Access in all areas? A round up of developments in market access and HTA: part 5.

In this latest update, we explore the recent announcement by Canada's Drug Agency (CDA-AMC, formerly CADTH) on their pilot to include the societal perspective in the evaluation of certain new medicines; a recent Office of Health Economics (OHE) report on the evaluation of HTA agency methods over time; and publications examining the impact of Project Orbis on patient access to oncology treatments.

Co-Designing a Conversational Agent With Older Adults With Chronic Obstructive Pulmonary Disease Who Age in Place: Qualitative Study.

BACKGROUND: As a reaction to the global demographic increase in older adults (aged 60+ years), policy makers call for initiatives to enable healthy aging. This includes a focus on person-centered care and access to long-term care for older adults, such as developing different services and digital health technologies. This can enable patients to engage in their health and reduce the burden on the health care systems and health care professionals. The European Union project Smart Inclusive Living Environments (SMILE) focuses on well-being and aging in place using new digital health technologies. The novelty of the SMILE project is the use of a cocreational approach focused on the needs and preferences of older adults with chronic obstructive pulmonary disease (COPD) in technology development, to enhance access, adaptation, and usability and to reduce stigma. OBJECTIVE: The study aimed to describe the perspective, needs, and preferences of older adults living with COPD in the context of the design and development of a conversational agent. METHODS: This study carried out a data-driven thematic analysis of interview data from 11 cocreation workshops with 33 older adults living with COPD. RESULTS: The three particular features that the workshop participants wanted to implement in a new technology were (1) a "my health" function, to use technology to manage and learn more about their condition; (2) a "daily activities" function, including an overview and information about social and physical activities in their local area; and (3) a "sleep" function, to manage circadian rhythm and enhance sleep quality, for example, through online video guides. In total, 2 overarching themes were identified for the 3 functions: measurements, which were actively discussed and received mixed interest among the participants, and health literacy, due to an overall interest in learning more about their condition in relation to everyday life. CONCLUSIONS: The future design of digital health technology must embrace the complexities of the everyday life of an older adult living with COPD and cater to their needs and preferences. Measurements should be optional and personalized, and digital solutions should be used as a supplement to health care professionals, not as substitute.

Rapid and noninvasive estimation of human arsenic exposure based on 4-photo-set of the hand and foot photos through artificial intelligence.

Chronic exposure to arsenic is linked to the development of cancers in the skin, lungs, and bladder. Arsenic exposure manifests as variegated pigmentation and characteristic pitted keratosis on the hands and feet, which often precede the onset of internal cancers. Traditionally, human arsenic exposure is estimated through arsenic levels in biological tissues; however, these methods are invasive and time-consuming. This study aims to develop a noninvasive approach to predict arsenic exposure using artificial intelligence (AI) to analyze photographs of hands and feet. By incorporating well water consumption data and arsenic concentration levels, we developed an AI algorithm trained on 9988 hand and foot photographs from 2497 subjects. This algorithm correlates visual features of palmoplantar hyperkeratosis with arsenic exposure levels. Four pictures per patient, capturing both ventral and dorsal aspects of hands and feet, were analyzed. The AI model utilized existing arsenic exposure data, including arsenic concentration (AC) and cumulative arsenic exposure (CAE), to make binary predictions of high and low arsenic exposure. The AI model achieved an optimal area under the curve (AUC) values of 0.813 for AC and 0.779 for CAE. Recall and precision metrics were 0.729 and 0.705 for CAE, and 0.750 and 0.763 for AC, respectively. While biomarkers have traditionally been used to assess arsenic exposure, efficient noninvasive methods are lacking. To our knowledge, this is the first study to leverage deep learning for noninvasive arsenic exposure assessment. Despite challenges with binary classification due to imbalanced and sparse data, this approach demonstrates the potential for noninvasive estimation of arsenic concentration. Future studies should focus on increasing data volume and categorizing arsenic concentration statistics to enhance model accuracy. This rapid estimation method could significantly contribute to epidemiological studies and aid physicians in diagnosis.

