William B. Capra
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View article: P1244: AN AUTOMATED QUANTIFICATION ALGORITHM FOR EVALUATING TOTAL METABOLIC TUMOR VOLUME IN PATIENTS WITH FDG-AVID LYMPHOMAS USING A DEEP LEARNING MODEL
P1244: AN AUTOMATED QUANTIFICATION ALGORITHM FOR EVALUATING TOTAL METABOLIC TUMOR VOLUME IN PATIENTS WITH FDG-AVID LYMPHOMAS USING A DEEP LEARNING MODEL Open
Topic: 20. Lymphoma Biology & Translational Research Background: Total metabolic tumor volume (TMTV) holds promise as a method for quantifying tumor burden in patients with F-18 fluorodeoxyglucose (FDG)-avid lymphomas. The TMTV metric is a…
View article: External Comparator Groups Derived from Real-world Data Used in Support of Regulatory Decision Making: Use Cases and Challenges
External Comparator Groups Derived from Real-world Data Used in Support of Regulatory Decision Making: Use Cases and Challenges Open
Real-world data (RWD) from electronic health records (EHRs) and administrative claims databases are used increasingly to generate real-world evidence (RWE). RWE is used to support clinical evidence packages for medicines that inform decisi…
View article: Augmenting control arms with Real-World Data for cancer trials: Hybrid control arm methods and considerations
Augmenting control arms with Real-World Data for cancer trials: Hybrid control arm methods and considerations Open
Randomized controlled trials (RCTs) are the gold standard for assessing drug safety and efficacy. However, RCTs have some drawbacks which have led to the use of single-arm studies to make certain internal drug development and regulatory de…
View article: Emulating Control Arms for Cancer Clinical Trials Using External Cohorts Created From Electronic Health Record‐Derived Real‐World Data
Emulating Control Arms for Cancer Clinical Trials Using External Cohorts Created From Electronic Health Record‐Derived Real‐World Data Open
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 clinica…
View article: 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
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 Open
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 characte…
View article: Using Electronic Health Records to Derive Control Arms for Early Phase Single‐Arm Lung Cancer Trials: Proof‐of‐Concept in Randomized Controlled Trials
Using Electronic Health Records to Derive Control Arms for Early Phase Single‐Arm Lung Cancer Trials: Proof‐of‐Concept in Randomized Controlled Trials Open
Oncology drug development increasingly relies on single‐arm clinical trials. External controls ( EC s) derived from electronic health record ( EHR ) databases may provide additional context. Patients from a US ‐based oncology EHR database …
View article: 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
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 Open
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 D…
View article: Development and Validation of a High‐Quality Composite Real‐World Mortality Endpoint
Development and Validation of a High‐Quality Composite Real‐World Mortality Endpoint Open
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 commer…