Questionnaire to assess relevance and credibility of modeling studies for informing health care decision making: an ISPOR-AMCP-NPC Good Practice Task Force report

Real-world service costs for neovascular-AMD clinics in the United Kingdom: structured literature review and scenario analysis

Objective: Current cost-effectiveness analyses (CEA) emphasise drug costs as the differentiator between NICE recommended anti-VEGF treatments but may neglect real-world non-drug costs of running nAMD services in the UK. To address this, this study identified real-world non-drug service cost items relevant to UK NHS nAMD clinics, including costs arising from operational strain (demand exceeding capacity).Methods: Cost items were identified by a structured literature review of peer-reviewed and grey literature, and an expert panel of 10 UK-based ophthalmologists with relevance to real-world practice. These items underwent meta-synthesis and were then determined in a consensus exercise.Results: Of 237 cost items identified, 217 (91.6%) met the consensus threshold of >0.51 and were included in the nAMD Service Non-Drug Cost Instrument (nAS). Sensitivity of cost items taken from UK Health Technology Assessment (HTA) using the nAS as the reference standard was low (HTAmin: 1.84%, 95% CI 0.50-4.65%; HTAmax: 70.51%, 95% CI 63.96-76.49%). False negative rates showed variable likelihood of misclassifying a service by cost burden depending on prevalence. Scenario analysis using cost magnitudes estimated annual per-patient clinic cost at £845 (within capacity) to £13,960 (under strain) compared to an HTAmin estimate of £210. Accounting for cost of strain under an assumed 50% increase in health resource utilisation influenced cost-effectiveness in a hypothetical genericisation scenario.Conclusion: Findings suggested that HTA underestimates UK NHS nAMD clinic cost burden with cost of strain contributing substantial additional unmeasured expense with impact on CEA. Given potential undertreatment due to strain, durability is suggested as one of the relevant factors in CEA of nAMD anti-VEGF treatments due to robustness under limited capacity conditions affecting UK ophthalmology services.

Microsimulation Models on Mental Health: A Critical Review of the Literature

OBJECTIVES

To retrieve and synthesize the literature on existing mental health-specific microsimulation models or generic microsimulation models used to examine mental health, and to critically appraise them.

METHODS

All studies on microsimulation and mental health published in English in MEDLINE, Embase, PsycINFO, and EconLit between January 1, 2010, and September 30, 2022, were considered. Snowballing, Google searches, and searches on specific journal websites were also undertaken. Data extraction was done on all studies retrieved and the reporting quality of each model was assessed using the Quality Assessment Reporting for Microsimulation Models checklist, a checklist developed by the research team. A narrative synthesis approach was used to synthesize the evidence.

RESULTS

Among 227 potential hits, 19 studies were found to be relevant. Some studies covered existing economic-demographic models, which included a component on mental health and were used to answer mental-health-related research questions. Other studies were focused solely on mental health and included models that were developed to examine the impact of specific policies or interventions on specific mental disorders or both. Most models examined were of medium quality. The main limitations included the use of model inputs based on self-reported and/or cross-sectional data, small and/or nonrepresentative samples and simplifying assumptions, and lack of model validation.

CONCLUSIONS

This review found few high-quality microsimulation models on mental health. Microsimulation models developed specifically to examine mental health are important to guide healthcare delivery and service planning. Future research should focus on developing high-quality mental health-specific microsimulation models with wide applicability and multiple functionalities.

Economic Evaluations of Screening Programs for Chronic Kidney Disease: A Systematic Review

OBJECTIVES

The aim of this review is to appraise and assimilate evidence from studies that have reported on the cost-effectiveness of screening programs for chronic kidney disease (CKD).

METHODS

The study protocol was registered on International Prospective Register of Systematic Reviews (PROSPERO). The final search was conducted on 18 January 2023 using 7 databases. Screening of articles, data extraction, and quality assessment was performed by 2 independent reviewers. The ISPOR-AMCP-NPC checklist was used to assess the credibility of the included studies.

RESULTS

From 4948 retrieved studies, a final total of 20 studies were included in the qualitative synthesis. Studies found that screening in diabetic populations was cost-effective (n = 8, 57%) or even cost-saving (n = 6, 43%). Four studies (67%) found that screening in hypertensive populations was also cost-effective. For the general population, findings were inconsistent across studies in which many found screening to be cost-effective (n = 11, 69%), some cost-saving (n = 2, 12%), and others not cost-effective (n = 3, 19%). The most influential parameters identified were prevalence of CKD and cost of screening.

CONCLUSIONS

Screening for CKD in patients with diabetes or hypertension is recommended from a cost-effectiveness point of view. For the general population, despite some inconsistent findings, the majority of studies demonstrated that screening in this population is cost-effective, depending mainly on the prevalence and the costs of screening. Healthcare decision makers need to consider the prevalence, stratification strategies, and advocate for lower screening costs to reduce the burden on healthcare budgets and to make screening even more favorable from the health-economic perspective.

SARS-CoV-2 variants of concern in children and adolescents with COVID-19: a systematic review

OBJECTIVES

Infections by SARS-CoV-2 variants of concern (VOCs) might affect children and adolescents differently than earlier viral lineages. We aimed to address five questions about SARS-CoV-2 VOC infections in children and adolescents: (1) symptoms and severity, (2) risk factors for severe disease, (3) the risk of infection, (4) the risk of transmission and (5) long-term consequences following a VOC infection.

DESIGN

Systematic review.

DATA SOURCES

The COVID-19 Open Access Project database was searched up to 1 March 2022 and PubMed was searched up to 9 May 2022.

ELIGIBILITY CRITERIA

We included observational studies about Alpha, Beta, Gamma, Delta and Omicron VOCs among ≤18-year-olds. We included studies in English, German, French, Greek, Italian, Spanish and Turkish.

DATA EXTRACTION AND SYNTHESIS

Two reviewers extracted and verified the data and assessed the risk of bias. We descriptively synthesised the data and assessed the risks of bias at the outcome level.

RESULTS

We included 53 articles. Most children with any VOC infection presented with mild disease, with more severe disease being described with the Delta or the Gamma VOC. Diabetes and obesity were reported as risk factors for severe disease during the whole pandemic period. The risk of becoming infected with a SARS-CoV-2 VOC seemed to increase with age, while in daycare settings the risk of onward transmission of VOCs was higher for younger than older children or partially vaccinated adults. Long-term symptoms following an infection with a VOC were described in <5% of children and adolescents.

CONCLUSION

Overall patterns of SARS-CoV-2 VOC infections in children and adolescents are similar to those of earlier lineages. Comparisons between different pandemic periods, countries and age groups should be improved with complete reporting of relevant contextual factors, including VOCs, vaccination status of study participants and the risk of exposure of the population to SARS-CoV-2.

PROSPERO REGISTRATION NUMBER

CRD42022295207.

Is there a place for sigmoidoscopy in colorectal cancer screening? A systematic review and critical appraisal of cost-effectiveness models

INTRODUCTION

Screening for colorectal cancer (CRC) is effective in reducing both incidence and mortality. Colonoscopy and stool tests are most frequently used for this purpose. Sigmoidoscopy is an alternative screening measure with a strong evidence base. Due to its distinct characteristics, it might be preferred by subgroups. The aim of this systematic review is to analyze the cost-effectiveness of sigmoidoscopy for CRC screening compared to other screening methods and to identify influencing parameters.

METHODS

A systematic literature search for the time frame 01/2010-01/2023 was conducted using the databases MEDLINE, Embase, EconLit, Web of Science, NHS EED, as well as the Cost-Effectiveness Registry. Full economic analyses examining sigmoidoscopy as a screening measure for the general population at average risk for CRC were included. Incremental cost-effectiveness ratios were calculated. All included studies were critically assessed based on a questionnaire for modelling studies.

RESULTS

Twenty-five studies are included in the review. Compared to no screening, sigmoidoscopy is a cost-effective screening strategy for CRC. When modelled as a single measure strategy, sigmoidoscopy is mostly dominated by colonoscopy or modern stool tests. When combined with annual stool testing, sigmoidoscopy in 5-year intervals is more effective and less costly than the respective strategies alone. The results of the studies are influenced by varying assumptions on adherence, costs, and test characteristics.

CONCLUSION

The combination of sigmoidoscopy and stool testing represents a cost-effective screening strategy that has not received much attention in current guidelines. Further research is needed that goes beyond a narrow focus on screening technology and models different, preference-based participation behavior in subgroups.

Cost-effectiveness of prehabilitation prior to elective surgery: a systematic review of economic evaluations

BACKGROUND

Prehabilitation aims at enhancing patients' functional capacity and overall health status to enable them to withstand a forthcoming stressor like surgery. Our aim was to synthesise the evidence on the cost-effectiveness of prehabilitation for patients awaiting elective surgery compared with usual preoperative care.

METHODS

We searched PubMed, Embase, the CRD database, ClinicalTrials.gov, the WHO ICTRP and the dissertation databases OADT and DART. Studies comparing prehabilitation for patients with elective surgery to usual preoperative care were included if they reported cost outcomes. All types of economic evaluations (EEs) were included. The primary outcome of the review was cost-effectiveness based on cost-utility analyses (CUAs). The risk of bias of trial-based EEs was assessed with the Cochrane risk of bias 2 tool and the ROBINS-I tool and the credibility of model-based EEs with the ISPOR checklist. Methodological quality of full EEs was assessed using the CHEC checklist. The EEs' results were synthesised narratively using vote counting based on direction of effect.

RESULTS

We included 45 unique studies: 25 completed EEs and 20 ongoing studies. Of the completed EEs, 22 were trial-based and three model-based, corresponding to four CUAs, three cost-effectiveness analyses, two cost-benefit analyses, 12 cost-consequence analyses and four cost-minimization analyses. Three of the four trial-based CUAs (75%) found prehabilitation cost-effective, i.e. more effective and/or less costly than usual care. Overall, 16/25 (64.0%) EEs found prehabilitation cost-effective. When excluding studies of insufficient credibility/critical risk of bias, this number reduced to 14/23 (60.9%). In 8/25 (32.0%), cost-effectiveness was unclear, e.g. because prehabilitation was more effective and more costly, and in one EE prehabilitation was not cost-effective.