A compound analysis of medical device clinical trials registered in Africa on clinicaltrials.gov.

BACKGROUND: Africa, specifically the Sub-Saharan region, has had numerous medical technology clinical trials to address the various healthcare challenges around infectious diseases, non-communicable diseases, and nutritional disorders it is facing. Medical device clinical trials provide performance data in terms of safety, efficacy, and efficiency, which is a requirement before commercialization. Key players such as academicians, governments, international organizations, and funders collaborate to drive these trials, but their growth in Africa remains slower compared to other parts of the globe. This paper aims to evaluate the number of medical device clinical trials conducted in different African countries that are registered on the clinicaltrials.gov website. METHODS: Data on medical device clinical trials was mined from clinicaltrials.gov website accessed on 22nd September, 2022. The data extracted was analyzed and cleaned in Microsoft Excel and R. Countries were grouped into regions and descriptive statistical analyses for each region were done. Additionally, frequency distributions were also generated and no inferential statistical tests were performed, as the primary focus of this analysis was to describe the distribution of medical conditions across regions. RESULTS: Thirty-one African countries had registered medical device clinical trials on the website with the majority taking place in Egypt and South Africa. Medical device trials for heart related issues took longer to complete compared to other conditions. Malaria, HIV, and male circumcision related device trials were mainly conducted in Eastern and Southern Africa while trials related to dental, fertility, and obesity were concentrated in Northern Africa. Female reproductive health issues were studied equally across all regions. Some African countries did not have any trials registered on clinicaltrials.gov website. CONCLUSION: Findings from this study clearly show the disparity in the number, status, and duration of medical device clinical trials across various African countries.

Developing SysteMatic: Prevention, precision and equity by design for people living with multiple long-term conditions.

Background: The number of individuals living with multiple (≥2) long term conditions (MLTCs) is a growing global challenge. People with MLTCs experience reduced life expectancy, complex healthcare needs, higher healthcare utilisation, increased burden of treatment, poorer quality of life and higher mortality. Evolving technologies including artificial intelligence (AI) could address some of these challenges by enabling more preventive and better integrated care, however, they may also exacerbate inequities. Objective: We aim to deliver an equity focused, action-ready plan for transforming MLTC prevention and care, co-designed by people with lived experience of MLTCs and delivered through an Innovation Hub: SysteMatic. Design: Our Hub is being co-designed by people with lived experience of MLTCs, practitioners, academics and industry partners in Liverpool and Glasgow, UK. This work builds on research into mental-physical health interdependence across the life-course, and on mobilisation of large-scale quantitative data and technology validation in health and care systems serving deprived populations in Glasgow and Liverpool. We work with 3 population segments: 1) Children & Families: facing psychosocial and environmental challenges with lifetime impacts; 2). Working Life: people with poorly integrated mental, physical and social care; and 3) Pre-Frailty: older people with MLTCs. We aim to understand their experiences and in parallel look at routinely collected health data on people with MLTCs to help us identify targets for intervention. We are co-identifying opportunities for systems transformation with our patient partners, healthcare professionals and through discussion with companies and public-sector organisations. We are co-defining 3/5/7-year MLTC innovation/transition targets and sustainable learning approaches. Discussion: SysteMatic will deliver an actionable MLTC Innovation Hub strategic plan, with investment from the UK National Health Service, civic health and care partners, universities, and industry, enabling feedback of well-translated, patient and public prioritised problems into the engineering, physical, health and social sciences to underpin future equitable innovation delivery.

A discrete choice experiment to understand preferences of patients with type 2 diabetes about the attributes of GLP1 receptor agonists in Spain.

