Augmenting control arms with real-world data for cancer trials: Hybrid control arm methods and considerations.

Background: Hybrid controlled trials with real-world data (RWD), where the control arm is composed of both trial and real-world patients, could facilitate research when the feasibility of randomized controlled trials (RCTs) is challenging and single-arm trials would provide insufficient information.

Methods: We propose a frequentist two-step borrowing method to construct hybrid control arms. We use parameters informed by a completed randomized trial in metastatic triple-negative breast cancer to simulate the operating characteristics of dynamic and static borrowing methods, highlighting key trade-offs and analytic decisions in the design of hybrid studies.

Emulating Control Arms for Cancer Clinical Trials Using External Cohorts Created From Electronic Health Record-Derived Real-World Data.

Electronic health record (EHR)-derived real-world data (RWD) can be sourced to create external comparator cohorts to oncology clinical trials. This exploratory study assessed whether EHR-derived patient cohorts could emulate select clinical trial control arms across multiple tumor types. The impact of analytic decisions on emulation results was also evaluated.

Evaluating eligibility criteria of oncology trials using real-world data and AI.

There is a growing focus on making clinical trials more inclusive but the design of trial eligibility criteria remains challenging. Here we systematically evaluate the effect of different eligibility criteria on cancer trial populations and outcomes with real-world data using the computational framework of Trial Pathfinder. We apply Trial Pathfinder to emulate completed trials of advanced non-small-cell lung cancer using data from a nationwide database of electronic health records comprising 61,094 patients with advanced non-small-cell lung cancer.

Characterizing the Feasibility and Performance of Real-World Tumor Progression End Points and Their Association With Overall Survival in a Large Advanced Non-Small-Cell Lung Cancer Data Set.

Purpose: Large, generalizable real-world data can enhance traditional clinical trial results. The current study evaluates reliability, clinical relevance, and large-scale feasibility for a previously documented method with which to characterize cancer progression outcomes in advanced non-small-cell lung cancer from electronic health record (EHR) data.

Methods: Patients who were diagnosed with advanced non-small-cell lung cancer between January 1, 2011, and February 28, 2018, with two or more EHR-documented visits and one or more systemic therapy line initiated were identified in Flatiron Health's longitudinal EHR-derived database.

Using Electronic Health Records to Derive Control Arms for Early Phase Single-Arm Lung Cancer Trials: Proof-of-Concept in Randomized Controlled Trials.

Oncology drug development increasingly relies on single-arm clinical trials. External controls (ECs) derived from electronic health record (EHR) databases may provide additional context. Patients from a US-based oncology EHR database were aligned with patients from randomized controlled trials (RCTs) and trial-specific eligibility criteria were applied to the EHR dataset.

An evaluation of the impact of missing deaths on overall survival analyses of advanced non-small cell lung cancer patients conducted in an electronic health records database.

Purpose: The aim of this study was to assess the impact of missing death data on survival analyses conducted in an oncology EHR-derived database.

Methods: The study was conducted using the Flatiron Health oncology database and the National Death Index (NDI) as a gold standard. Three analytic frameworks were evaluated in advanced non-small cell lung cancer (aNSCLC) patients: median overall survival [mOS]), relative risk estimates conducted within the EHR-derived database, and "external control arm" analyses comparing an experimental group augmented with mortality data from the gold standard to a control group from the EHR-derived database only.

Development and Validation of a High-Quality Composite Real-World Mortality Endpoint.

Objective: To create a high-quality electronic health record (EHR)-derived mortality dataset for retrospective and prospective real-world evidence generation.

Data Sources/study Setting: Oncology EHR data, supplemented with external commercial and US Social Security Death Index data, benchmarked to the National Death Index (NDI).

Study Design: We developed a recent, linkable, high-quality mortality variable amalgamated from multiple data sources to supplement EHR data, benchmarked against the highest completeness U.

A phase I clinical trial of a ribozyme-based angiogenesis inhibitor targeting vascular endothelial growth factor receptor-1 for patients with refractory solid tumors.

Purpose: This study intended to determine the maximum tolerated dose, safety, pharmacokinetic variables, clinical response, and pharmacodynamic markers of daily s.c. administration of Angiozyme.

Comparing the power of the discontinuation design to that of the classic randomized design on time-to-event endpoints.

The discontinuation design has been proposed as an alternative to the classic randomized design for evaluating the effect of an experimental agent on time-to-disease progression and survival duration. With this design, all enrolled patients are treated with an experimental agent for a fixed course of therapy. Those patients with progressive disease at or before the end of this fixed period are removed from trial while those with stable disease or better are randomized to continued treatment with the experimental agent or standard of care.