CONCLUSIONS

We found some evidence that prehabilitation for patients awaiting elective surgery is cost-effective compared to usual preoperative care. However, we suspect a relevant risk of publication bias, and most EEs were of high risk of bias and/or low methodological quality. Furthermore, there was relevant heterogeneity depending on the population, intervention and methods. Future EEs should be performed over a longer time horizon and apply a more comprehensive perspective.

TRIAL REGISTRATION

PROSPERO CRD42020182813.

Evaluations of statistical methods for outlier detection when benchmarking in clinical registries: a systematic review

OBJECTIVES

Benchmarking is common in clinical registries to support the improvement of health outcomes by identifying underperforming clinician or health service providers. Despite the rise in clinical registries and interest in publicly reporting benchmarking results, appropriate methods for benchmarking and outlier detection within clinical registries are not well established, and the current application of methods is inconsistent. The aim of this review was to determine the current statistical methods of outlier detection that have been evaluated in the context of clinical registry benchmarking.

DESIGN

A systematic search for studies evaluating the performance of methods to detect outliers when benchmarking in clinical registries was conducted in five databases: EMBASE, ProQuest, Scopus, Web of Science and Google Scholar. A modified healthcare modelling evaluation tool was used to assess quality; data extracted from each study were summarised and presented in a narrative synthesis.

RESULTS

Nineteen studies evaluating a variety of statistical methods in 20 clinical registries were included. The majority of studies conducted application studies comparing outliers without statistical performance assessment (79%), while only few studies used simulations to conduct more rigorous evaluations (21%). A common comparison was between random effects and fixed effects regression, which provided mixed results. Registry population coverage, provider case volume minimum and missing data handling were all poorly reported.

CONCLUSIONS

The optimal methods for detecting outliers when benchmarking clinical registry data remains unclear, and the use of different models may provide vastly different results. Further research is needed to address the unresolved methodological considerations and evaluate methods across a range of registry conditions.

PROSPERO REGISTRATION NUMBER

CRD42022296520.

Comprehensive Review of Methods to Assess Uncertainty in Health Economic Evaluations

Uncertainty assessment is a cornerstone in model-based health economic evaluations (HEEs) that inform reimbursement decisions. No comprehensive overview of available uncertainty assessment methods currently exists. We aimed to review methods for uncertainty assessment for use in model-based HEEs, by conducting a snowballing review. We categorised all methods according to their stage of use relating to uncertainty assessment (identification, analysis, communication). Additionally, we classified identification methods according to sources of uncertainty, and subdivided analysis and communication methods according to their purpose. The review identified a total of 80 uncertainty methods: 30 identification, 28 analysis, and 22 communication methods. Uncertainty identification methods exist to address uncertainty from different sources. Most identification methods were developed with the objective to assess related concepts such as validity, model quality, and relevance. Almost all uncertainty analysis and communication methods required uncertainty to be quantified and inclusion of uncertainties in probabilistic analysis. Our review can help analysts and decision makers in selecting uncertainty assessment methods according to their aim and purpose of the assessment. We noted a need for further clarification of terminology and guidance on the use of (combinations of) methods to identify uncertainty and related concepts such as validity and quality. A key finding is that uncertainty assessment relies heavily on quantification, which may necessitate increased use of expert elicitation and/or the development of methods to assess unquantified uncertainty.

Cost-effectiveness of metabolic surgery for the treatment of type 2 diabetes and obesity: a systematic review of economic evaluations

AIM

To systematically identify and appraise the international literature on the cost-effectiveness of metabolic surgery for the treatment of comorbid type 2 diabetes (T2D) and obesity.

METHODS

A systematic search was conducted in electronic databases and grey literature sources up to 20 January 2021. Economic evaluations in a T2D population or a subpopulation with T2D were eligible for inclusion. Screening, data extraction, critical appraisal of methodological quality (Consensus Health Economic Criteria list) and assessment of transferability (International Society for Pharmacoeconomics and Outcomes Research questionnaire) were undertaken in duplicate. The incremental cost-effectiveness ratio (ICER) was the main outcome. Costs were reported in 2020 Irish Euro. Cost-effectiveness was interpreted using willingness-to-pay (WTP) thresholds of €20,000 and €45,000/quality-adjusted life year (QALY). Due to heterogeneity arising from various sources, a narrative synthesis was undertaken.

RESULTS

Thirty studies across seventeen jurisdictions met the inclusion criteria; 16 specifically in a T2D population and 14 in a subpopulation with T2D. Overall, metabolic surgery was found to be cost-effective or cost-saving. Where undertaken, the results were robust to sensitivity and scenario analyses. Of the 30 studies included, 15 were considered high quality. Identified limitations included limited long-term follow-up data and uncertainty regarding the utility associated with T2D remission.

CONCLUSION

Published high-quality studies suggest metabolic surgery is a cost-effective or cost-saving intervention. As the prevalence of obesity and obesity-related diseases increases worldwide, significant investment and careful consideration of the resource requirements needed for metabolic surgery programmes will be necessary to ensure that service provision is adequate to meet demand.

The impact of pancreatic cancer screening on life expectancy: A systematic review of modeling studies

Evidence supporting the effectiveness of pancreatic cancer (PC) screening is scant. Most clinical studies concern small populations with short follow-up durations. Mathematical models are useful to estimate long-term effects of PC screening using short-term indicators. This systematic review aims to evaluate the impact of PC screening on life expectancy (LE) in model-based studies. Therefore, we searched four databases (Embase, Medline, Web-of-science, Cochrane) until 30 May 2022 to identify model-based studies evaluating the impact of PC screening on LE in different risk populations. Two authors independently screened identified papers, extracted data and assessed the methodological quality of studies. A descriptive analysis was performed and the impact of screening strategies on LE of different risk groups was reported. Our search resulted in 419 studies, of which eight met the eligibility criteria (mathematical model, PC screening, LE). Reported relative risks (RR) for PC varied from 1 to 70. In higher risk individuals (RR > 5), annual screening (by imaging with 56% sensitivity for HGD/early stage PC) predicted to increase LE of screened individuals by 20 to 260 days. In the general population, one-time PC screening was estimated to decrease LE (2-110 days), depending on the test characteristics and treatment mortality risk. In conclusion, although the models use different and sometimes outdated or unrealistic assumptions, it seems that PC screening in high-risk populations improves LE, and that this gain increases with a higher PC risk. Updated model studies, with data from large clinical trials are necessary to predict the long-term effect of PC screening more accurately.

Data Governance for Real-World Data Management: A Proposal for a Checklist to Support Decision Making

OBJECTIVES

Real-world data (RWD) and real-world evidence (RWE) can provide extensive information on healthcare for use in health technology assessment and decision making. Nevertheless, there is a lack of consensus surrounding the appropriate data governance (DG) practices for RWD/RWE. Data sharing is also a large concern, especially considering evolving data protection regulations. Our objective is to propose recommendations for international standards of evaluating the acceptability of RWD governance practices.

METHODS

After reviewing the literature, we created a checklist targeting DG practices for RWD/RWE. We then carried out a 3-round Delphi panel, including European policy makers, health technology assessment experts, and hospital managers. The consensus for each statement was measured and the checklist adjusted accordingly.

RESULTS

The literature review identified the main topics regarding RWD/RWE DG practices: data privacy and security, data management and linkage, data access management, and the generation and use of RWE. Members of the Delphi panel (21 experts/25 invited) were presented a total of 24 statements related to each of the topics. Experts demonstrated a progressive level of consensus and importance ratings in all topics and to most statements. We suggest a refined checklist in which the statements rated less important or with less consensus have been removed.

CONCLUSIONS

This study suggests how the DG of RWD/RWE could be qualitatively evaluated. We propose checklists that could be used by all RWD/RWE users to help ensure the quality and integrity of RWD/RWE governance and complement data protection law.

Identification of the elements of models of antimicrobial resistance of bacteria for assessing their usefulness and usability in One Health decision making: a protocol for scoping review

INTRODUCTION

Antimicrobial resistance (AMR) is a complex problem that requires the One Health approach, that is, a collaboration among various disciplines working in different sectors (animal, human and environment) to resolve it. Mathematical and statistical models have been used to understand AMR development, emergence, dissemination, prediction and forecasting. A review of the published models of AMR will help consolidate our knowledge of the dynamics of AMR and will also facilitate decision-makers and researchers in evaluating the credibility, generalisability and interpretation of the results and aspects of AMR models. The study objective is to identify and synthesise knowledge on mathematical and statistical models of AMR among bacteria in animals, humans and environmental compartments.

METHODS AND ANALYSIS

Eligibility criteria: Original research studies reporting mathematical and statistical models of AMR among bacteria in animal, human and environmental compartments that were published until 2022 in English, French and Spanish will be included in this study.

SOURCES OF EVIDENCE

Database of PubMed, Agricola (Ovid), Centre for Agriculture and Bioscience Direct (CABI), Web of Science (Clarivate), Cumulative Index to Nursing and Allied Health Literature (CINAHL) and MathScinet. Data charting: Metadata of the study, the context of the study, model structure, model process and reporting quality will be extracted. A narrative summary of this information, gaps and recommendations will be prepared and reported in One Health decision-making context.

ETHICS AND DISSEMINATION

Research ethics board approval was not obtained for this study as neither human participation nor unpublished human data were used in this study. The study findings will be widely disseminated among the One Health Modelling Network for Emerging Infections network and stakeholders by means of conferences, and publication in open-access peer-reviewed journals.

Systematic review of applied mathematical models for the control of Schistosoma japonicum

BACKGROUND

Schistosoma japonicum remains endemic in China and the Philippines. Substantial progress has been made in the control of Japonicum in both China and the Philippines. China is reaching elimination thanks to a concerted effort of control strategies. Mathematical modelling has been a key tool in the design of control strategies, in place of expensive randomised-controlled trials. We conducted a systematic review to investigate mathematical models of Japonicum control strategies in China and the Philippines.

