Diagnostics and Treatments of COVID-19: A Living Systematic Review of Economic Evaluations

A living critical interpretive synthesis to yield a framework on the production and dissemination of living evidence syntheses for decision-making

BACKGROUND

The COVID-19 pandemic has had an unprecedented impact in the global research production and has also increased research waste. Living evidence syntheses (LESs) seek to regularly update a body of evidence addressing a specific question. During the COVID-19 pandemic, the production and dissemination of LESs emerged as a cornerstone of the evidence infrastructure. This critical interpretive synthesis answers the questions: What constitutes an LES to support decision-making?; when should one be produced, updated, and discontinued?; and how should one be disseminated?

METHODS

Searches included the Cochrane Library, EMBASE (Ovid), Health Systems Evidence, MEDLINE (Ovid), PubMed, and Web of Science up to 23 April 2024 and included articles that provide any insights on addressing the compass questions on LESs. Articles were selected and appraised, and their insights extracted. An interpretive and iterative coding process was used to identify relevant thematic categories and create a conceptual framework.

RESULTS

Among the 16,630 non-duplicate records identified, 208 publications proved eligible. Most were non-empirical articles, followed by actual LESs. Approximately one in three articles were published in response to the COVID-19 pandemic. The conceptual framework addresses six thematic categories: (1) what is an LES; (2) what methodological approaches facilitate LESs production; (3) when to produce an LES; (4) when to update an LES; (5) how to make available the findings of an LES; and (6) when to discontinue LES updates.

CONCLUSION

LESs can play a critical role in reducing research waste and ensuring alignment with advisory and decision-making processes. This critical interpretive synthesis provides relevant insights on how to better organize the global evidence architecture to support their production.

TRIAL REGISTRATION

PROSPERO registration: CRD42021241875.

Multi-channel prismatic localized surface plasmon resonance biosensor for real-time competitive assay multiple COVID-19 characteristic miRNAs

A multi-channel prismatic localized surface plasmon resonance (LSPR) biosensor was developed for quantitative and real-time detection of multiple COVID-19 characteristic miRNAs. The well-dispersed and dense gold nanoparticles (AuNPs) arrays for LSPR biosensing were fabricated through a nano-thickness diblock copolymer template (BCPT). Both theoretical and experimental analyses were conducted to investigate the effects of particle size, interparticle spacing, and surface coverage on LSPR sensing spectrum and intensity sensitivity of varied AuNPs sizes. A competitive assay strategy was proposed and used for non-amplification miRNA detection with a low limit detection of 3.41 nM, while a four-channel prismatic LSPR system enables parallel detection of multiple miRNAs. Furthermore, this sensing strategy can effectively and specifically identify target miRNA, distinguish mismatched miRNA and interfering miRNA, and exhibit low non-specific adsorption. This BCPT-based LSPR biosensor demonstrates the practicality and potential of a multi-channel, adaptable, and integrated prismatic sensor in medical testing and diagnostic applications.

Lessons Learned from Model-based Economic Evaluations of COVID-19 Drug Treatments Under Pandemic Circumstances: Results from a Systematic Review

BACKGROUND

Following clinical research of potential coronavirus disease 2019 (COVID-19) treatments, numerous decision-analytic models have been developed. Due to pandemic circumstances, clinical evidence was limited and modelling choices were made under great uncertainty. This study aimed to analyse key methodological characteristics of model-based economic evaluations of COVID-19 drug treatments, and specifically focused on modelling choices which pertain to disease severity levels during hospitalisation, model structure, sources of effectiveness and quality of life and long-term sequelae.

METHODS

We conducted a systematic literature review and searched key databases (including MEDLINE, EMBASE, Web of Science, Scopus) for original articles on model-based full economic evaluations of COVID-19 drug treatments. Studies focussing on vaccines, diagnostic techniques and non-pharmaceutical interventions were excluded. The search was last rerun on 22 July 2023. Results were narratively synthesised in tabular form. Several aspects were categorised into rubrics to enable comparison across studies.

