Use of external comparators for health technology assessment submissions based on single-arm trials

Background: Single-arm trial (SAT) data is increasingly reviewed for drug approvals by regulators and Health Technology Assessment (HTA) bodies. Supplementary data in the form of external comparators (ECs) can be used to provide clinical context to support these drug evaluations. In this study we characterized HTAs for SAT-based submissions, the use of supplementary EC data and outcomes from HTA review. Methods: HTA Accelerator database was used to describe SAT-based HTA submissions with decisions (2011-2019). Results: A total of 433 SAT-based HTA submissions were identified between 2011 and 2019 with a 13-fold increase during this period. Around 65%(283/433) were in oncology or hem-oncology. Around 52%(226/433) of submissions contained some type of EC data, including prior clinical trials (24%, 104) and real-world data (RWD) (20%, 87), but 40%(175) contained no EC data. The overall acceptance rate for SAT-based submissions was 48% and with RWD EC data acceptance was 59%. In the latest 5-year period (2015-2019), use of RWD ECs increased 22% as a proportion of submissions per year, whereas, prior trial ECs decreased (–14%) and use of no EC remained stable (–2%). Between 2015 to 2017 and 2018 to 2019, acceptance rate for RWD ECs increased by 20% (41% in 2015-2017 to 61% in 2018-2019) whereas prior trial EC use decreased by 10% and no EC submissions decreased 16%. Of 226 submissions using ECs, only 29%(66) used an adjusted indirect treatment comparison method. Conclusions: SAT-based submissions to HTA bodies are rapidly evolving in terms of composition and acceptance. Types of EC and methodological approach used are important determinants of positive outcomes

A Framework for Methodological Choice and Evidence Assessment for Studies Using External Comparators from Real-World Data.

Several approaches have been proposed recently to accelerate the pathway from drug discovery to patient access. These include novel designs such as using controls external to the clinical trial where standard randomised controls are not feasible. In parallel, there has been rapid growth in the application of routinely collected healthcare 'real-world' data for post-market safety and effectiveness studies. Thus, using real-world data to establish an external comparator arm in clinical trials is a natural next step. Regulatory authorities have begun to endorse the use of external comparators in certain circumstances, with some positive outcomes for new drug approvals. Given the potential to introduce bias associated with observational studies, there is a need for recommendations on how external comparators should be best used. In this article, we propose an evaluation framework for real-world data external comparator studies that enables full assessment of available evidence and related bias. We define the principle of exchangeability and discuss the applicability of criteria described by Pocock for consideration of the exchangeability of the external and trial populations. We explore how trial designs using real-world data external comparators fit within the evidence hierarchy and propose a four-step process for good conduct of external comparator studies. This process is intended to maximise the quality of evidence based on careful study design and the combination of covariate balancing, bias analysis and combining outcomes

Identity-by-descent estimation with population- and pedigree-based imputation in admixed family data

Background: In the past few years, imputation approaches have been mainly used in population-based designs of genome-wide association studies, although both family- and population-based imputation methods have been proposed. With the recent surge of family-based designs, family-based imputation has become more important. Imputation methods for both designs are based on identity-by-descent (IBD) information. Apart from imputation, the use of IBD information is also common for several types of genetic analysis, including pedigree-based linkage analysis. Methods: We compared the performance of several family- and population-based imputation methods in large pedigrees provided by Genetic Analysis Workshop 19 (GAW19). We also evaluated the performance of a new IBD mapping approach that we propose, which combines IBD information from known pedigrees with information from unrelated individuals. Results: Different combinations of the imputation methods have varied imputation accuracies. Moreover, we showed gains from the use of both known pedigrees and unrelated individuals with our IBD mapping approach over the use of known pedigrees only. Conclusions: Our results represent accuracies of different combinations of imputation methods that may be useful for data sets similar to the GAW19 pedigree data. Our IBD mapping approach, which uses both known pedigree and unrelated individuals, performed better than classical linkage analysis

Identity-by-descent estimation with population- and pedigree-based imputation in admixed family data