METHODS

We conducted a systematic review on July 5, 2020, in four electronic bibliographic databases - PubMed, Web of Science, SCOPUS and Embase. Articles were screened for relevance and for meeting the inclusion criteria. Data extracted included authors, year of publication, year of data collection, setting and ecological context, objectives, control strategies, main findings, the form and content of the model including its background, type, representation of population dynamics, heterogeneity of hosts, simulation period, source of parameters, model validation and sensitivity analysis. Results After screening, 19 eligible papers were included in the systematic review. Seventeen considered control strategies in China and two in the Philippines. Two frameworks were identified; the mean-worm burden framework and the prevalence-based framework, the latter of which increasingly common. Most models considered human and bovine definitive hosts. There were mixed additional elements included in the models, such as alternative definitive hosts and the role of seasonality and weather. Models generally agreed upon the need for an integrated control strategy rather than reliance on mass drug administration alone to sustain reductions in prevalence.

CONCLUSIONS

Mathematical modelling of Japonicum has converged from multiple approaches to modelling using the prevalence-based framework with human and bovine definitive hosts and find integrated control strategies to be most effective. Further research could investigate the role of other definitive hosts and model the effect of seasonal fluctuations in transmission.

Impact of interventions for tuberculosis prevention and care in South Africa - a systematic review of mathematical modelling studies

BACKGROUND

Substantial additional efforts are needed to prevent, find and successfully treat tuberculosis (TB) in South Africa (SA). In thepast decade, an increasing body of mathematical modelling research has investigated the population-level impact of TB prevention and careinterventions. To date, this evidence has not been assessed in the SA context.

OBJECTIVE

To systematically review mathematical modelling studies that estimated the impact of interventions towards the World HealthOrganization's End TB Strategy targets for TB incidence, TB deaths and catastrophic costs due to TB in SA.

METHODS

We searched the PubMed, Web of Science and Scopus databases for studies that used transmission-dynamic models of TB in SAand reported on at least one of the End TB Strategy targets at population level. We described study populations, type of interventions andtheir target groups, and estimates of impact and other key findings. For studies of country-level interventions, we estimated average annualpercentage declines (AAPDs) in TB incidence and mortality attributable to the intervention.

RESULTS

We identified 29 studies that met our inclusion criteria, of which 7 modelled TB preventive interventions (vaccination,antiretroviral treatment (ART) for HIV, TB preventive treatment (TPT)), 12 considered interventions along the care cascade for TB(screening/case finding, reducing initial loss to follow-up, diagnostic and treatment interventions), and 10 modelled combinationsof preventive and care-cascade interventions. Only one study focused on reducing catastrophic costs due to TB. The highest impactof a single intervention was estimated in studies of TB vaccination, TPT among people living with HIV, and scale-up of ART. Forpreventive interventions, AAPDs for TB incidence varied between 0.06% and 7.07%, and for care-cascade interventions between 0.05%and 3.27%.

CONCLUSION

We describe a body of mathematical modelling research with a focus on TB prevention and care in SA. We found higherestimates of impact reported in studies of preventive interventions, highlighting the need to invest in TB prevention in SA. However, studyheterogeneity and inconsistent baseline scenarios limit the ability to compare impact estimates between studies. Combinations, rather thansingle interventions, are likely needed to reach the End TB Strategy targets in SA.

Challenges for Economic Evaluations of Advanced Therapy Medicinal Products: A Systematic Review

OBJECTIVES

Advanced therapy medicinal products (ATMPs) are drugs for human use for the treatment of chronic, degenerative, or life-threatening diseases that are based on genes, tissues, or cells. This article aimed to identify and critically review published economic analyses of ATMPs.

METHODS

A systematic review of economic analyses of ATMPs was undertaken. Study characteristics, design, sources of data, resources and unit costs, modeling and extrapolation methods, study results, and sensitivity analyses were assessed.

RESULTS

A total of 46 economic analyses of ATMP (from 45 articles) were included; 4 were cell therapy medicinal products, 33 gene therapy medicinal products, and 9 tissue-engineered products. 30 therapies had commercial marketing approval; 39 studies were cost-utility analysis, 5 were cost-effectiveness analysis, and 2 were cost only studies. Four studies predicted that the ATMP offered a step change in the management of the condition and 10 studies estimated that the ATMP would offer a lower mean cost.

CONCLUSIONS

Comparison with historical controls, pooling of data, and use of techniques such as mixture cure fraction models should be used cautiously. Sensitivity analyses should be used across a plausible range of prices. Clinical studies need to be designed to align with health technology assessment requirements, including generic quality of life, and payers should aim for clarity of criteria. Regulators and national payers should aim for compatibility of registers to allow interchange of data. Given the increasing reliance on industry-funded economic analyses, careful critical review is recommended.

Considerations for transferability of health technology assessments: a scoping review of tools, methods, and practices

Health technology assessment (HTA) is commonly used to guide evidence-informed decisions to optimize resource use, prioritize policies, and support countries to achieve universal health coverage. Producing HTAs requires time, scientific expertise, and political commitment, but these are not available in all settings - especially in low- and middle-income countries (LMIC) where HTA processes may be less institutionalized. Transferring and adapting existing HTAs to local settings may offer a solution while reducing duplication efforts. This scoping review aims to provide an overview of tools, methods, approaches, and considerations which can aid HTA transfers. We systematically searched (from 2005 to 2020) six databases and, using predefined inclusion criteria, included twenty-two studies. Data extraction followed a structured process, while synthesis was more iterative. We identified a common approach for HTA transfers. It follows the de novo process of undertaking original HTAs, but with additional steps to assess relevance (applicability), quality, and transferability, as well as steps to adapt parameters where necessary. The EUnetHTA Adaptation Toolkit was the only tool that provided guidance for adapting multiple HTA domains. Other tools were specific to systematic reviews (n = 1) or economic evaluations (n = 12), where one provided guidance for systematic reviews of economic evaluations. Eight papers reported transferring an HTA, with only one transferring to an LMIC. Finally, we reported issues that may facilitate or hinder transferability. In conclusion, we identified fourteen transfer approaches in the form of guidance or checklists, but harmonized and pragmatic guidance for HTA transfers to suit settings with limited HTA capacity seems warranted.

A Comparison of the Content and Consistency of Methodological Quality and Transferability Checklists for Reviewing Model-Based Economic Evaluations

OBJECTIVES

The aim of this study was to examine whether and how the content of six checklists (Caro, Consensus on Health Economic Criteria [CHEC]-Extended, European Network of Health Economic Databases [EURONHEED], National Institute for Health and Care Excellence [NICE], Philips, Welte) affect the consistency in findings on methodological quality and transferability, using 10 model-based economic evaluations of genetic-guided pharmacotherapy for venous thromboembolism.

METHODS

Each checklist was categorised by domain (structure, data, consistency, etc.) and type of assessment (presence vs. appropriateness) and was applied to each study by two independent reviewers who agreed on ratings via consensus, and discussion with a third reviewer when necessary. Methodological quality scores and rankings were examined using Spearman correlation tests, with subgroup analyses for domains and types of assessment. We compared overall ratings of transferability qualitatively, including how content may affect what is considered 'transferable'.

RESULTS

The checklists had similar proportions of items judging presence and appropriateness, but varying proportions of items across domains. For methodological quality, ranking consistencies were the highest between CHEC-Extended-Philips, Philips-NICE and NICE-Caro, with similar consistencies for domains and type of assessment. For transferability, NICE and Caro identified the same study, which scored high on EURONHEED, as transferable to the UK, while Welte, which considered methodological quality, identified none as transferable.

CONCLUSIONS

We found that the choice of checklist can affect findings on study quality and decisions about whether study results are transferable, indicating that different checklists may shortlist different sets of studies in formulating policy recommendations, leading to different policy decisions. Our systematic approach for evaluating the content of methodological quality and transferability checklists of economic evaluations can be extended to other checklists.

Developing a cross-validation tool for evaluating economic evidence in rapid literature reviews

Background: Rapid economic reviews efficiently summarize economic evidence. However, reporting main findings without assessing quality and credibility can be misleading. The objective of this study was to develop a rapid cross-validation screening tool to evaluate economic evidence when conducting rapid economic literature reviews. Methods: This article outlines our reasoning and the theoretical concepts for developing the screening tool. Results: This cross-validation tool is a qualitative approach under a Bayesian framework that uses prior health economic evidence to gauge the credibility of the rapid economic review's findings. This article describes an application of this tool and highlights practical considerations for its development and deployment. Conclusion: This tool can provide a valuable screening instrument to evaluate the quality and credibility of the economic evidence.

Economic Evaluations of Magnetic Resonance Image-Guided Radiotherapy (MRIgRT): A Systematic Review

OBJECTIVES

This review systematically summarizes the evidence on the economic impact of magnetic resonance image-guided RT (MRIgRT).

METHODS

We systematically searched INAHTA, MEDLINE, and Scopus up to March 2022 to retrieve health economic studies. Relevant data were extracted on study type, model inputs, modeling methods and economic results.

RESULTS

Five studies were included. Two studies performed a full economic assessment to compare the cost-effectiveness of MRIgRT with other forms of image-guided radiation therapy. One study performed a cost minimization analysis and two studies performed an activity-based costing, all comparing MRIgRT with X-ray computed tomography image-guided radiation therapy (CTIgRT). Prostate cancer was the target condition in four studies and hepatocellular carcinoma in one. Considering the studies with a full economic assessment, MR-guided stereotactic body radiation therapy was found to be cost effective with respect to CTIgRT or conventional or moderate hypofractionated RT, even with a low reduction in toxicity. Conversely, a greater reduction in toxicity is required to compete with extreme hypofractionated RT without MR guidance.

CONCLUSIONS

This review highlights the great potential of MRIgRT but also the need for further evidence, especially for late toxicity, whose reduction is expected to be the real added value of this technology.