OBJECTIVE: To determine the preferences regarding injection, medication frequency and complexity of GLP1 receptor agonists among patients with type 2 diabetes, treatment-naïve for such drugs in Spain. Additionally, patients' willingness to pay according to these attributes was evaluated. METHODS: A discrete-choice experiment survey designed to evaluate patients' preferences over three attributes discriminating by age, sex and patients experience with previous injectable treatment was fulfilled by patients. The resulting model was analyzed using a conditional (fixed-effects) logistic regression. RESULTS: A total of 180 patients (63.35 ± 11.49 years, 63.28% men, 48.41% with previous cardiovascular disease, 54.69% with a time of evolution of diabetes >10 years) recruited from 5 health care centers in Spain completed the survey. Patients viewed positively weekly injections (vs daily injections), but rated negatively a complex preparation of the dose (vs simple preparation). Whereas naïve patients for injectable medications did not consider administration timing of importance, no naïve patients considered it relevant. No relevant differences were observed according to age or gender. Patients were willing to pay 83.25€for a "no preparation required" dose. No naïve and naïve patients were willing to pay 34.61€ and 14.35€; p = 0.000, to change daily injection for a weekly injection. CONCLUSIONS: Patients highly valued the avoidance of injections, with weekly dosing clearly preferred over daily dosing, as well as reducing the treatment complexity. These findings may provide a better understanding of what patients prefer and value in their treatment and provide guidance for clinicians making therapeutic decisions regarding treatments of patients with type 2 diabetes.

Unleashing the potential: the imperative of political support for health technology assessment in Iran.

Health Technology Assessment (HTA) is essential for evidence-based healthcare decision-making, yet its integration into Iran's healthcare system faces political and logistical challenges. Despite HTA's potential to improve resource allocation, limited awareness, data gaps, and competing priorities hinder its implementation. This commentary emphasizes the need for political support, advocating capacity-building, collaboration, and alignment with long-term health policies. Leveraging international partnerships and monitoring outcomes can enhance HTA's role in improving healthcare in Iran and contributing to global health advancements.

Cost-effectiveness of multigene sequencing test and treatment for metastatic non-small cell lung cancer: A unique setting in the initial adoption phase in Japan allowing testing only after standard treatment.

Objective: To clarify the cost-effectiveness of comprehensive diagnosis and treatment of metastatic non-small cell lung cancer in Japan, from initial diagnosis to post-standard treatment, using three different strategies. Methods: A decision tree was created using three diagnostic and treatment strategies, assuming that Foundation One CDx (F1CDx), a comprehensive genome panel, was introduced in Japan in June 2019. This comprehensive decision tree includes Markov models, cost-effectiveness analyses (CEA), and cost-utility analyses (CUA) of the three strategies from the perspective of Japanese payers. Specifically, Strategy1 involves single-gene testing at the initial diagnosis and F1CDx after standard treatment; Strategy2 involves only single-gene testing at the initial diagnosis; Strategy3 involves F1CDx at the initial diagnosis. The incremental cost-effectiveness ratios (ICERs) of the three strategies are estimated. Sensitivity analyses were performed to assess the uncertainty of the parameter settings. Results: Strategy3 was dominated for both CUA and CEA. The ICER/quality-adjusted life year (QALY) for Strategy2 versus Strategy1 was USD 13,734 (JPY 2,080,923, USD 1 = JPY 151.39 on April 1st, 2024), which is less than the willingness to pay of USD 45,900 (JPY 7,500,000), and Strategy2 was more cost-effective than Strategy1. F1CDx was not cost-effective compared to multiple simultaneous single tests at the initial diagnosis, either after standard treatment or at the initial diagnosis. Sensitivity analysis also showed that the most influential factor on the ICER for both CEA and CUA was treatment cost. Conclusions: From both patient benefit and health economic perspectives, introducing F1CDx after standard treatment in June 2019 was not as cost-effective as multiple simultaneous single tests at the initial diagnosis but was more realistic from a health economic perspective than introducing F1CDx at the time of initial diagnosis. Therefore, the policy at the time of F1CDx introduction in Japan was appropriate from a short-term health-economic perspective.

Co-Designing Remote Patient Monitoring Technologies for Inpatients: Systematic Review.

