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In this update, we discuss a position statement from the National Institute of Health and Care Excellence (NICE) on the use of artificial intelligence for evidence generation and publications reviewing the use of real-world data as external control arms. Finally, we discuss a number of recent studies investigating the real-world effectiveness of glucagon-like peptide-1 receptor agonists and whether these studies are informative for reimbursement decision making.

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.

In this update, we discuss recent US FDA guidance offering more specific guidelines on appropriate study design and analysis to support causal inference for non-interventional studies and the launch of the European Medicines Agency (EMA) and the Heads of Medicines Agencies (HMA) public electronic catalogues. We also highlight an article recommending assessing data quality and suitability prior to protocol finalization and a Journal of the American Medical Association-endorsed framework for using causal language when publishing real-world evidence studies. Finally, we explore the potential of large language models to automate the development of health economic models.

In this latest update, we look at recent developments in market access including the pricing agreement of Libmeldy by the Beneluxa Initiative, the financial impact of managed entry agreements in Italy and the restructuring of Agenzia Italiana del Farmaco (AIFA). We also highlight the collaboration between FINOSE and the New Expensive Drug (NED) section of the Nordic Pharmaceutical Forum.

In this latest update, we explore some of the key updates in market access over recent months including the UK’s voluntary scheme for branded medicines pricing, access and growth (VPAG), the first drugs funded by the Innovative Medicines Fund in the UK and the Direct Access Scheme in France, and, finally, the new Institute for Clinical and Economic Review (ICER) value assessment framework in the USA.

In this latest update we highlight: a publication from the US FDA regarding the definitions of real-world data (RWD) and real-world evidence (RWE); a publication from academic researchers on a demonstration project for target trial emulation; a publication from the National Institute of Health and Care Excellence (NICE) on the 1 year anniversary of their RWE framework; and a publication from NICE and Flatiron Health on the utility of US RWD for initial UK health technology assessment decision making.

In this latest update, we explore the Inflation Reduction Act (IRA) enacted by the US Congress in August 2022, with the Centers for Medicare and Medicaid Services (CMS) recently releasing the list of the first ten drugs it will negotiate prices on. We also cover the consequences of price controls and rigid value assessment in Germany which have led to the withdrawal of a number of medicines. It will be important to see how the IRA balances cost-saving with holistic value assessment, incentives for innovation and patient access to treatment.

In this latest update we highlight a report from the European Medicines Agency on their use of realworld evidence (RWE) in decision making, RWE reporting guidance from the Canadian Agency for Drugs and Technologies in Health and highlight some new data demonstrating the value medicines for spinal muscular atrophy have brought patients.

In this new series reviewing recent developments inmarket access, we highlight publications investigating health technology assessment (HTA) guidance, review processes and outcomes across the world and discuss how forthcoming changes in the HTA and regulatory environment in the European Union may allow for more consistency in decision making.

In this latest update we discuss the transportability of comparative effectiveness evidence across countries. We highlight results of a survey indicating that European HTA agencies are reluctant to accept real-world data from other countries, review recent benefit assessments indicating a potential softening of a requirement for the use of local real-world data in Germany, and outline a recent review presenting approaches that can correct for a lack of transportability.

Objective: To derive a score for finishing in the top three positions of the television show, Love Island, UK. Design: A retrospective study was undertaken using data from all previous contestants. Results: A score predicting show success termed DO-BITS (different coupling approaches [islanders pursuing one or many people on the show], Original islander [being on the show from the start], [being] Brunette, [having] intimate relationships on screen, Tradesman [occupation before being on the show] and Short name [having a four-letter first name]) was developed. The accuracy of this score in this derivation cohort yielded a C-statistic of 0.85. Conclusion: This simple, novel score provides a practical tool to assess the likelihood of success on Love Island.