RESULTS

Of the 1047 records identified, 27 were included, and 23 studies (85.2%) differentiated patients by disease severity in the hospitalisation phase. Patients were differentiated by type of respiratory support, level of care management, a combination of both or symptoms. A Markov model was applied in 16 studies (59.3%), whether or not preceded by a decision tree or an epidemiological model. Most cost-utility analyses lacked the incorporation of COVID-19-specific health utility values. Of ten studies with a lifetime horizon, seven adjusted general population estimates to account for long-term sequelae (i.e. mortality, quality of life and costs), lasting for 1 year, 5 years, or a patient's lifetime. The most often reported parameter influencing the outcome of the analysis was related to treatment effectiveness.

CONCLUSION

The results illustrate the variety in modelling approaches of COVID-19 drug treatments and address the need for a more standardized approach in model-based economic evaluations of infectious diseases such as COVID-19.

TRIAL REGISTRY

Protocol registered in PROSPERO under CRD42023407646.

A systematic review of economic evaluations of pharmacological treatments for active tuberculosis

Objectives

The continuing spread of tuberculosis (TB) worldwide, especially drug-resistant TB, poses a major challenge to healthcare systems globally. Addressing this requires appraising the cost effectiveness of existing pharmacological interventions against TB to identify key drivers of cost effectiveness and value and guide pharmaceutical innovation and novel drug regimen development.

Methods

Studies were identified from a search of six database: MEDLINE MEDLINE-In Process, MEDLINE Epub Ahead of Print, EMBASE, Cochrane Database of Systematic Reviews, and Econlit in July 2022. Two reviewers independently assessed all identified studies and reports using pre-defined inclusion/exclusion criteria. Study methodological quality was assessed, data were extracted in standard tables, and results were narratively synthesized.

Results

Overall, 991 studies and 53 HTA reports were identified with 20 studies and 3 HTA reports meeting the inclusion criteria. Quality assessment of the 20 studies identified 4 with minor limitations, while the remainder were assessed as having potentially or very serious limitations. Sixteen studies conducted cost-utility analyses, 6 conducted cost-effectiveness analyses, and 2 conducted cost-comparison analyses with some studies performing multiple analyses. The majority (n = 16) were model-based. Eleven studies analyzed the cost-effectiveness of bedaquiline, 6 compared shorter to longer/standard duration regimens, 2 assessed ethambutol, and 1 assessed delamanid. Key drivers of cost effectiveness were drug costs, the number of TB cases, the portion of cases with sputum culture conversion, treatment delivery costs, and treatment efficacy. Common value elements considered included adverse events, drug resistance, and improving treatment adherence.

Conclusion

Our results suggest that out of the pharmacological treatments assessed, bedaquiline is likely a cost-effective addition to existing treatment regimens/background treatment regimens, while ethambutol is not likely to be. Newer shorter regimens, even if more costly, seem to be more cost-effective compared to longer regimens. These results illustrate the limited number of novel cost-effective pharmacological interventions and highlight a need to develop new drugs/regimens against TB to overcome resistance, taking into account the key drivers of cost effectiveness and other value attributes identified from this review.

Lessons from the pandemic: new best practices in selecting molecular diagnostics for point-of-care testing of infectious diseases in sub-Saharan Africa

INTRODUCTION

Point-of-care molecular diagnostics offer solutions to the limited diagnostic availability and accessibility in resource-limited settings. During the COVID-19 pandemic, molecular diagnostics became essential tools for accurate detection and monitoring of SARS-CoV-2. The unprecedented demand for molecular diagnostics presented challenges and catalyzed innovations which may provide lessons for the future selection of point-of-care molecular diagnostics.

AREAS COVERED

We searched PubMed from January 2020 to August 2023 to identify lessons learned from the COVID-19 pandemic which may impact the selection of point-of-care molecular diagnostics for future use in sub-Saharan Africa. We evaluated this in the context of REASSURED criteria (Real-time connectivity; Ease of specimen collection; Affordable; Sensitive; Specific; User-friendly; Rapid and robust; Equipment free; and Deliverable to users at the point of need) for point-of-care diagnostics for resource-limited settings.