Modelling in economic evaluation of mental health prevention: current status and quality of studies

Background

The present study aimed to identify and critically appraise the quality of model-based economic evaluation studies in mental health prevention.

Methods

A systematic search was performed on MEDLINE, EMBASE, EconLit, PsycINFO, and Web of Science. Two reviewers independently screened for eligible records using predefined criteria and extracted data using a pre-piloted data extraction form. The 61-item Philips Checklist was used to critically appraise the studies. Systematic review registration number: CRD42020184519.

Results

Forty-nine studies were eligible to be included. Thirty studies (61.2%) were published in 2015–2021. Forty-seven studies were conducted for higher-income countries. There were mainly cost-utility analyses (n = 31) with the dominant primary outcome of quality-adjusted life year. The most common model was Markov (n = 26). Most of the studies were conducted from a societal or health care perspective (n = 37). Only ten models used a 50-year time horizon (n = 2) or lifetime horizon (n = 8). A wide range of mental health prevention strategies was evaluated with the dominance of selective/indicate strategy and focusing on common mental health problems (e.g., depression, suicide). The percentage of the Philip checkilst’s criteria fulfilled by included studies was 69.3% on average and ranged from 43.3 to 90%. Among three domains of the Philip checklist, criteria on the model structure were fulfilled the most (72.1% on average, ranging from 50.0% to 91.7%), followed by the data domain (69.5% on average, ranging from 28.9% to 94.0%) and the consistency domain (54.6% on average, ranging from 20.0% to 100%). The practice of identification of ‘relevant’ evidence to inform model structure and inputs was inadequately performed. The model validation practice was rarely reported.

Conclusions

There is an increasing number of model-based economic evaluations of mental health prevention available to decision-makers, but evidence has been limited to the higher-income countries and the short-term horizon. Despite a high level of heterogeneity in study scope and model structure among included studies, almost all mental health prevention interventions were either cost-saving or cost-effective. Future models should make efforts to conduct in the low-resource context setting, expand the time horizon, improve the evidence identification to inform model structure and inputs, and promote the practice of model validation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08206-9.

Evaluating the quality of the economic evidence in colorectal cancer genomics studies

The increase in the use of genome-based screening and diagnostic tests adds to the overall costs of oncologic care for colorectal cancer. This, in turn, has resulted in an increase in published economic analyses. Aim: To perform a systematic literature review of the available economic evidence evaluating the value of genomic testing for colorectal cancer and appraise the quality of the economic studies conducted to date. Methods: A systematic review of the literature for economic studies of colorectal cancer genomics from January 2006 through October 2020, and evaluation of study quality using the Quality of Health Economic Studies (QHES) instrument was conducted. The validated QHES was then applied to a final set of articles that met eligibility criteria. Results: Our search of the literature initially yielded 12,859 records. A final set of 49 articles met our inclusion criteria. The QHES score ranged from 24 to 100, with an average score of 82. Most of the studies (n = 40, 82%) scored above 75 and were considered of good quality. Conclusion: Our analysis revealed that most of the economic analyses of colorectal cancer genomic molecular diagnostics in the literature may be of good quality. There is, however, some variation in methodological rigor between the articles.

Data-Related Challenges in Cost-Effectiveness Analyses of Vaccines

Cost-effectiveness analyses (CEAs) are often prepared to quantify the expected economic value of potential vaccination strategies. Estimated outcomes and costs of vaccination strategies depend on numerous data inputs or assumptions, including estimates of vaccine efficacy and disease incidence in the absence of vaccination. Limitations in epidemiologic data can meaningfully affect both CEA estimates and the interpretation of those results by groups involved in vaccination policy decisions. Developers of CEAs should be transparent with regard to the ambiguity and uncertainty associated with epidemiologic information that is incorporated into their models. We describe selected data-related challenges to conducting CEAs for vaccination strategies, including generalizability of estimates of vaccine effectiveness, duration and functional form of vaccine protection that can change over time, indirect (herd) protection, and serotype replacement. We illustrate how CEA estimates can be sensitive to variations in specific epidemiologic assumptions, with examples from CEAs conducted for the USA that assessed vaccinations against human papillomavirus and pneumococcal disease. These challenges are certainly not limited to these two case studies and may be relevant to other vaccines.

Cost-Effectiveness of HIV Retention and Re-engagement Interventions in High-Income Countries: A Systematic Literature Review

Engagement in lifelong HIV care is critical for both patient and public health, yet there are limited resources to invest in improving HIV outcomes. We systematically reviewed evidence on the cost-effectiveness of retention and re-engagement interventions. We searched five databases for peer-reviewed studies published between 2010 and 2020. We assessed reporting and methods quality, extracted data on target populations, interventions, and cost-effectiveness, and evaluated overall strength of evidence. Eleven studies met inclusion criteria, and eight had moderate-high quality. Cost-effectiveness estimates ranged from cost-saving to over $1,000,000/quality-adjusted life year (QALY) gained. Of the 73 cost-effectiveness ratios reported, 64% were < $100,000/QALY gained. Interventions were more likely to be cost-effective when targeted to high-risk groups, implemented in locations where baseline retention levels were low, and when used in combination with other high-impact HIV interventions (such as prevention). Overall, existing evidence is moderately strong that retention and/or re-engagement interventions can be cost-effective in high-income countries.

Contribution and quality of mathematical modeling evidence in World Health Organization guidelines: A systematic review

Mathematical modeling studies are frequently conducted to guide policy in global health. However, the contribution of mathematical modeling studies to World Health Organization (WHO) guideline recommendations, and the quality of evidence contributed by these studies remains unknown. We conducted a systematic review of the WHO Guidelines Review Committee database to identify guideline recommendations that included evidence from mathematical modeling studies since inception of the Guidelines Review Committee on 1 December, 2007. We included WHO guideline recommendations citing a mathematical modeling study in the primary evidence base. We defined a mathematical model as a framework that predicted epidemiologic, health or economic impact of an intervention or decision in the clinical or public health context. The primary outcome was inclusion of evidence from mathematical modeling studies in a guideline recommendation. We evaluated each unique modeling study across multiple domains of quality. Between 1 December 2007 and 1 April 2019, the WHO Guidelines Review Committee approved 154 guidelines providing 1619 guideline recommendations. Mathematical modeling studies informed 46 WHO guidelines (29.9%) and 101 unique guideline recommendations (6.2%). Modeling evidence addressed topics related to infectious diseases in 38 guidelines (82.6%) and 81 recommendations (80.2%), most commonly for HIV and tuberculosis. Evidence from modeling studies was assessed in the GRADE evidence profile for 12 recommendations (12.9%) and GRADE evidence-to-decision framework for 45 recommendations (44.6%). Modeling-informed recommendations were more likely than other recommendations within the same guidelines to be issued with a "conditional" rather than "strong" strength of recommendation (53.5% versus 37.8%), and the evidence underlying modeling-informed recommendations was more likely to be assessed as very low quality (41.6% versus 24.1%). Upon review of individual modeling studies, we estimated that 33.8% of models performed a calibration, 29.4% of models performed a validation of results, and 20.6% of models reported a change in the study conclusion in the sensitivity analysis. While policy recommendations in WHO guidelines are informed by evidence from modeling studies, the validity of modeling studies included in guidelines development is heterogeneous. Quality assessment is needed to support the evaluation and incorporation of evidence from mathematical modeling studies in guidelines development.

The Health Economics of Metastatic Hormone-Sensitive and Non-Metastatic Castration-Resistant Prostate Cancer—A Systematic Literature Review with Application to the Canadian Context

Background: Health economic evaluations are needed to assess the impact on the healthcare system of emerging treatment patterns for advanced prostate cancer. The objective of this study is to review the scientific literature identifying cost-effectiveness and cost analyses that are assessing treatments for metastatic hormone-sensitive prostate cancer (mHSPC) and nonmetastatic castration-resistant prostate cancer (nmCRPC). Methods: On 29 June 2021, we searched the scientific (MEDLINE, Embase, and EBSCO) and grey literature for health economic studies targeting mHSPC and nmCRPC. We used the CHEC-extended checklist and the Welte checklist for risk-of-bias assessment and transferability analysis, respectively. Results: We retained 20 cost-effectiveness and 4 cost analyses in the mHSPC setting, and 14 cost-effectiveness and 6 cost analyses in the nmCRPC setting. Docetaxel in combination with androgen deprivation therapy (ADT) was the most cost-effective treatment in the mHSPC setting. Apalutamide, darolutamide, and enzalutamide presented similar results vs. ADT alone and were identified as cost-effective treatments for nmCRPC. An increase in costs as patients transitioned from nmCRPC to mCRPC was noted. Conclusions: We concluded that there is an important unmet need for health economic evaluations in the mHSPC and nmCRPC setting incorporating real-world data to support healthcare decision making.

Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: Update of a living systematic review and meta-analysis

BACKGROUND

Debate about the level of asymptomatic Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection continues. The amount of evidence is increasing and study designs have changed over time. We updated a living systematic review to address 3 questions: (1) Among people who become infected with SARS-CoV-2, what proportion does not experience symptoms at all during their infection? (2) What is the infectiousness of asymptomatic and presymptomatic, compared with symptomatic, SARS-CoV-2 infection? (3) What proportion of SARS-CoV-2 transmission in a population is accounted for by people who are asymptomatic or presymptomatic?

