Diversity and Representation Among United States Participants in Amgen Clinical Trials.

Objective: Describe the demographic profile of US participants in Amgen clinical trials over a 10-year period and variations across therapeutic areas, indications, and geographies.

Methods: Cross-sectional retrospective study including participants enrolled (2005-2020) in phase 1-3 trials completed between January 1, 2012 and June 30, 2021.

Results: Among 31,619 participants enrolled across 258 trials, one-fifth represented racial minority populations (Asian, 3%; Black or African American, 17%; American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, multiracial, each < 1%); fewer than one-fifth (16%) represented an ethnic minority population (Hispanic or Latino).

Data-driven strategies for increasing patient diversity in Bristol Myers Squibb-sponsored US oncology clinical trials.

Background/aims: Determining whether clinical trial findings are applicable to diverse, real-world patient populations can be challenging when the full demographic characteristics of enrolled patients are not consistently reported. Here, we present the results of a descriptive analysis of racial and ethnic demographic information for patients in Bristol Myers Squibb (BMS)-sponsored oncology trials in the United States (US) and describe factors associated with increased patient diversity.

Methods: BMS-sponsored oncology trials conducted at US sites with study enrollment dates between 1 January 2013 and 31 May 2021 were analyzed.

Deep Learning With Electronic Health Records for Short-Term Fracture Risk Identification: Crystal Bone Algorithm Development and Validation.

Background: Fractures as a result of osteoporosis and low bone mass are common and give rise to significant clinical, personal, and economic burden. Even after a fracture occurs, high fracture risk remains widely underdiagnosed and undertreated. Common fracture risk assessment tools utilize a subset of clinical risk factors for prediction, and often require manual data entry.