Background: Multiple sclerosis (MS) is an inflammatory disease while there are controversies regarding the role of vitamin D supplements in controlling relapse and disability improvement during treatment. Objective: The goal of this systematic review and meta-analysis was to evaluate the effect of vitamin D supplements on MS-related relapse and the Expanded Disability Status Scale (EDSS). Methods: We searched databases to include randomized clinical trials (RCTs) which were published up to October 2018. We included RCTs, being single-blinded or double-blinded or open-label trials in which one of the main outcomes was EDSS and/or relapse after vitamin D supplementation. All statistical analyses were performed using RevMan 5.3. Odds ratios (OR) and 95% confidence intervals (CI) were calculated for relapse between treatment arms. The mean difference was calculated for EDSS comparisons. Results: Nine articles were included for analysis. Of these nine studies, five compared vitamin D supplement groups with placebo (group 1 studies), and four compared high- and low-dose vitamin D groups. A total of 561 patients were analyzed. Being treated with vitamin D instead of placebo showed no effect on relapse rate (OR = 0.66, 95% CI = 0.28–1.54) as well as EDSS (mean difference = 0.06, 95%CI [-0.31, 0.42]). The results of studies comparing high- vs. low-dose vitamin D interventions showed no significant effect on relapse rate (OR = 1.08, 95%CI [0.29–4.08] as well as final EDSS (mean difference = 0.17, 95% CI = -0.73, 1.07). Conclusions: Our findings show that vitamin D supplements (high or low dose) have no significant effect on relapse rate and disability during treatment in MS patients.

Background: We and others have shown a significant proportion of interventional trials registered on ClinicalTrials.gov have their primary outcomes altered after the listed study start and completion dates. The objectives of this study were to investigate whether changes made to primary outcomes are associated with the likelihood of reporting a statistically significant primary outcome on ClinicalTrials.gov. Methods: A cross-sectional analysis of all interventional clinical trials registered on ClinicalTrials.gov as of 20 November 2014 was performed. The main outcome was any change made to the initially listed primary outcome and the time of the change in relation to the trial start and end date. Findings: 13,238 completed interventional trials were registered with ClinicalTrials.gov that also had study results posted on the website. 2555 (19.3%) had one or more statistically significant primary outcomes. Statistical analysis showed that registration year, funding source and primary outcome change after trial completion were associated with reporting a statistically significant primary outcome. Conclusions: Funding source and primary outcome change after trial completion are associated with a statistically significant primary outcome report on clinicaltrials.gov.

Recent studies have used mainstream consumer devices (Fitbit) to assess sleep objectively and test the well documented association between sleep and body mass index (BMI). In order to further investigate the applicability of Fitbit data for biomedical research across the globe, we analysed openly available Fitbit data from a largely Chinese population. We found that after adjusting for age, gender, race, and average number of steps taken per day, average hours of sleep per day was negatively associated with BMI (p=0.02), further demonstrating the significant potential for wearables in international scientific research.

Recent studies have used mainstream consumer devices (Fitbit) to assess sleep objectively and test the well documented association between sleep and body mass index (BMI). In order to further investigate the applicability of Fitbit data for biomedical research across the globe, we analysed openly available Fitbit data from a largely Chinese population. We found that after adjusting for age, gender, race, and average number of steps taken per day, average hours of sleep per day was negatively associated with BMI (p=0.02), further demonstrating the significant potential for wearables in international scientific research.

Background: The objective of this study was to investigate the study design characteristics of Post-Authorisation Studies (PAS) requested by the European Medicines Agency which were recorded on the European Union (EU) PAS Register held by the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCePP). Methods: We undertook a cross-sectional descriptive analysis of all studies registered on the EU PAS Register as of 18 th October 2016. Results: We identified a total of 314 studies on the EU PAS Register, including 81 (26%) finalised, 160 (51%) ongoing and 73 (23%) planned. Of those studies identified, 205 (65%) included risk assessment in their scope, 133 (42%) included drug utilisation and 94 (30%) included effectiveness evaluation. Just over half of the studies (175; 56%) used primary data capture, 135 (43%) used secondary data and 4 (1%) used a hybrid design combining both approaches. Risk assessment and effectiveness studies were more likely to use primary data capture (60% and 85% respectively as compared to 39% and 14% respectively for secondary). The converse was true for drug utilisation studies where 59% were secondary vs. 39% for primary. For type 2 diabetes mellitus, database studies were more commonly used (80% vs 3% chart review, 3% hybrid and 13% primary data capture study designs) whereas for studies in oncology, primary data capture were more likely to be used (85% vs 4% chart review, and 11% database study designs). Conclusions: Results of this analysis show that PAS design varies according to study objectives and therapeutic area.

In order to understand the current state of data sharing in observational research studies, we reviewed data sharing statements of observational studies published in a general medical journal, the British Medical Journal. We found that the majority (63%) of observational studies published between 2015 and 2017 included a statement that implied that data used in the study could not be shared. If the findings of our exploratory study are confirmed, room for improvement in the sharing of real-world or observational research data exists.