METHODS AND FINDINGS

The protocol was first published on 1 April 2020 and last updated on 18 June 2021. We searched PubMed, Embase, bioRxiv, and medRxiv, aggregated in a database of SARS-CoV-2 literature, most recently on 6 July 2021. Studies of people with PCR-diagnosed SARS-CoV-2, which documented symptom status at the beginning and end of follow-up, or mathematical modelling studies were included. Studies restricted to people already diagnosed, of single individuals or families, or without sufficient follow-up were excluded. One reviewer extracted data and a second verified the extraction, with disagreement resolved by discussion or a third reviewer. Risk of bias in empirical studies was assessed with a bespoke checklist and modelling studies with a published checklist. All data syntheses were done using random effects models. Review question (1): We included 130 studies. Heterogeneity was high so we did not estimate a mean proportion of asymptomatic infections overall (interquartile range (IQR) 14% to 50%, prediction interval 2% to 90%), or in 84 studies based on screening of defined populations (IQR 20% to 65%, prediction interval 4% to 94%). In 46 studies based on contact or outbreak investigations, the summary proportion asymptomatic was 19% (95% confidence interval (CI) 15% to 25%, prediction interval 2% to 70%). (2) The secondary attack rate in contacts of people with asymptomatic infection compared with symptomatic infection was 0.32 (95% CI 0.16 to 0.64, prediction interval 0.11 to 0.95, 8 studies). (3) In 13 modelling studies fit to data, the proportion of all SARS-CoV-2 transmission from presymptomatic individuals was higher than from asymptomatic individuals. Limitations of the evidence include high heterogeneity and high risks of selection and information bias in studies that were not designed to measure persistently asymptomatic infection, and limited information about variants of concern or in people who have been vaccinated.

CONCLUSIONS

Based on studies published up to July 2021, most SARS-CoV-2 infections were not persistently asymptomatic, and asymptomatic infections were less infectious than symptomatic infections. Summary estimates from meta-analysis may be misleading when variability between studies is extreme and prediction intervals should be presented. Future studies should determine the asymptomatic proportion of SARS-CoV-2 infections caused by variants of concern and in people with immunity following vaccination or previous infection. Without prospective longitudinal studies with methods that minimise selection and measurement biases, further updates with the study types included in this living systematic review are unlikely to be able to provide a reliable summary estimate of the proportion of asymptomatic infections caused by SARS-CoV-2.

REVIEW PROTOCOL

Open Science Framework (https://osf.io/9ewys/).

Indirectness (transferability) is critical when considering existing economic evaluations for GRADE Clinical Practice Guidelines: A systematic review

OBJECTIVE

GRADE practice guideline developers often perform systematic reviews of potential economic evaluations to inform recommendation decision-making. We aimed to identify indirectness characteristics of economic evaluations, related to GRADE evidence-to-decision (EtD) theoretical frameworks, that influence selection of these articles.

STUDY DESIGN AND SETTING

MEDLINE, EMBASE, CINAHL and EconLit were systematically searched to May 2020 to identify indirectness characteristics relevant for economic evaluation transferability to GRADE evidence-to-decision (EtD) theoretical frameworks. Four reviewers screened citations to identify articles of any type that explored study characteristics most important or relevant to economic evaluation transferability, restricted to English language We generated frequencies of article features, used thematic analysis to summarize study characteristics and assessed certainty in the evidence using GRADE-CERQual.

RESULTS

We included 57 articles, with a dearth of empirical literature - some may have been missed. We identified 8 general themes and 28 sub-themes most important to transferability from 41% of articles. Moderate-to-high confidence evidence suggested that GRADE EtD domains of population, intervention and comparison research question elements, resource use estimation and methodology, and provider and decision-maker acceptability are most important indirectness study characteristics that economists consider when choosing economic evaluation outcomes for use in recommendation decision-making.

CONCLUSION

We have identified factors important for guideline developers to consider when selecting economic evaluations as research evidence. An economic competency on the development team facilitates these endeavors. This supports the GRADE Working Group's tenant of transparent reporting or availability of sufficient information elsewhere to assess indirectness.

School Closures During Social Lockdown and Mental Health, Health Behaviors, and Well-being Among Children and Adolescents During the First COVID-19 Wave: A Systematic Review

IMPORTANCE

School closures as part of broader social lockdown measures during the COVID-19 pandemic may be associated with the health and well-being of children and adolescents.

OBJECTIVE

To review published reports on the association of school closures during broader social lockdown with mental health, health behaviors, and well-being in children and adolescents aged 0 to 19 years, excluding associations with transmission of infection.

EVIDENCE REVIEW

Eleven databases were searched from inception to September 2020, and machine learning was applied for screening articles. A total of 16 817 records were screened, 151 were reviewed in full text, and 36 studies were included. Quality assessment was tailored to study type. A narrative synthesis of results was undertaken because data did not allow meta-analysis.

FINDINGS

A total of 36 studies from 11 countries were identified, involving a total of 79 781 children and adolescents and 18 028 parents, which occurred during the first wave of the COVID-19 pandemic (February to July 2020). All evaluated school closure as part of broader social lockdown during the first COVID-19 wave, and the duration of school closure ranged from 1 week to 3 months. Of those, 9 (25%) were longitudinal pre-post studies, 5 (14%) were cohort, 21 (58%) were cross-sectional, and 1 (3%) was a modeling study. Thirteen studies (36%) were high quality, 17 (47%) were medium quality, and 6 (17%) were low quality. Twenty-three studies (64%) were published, 8 (22%) were online reports, and 5 (14%) were preprints. Twenty-five studies (69%) concerning mental health identified associations across emotional, behavioral, and restlessness/inattention problems; 18% to 60% of children and adolescents scored above risk thresholds for distress, particularly anxiety and depressive symptoms, and 2 studies reported no significant association with suicide. Three studies reported that child protection referrals were lower than expected number of referrals originating in schools. Three studies suggested higher screen time usage, 2 studies reported greater social media use, and 6 studies reported lower physical activity. Studies on sleep (10 studies) and diet (5 studies) provided inconclusive evidence on harms.

CONCLUSIONS AND RELEVANCE

In this narrative synthesis of reports from the first wave of the COVID-19 pandemic, studies of short-term school closures as part of social lockdown measures reported adverse mental health symptoms and health behaviors among children and adolescents. Associations between school closure and health outcomes and behaviors could not be separated from broader lockdown measures.

Benefits and harms of annual, biennial, or triennial breast cancer mammography screening for women at average risk of breast cancer: a systematic review for the European Commission Initiative on Breast Cancer (ECIBC)

BACKGROUND

Although mammography screening is recommended in most European countries, the balance between the benefits and harms of different screening intervals is still a matter of debate. This review informed the European Commission Initiative on Breast Cancer (BC) recommendations.

METHODS

We searched PubMed, EMBASE, and the Cochrane Library to identify RCTs, observational or modelling studies, comparing desirable (BC deaths averted, QALYs, BC stage, interval cancer) and undesirable (overdiagnosis, false positive related, radiation related) effects from annual, biennial, or triennial mammography screening in women of average risk for BC. We assessed the certainty of the evidence using the GRADE approach.

RESULTS

We included one RCT, 13 observational, and 11 modelling studies. In women 50-69, annual compared to biennial screening may have small additional benefits but an important increase in false positive results; triennial compared to biennial screening may have smaller benefits while avoiding some harms. In younger women (aged 45-49), annual compared to biennial screening had a smaller gain in benefits and larger harms, showing a less favourable balance in this age group than in women 50-69. In women 70-74, there were fewer additional harms and similar benefits with shorter screening intervals. The overall certainty of the evidence for each of these comparisons was very low.

CONCLUSIONS

In women of average BC risk, screening intervals have different trade-offs for each age group. The balance probably favours biennial screening in women 50-69. In younger women, annual screening may have a less favourable balance, while in women aged 70-74 years longer screening intervals may be more favourable.

The current status of risk-stratified breast screening

Apart from high-risk scenarios such as the presence of highly penetrant genetic mutations, breast screening typically comprises mammography or tomosynthesis strategies defined by age. However, age-based screening ignores the range of breast cancer risks that individual women may possess and is antithetical to the ambitions of personalised early detection. Whilst screening mammography reduces breast cancer mortality, this is at the risk of potentially significant harms including overdiagnosis with overtreatment, and psychological morbidity associated with false positives. In risk-stratified screening, individualised risk assessment may inform screening intensity/interval, starting age, imaging modality used, or even decisions not to screen. However, clear evidence for its benefits and harms needs to be established. In this scoping review, the authors summarise the established and emerging evidence regarding several critical dependencies for successful risk-stratified breast screening: risk prediction model performance, epidemiological studies, retrospective clinical evaluations, health economic evaluations and qualitative research on feasibility and acceptability. Family history, breast density or reproductive factors are not on their own suitable for precisely estimating risk and risk prediction models increasingly incorporate combinations of demographic, clinical, genetic and imaging-related parameters. Clinical evaluations of risk-stratified screening are currently limited. Epidemiological evidence is sparse, and randomised trials only began in recent years.

Population-Based Testing for Undiagnosed Hepatitis C: A Systematic Review of Economic Evaluations

BACKGROUND AND OBJECTIVES

Recognising the significant public health threat posed by hepatitis C, international targets have been established by the World Health Organization with the aim of eradicating the hepatitis C virus (HCV) by 2030. With the availability of safe and effective therapies, the greatest challenge to achieving elimination is the identification and treatment of those currently undiagnosed. This systematic review aimed to identify and appraise the international literature on the cost-effectiveness of birth cohort, universal, and age-based general population testing for identifying people with undiagnosed chronic HCV infection.

METHODS

A comprehensive literature search was undertaken in Medline, Embase and grey literature sources to identify studies published between 1 January 2000 and 17 July 2020. Retrieved citations were independently reviewed by two reviewers according to pre-defined eligibility criteria. Data extraction and critical appraisal were completed in duplicate. Study quality, relevance and credibility were assessed using the Consensus for Health Economic Criteria and the ISPOR questionnaires. All costs were reported in 2019 Irish Euro following adjustment for inflation and purchasing power parity. Willingness-to-pay (WTP) thresholds of €20,000 and €45,000 were adopted as reference points for interpreting cost-effectiveness in the narrative synthesis. The systematic review is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria.

RESULTS

Overall, 4622 citations were retrieved in the literature search. Of these, 27 studies met the inclusion criteria. Six (22%) of the 27 studies were rated as low quality, 17 (63%) were moderate quality and four (15%) were high quality. Compared with no testing or risk-based testing: 14 of 16 (88%) cost-utility analyses found that birth cohort testing was cost effective, eight of nine (89%) analyses found that universal testing was cost effective, and eight of eight (100%) analyses found that age-based general population testing was cost effective. Cost effectiveness was influenced by disease prevalence and progression, testing and treatment uptake, treatment eligibility of those identified by testing, the cost of treatment and the proportion of those treated that achieve sustained virological response.

