RWE ready for reimbursement? A round up of developments in real-world evidence relating to health technology assessment: part 16.

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.

Access in all areas? a round up of developments in market access and health technology assessment: part 4.

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.

R WE ready for reimbursement? A round up of developments in real-world evidence relating to health technology assessment: part 15.

In this latest update we discuss real-world evidence (RWE) guidance from the leading oncology professional societies, the American Society of Clinical Oncology and the European Society for Medical Oncology, and the PRINCIPLED practical guide on the design and analysis of causal RWE studies.

Acceptability of Using Real-World Data to Estimate Relative Treatment Effects in Health Technology Assessments: Barriers and Future Steps.

OBJECTIVES: Evidence about the comparative effects of new treatments is typically collected in randomized controlled trials (RCTs). In some instances, RCTs are not possible, or their value is limited by an inability to capture treatment effects over the longer term or in all relevant population subgroups. In these cases, nonrandomized studies (NRS) using real-world data (RWD) are increasingly used to complement trial evidence on treatment effects for health technology assessment (HTA). However, there have been concerns over a lack of acceptability of this evidence by HTA agencies. This article aims to identify the barriers to the acceptance of NRS and steps that may facilitate increases in the acceptability of NRS in the future. METHODS: Opinions of the authorship team based on their experience in real-world evidence research in academic, HTA, and industry settings, supported by a critical assessment of existing studies. RESULTS: Barriers were identified that are applicable to key stakeholder groups, including HTA agencies (eg, the lack of comprehensive methodological guidelines for using RWD), evidence generators (eg, avoidable deviations from best practices), and external stakeholders (eg, data controllers providing timely access to high-quality RWD). Future steps that may facilitate future acceptability of NRS include improvements in the quality, integration, and accessibility of RWD, wider use of demonstration projects to highlight the value and applicability of nonrandomized designs, living, and more detailed HTA guidelines, and improvements in HTA infrastructure relating to RWD. CONCLUSION: NRS can represent a crucial source of evidence on treatment effects for use in HTA when RCT evidence is limited.

Access in all areas? A round up of developments in market access and health technology assessment: part 3.

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.

Is the price right? Paying for value today to get more value tomorrow.

BACKGROUND: Contemporary debates about drug pricing feature several widely held misconceptions, including the relationship between incentives and innovation, the proportion of total healthcare spending on pharmaceuticals, and whether the economic evaluation of a medicine can be influenced by things other than clinical efficacy. MAIN BODY: All citizens should have access to timely, equitable, and cost-effective care covered by public funds, private insurance, or a combination of both. Better managing the collective burden of diseases borne by today's and future generations depends in part on developing better technologies, including better medicines. As in any innovative industry, the expectation of adequate financial returns incentivizes innovators and their investors to develop new medicines. Estimating expected returns requires that they forecast revenues, based on the future price trajectory and volume of use over time. How market participants decide what price to set or accept can be complicated, and some observers and stakeholders want to confirm whether the net prices society pays for novel medicines, whether as a reward for past innovation or an incentive for future innovation, are commensurate with those medicines' incremental value. But we must also ask "value to whom?"; medicines not only bring immediate clinical benefits to patients treated today, but also can provide a broad spectrum of short- and long-term benefits to patients, their families, and society. Spending across all facets of healthcare has grown over the last 25 years, but both inpatient and outpatient spending has outpaced drug spending growth even as our drug armamentarium is constantly improving with safer and more effective medicines. In large part, this is because, unlike hospitals, drugs typically go generic, thus making room in our budgets for new and better ones, even as they often keep patients out of hospitals, driving further savings. CONCLUSION: A thorough evaluation of drug spending and value can help to promote a better allocation of healthcare resources for both the healthy and the sick, both of whom must pay for healthcare. Taking a holistic approach to assessing drug value makes it clear that a branded drug's value to a patient is often only a small fraction of the drug's total value to society. Societal value merits consideration when determining whether and how to make a medicine affordable and accessible to patients: a drug that is worth its price to society should not be rendered inaccessible to ill patients by imposing high out-of-pocket costs or restricting coverage based on narrow health technology assessments (HTAs). Furthermore, recognizing the total societal cost of un- or undertreated conditions is crucial to gaining a thorough understanding of what guides the biomedical innovation ecosystem to create value for society. It would be unwise to discourage the development of new solutions without first appreciating the cost of leaving the problems unsolved.

R WE ready for reimbursement? A round up of developments in real-world evidence relating to health technology assessment: part 14.

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.

Quantitative bias analysis for external control arms using real-world data in clinical trials: a primer for clinical researchers.

Development of medicines in rare oncologic patient populations are growing, but well-powered randomized controlled trials are typically extremely challenging or unethical to conduct in such settings. External control arms using real-world data are increasingly used to supplement clinical trial evidence where no or little control arm data exists. The construction of an external control arm should always aim to match the population, treatment settings and outcome measurements of the corresponding treatment arm. Yet, external real-world data is typically fraught with limitations including missing data, measurement error and the potential for unmeasured confounding given a nonrandomized comparison. Quantitative bias analysis (QBA) comprises a collection of approaches for modelling the magnitude of systematic errors in data which cannot be addressed with conventional statistical adjustment. Their applications can range from simple deterministic equations to complex hierarchical models. QBA applied to external control arm represent an opportunity for evaluating the validity of the corresponding comparative efficacy estimates. We provide a brief overview of available QBA approaches and explore their application in practice. Using a motivating example of a comparison between pralsetinib single-arm trial data versus pembrolizumab alone or combined with chemotherapy real-world data for RET fusion-positive advanced non-small cell lung cancer (aNSCLC) patients (1-2% among all NSCLC), we illustrate how QBA can be applied to external control arms. We illustrate how QBA is used to ascertain robustness of results despite a large proportion of missing data on baseline ECOG performance status and suspicion of unknown confounding. The robustness of findings is illustrated by showing that no meaningful change to the comparative effect was observed across several 'tipping-point' scenario analyses, and by showing that suspicion of unknown confounding was ruled out by use of E-values. Full R code is also provided.

Association between treatment and improvements in overall survival of patients with advanced/metastatic non-small cell lung cancer since 2011: A study in the United States, Canada, and Germany using retrospective real-world databases.

BACKGROUND: This study aimed to describe treatment patterns and overall survival (OS) in patients with advanced non-small cell lung cancer (aNSCLC) in three countries between 2011 and 2020. METHODS: Three databases (US, Canada, Germany) were used to identify incident aNSCLC patients. OS was assessed from the date of incident aNSCLC diagnosis and, for patients who received at least a first line of therapy (1LOT), from the date of 1LOT initiation. In multivariable analyses, we analyzed the influence of index year and type of prescribed treatment on OS. FINDINGS: We included 51,318 patients with an incident aNSCLC diagnosis. The percentage of patients treated with a 1LOT differed substantially between countries, whereas the number of patients receiving immunotherapies/targeted treatments increased over time in all three countries. Median OS from the date of incident diagnosis was 9.9 months in the United States vs. 4.1 months in Canada. When measured from the start of 1LOT, patients had a median OS of 10.7 months in the United States, 10.9 months in Canada, and 10.9 months in Germany. OS from the start of 1LOT improved in all three countries from 2011 to 2020 by approximately 3 to 4 months. CONCLUSIONS: Observed continuous improvement in OS among patients receiving at least a 1LOT from 2011 to 2020 was likely driven by improved care and changes in the treatment landscape. The difference in the proportion of patients receiving a 1LOT in the observed countries requires further investigation.