONCLUSION: Given minor differences in QALYs gained between bDMARD sequences with large cost differences, starting with biosimilars was more efficient than starting with branded products. Our model and findings should provide French and other decision makers with useful tools to address the challenges of comparing sequences of treatments for RA.

Effect of Fresh vs Standard-issue Red Blood Cell Transfusions on Multiple Organ Dysfunction Syndrome in Critically Ill Pediatric Patients: A Randomized Clinical Trial.

Importance: The clinical consequences of red blood cell storage age for critically ill pediatric patients have not been examined in a large, randomized clinical trial. Objective: To determine if the transfusion of fresh red blood cells (stored ≤7 days) reduced new or progressive multiple organ dysfunction syndrome compared with the use of standard-issue red blood cells in critically ill children. Design, Setting, and Participants: The Age of Transfused Blood in Critically-Ill Children trial was an international, multicenter, blinded, randomized clinical trial, performed between February 2014 and November 2018 in 50 tertiary care centers. Pediatric patients between the ages of 3 days and 16 years were eligible if the first red blood cell transfusion was administered within 7 days of intensive care unit admission. A total of 15 568 patients were screened, and 13 308 were excluded. Interventions: Patients were randomized to receive either fresh or standard-issue red blood cells. A total of 1538 patients were randomized with 768 patients in the fresh red blood cell group and 770 in the standard-issue group. Main Outcomes and Measures: The primary outcome measure was new or progressive multiple organ dysfunction syndrome, measured for 28 days or to discharge or death. Results: Among 1538 patients who were randomized, 1461 patients (95%) were included in the primary analysis (median age, 1.8 years; 47.3% girls), in which there were 728 patients randomized to the fresh red blood cell group and 733 to the standard-issue group. The median storage duration was 5 days (interquartile range [IQR], 4-6 days) in the fresh group vs 18 days (IQR, 12-25 days) in the standard-issue group (P < .001). There were no significant differences in new or progressive multiple organ dysfunction syndrome between fresh (147 of 728 [20.2%]) and standard-issue red blood cell groups (133 of 732 [18.2%]), with an unadjusted absolute risk difference of 2.0% (95% CI, -2.0% to 6.1%; P = .33). The prevalence of sepsis was 25.8% (160 of 619) in the fresh group and 25.3% (154 of 608) in the standard-issue group. The prevalence of acute respiratory distress syndrome was 6.6% (41 of 619) in the fresh group and 4.8% (29 of 608) in the standard-issue group. Intensive care unit mortality was 4.5% (33 of 728) in the fresh group vs 3.5 % (26 of 732) in the standard-issue group (P = .34). Conclusions and Relevance: Among critically ill pediatric patients, the use of fresh red blood cells did not reduce the incidence of new or progressive multiple organ dysfunction syndrome (including mortality) compared with standard-issue red blood cells. Trial Registration: ClinicalTrials.gov Identifier: NCT01977547.

Trusting the Results of Model-Based Economic Analyses: Is there a Pragmatic Validation Solution?

Models have become a nearly essential component of health technology assessment. This is because the efficacy and safety data available from clinical trials are insufficient to provide the required estimates of impact of new interventions over long periods of time and for other populations and subgroups. Despite more than five decades of use of these decision-analytic models, decision makers are still often presented with poorly validated models and thus trust in their results is impaired. Among the reasons for this vexing situation are the artificial nature of the models, impairing their validation against observable data, the complexity in their formulation and implementation, the lack of data against which to validate the model results, and the challenges of short timelines and insufficient resources. This article addresses this crucial problem of achieving models that produce results that can be trusted and the resulting requirements for validation and transparency, areas where our field is currently deficient. Based on their differing perspectives and experiences, the authors characterize the situation and outline the requirements for improvement and pragmatic solutions to the problem of inadequate validation.

Determining Value in Health Technology Assessment: Stay the Course or Tack Away?

The economic evaluation of new health technologies to assess whether the value of the expected health benefits warrants the proposed additional costs has become an essential step in making novel interventions available to patients. This assessment of value is problematic because there exists no natural means to measure it. One approach is to assume that society wishes to maximize aggregate health, measured in terms of quality-adjusted life-years (QALYs). Commonly, a single 'cost-effectiveness' threshold is used to gauge whether the intervention is sufficiently efficient in doing so. This approach has come under fire for failing to account for societal values that favor treating more severe illness and ensuring equal access to resources, regardless of pre-existing conditions or capacity to benefit. Alternatives involving expansion of the measure of benefit or adjusting the threshold have been proposed and some have advocated tacking away from the cost per QALY entirely to implement therapeutic area-specific efficiency frontiers, multicriteria decision analysis or other approaches that keep the dimensions of benefit distinct and value them separately. In this paper, each of these alternative courses is considered, based on the experiences of the authors, with a view to clarifying their implications.