CONCLUSION

Overall, the international evidence supports the potential cost effectiveness of birth cohort, universal, and age-based general population testing, but is caveated by study generalisability, specifically the transferability of findings from one jurisdiction to another, and institutional variations in healthcare delivery systems and budgetary constraints. The cost effectiveness of each approach will vary according to population- and health system-specific characteristics such as epidemiological context, testing coverage, linkage to care and capacity to treat. Given issues regarding the transferability of economic evaluations (for example, model inputs and assumptions) and the significant resources required to implement these interventions, jurisdiction-specific economic evaluations and budget impact analyses will likely be required to inform investment and implementation decisions.

REGISTRATION

PROSPERO, CRD42019127159. Registered 29 April 2019.

Development of a critical appraisal tool for models predicting the impact of 'test, trace, and protect' programmes on COVID-19 transmission

OBJECTIVES

To develop a critical appraisal tool for non-computational-specialist public health professionals to assess the quality and relevance of modelling studies about Test and Trace (and Protect - TTP) programmes' impact on COVID-19 transmission.

STUDY DESIGN

Decision-making tool development.

METHODS

Using Tugwell et al.'s 1985 Health Care Effectiveness equation as a conceptual framework, combined with a purposive search of the relevant early modeling literature, we developed six critical appraisal questions for the rapid assessment of modeling studies related to the evaluation of TTP programmes' effectiveness.

RESULTS

By applying the critical appraisal tool to selected recent COVID-19 modeling studies, we demonstrate how models can be evaluated using the six questions to evaluate internal and external validity and relevance.

CONCLUSIONS

These six critical appraisal questions are able to discriminate between modeling studies of higher and lower quality and relevance to evaluating TTP programmes' impact. However, these questions require independent validation in a larger and systematic sample of relevant modeling studies which have appeared in later stages of the pandemic.

Payer perceptions on the use of economic models in oncology decision making

BACKGROUND: To support oncology formulary decisions, especially with accelerated regulatory approvals and niche populations, payers desire data beyond what regulators review. Economic models showing financial impact of treatments may help, but data on payers' use of economic models in oncology are limited. OBJECTIVE: To assess payer perceptions regarding use of economic models in informing oncology formulary decisions. METHODS: A multidisciplinary steering committee involving health economists and payers developed a survey containing singleanswer, multiple-answer, and free-response questions. The pilot survey was tested at a mini-advisory board with 5 US payers and revised based on feedback. In February 2020, the survey was distributed to 221 US payers through the AMCP Market Insights program and 10 additional payer panelists, who were invited to discuss survey results. Results were presented primarily as frequencies of responses and evaluated by plan size, type of health plan, and geography (regional vs national). Differences in categorical data responses were compared using Pearson chi-square or Fisher's exact tests. Two-tailed values were reported and an alpha level of 0.05 or less was used to indicate statistical significance. RESULTS: Overall, 106 of 231 payers completed the survey (45.9%); 45.5% represented small plans (< 1 million lives), and 54.5% represented large plans (≥ 1 million lives). Respondents were largely pharmacists (89.9%), and 55.6% indicated that their job was pharmacy administrator. Payers indicated moderate/most interest in cost-effectiveness models (CEMs; 85.3%) and budget impact models (BIMs; 80.4%). Overall, 51.6% of respondents claimed oncology expertise on their pharmacy and therapeutics committees. Large plans were more likely to have expertise in reviewing oncology economic models than small plans (55.6% vs 31.1%, P = 0.015). The most common reasons for not reviewing economic models included "not available at time of review" (44.1%) and "potential bias" (38.2%). Overall, 43.1% of payers conduct analyses using their own data after reviewing a manufacturer-sponsored economic model. To inform formulary decisions, 62.7% of payers use BIMs and 66.7% use CEMs sometimes, often, or always. When comparing therapies with similar safety/efficacy profiles, 68.6% of payers reported economic models as helpful a moderate amount, a lot, or a great deal. Over one-third of payers (37.3%) were willing to partner with manufacturers on economic models using their plans' data. Payers valued preapproval information, data on total cost of care, and early access to models. Concerns remained regarding model transparency and assumptions. CONCLUSIONS: Most US payers reported interest in using economic models to inform oncology formulary decision making. Opportunities exist to educate payers in assessing economic models, especially among small health plans. Ensuring model availability at launch, transparency in model assumptions, and payer-manufacturer partnership in model development may increase the utility of oncology economic models among US payers. DISCLOSURES: Pfizer provided funding for this research, and Pfizer employees led the development of the survey instrument, were involved in the analysis and interpretation of the data, and contributed to the manuscript as authors. Arondekar and Niyazov are employed by Pfizer. Biskupiak, Oderda, and Brixner are managers of Millcreek Outcomes Group and were paid as consultants on this project. Burgoyne was a consultant for Pfizer on this project.

Interventions for people at ultra-high risk for psychosis: A systematic review of economic evaluations

AIM

Psychotic disorders have long-term negative consequences for functioning and quality of life. Ultra-high risk (UHR) programs aim to identify and treat people during the prodromal period before their first psychotic episode. Though studies on the clinical effectiveness of treating prodromal symptoms in people at UHR for psychosis exist, no review has exclusively and comprehensively evaluated the economic impact of UHR programs. Our objective was to systematically review the literature on economic evaluations of UHR programs.

METHODS

We searched the Cochrane, EMBASE, MEDLINE, and PsycInfo electronic databases, in addition to grey literature, from inception to March 2020 to identify economic evaluations of UHR programs. We included all cost and cost-effectiveness studies of interventions for people at UHR. The data were synthesized qualitatively, and a risk of bias assessment was performed.

RESULTS

Of the 1916 articles retrieved, six studies met our inclusion criteria. These included three cost analysis studies and three cost-effectiveness studies. Five studies were conducted from the health system perspective and the time horizon varied between six months and ten years. Only two reported quality-adjusted life-years (QALYs) as their outcome. Overall, all cost-effectiveness studies and one cost analysis suggested that UHR programs were cost-effective and cost saving, respectively. The risk of bias assessment suggested moderate levels of bias across all studies.

CONCLUSION

Economic evaluations of UHR programs varied in terms of outcomes and length of follow-up; however, most studies found them to be cost-effective. Future studies would benefit from long-term evaluations of UHR programs and consistent valuation of outcomes.

Non-pharmacological measures implemented in the setting of long-term care facilities to prevent SARS-CoV-2 infections and their consequences: a rapid review

BACKGROUND

Starting in late 2019, COVID-19, caused by the novel coronavirus SARS-CoV-2, spread around the world. Long-term care facilities are at particularly high risk of outbreaks, and the burden of morbidity and mortality is very high among residents living in these facilities.

OBJECTIVES

To assess the effects of non-pharmacological measures implemented in long-term care facilities to prevent or reduce the transmission of SARS-CoV-2 infection among residents, staff, and visitors.

SEARCH METHODS

On 22 January 2021, we searched the Cochrane COVID-19 Study Register, WHO COVID-19 Global literature on coronavirus disease, Web of Science, and CINAHL. We also conducted backward citation searches of existing reviews.

SELECTION CRITERIA

We considered experimental, quasi-experimental, observational and modelling studies that assessed the effects of the measures implemented in long-term care facilities to protect residents and staff against SARS-CoV-2 infection. Primary outcomes were infections, hospitalisations and deaths due to COVID-19, contaminations of and outbreaks in long-term care facilities, and adverse health effects.

DATA COLLECTION AND ANALYSIS

Two review authors independently screened titles, abstracts and full texts. One review author performed data extractions, risk of bias assessments and quality appraisals, and at least one other author checked their accuracy. Risk of bias and quality assessments were conducted using the ROBINS-I tool for cohort and interrupted-time-series studies, the Joanna Briggs Institute (JBI) checklist for case-control studies, and a bespoke tool for modelling studies. We synthesised findings narratively, focusing on the direction of effect. One review author assessed certainty of evidence with GRADE, with the author team critically discussing the ratings.

MAIN RESULTS

We included 11 observational studies and 11 modelling studies in the analysis. All studies were conducted in high-income countries. Most studies compared outcomes in long-term care facilities that implemented the measures with predicted or observed control scenarios without the measure (but often with baseline infection control measures also in place). Several modelling studies assessed additional comparator scenarios, such as comparing higher with lower rates of testing. There were serious concerns regarding risk of bias in almost all observational studies and major or critical concerns regarding the quality of many modelling studies. Most observational studies did not adequately control for confounding. Many modelling studies used inappropriate assumptions about the structure and input parameters of the models, and failed to adequately assess uncertainty. Overall, we identified five intervention domains, each including a number of specific measures. Entry regulation measures (4 observational studies; 4 modelling studies) Self-confinement of staff with residents may reduce the number of infections, probability of facility contamination, and number of deaths. Quarantine for new admissions may reduce the number of infections. Testing of new admissions and intensified testing of residents and of staff after holidays may reduce the number of infections, but the evidence is very uncertain. The evidence is very uncertain regarding whether restricting admissions of new residents reduces the number of infections, but the measure may reduce the probability of facility contamination. Visiting restrictions may reduce the number of infections and deaths. Furthermore, it may increase the probability of facility contamination, but the evidence is very uncertain. It is very uncertain how visiting restrictions may adversely affect the mental health of residents. Contact-regulating and transmission-reducing measures (6 observational studies; 2 modelling studies) Barrier nursing may increase the number of infections and the probability of outbreaks, but the evidence is very uncertain. Multicomponent cleaning and environmental hygiene measures may reduce the number of infections, but the evidence is very uncertain. It is unclear how contact reduction measures affect the probability of outbreaks. These measures may reduce the number of infections, but the evidence is very uncertain. Personal hygiene measures may reduce the probability of outbreaks, but the evidence is very uncertain.  Mask and personal protective equipment usage may reduce the number of infections, the probability of outbreaks, and the number of deaths, but the evidence is very uncertain. Cohorting residents and staff may reduce the number of infections, although evidence is very uncertain. Multicomponent contact -regulating and transmission -reducing measures may reduce the probability of outbreaks, but the evidence is very uncertain. Surveillance measures (2 observational studies; 6 modelling studies) Routine testing of residents and staff independent of symptoms may reduce the number of infections. It may reduce the probability of outbreaks, but the evidence is very uncertain. Evidence from one observational study suggests that the measure may reduce, while the evidence from one modelling study suggests that it probably reduces hospitalisations. The measure may reduce the number of deaths among residents, but the evidence on deaths among staff is unclear.  Symptom-based surveillance testing may reduce the number of infections and the probability of outbreaks, but the evidence is very uncertain. Outbreak control measures (4 observational studies; 3 modelling studies) Separating infected and non-infected residents or staff caring for them may reduce the number of infections. The measure may reduce the probability of outbreaks and may reduce the number of deaths, but the evidence for the latter is very uncertain. Isolation of cases may reduce the number of infections and the probability of outbreaks, but the evidence is very uncertain. Multicomponent measures (2 observational studies; 1 modelling study) A combination of multiple infection-control measures, including various combinations of the above categories, may reduce the number of infections and may reduce the number of deaths, but the evidence for the latter is very uncertain.