EXPERT OPINION

The diagnostic challenges and successes during the COVID-19 pandemic affirmed the importance of the REASSURED criteria but demonstrated that these are not sufficient to ensure new diagnostics will be appropriate for public health emergencies. Capacity for rapid scale-up of diagnostic testing and transferability of assays, data, and technology are also important, resulting in updated REST-ASSURED criteria. Few diagnostics will meet all criteria, and trade-offs between criteria will need to be context-specific.

Cost-Effectiveness Analysis of Vaccines for COVID-19 According to Sex, Comorbidity and Socioeconomic Status: A Population Study

BACKGROUND AND OBJECTIVE

Coronavirus disease 2019 (COVID-19) vaccines are extremely effective in preventing severe disease, but their real-world cost effectiveness is still an open question. We present an analysis of the cost-effectiveness and economic impact of the initial phase of the COVID-19 vaccination rollout in the Basque Country, Spain.

METHODS

To calculate costs and quality-adjusted life years for the entire population of the Basque Country, dynamic modelling and a real-world data analysis were combined. Data on COVID-19 infection outcomes (cases, hospitalisations, intensive care unit admissions and deaths) and population characteristics (age, sex, socioeconomic status and comorbidity) during the initial phase of the vaccination rollout, from January to June of 2021, were retrieved from the Basque Health Service database. The outcomes in the alternative scenario (without vaccination) were estimated with the dynamic model used to guide public health authority policies, from February to December 2020. Individual comorbidity-adjusted life expectancy and costs were estimated.

RESULTS

By averting severe disease-related outcomes, COVID-19 vaccination resulted in monetary savings of €26.44 million for the first semester of 2021. The incremental cost-effectiveness ratio was €707/quality-adjusted life year considering official vaccine prices and dominant real prices. While the analysis by comorbidity showed that vaccines were considerably more cost effective in individuals with pre-existing health conditions, this benefit was lower in the low socioeconomic status group.

CONCLUSIONS

The incremental cost-effectiveness ratio of the vaccination programme justified the policy of prioritising high-comorbidity patients. The initial phase of COVID-19 vaccination was dominant from the perspective of the healthcare payer.

Clinical trials and their impact on policy during COVID-19: a review

Background

Of over 8,000 recorded randomised trials addressing COVID-19, around 80% were of treatments, and 17% have reported results. Approximately 1% were adaptive or platform trials, with 25 having results available, across 29 journal articles and 10 preprint articles.

Methods

We conducted an extensive literature review to address four questions about COVID-19 trials, particularly the role and impact of platform/adaptive trials and lessons learned.

Results

The key findings were: Q1. Social value in conducting trials and uptake into policy? COVID-19 drug treatments varied substantially and changed considerably, with drugs found effective in definitive clinical trials replacing unproven drugs. Dexamethasone has likely saved ½-2 million lives, and was cost effective across a range of countries and populations, whereas the cost effectiveness of remdesivir is uncertain. Published economic and health system impacts of COVID-19 treatments were infrequent. Q2. Issues with adaptive trial designs. Of the 77 platform trials registered, 6 major platform trials, with approximately 50 treatment arms, recruited ~135,000 participants with funding over $100 million. Q3. Models of good practice. Streamlined set-up processes such as flexible and fast-track funding, ethics, and governance approvals are vital. To facilitate recruitment, simple and streamlined research processes, and pre-existing research networks to coordinate trial planning, design, conduct and practice change are crucial to success. Q4. Potential conflicts to avoid? When treating patients through trials, balancing individual and collective rights and allocating scarce resources between healthcare and research are challenging. Tensions occur between commercial and non-commercial sectors, and academic and public health interests, such as publication and funding driven indicators and the public good.

Conclusion

There is a need to (i) reduce small, repetitive, single centre trials, (ii) increase coordination to ensure robust research conducted for treatments, and (iii) a wider adoption of adaptive/platform trial designs to respond to fast-evolving evidence landscape.