BACKGROUND: The co-design of health technology enables patient-centeredness and can help reduce barriers to technology use. OBJECTIVE: The study objectives were to identify what remote patient monitoring (RPM) technology has been co-designed for inpatients and how effective it is, to identify and describe the co-design approaches used to develop RPM technologies and in which contexts they emerge, and to identify and describe barriers and facilitators of the co-design process. METHODS: We conducted a systematic review of co-designed RPM technologies for inpatients or for the immediate postdischarge period and assessed (1) their effectiveness in improving health outcomes, (2) the co-design approaches used, and (3) barriers and facilitators to the co-design process. Eligible records included those involving stakeholders co-designing RPM technology for use in the inpatient setting or during the immediate postdischarge period. Searches were limited to the English language within the last 10 years. We searched MEDLINE, Embase, CINAHL, PsycInfo, and Science Citation Index (Web of Science) in April 2023. We used the Joanna Briggs Institute critical appraisal checklist for quasi-experimental studies and qualitative research. Findings are presented narratively. RESULTS: We screened 3334 reports, and 17 projects met the eligibility criteria. Interventions were designed for pre- and postsurgical monitoring (n=6), intensive care monitoring (n=2), posttransplant monitoring (n=3), rehabilitation (n=4), acute inpatients (n=1), and postpartum care (n=1). No projects evaluated the efficacy of their co-designed RPM technology. Three pilot studies reported clinical outcomes; their risk of bias was low to moderate. Pilot evaluations (11/17) also focused on nonclinical outcomes such as usability, usefulness, feasibility, and satisfaction. Common co-design approaches included needs assessment or ideation (16/17), prototyping (15/17), and pilot testing (11/17). The most commonly reported challenge to the co-design process was the generalizability of findings, closely followed by time and resource constraints and participant bias. Stakeholders' perceived value was the most frequently reported enabler of co-design. Other enablers included continued stakeholder engagement and methodological factors (ie, the use of flexible mixed method approaches and prototyping). CONCLUSIONS: Co-design methods can help enhance interventions' relevance, usability, and adoption. While included studies measured usability, satisfaction, and acceptability-critical factors for successful implementation and uptake-we could not determine the clinical effectiveness of co-designed RPM technologies. A stronger commitment to clinical evaluation is needed. Studies' use of diverse co-design approaches can foster stakeholder inclusivity, but greater standardization in co-design terminology is needed to improve the quality and consistency of co-design research.

Development and validation of a multimodal deep learning framework for vascular cognitive impairment diagnosis.

Cerebrovascular disease (CVD) is the second leading cause of dementia worldwide. The accurate detection of vascular cognitive impairment (VCI) in CVD patients remains an unresolved challenge. We collected the clinical non-imaging data and neuroimaging data from 307 subjects with CVD. Using these data, we developed a multimodal deep learning framework that combined the vision transformer and extreme gradient boosting algorithms. The final hybrid model within the framework included only two neuroimaging features and six clinical features, demonstrating robust performance across both internal and external datasets. Furthermore, the diagnostic performance of our model on a specific dataset was demonstrated to be comparable to that of expert clinicians. Notably, our model can identify the brain regions and clinical features that significantly contribute to the VCI diagnosis, thereby enhancing transparency and interpretability. We developed an accurate and explainable clinical decision support tool to identify the presence of VCI in patients with CVD.

A Review and Comparative Case Study Analysis of Real-world Evidence in European Regulatory and HTA Decision-making for Oncology Medicines.

OBJECTIVES: Real-world evidence (RWE) is valuable in supporting regulatory and HTA decisions, however, the actual contribution in approvals remains elusive. This study aims to review RWE approaches and use in oncology medicines approvals in Europe and understand cohesion and discrepancy in acceptance of the RWE by EMA and European HTA bodies. METHODS: This scoping review involved a search of the EMA database, NICE, G-BA and HAS websites to identify final reports and appraisals for oncology medicines with references to RWE. The selection was guided by research terms associated with RWE study designs, data sources and outcomes. Qualitative analysis was used to systemize the data. Case studies assessed by more than one agency were selected for comparative assessment of RWE approach, use and acceptability. RESULTS: RWE was mainly leveraged as an external control for indirect treatment comparisons or contextualization to support clinical trial results by the EMA, NICE, G-BA and HAS. However, this approach was mostly rejected due to methodology biases. Comparative assessment of RWE acceptability for the same oncology medicines across agencies suggest discrepancies between EMA and European HTA bodies, and amongst NICE, G-BA and HAS. CONCLUSIONS: There is diverging acceptance of RWE in EMA and European HTA bodies with no clear consensus on the most effective way to leverage RWE in approvals. With the introduction of joint EU Joint Clinical Assessment in 2025, it is crucial for European HTA bodies and EMA to develop synergetic standards for the use of RWE to ensure equitable and timely access to medicines.