AUTHORS' CONCLUSIONS

This review provides a comprehensive framework and synthesis of a range of non-pharmacological measures implemented in long-term care facilities. These may prevent SARS-CoV-2 infections and their consequences. However, the certainty of evidence is predominantly low to very low, due to the limited availability of evidence and the design and quality of available studies. Therefore, true effects may be substantially different from those reported here. Overall, more studies producing stronger evidence on the effects of non-pharmacological measures are needed, especially in low- and middle-income countries and on possible unintended consequences of these measures. Future research should explore the reasons behind the paucity of evidence to guide pandemic research priority setting in the future.

Appraisal of patient-level health economic models of severe mental illness: systematic review

BACKGROUND

Healthcare decision makers require accurate long-term economic models to evaluate the cost-effectiveness of new mental health interventions.

AIMS

To assess the suitability of current patient-level economic models to estimate long-term economic outcomes in severe mental illness.

METHOD

We undertook pre-specified systematic searches in MEDLINE, Embase and PsycINFO to identify reviews and stand-alone publications of economic models of interventions for schizophrenia, bipolar disorder and major depressive disorder (PROSPERO: CRD42020158243). We screened paper titles and abstracts to identify unique patient-level economic models. We conducted a structured extraction of identified models, recording the presence of key predefined model features. Model quality and validation were appraised using the 2014 ISPOR and 2016 AdViSHE model checklists.

RESULTS

We identified 15 unique patient-level models for psychosis and major depressive disorder from 1481 non-duplicate records. Models addressed schizophrenia (n = 6), bipolar disorder (n = 2) and major depressive disorder (n = 7). The predominant model type was discrete event simulation (n = 9). Model complexity and incorporation of patient heterogeneity varied considerably, and only five models extrapolated costs and outcomes over a lifetime horizon. Key model parameters were often based on low-quality evidence, and checklist quality assessment revealed weak model verification procedures.

CONCLUSIONS

Existing patient-level economic models of interventions for severe mental illness have considerable limitations. New modelling efforts must be supplemented by the generation of good-quality, contemporary evidence suitable for model building. Combined effort across the research community is required to build and validate economic extrapolation models suitable for accurately assessing the long-term value of new interventions from short-term clinical trial data.

Stakeholder engagement in economic evaluation: Protocol for using the nominal group technique to elicit patient, healthcare provider, and health system stakeholder input in the development of an early economic evaluation model of chimeric antigen receptor T-cell therapy

INTRODUCTION

Chimeric antigen receptor T-cell (CAR-T) therapy is a class of immunotherapy. An economic evaluation conducted at an early stage of development of CAR-T therapy for treatment of adult relapsed or refractory acute lymphoblastic leukaemia could provide insight into factors contributing to the cost of treatment, the potential clinical benefits, and what the health system can afford. Traditionally, stakeholders are engaged in certain parts of health technology assessment processes, such as in the identification and selection of technologies, formulation of recommendations, and implementation of recommendations; however, little is known about processes for stakeholder engagement during the conduct of the assessment. This is especially the case for economic evaluations. Stakeholders, such as clinicians, policy-makers, patients, and their support networks, have insight into factors that can enhance the validity of an economic evaluation model. This research outlines a specific methodology for stakeholder engagement and represents an avenue to enhance health economic evaluations and support the use of these models to inform decision making for resource allocation. This protocol may inform a tailored framework for stakeholder engagement processes in future economic evaluation model development.

METHODS AND ANALYSIS

We will involve clinicians, healthcare researchers, payers, and policy-makers, as well as patients and their support networks in the conduct and verification of an early economic evaluation of a novel health technology to incorporate stakeholder-generated knowledge. Three stakeholder-specific focus groups will be conducted using an online adaptation of the nominal group technique to elicit considerations from each. This study will use CAR-T therapy for adults with relapsed or refractory B-cell acute lymphoblastic leukaemia as a basis for investigating broader stakeholder engagement processes.

ETHICS AND DISSEMINATION

This study received ethics approval from the Ottawa Hospital Research Institute Research Ethics Board (REB 20200320-01HT) and the results will be shared via conference presentations, peer-reviewed publications, and ongoing stakeholder engagement.

Efficacy and safety of treatment with biologicals for severe chronic rhinosinusitis with nasal polyps: A systematic review for the EAACI guidelines

This systematic review evaluates the efficacy and safety of biologicals for chronic rhinosinusitis with nasal polyps (CRSwNP) compared with the standard of care. PubMed, Embase, and Cochrane Library were searched for RCTs. Critical and important CRSwNP-related outcomes were considered. The risk of bias and the certainty of the evidence were assessed using GRADE. RCTs evaluated (dupilumab-2, omalizumab-4, mepolizumab-2, and reslizumab-1) included 1236 adults, with follow-up of 20-64 weeks. Dupilumab reduces the need for surgery (NFS) or oral corticosteroid (OCS) use (RR 0.28; 95% CI 0.20-0.39, moderate certainty) and improves with high certainty smell evaluated with UPSIT score (mean difference (MD) +10.54; 95% CI +9.24 to +11.84) and quality of life (QoL) evaluated with SNOT-22 (MD -19.14; 95% CI -22.80 to -15.47), with fewer treatment-related adverse events (TAEs) (RR 0.95; 95% CI 0.89-1.02, moderate certainty). Omalizumab reduces NFS (RR 0.85; 95% CI 0.78-0.92, high certainty), decreases OCS use (RR 0.38; 95% CI 0.10-1.38, moderate certainty), and improves high certainty smell (MD +3.84; 95% CI +3.64 to +4.04) and QoL (MD -15.65; 95% CI -16.16 to -15.13), with increased TAE (RR 1.73; 95% CI 0.60-5.03, moderate certainty). There is low certainty for mepolizumab reducing NFS (RR 0.78; 95% CI 0.64-0.94) and improving QoL (MD -13.3; 95% CI -23.93 to -2.67) and smell (MD +0.7; 95% CI -0.48 to +1.88), with increased TAEs (RR 1.64; 95% CI 0.41-6.50). The evidence for reslizumab is very uncertain.

Updated Pathway to Micro-elimination of Hepatitis C Virus in the Hemodialysis Population

Chronic hepatitis C virus (HCV) infection continues to be transmitted to hemodialysis (HD) patients within HD facilities globally. The goal of the World Health Organization to micro-eliminate HCV infection from the HD population by the year 2030 is not on target to be achieved. Obstacles to eliminate HCV in HD settings remain daunting due to a complex system created by a confluence of guidelines, legislation, regulation, and economics. HCV prevalence remains high and seroconversion continues among the HD patient population globally as a result of the HD procedure. Preventive strategies that effectively prevent HCV transmission, treatment-as-prevention, and rapid referral to treatment balanced with kidney transplant candidacy should be added to the current universal precautions approach. A safer system must be designed before HCV transmission can be halted and eliminated from the HD population.

Mass Testing With Contact Tracing Compared to Test and Trace for the Effective Suppression of COVID-19 in the United Kingdom: Systematic Review

BACKGROUND

Making testing available to everyone and tracing contacts might be the gold standard to control COVID-19. Many countries including the United Kingdom have relied on the symptom-based test and trace strategy in bringing the COVID-19 pandemic under control. The effectiveness of a test and trace strategy based on symptoms has been questionable and has failed to meet testing and tracing needs. This is further exacerbated by it not being delivered at the point of care, leading to rising cases and deaths. Increases in COVID-19 cases and deaths in the United Kingdom despite performing the highest number of tests in Europe suggest that symptom-based testing and contact tracing might not be effective as a control strategy. An alternative strategy is making testing available to all.

OBJECTIVE

The primary objective of this review was to compare mass testing and contact tracing with the conventional test and trace method in the suppression of SARS-CoV-2 infections. The secondary objective was to determine the proportion of asymptomatic COVID-19 cases reported during mass testing interventions.

METHODS

Literature in English was searched from September through December 2020 in Google Scholar, ScienceDirect, Mendeley, and PubMed. Search terms included "mass testing," "test and trace," "contact tracing," "COVID-19," "SARS-CoV-2," "effectiveness," "asymptomatic," "symptomatic," "community screening," "UK," and "2020." Search results were synthesized without meta-analysis using the direction of effect as the standardized metric and vote counting as the synthesis metric. A statistical synthesis was performed using Stata 14.2. Tabular and graphical methods were used to present findings.

RESULTS

The literature search yielded 286 articles from Google Scholar, 20 from ScienceDirect, 14 from Mendeley, 27 from PubMed, and 15 through manual search. A total of 35 articles were included in the review, with a sample size of nearly 1 million participants. We found a 76.9% (10/13, 95% CI 46.2%-95.0%; P=.09) majority vote in favor of the intervention under the primary objective. The overall proportion of asymptomatic cases among those who tested positive and in the tested sample populations under the secondary objective was 40.7% (1084/2661, 95% CI 38.9%-42.6%) and 0.0% (1084/9,942,878, 95% CI 0.0%-0.0%), respectively.