Diagnostics and treatments of COVID-19: two-year update to a living systematic review of economic evaluations

Objectives: As the initial crisis of the COVID-19 pandemic recedes, healthcare decision makers are likely to want to make rational evidence-guided choices between the many interventions now available. We sought to update a systematic review to provide an up-to-date summary of the cost-effectiveness evidence regarding tests for SARS-CoV-2 and treatments for COVID-19. Methods: Key databases, including MEDLINE, EconLit and Embase, were searched on 3 July 2023, 2 years on from the first iteration of this review in July 2021. We also examined health technology assessment (HTA) reports and the citations of included studies and reviews. Peer-reviewed studies reporting full health economic evaluations of tests or treatments in English were included. Studies were quality assessed using an established checklist, and those with very serious limitations were excluded. Data from included studies were extracted into predefined tables. Results: The database search identified 8,287 unique records, of which 54 full texts were reviewed, 28 proceeded for quality assessment, and 15 were included. Three further studies were included through HTA sources and citation checking. Of the 18 studies ultimately included, 17 evaluated treatments including corticosteroids, antivirals and immunotherapies. In most studies, the comparator was standard care. Two studies in lower-income settings evaluated the cost effectiveness of rapid antigen tests and critical care provision. There were 17 modelling analyses and 1 trial-based evaluation. Conclusion: A large number of economic evaluations of interventions for COVID-19 have been published since July 2021. Their findings can help decision makers to prioritise between competing interventions, such as the repurposed antivirals and immunotherapies now available to treat COVID-19. However, some evidence gaps remain present, including head-to-head analyses, disease-specific utility values, and consideration of different disease variants. Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021272219], identifier [PROSPERO 2021 CRD42021272219].

Economic evaluations of artificial intelligence-based healthcare interventions: a systematic literature review of best practices in their conduct and reporting

Objectives: Health economic evaluations (HEEs) help healthcare decision makers understand the value of new technologies. Artificial intelligence (AI) is increasingly being used in healthcare interventions. We sought to review the conduct and reporting of published HEEs for AI-based health interventions. Methods: We conducted a systematic literature review with a 15-month search window (April 2021 to June 2022) on 17th June 2022 to identify HEEs of AI health interventions and update a previous review. Records were identified from 3 databases (Medline, Embase, and Cochrane Central). Two reviewers screened papers against predefined study selection criteria. Data were extracted from included studies using prespecified data extraction tables. Included studies were quality assessed using the National Institute for Health and Care Excellence (NICE) checklist. Results were synthesized narratively. Results: A total of 21 studies were included. The most common type of AI intervention was automated image analysis (9/21, 43%) mainly used for screening or diagnosis in general medicine and oncology. Nearly all were cost-utility (10/21, 48%) or cost-effectiveness analyses (8/21, 38%) that took a healthcare system or payer perspective. Decision-analytic models were used in 16/21 (76%) studies, mostly Markov models and decision trees. Three (3/16, 19%) used a short-term decision tree followed by a longer-term Markov component. Thirteen studies (13/21, 62%) reported the AI intervention to be cost effective or dominant. Limitations tended to result from the input data, authorship conflicts of interest, and a lack of transparent reporting, especially regarding the AI nature of the intervention. Conclusion: Published HEEs of AI-based health interventions are rapidly increasing in number. Despite the potentially innovative nature of AI, most have used traditional methods like Markov models or decision trees. Most attempted to assess the impact on quality of life to present the cost per QALY gained. However, studies have not been comprehensively reported. Specific reporting standards for the economic evaluation of AI interventions would help improve transparency and promote their usefulness for decision making. This is fundamental for reimbursement decisions, which in turn will generate the necessary data to develop flexible models better suited to capturing the potentially dynamic nature of AI interventions.

Methodological quality and reporting quality of COVID-19 living systematic review: a cross-sectional study

OBJECTIVES

The main objective of this study is to evaluate the methodological quality and reporting quality of living systematic reviews (LSRs) on Coronavirus disease 2019 (COVID-19), while the secondary objective is to investigate potential factors that may influence the overall quality of COVID-19 LSRs.