A landscape analysis of digital health technology in medical schools: preparing students for the future of health care.

Although Digital Health Technology is increasingly implemented in hospitals and clinics, physicians are not sufficiently equipped with the competencies needed to optimize technology utilization. Medical schools seem to be the most appropriate channel to better prepare future physicians for this development. The purpose of this research study is to investigate the extent to which top-ranked medical schools equip future physicians with the competencies necessary for them to leverage Digital Health Technology in the provision of care. This research work relied on a descriptive landscape analysis, and was composed of two phases: Phase I aimed at investigating the articulation of the direction of the selected universities and medical schools to identify any expressed inclination towards teaching innovation or Digital Health Technology. In phase II, medical schools' websites were analyzed to discover how innovation and Digital Health Technology are integrated in their curricula. Among the 60 medical schools that were analyzed, none mentioned any type of Digital Health Technology in their mission statements (that of the universities, in general, and medical schools, specifically). When investigating the medical schools' curricula to determine how universities nurture their learners in relation to Digital Health Technology, four universities covering different Digital Health Technology areas were identified. The results of the current study shed light on the untapped potential of working towards better equipping medical students with competencies that will enable them to leverage Digital Health Technology in their future practice and in turn enhance the quality of care.

Stool-Based Testing for Post-Polypectomy Colorectal Cancer Surveillance Safely Reduces Colonoscopies: The Molecular Stool Testing for Colorectal Cancer Surveillance Study.

BACKGROUND & AIMS: Colonoscopy-based surveillance to prevent colorectal cancer (CRC) causes substantial burden for patients and health care. Stool tests may help to reduce surveillance colonoscopies by limiting colonoscopies to individuals at increased risk of advanced neoplasia. METHODS: This cross-sectional observational study included individuals aged 50-75 years with surveillance indication. Before bowel preparation, participants collected samples for a multitarget stool DNA test and 2 fecal immunochemical tests (FITs). Test accuracy was calculated for all surveillance indications. For the post-polypectomy indication only, which is the most common and is associated with a relatively low CRC risk, long-term impact of stool-based surveillance was evaluated with the Adenoma and Serrated Pathway to Colorectal Cancer model. Stool-based strategies were simulated to tune each test's positivity threshold to obtain strategies at least as effective as colonoscopy surveillance. RESULTS: There were 3453 individuals with results for all stool tests and colonoscopy; 2226 had previous polypectomy, 1003 had previous CRC, and 224 had a familial risk. Areas under the receiver operating characteristic curve for advanced neoplasia were 0.72 (95% CI, 0.69-0.75) for the multitarget stool DNA test, 0.61 (95% CI, 0.58-0.64) for the FIT OC-SENSOR (Eiken Chemical Co, Tokyo, Japan) and 0.59 (95% CI, 0.56-0.61) for the FIT FOB-Gold (Sentinel, Milan, Italy). Stool-based post-polypectomy surveillance strategies at least as effective as colonoscopy surveillance reduced the number of colonoscopies by 15%-41% and required 5.6-9.5 stool tests over a person's lifetime. Multitarget stool DNA-based surveillance was more costly than colonoscopy surveillance, whereas FIT-based surveillance saved costs. CONCLUSIONS: This study found that stool-based post-polypectomy surveillance strategies can be safe and cost-effective, with potential to reduce the number of colonoscopies by up to 41%. CLINICALTRIALS: gov, Number: NCT02715141.

What methods are currently available for incorporating implementation considerations within the economic evaluation of health technologies? A scoping review.