BACKGROUND: In the past few years, imputation approaches have been mainly used in population-based designs of genome-wide association studies, although both family- and population-based imputation methods have been proposed. With the recent surge of family-based designs, family-based imputation has become more important. Imputation methods for both designs are based on identity-by-descent (IBD) information. Apart from imputation, the use of IBD information is also common for several types of genetic analysis, including pedigree-based linkage analysis. METHODS: We compared the performance of several family- and population-based imputation methods in large pedigrees provided by Genetic Analysis Workshop 19 (GAW19). We also evaluated the performance of a new IBD mapping approach that we propose, which combines IBD information from known pedigrees with information from unrelated individuals. RESULTS: Different combinations of the imputation methods have varied imputation accuracies. Moreover, we showed gains from the use of both known pedigrees and unrelated individuals with our IBD mapping approach over the use of known pedigrees only. CONCLUSIONS: Our results represent accuracies of different combinations of imputation methods that may be useful for data sets similar to the GAW19 pedigree data. Our IBD mapping approach, which uses both known pedigree and unrelated individuals, performed better than classical linkage analysis

Scalable Methods for the Inference of Identity by Descent

Thesis (Ph.D.)--University of Washington, 2017-03Identity by descent (IBD) describes the shared inheritance of DNA and underlies genetic similarity between individuals. Estimated IBD graphs describing the IBD relationships among individuals have many uses in statistical genetics. An important application is to detect, through linkage analysis, the location of genes that cause genetic diseases. Accurate estimation of IBD graphs among large groups of individuals is essential. IBD is typically estimated either among individuals in small family pedigrees or among distantly related individuals sampled from a population with an unknown pedigree relationship. Both pedigree and population approaches require different modeling assumptions and are applied to different study designs. In this thesis, scalable methods of estimating IBD that combine both pedigree and population estimation methods are developed for family based studies. IBD is estimated between the founders of the family pedigrees to incorporate more information about shared inheritance without additional data collection. A combined IBD model is developed for sib-pair studies, and is demonstrated on siblings from a 50 generation simulated population. A merging algorithm is also developed to combine pedigree and population IBD estimates for family based studies with larger component pedigrees. The merging method is demonstrated on pedigrees from the simulated population and on an Alzheimer’s disease family study. Combined IBD models are shown to increase power and resolution for locating genes that cause genetic diseases

Using Climate-HIV to describe real-world clinical outcomes for people living with HIV taking dolutegravir-based regimens.

OBJECTIVES The objective of this study was to describe the real-world use and effectiveness of dolutegravir-based regimens (DBRs) in routine clinical practice in the United Kingdom. METHODS Retrospective analysis was conducted using data from four National Health Service trusts using Climate-HIV, an electronic case record system. Eligible patients were aged ≥18 years with HIV-1 infection who were prescribed a DBR from December 2012 to March 2018. Outcome measurements were accessed at DBR initiation and at weeks 24, 48 and 96 and the last recorded visit up to the extraction date (last measurement). The primary endpoint was the proportion of patients with HIV-1 RNA <50 copies/mL at Week 48. RESULTS The study cohort included 934 patients; 337 (36%) were female, 414 (47%) were white and 717 (77%) were treatment experienced (TE). The Kaplan-Meier estimated probability of achieving HIV-1 RNA <50 copies/mL at 48 weeks was 96% for treatment-naive (TN) patients and 86% for TE patients. Median times to viral suppression (<50 copies/mL) were 49 and 57 days for TN and TE patients with detectable baseline viral load, respectively, according to Kaplan-Meier analysis. Median follow-up time was 377 days (interquartile range: 131-683). At last measurement, 87% (809/934) of patients remained on a DBR; among those patients, 681 (84%) had HIV-1 RNA <50 copies/mL. CONCLUSIONS High levels of virologic suppression and low rates of discontinuation of DBRs were seen in a large, diverse, UK-based population with HIV-1 infection. These findings are broadly consistent with efficacy data from phase III studies