METHODS

Six representative databases, including Medline, Excerpta Medica Database (Embase), Cochrane Library, China national knowledge infrastructure (CNKI), Wanfang Database, and China Science, Technology Journal Database (VIP) were systematically searched for COVID-19 LSRs. Two authors independently screened articles, extracted data, and then assessed the methodological and reporting quality of COVID-19 LSRs using the "A Measurement Tool to Assess systematic Reviews-2" (AMSTAR-2) tool and "Preferred Reporting Items for Systematic reviews and Meta-Analyses" (PRISMA) 2020 statement, respectively. Univariate linear regression and multivariate linear regression were used to explore eight potential factors that might affect the methodological quality and reporting quality of COVID-19 LSRs.

RESULTS

A total of 64 COVID-19 LSRs were included. The AMSTAR-2 evaluation results revealed that the number of "yes" responses for each COVID-19 LSR was 13 ± 2.68 (mean ± standard deviation). Among them, 21.9% COVID-19 LSRs were rated as "high", 4.7% as "moderate", 23.4% as "low", and 50% as "critically low". The evaluation results of the PRISMA 2020 statement showed that the sections with poor adherence were methods, results and other information. The number of "yes" responses for each COVID-19 LSR was 21 ± 4.18 (mean ± standard deviation). The number of included studies and registration are associated with better methodological quality; the number of included studies and funding are associated with better reporting quality.

CONCLUSIONS

Improvement is needed in the methodological and reporting quality of COVID-19 LSRs. Researchers conducting COVID-19 LSRs should take note of the quality-related factors identified in this study to generate evidence-based evidence of higher quality.

Health technology assessment of tests for SARS-CoV-2 and treatments for COVID-19: A proposed approach and best-practice recommendations

OBJECTIVES

To develop best-practice guidance for health technology assessment (HTA) agencies when appraising diagnostic tests for SARS-CoV-2 and treatments for COVID-19.

METHODS

We used a policy sandbox approach to develop best-practice guidance for HTA agencies to approach known challenges associated with assessing tests and treatments for COVID-19. The guidance was developed by a multi-stakeholder workshop of twenty-one participants representing HTA agencies, clinical and patient experts, academia, industry, and a payer, from across Europe and North America. The workshop was supported by extensive background work to identify the key challenges, including: targeted reviews of existing COVID-related methods guidance for assessing interventions and clinical guidelines, engagement with clinical experts, a survey and workshop of HTA agencies, a systematic review of published economic evaluations, and a workshop of health economic modelers.

RESULTS

We suggest HTA agencies should consider using other types of evidence (e.g., real world) where high-quality randomized controlled trials may be lacking and healthcare systems would value timely HTA outputs. A "living" HTA approach may be useful, given the context of an evolving disease, scientific understanding and evidence base, allowing for decisions to be efficiently revisited in response to new information; particularly, if supported by a common "disease model" for COVID-19. Innovative ways of engaging with the public and clinicians, and early engagement with regulators and payers, are recommended.

CONCLUSIONS

HTA agencies should consider the elements of this guidance that are most suited to their existing processes to enable them to assess the effectiveness and value of interventions for COVID-19.

Epidemiologic and economic modelling of optimal COVID-19 policy: public health and social measures, masks and vaccines in Victoria, Australia

Background

Identifying optimal COVID-19 policies is challenging. For Victoria, Australia (6.6 million people), we evaluated 104 policy packages (two levels of stringency of public health and social measures [PHSMs], by two levels each of mask-wearing and respirator provision during large outbreaks, by 13 vaccination schedules) for nine future SARS-CoV-2 variant scenarios.

Methods

We used an agent-based model to estimate morbidity, mortality, and costs over 12 months from October 2022 for each scenario. The 104 policies (each averaged over the nine future variant scenarios) were ranked based on four evenly weighted criteria: cost-effectiveness from (a) health system only and (b) health system plus GDP perspectives, (c) deaths and (d) days exceeding hospital occupancy thresholds.

Findings

More compared to less stringent PHSMs reduced cumulative infections, hospitalisations and deaths but also increased time in stage ≥3 PHSMs. Any further vaccination from October 2022 decreased hospitalisations and deaths by 12% and 27% respectively compared to no further vaccination and was usually a cost-saving intervention from a health expenditure plus GDP perspective. High versus low vaccine coverage decreased deaths by 15% and reduced time in stage ≥3 PHSMs by 20%. The modelled mask policies had modest impacts on morbidity, mortality, and health system pressure. The highest-ranking policy combination was more stringent PHSMs, two further vaccine doses (an Omicron-targeted vaccine followed by a multivalent vaccine) for ≥30-year-olds with high uptake, and promotion of increased mask wearing (but not Government provision of respirators).