BACKGROUND: When clinically effective, cost-effective health interventions are not fully implemented in clinical practice, population health suffers. Economic factors are among the most commonly cited reasons for suboptimal implementation. Despite this, implementation and economic evaluation are not routinely performed in conjunction with one another. This review sought to identify and describe what methods are available for researchers to incorporate implementation within economic evaluation, how these methods differ, when they should be used, and where gaps remain. METHODS: We conducted a scoping review using systematic methods. A pearl-growing approach was used to identify studies. References and citations were identified using Web of Science and Scopus. We included for review any study that contained terms relating to economic evaluation and a series of implementation-related terms in the title or abstract. The search was conducted and validated using two independent researchers. RESULTS: Our review identified 42 unique studies that included a methodology for combining implementation and economic evaluation. The methods identified could be categorized into four broad themes: (i) policy cost-effectiveness approach (11 studies), (ii) value of information and value of implementation approach (16 studies), (iii) mixed methods approach (6 studies), and (iv) costing approach (9 studies). We identified a trend over time from methods that adopted the policy cost-effectiveness approach to methods that considered the trade-off between the value of information and value of implementation. More recently, mixed methods approaches to incorporate economic evaluation and implementation have been developed, alongside methods to define, measure and cost individual components of the implementation process for use in economic evaluation. CONCLUSION: Our review identified a range of methods currently available for researchers considering implementation alongside economic evaluation. There is no single method or tool that can incorporate all the relevant issues to fully incorporate implementation within an economic evaluation. Instead, there are a suite of tools available, each of which can be used to answer a specific question relating to implementation. Researchers, reimbursement agencies and national and local decision-makers need to consider how best to utilize these tools to improve implementation.

Real time monitoring of respiratory viral infections in cohort studies using a smartphone app.

Cohort studies investigating respiratory disease pathogenesis aim to pair mechanistic investigations with longitudinal virus detection but are limited by the burden of methods tracking illness over time. In this study, we explored the utility of a purpose-built AERIAL TempTracker smartphone app to assess real-time data collection and adherence monitoring and overall burden to participants, while identifying symptomatic respiratory illnesses in two birth cohort studies. We observed strong adherence with daily app usage over the six-month study period, with positive feedback from participant families. A total of 648 symptomatic respiratory illness events were identified with significant variability between individuals in the frequency, duration, and virus detected. Collectively, our data show that a smartphone app provides a reliable method to capture the longitudinal virus data in cohort studies which facilitates the understanding of early life infections in chronic respiratory disease development.

Leveraging Personal Technologies in the Treatment of Schizophrenia Spectrum Disorders: Scoping Review.

BACKGROUND: Digital mental health is a rapidly growing field with an increasing evidence base due to its potential scalability and impacts on access to mental health care. Further, within underfunded service systems, leveraging personal technologies to deliver or support specialized service delivery has garnered attention as a feasible and cost-effective means of improving access. Digital health relevance has also improved as technology ownership in individuals with schizophrenia has improved and is comparable to that of the general population. However, less digital health research has been conducted in groups with schizophrenia spectrum disorders compared to other mental health conditions, and overall feasibility, efficacy, and clinical integration remain largely unknown. OBJECTIVE: This review aims to describe the available literature investigating the use of personal technologies (ie, phone, computer, tablet, and wearables) to deliver or support specialized care for schizophrenia and examine opportunities and barriers to integrating this technology into care. METHODS: Given the size of this review, we used scoping review methods. We searched 3 major databases with search teams related to schizophrenia spectrum disorders, various personal technologies, and intervention outcomes related to recovery. We included studies from the full spectrum of methodologies, from development papers to implementation trials. Methods and reporting follow the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. RESULTS: This search resulted in 999 studies, which, through review by at least 2 reviewers, included 92 publications. Included studies were published from 2010 to 2023. Most studies examined multitechnology interventions (40/92, 43%) or smartphone apps (25/92, 27%), followed by SMS text messaging (16/92, 17%) and internet-based interventions (11/92, 12%). No studies used wearable technology on its own to deliver an intervention. Regarding the stage of research in the field, the largest number of publications were pilot studies (32/92, 35%), followed by randomized control trials (RCTs; 20/92, 22%), secondary analyses (16/92, 17%), RCT protocols (16/92, 17%), development papers (5/92, 5%), and nonrandomized or quasi-experimental trials (3/92, 3%). Most studies did not report on safety indices (55/92, 60%) or privacy precautions (64/92, 70%). Included studies tend to report consistent positive user feedback regarding the usability, acceptability, and satisfaction with technology; however, engagement metrics are highly variable and report mixed outcomes. Furthermore, efficacy at both the pilot and RCT levels report mixed findings on primary outcomes. CONCLUSIONS: Overall, the findings of this review highlight the discrepancy between the high levels of acceptability and usability of these digital interventions, mixed efficacy results, and difficulties with sustained engagement. The discussion highlights common patterns that may underscore this observation in the field; however, as this was a scoping review, a more in-depth systematic review or meta-analysis may be required to better understand the trends outlined in this review.