CONCLUSIONS

There was low-level but promising evidence that mass testing and contact tracing could be more effective in bringing the virus under control and even more effective if combined with social distancing and face coverings. The conventional test and trace method should be superseded by decentralized and regular mass rapid testing and contact tracing, championed by general practitioner surgeries and low-cost community services.

International travel-related control measures to contain the COVID-19 pandemic: a rapid review

BACKGROUND

In late 2019, the first cases of coronavirus disease 2019 (COVID-19) were reported in Wuhan, China, followed by a worldwide spread. Numerous countries have implemented control measures related to international travel, including border closures, travel restrictions, screening at borders, and quarantine of travellers.

OBJECTIVES

To assess the effectiveness of international travel-related control measures during the COVID-19 pandemic on infectious disease transmission and screening-related outcomes.

SEARCH METHODS

We searched MEDLINE, Embase and COVID-19-specific databases, including the Cochrane COVID-19 Study Register and the WHO Global Database on COVID-19 Research to 13 November 2020.

SELECTION CRITERIA

We considered experimental, quasi-experimental, observational and modelling studies assessing the effects of travel-related control measures affecting human travel across international borders during the COVID-19 pandemic. In the original review, we also considered evidence on severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). In this version we decided to focus on COVID-19 evidence only. Primary outcome categories were (i) cases avoided, (ii) cases detected, and (iii) a shift in epidemic development. Secondary outcomes were other infectious disease transmission outcomes, healthcare utilisation, resource requirements and adverse effects if identified in studies assessing at least one primary outcome.

DATA COLLECTION AND ANALYSIS

Two review authors independently screened titles and abstracts and subsequently full texts. For studies included in the analysis, one review author extracted data and appraised the study. At least one additional review author checked for correctness of data. To assess the risk of bias and quality of included studies, we used the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for observational studies concerned with screening, and a bespoke tool for modelling studies. We synthesised findings narratively. One review author assessed the certainty of evidence with GRADE, and several review authors discussed these GRADE judgements.

MAIN RESULTS

Overall, we included 62 unique studies in the analysis; 49 were modelling studies and 13 were observational studies. Studies covered a variety of settings and levels of community transmission. Most studies compared travel-related control measures against a counterfactual scenario in which the measure was not implemented. However, some modelling studies described additional comparator scenarios, such as different levels of stringency of the measures (including relaxation of restrictions), or a combination of measures. Concerns with the quality of modelling studies related to potentially inappropriate assumptions about the structure and input parameters, and an inadequate assessment of model uncertainty. Concerns with risk of bias in observational studies related to the selection of travellers and the reference test, and unclear reporting of certain methodological aspects. Below we outline the results for each intervention category by illustrating the findings from selected outcomes. Travel restrictions reducing or stopping cross-border travel (31 modelling studies) The studies assessed cases avoided and shift in epidemic development. We found very low-certainty evidence for a reduction in COVID-19 cases in the community (13 studies) and cases exported or imported (9 studies). Most studies reported positive effects, with effect sizes varying widely; only a few studies showed no effect. There was very low-certainty evidence that cross-border travel controls can slow the spread of COVID-19. Most studies predicted positive effects, however, results from individual studies varied from a delay of less than one day to a delay of 85 days; very few studies predicted no effect of the measure. Screening at borders (13 modelling studies; 13 observational studies) Screening measures covered symptom/exposure-based screening or test-based screening (commonly specifying polymerase chain reaction (PCR) testing), or both, before departure or upon or within a few days of arrival. Studies assessed cases avoided, shift in epidemic development and cases detected. Studies generally predicted or observed some benefit from screening at borders, however these varied widely. For symptom/exposure-based screening, one modelling study reported that global implementation of screening measures would reduce the number of cases exported per day from another country by 82% (95% confidence interval (CI) 72% to 95%) (moderate-certainty evidence). Four modelling studies predicted delays in epidemic development, although there was wide variation in the results between the studies (very low-certainty evidence). Four modelling studies predicted that the proportion of cases detected would range from 1% to 53% (very low-certainty evidence). Nine observational studies observed the detected proportion to range from 0% to 100% (very low-certainty evidence), although all but one study observed this proportion to be less than 54%. For test-based screening, one modelling study provided very low-certainty evidence for the number of cases avoided. It reported that testing travellers reduced imported or exported cases as well as secondary cases. Five observational studies observed that the proportion of cases detected varied from 58% to 90% (very low-certainty evidence). Quarantine (12 modelling studies) The studies assessed cases avoided, shift in epidemic development and cases detected. All studies suggested some benefit of quarantine, however the magnitude of the effect ranged from small to large across the different outcomes (very low- to low-certainty evidence). Three modelling studies predicted that the reduction in the number of cases in the community ranged from 450 to over 64,000 fewer cases (very low-certainty evidence). The variation in effect was possibly related to the duration of quarantine and compliance. Quarantine and screening at borders (7 modelling studies; 4 observational studies) The studies assessed shift in epidemic development and cases detected. Most studies predicted positive effects for the combined measures with varying magnitudes (very low- to low-certainty evidence). Four observational studies observed that the proportion of cases detected for quarantine and screening at borders ranged from 68% to 92% (low-certainty evidence). The variation may depend on how the measures were combined, including the length of the quarantine period and days when the test was conducted in quarantine.

AUTHORS' CONCLUSIONS

With much of the evidence derived from modelling studies, notably for travel restrictions reducing or stopping cross-border travel and quarantine of travellers, there is a lack of 'real-world' evidence. The certainty of the evidence for most travel-related control measures and outcomes is very low and the true effects are likely to be substantially different from those reported here. Broadly, travel restrictions may limit the spread of disease across national borders. Symptom/exposure-based screening measures at borders on their own are likely not effective; PCR testing at borders as a screening measure likely detects more cases than symptom/exposure-based screening at borders, although if performed only upon arrival this will likely also miss a meaningful proportion of cases. Quarantine, based on a sufficiently long quarantine period and high compliance is likely to largely avoid further transmission from travellers. Combining quarantine with PCR testing at borders will likely improve effectiveness. Many studies suggest that effects depend on factors, such as levels of community transmission, travel volumes and duration, other public health measures in place, and the exact specification and timing of the measure. Future research should be better reported, employ a range of designs beyond modelling and assess potential benefits and harms of the travel-related control measures from a societal perspective.

The Impact of Enhanced Recovery After Surgery on Total Joint Arthroplasty: Protocol for a Systematic Review and Meta-analysis

BACKGROUND

The number of total joint arthroplasties (TJAs) being performed is increasing worldwide. To match this increasing demand, there has been focus on hastening patients' recovery of function. This effort has culminated in the formulation of enhanced recovery after surgery (ERAS) strategies. However, with evolving ERAS programs and new recommendations, a review of current evidence is required to provide clinicians with up-to-date information about its effect on outcomes for TJA.

OBJECTIVE

The objective of this study is to assess the utility of ERAS programs on patient, health service, and economic outcomes for primary, elective total hip arthroplasty (THA) and total knee arthroplasty (TKA).

METHODS

A systematic search will be conducted in Medline (Ovid), EMCARE (Ovid), EMBASE (Ovid), Web of Science, CINAHL, National Health Service Economic Evaluations Database, and the Cochrane Library. Analytical, observational, and experimental designs will be included in this systematic review. Only studies including patients undergoing primary TKA and THA comparing ERAS programs with conventional surgery and postoperative care will be included. Data related to patient outcomes, health service outcomes, safety, and economic evaluation will be extracted.

RESULTS

The search terms and primary database searches have been finalized. Findings will be reported in narrative and tabular form. Where appropriate, random effects meta-analyses will be conducted for each outcome, and heterogeneity quantified with Cochran Q test and I2 statistic. Measures of effect or mean differences will be reported with 95% confidence intervals. The results of this systematic review will be disseminated in a peer-reviewed journal.

CONCLUSIONS

This protocol will guide a systematic review assessing outcomes associated with ERAS surgery in primary THA and TKA.

TRIAL REGISTRATION

Open Science Framework osf.io/y4bhs; https://osf.io/y4bhs.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/25581.

Economic evaluation of high-dose inactivated influenza vaccine in adults aged ≥65 years: A systematic literature review

INTRODUCTION

Due to waning immunity, adults aged ≥65 years are at increased risk of seasonal influenza infection and its complications. Adding to this risk, older adults have reduced responses to influenza vaccines. A high-dose trivalent inactivated influenza vaccine (Fluzone High-Dose, Sanofi Pasteur) (IIV3-HD) was developed to improve protection against influenza in adults aged ≥65 years and has been licensed in the US since 2009 and in Canada since 2015. Post-licensure studies have shown that IIV3-HD is more effective than standard-dose trivalent inactivated influenza vaccine (IIV3-SD) at protecting against influenza infection in this population. Here, we performed a systematic review of economic analyses of IIV3-HD in adults aged ≥65 years.

METHODS

On June 9, 2019, using the Ovid search platform, we searched Econlit, Embase, and Ovid MEDLINE® for original studies published in peer-reviewed journals examining the economics or cost-effectiveness of IIV3-HD in adults aged ≥65 years. Two reviewers independently selected studies and assessed their quality.

RESULTS

Seven studies were selected, all performed in the US or Canada. Five studies were funded by IIV3-HD manufacturer, and the remaining two by the US National Institute of General Medical Sciences. In all studies, IIV3-HD reduces healthcare resource utilization and is cost-effective or cost-saving compared to IIV3-SD. The main driver is reduced hospitalizations for cardiorespiratory events.

CONCLUSION

IIV3-HD is cost-saving or cost-effective versus IIV3-SD in adults aged ≥65 years. Reduced cardiorespiratory complications are an important driver of these economic benefits. A video summary of the article can be accessed via the Supplementary data link at the end of this article.