Interpretation

Ongoing vaccination and PHSMs continue to be key components of the COVID-19 pandemic response. Integrated epidemiologic and economic modelling, as exemplified in this paper, can be rapidly updated and used in pandemic decision making.

Funding

Anonymous donation, University of Melbourne funding.

Characteristics of Living Systematic Review for COVID-19

Purpose

The systematic review aims to analyze and summarize the characteristics of living systematic review (LSR) for coronavirus disease 2019 (COVID-19).

Methods

Six databases including Medline, Excerpta Medica (Embase), Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang Database and China Science, and Technology Journal Database (VIP), were searched as the source of basic information and methodology of LSR. Descriptive analytical methods were used to analyze the included COVID-19 LSRs, and the study characteristics of COVID-19 LSRs were further assessed.

Results

Sixty-four COVID-19 LSRs were included. Eighty-nine point one percent of LSRs were published on Science Citation Index (SCI) journals, and 64.1% publication with an impact factor (IF) >5 and 17.2% with an IF >15 among SCI journals. The first unit of the published LSRs for COVID-19 came from 19 countries, with the largest contribution from the UK (17.2%, 11/64). Forty point six percent of LSRs for COVID-19 were related to therapeutics topic which was considered the most concerned perspective for LSRs for COVID-19. Seventy-six point six percent of LSRs focused on the general population, with less attention to children, pregnant women and the elderly. However, the LSR for COVID-19 was reported incomplete on “living” process, including 40.6% of studies without search frequency, 79.7% of studies without screening frequency, 20.3% of studies without update frequency, and 65.6% of studies without the timing or criteria of transitioning LSR out of living mode.

Conclusion

Although researchers in many countries have applied LSRs to COVID-19, most of the LSRs for COVID-19 were incomplete in reporting on the “living” process and less focused on special populations. This could reduce the confidence of health-care providers and policy makers in the results of COVID-19 LSR, thereby hindering the translation of evidence on COVID-19 LSR into clinical practice. It was necessary to explicitly enact preferred reporting items for systematic reviews and meta-analyses (PRISMA) to improve the reporting quality of LSR and support ongoing efforts of therapeutics research for special patients with COVID-19.

Diagnostics and Treatments of COVID-19: A Living Systematic Review of Economic Evaluations

OBJECTIVES

As healthcare systems continue to respond to the COVID-19 pandemic, cost-effectiveness evidence will be needed to identify which tests and treatments for COVID-19 offer value for money. We sought to review economic evaluations of diagnostic tests and treatments for COVID-19, critically appraising the methodological approaches used and reporting cost-effectiveness estimates, using a "living" systematic review approach.

METHODS

Key databases (including MEDLINE, EconLit, Embase) were last searched on July 12, 2021. Gray literature and model repositories were also searched. Only full economic evaluations published in English were included. Studies were quality assessed and data were extracted into standard tables. Results were narratively summarized. The review was completed by 2 reviewers independently, with disagreements resolved through discussion with a senior reviewer.

RESULTS

Overall, 3540 records were identified, with 13 meeting the inclusion criteria. After quality assessment, 6 were excluded because of very severe limitations. Of the 7 studies included, 5 were cost-utility analyses and 2 were cost-effectiveness analyses. All were model-based analyses. A total of 5 evaluated treatments (dexamethasone, remdesivir, hypothetical) and 2 evaluated hypothetical testing strategies. Cost-effectiveness estimates were sensitive to the treatment effect on survival and hospitalization, testing speed and accuracy, disease severity, and price.

CONCLUSIONS

Presently, there are few economic evaluations for COVID-19 tests and treatments. They suggest treatments that confer a survival benefit and fast diagnostic tests may be cost effective. Nevertheless, studies are subject to major evidence gaps and take inconsistent analytical approaches. The evidence may improve for planned updates of this "living" review.