In order to understand the current state of data sharing in observational research studies, we reviewed data sharing statements of observational studies published in a general medical journal, the British Medical Journal. We found that the majority (63%) of observational studies published between 2015 and 2017 included a statement that implied that data used in the study could not be shared. If the findings of our exploratory study are confirmed, room for improvement in the sharing of real-world or observational research data exists.

Machine learning (ML) has the potential to significantly aid medical practice. However, a recent article highlighted some negative consequences that may arise from using ML decision support in medicine. We argue here that whilst the concerns raised by the authors may be appropriate, they are not specific to ML, and thus the article may lead to an adverse perception about this technique in particular. Whilst ML is not without its limitations like any methodology, a balanced view is needed in order to not hamper its use in potentially enabling better patient care.

Background: The objective of this study was to investigate the study design characteristics of Post-Authorisation Studies (PAS) requested by the European Medicines Agency which were recorded on the European Union (EU) PAS Register held by the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCePP). Methods: We undertook a cross-sectional descriptive analysis of all studies registered on the EU PAS Register as of 18 th October 2016. Results: We identified a total of 314 studies on the EU PAS Register, including 81 (26%) finalised, 160 (51%) ongoing and 73 (23%) planned. Of those studies identified, 205 (65%) included risk assessment in their scope, 133 (42%) included drug utilisation and 94 (30%) included effectiveness evaluation. Just over half of the studies (175; 56%) used primary data capture, 135 (43%) used secondary data and 4 (1%) used a hybrid design combining both approaches. Risk assessment and effectiveness studies were more likely to use primary data capture (60% and 85% respectively as compared to 39% and 14% respectively for secondary). The converse was true for drug utilisation studies where 59% were secondary vs. 39% for primary. For type 2 diabetes mellitus, database studies were more commonly used (80% vs 3% chart review, 3% hybrid and 13% primary data capture study designs) whereas for studies in oncology, primary data capture were more likely to be used (85% vs 4% chart review, and 11% database study designs). Conclusions: Results of this analysis show that study objectives and therapeutic area influence PAS design in terms of type of data capture used.

We sought to investigate the rate of multiple sclerosis (MS)-related hospitalizations in Portugal and assess whether there have been temporal changes as described in other countries. Using data from the Portuguese National Discharge Registry, we observed that between 2008 and 2013 the rate of MS-related hospitalizations decreased by 44%, from 15.9/100 person-years (95% confidence interval (CI: 14.9-16.9) in 2008 to 8.9/100 person-years (95% CI: 8.2-9.6) in 2013. The change in hospitalization rates is in accordance with what has been observed in other countries, and coincides with the release of new therapies for MS in Portugal.

Background: We and others have shown a significant proportion of interventional trials registered on ClinicalTrials.gov have their primary outcomes altered after the listed study start and completion dates. The objectives of this study were to investigate whether changes made to primary outcomes are associated with the likelihood of reporting a statistically significant primary outcome on ClinicalTrials.gov. Methods: A cross-sectional analysis of all interventional clinical trials registered on ClinicalTrials.gov as of 20 November 2014 was performed. The main outcome was any change made to the initially listed primary outcome and the time of the change in relation to the trial start and end date. Findings: 13,238 completed interventional trials were registered with ClinicalTrials.gov that also had study results posted on the website. 2555 (19.3%) had one or more statistically significant primary outcomes. Statistical analysis showed that registration year, funding source and primary outcome change after trial completion were associated with reporting a statistically significant primary outcome . Conclusions: Funding source and primary outcome change after trial completion are associated with a statistically significant primary outcome report on clinicaltrials.gov.

Background: We and others have shown a significant proportion of interventional trials registered on ClinicalTrials.gov have their primary outcomes altered after the listed study start and completion dates. The objectives of this study were to investigate whether changes made to primary outcomes are associated with the likelihood of reporting a statistically significant primary outcome on ClinicalTrials.gov. Methods: A cross-sectional analysis of all interventional clinical trials registered on ClinicalTrials.gov as of 20 November 2014 was performed. The main outcome was any change made to the initially listed primary outcome and the time of the change in relation to the trial start and end date. Findings: 13,238 completed interventional trials were registered with ClinicalTrials.gov that also had study results posted on the website. 2555 (19.3%) had one or more statistically significant primary outcomes. Statistical analysis showed that registration year, funding source and primary outcome change after trial completion were associated with reporting a statistically significant primary outcome . Conclusions: Funding source and primary outcome change after trial completion are associated with a statistically significant primary outcome report on clinicaltrials.gov.