Development of a Canadian Guidance for Reporting Real-world Evidence for Regulatory and Health-Technology Assessment (HTA) Decision Making.

Real-world evidence (RWE) can complement and fill knowledge gaps from randomized controlled trials to assist in health-technology assessment (HTA) for regulatory decision-making. However, the generation of RWE is an intricate process with many sequential decision points, and different methods and approaches may impact the quality and reliability of evidence. Standardization and transparency in reporting these decisions is imperative to appraise RWE and incorporate it into HTA decision-making. A partnership between Canadian health system stakeholders, namely Health Canada and Canada's Drug Agency (formerly the Canadian Agency for Drugs and Technologies in Health (CADTH)), was established to develop a guidance for standardization of reporting of RWE for regulatory and HTA decision-making in Canada. In this article, we describe the methods to develop the Guidance for Reporting Real-World Evidence document and checklist for reporting RWE for regulatory and HTA decision-making in Canada. This guidance can be adapted for other jurisdictions and will have future extensions to incorporate emerging issues with RWE and HTA decision-making.

Early health technology assessment of gene silencing therapies for lowering lipoprotein(a) in the secondary prevention of coronary heart disease.

BACKGROUND: Olpasiran and pelacarsen are gene-silencing therapies that lower lipoprotein(a). Cardiovascular outcome trials are ongoing. Mendelian randomisation studies estimated clinical benefits from lipoprotein(a) lowering. OBJECTIVE: Our study estimated prices at which olpasiran and pelacarsen, in addition to standard-of-care, would be deemed cost-effective in reducing risk of recurrent coronary heart disease (CHD) events in the Australian healthcare system. METHODS: We developed a decision tree and lifetime Markov model. For olpasiran, participants had CHD and lipoprotein(a) 260 nmol/L at baseline and three-monthly injections, profiled on OCEAN(a) Outcomes trial (NCT05581303). Baseline risks of CHD, costs and utilities were obtained from published sources. Clinical trial data were used to derive reductions in lipoprotein(a) from treatment. Mendelian randomisation study data were used to estimate downstream clinical benefits. Annual discounting was 5 %. For pelacarsen, participants had CHD and lipoprotein(a) 226 nmol/L at baseline and one- monthly injections, profiled on Lp(a) HORIZON (NCT04023552) trial. RESULTS: Olpasiran in addition to standard-of-care saved 0.87 discounted quality-adjusted life years (QALYs) per person. Olpasiran in addition to standard-of-care would be cost- effective at annual prices of AU$1867 (AU$467 per dose) at threshold AU$28,000 per QALY. Pelacarsen would be cost-effective at annual prices of AU$984 (AU$82 per dose). For ICER threshold AU$50,000 per QALY, olpasiran and pelacarsen would be cost-effective at annual prices AU$4207 and AU$2464 respectively. CONCLUSION: This early health technology assessment model used inclusion criteria from clinical trials. Olpasiran and pelacarsen would be cost-effective if annual treatment prices were AU$1867 and AU$984 respectively, from the Australian healthcare perspective.