Two therapies are placed in head-to-head clinical trials when they are compared against each other as opposed to a standard of care. When multiple treatment options are available to patients, a head-to-head clinical trial can establish how well these treatments compare to each other.
In 2020, Cytel pioneered two “Head-to-Head Comparisons using Real World Data” studies, one in oncology one in cardiovascular disease. The conduct of these investigations can be followed through a Cytel webinar series, which includes Professor Miguel Hernan of Harvard University’s TH Chan School of Public Health.
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The spotlight for this year’s World Evidence-Based Healthcare Day (EBHC) (October 20, 2023), is on the generation and application of evidence to improve global health equity.
According to the World Health Organization (WHO), “health equity is the absence of unfair, avoidable or remediable differences in health among population groups, defined by social, economic, demographic or geographic characteristics.”
Health inequity (or disparity) is not a new health topic; it has been widely documented across the world for the last four decades. What is new are the recent efforts to make health equity a strategic priority in healthcare decision-making. A couple of things are clearer now more than ever — 1) there is a need to
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When conducting network meta-analysis (NMA) – that is, a technique that involves comparing multiple treatments simultaneously in one analysis by combining both direct comparisons of treatments trialed against each other in randomized control trials and indirect comparisons, based on a common comparator – bias can be caused by effect modification, potentially leading to inaccurate conclusions.
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By Grammati Sarri, Evie Merinopoulou, Vinusha Kalatharan, and Jason Simeone
The Canadian Agency for Drugs and Technologies in Health’s (CADTH) long-expected guidance on real-world evidence (RWE) is now in the public domain; however, it solely provides standardized (core) reporting practices for manufacturers submitting RWE studies to support their drugs applications, and important aspects of the incorporation of RWE in decision-making are missing.
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Real-world data has been increasingly used to answer questions related to the course, prognosis, and treatment of multiple sclerosis – yet each data source has its limitations, restricting the questions that can be addressed. Here is our solution.
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While randomized control trials remain the industry gold-standard for regulatory and reimbursement submissions, there are occasions when such trials are either infeasible or unethical. In such situations, regulatory approvals for products can be achieved based on single-arm trials where an external control creates a comparator arm, most commonly by using real-world data (RWD) such as, electronic health records or patient registries. However, this poses several challenges around the selection of an appropriate, fit-for-purpose real-world data source to construct the external control arm, in particular the trade-offs between data quality and locality.
At ISPOR US 2022, Cytel’s Lead Scientist Dr. Grammati Sarri will moderate an issue panel, “Is the Global Real World Data Supply Chain Broken?” Grammati has over 15 years of experience, specializing in evidence synthesis, epidemiology, and the use of real-world data in reimbursement decision-making. As a senior leader, she has held positions in academia, payer, and private consultancies, and has published over 60 peer-reviewed manuscripts and delivered several webinars and issue panels. As an internationally recognized thought leader, Grammati is currently chair-elect for the Comparative Effectiveness Research Special Interest Group at the International Society for Pharmacoepidemiology.
In this interview, we ask Grammati about the agenda of this panel discussion and get her insights on the challenges affecting single arm studies, the importance of real-world data and the selection of its source.
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Regulatory requirements regarding documentation for new medicines are constantly evolving. Previously, randomized controlled trials alone qualified as high-level evidence in pharmaceutical development — today, approval is often followed by requirements for additional post-approval studies or for so-called real-world evidence (RWE) studies. Here, I’ll explain these concepts and share epidemiological and statistical methods to tackle RWE challenges.
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ClinicReal-world data and evidence are increasingly being used in health care decisions and publications. However, there are challenges in identifying suitable data for external control arms, and researchers need to consider solutions to address issues like data quality, bias, and selection bias when using real-world evidence for comparative efficacy analyses.1 Read more »
The ability to draw on electronic medical records is foundational to the use of real-world data (RWD). In China, companies like HappyLife Tech (HLT), an affiliated company of Yidu Tech Inc., can build digital ecosystems with 1.3 billion data records and over 300 million patients, thereby opening new horizons for real world solutions. Such solutions have the potential to improve every stage of the product lifecycle and study journey including feasibility studies, clinical trial design, and market access. They also open new development pathways including those for decentralized trials and AI-driven solutions. According to Dr. Luyan Connie Dai in her recent webinar‚ “Embrace the Era of Digital Clinical Trials in China: Challenges & Opportunities” there are seven key ways in which RWD is transforming the product journey in China.
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