Pragmatic considerations for negative control outcome studies to guide non-randomized comparative analyses: A narrative review.

Purpose: This narrative review describes the application of negative control outcome (NCO) methods to assess potential bias due to unmeasured or mismeasured confounders in non-randomized comparisons of drug effectiveness and safety. An NCO is assumed to have no causal relationship with a treatment under study while subject to the same confounding structure as the treatment and outcome of interest; an association between treatment and NCO then reflects the potential for uncontrolled confounding between treatment and outcome.

Methods: We focus on two recently completed NCO studies that assessed the comparability of outcome risk for patients initiating different osteoporosis medications and lipid-lowering therapies, illustrating several ways in which confounding may result.

Trends in characteristics and outcomes among US adults hospitalised with COVID-19 throughout 2020: an observational cohort study.

Objectives: To examine the temporal patterns of patient characteristics, treatments used and outcomes associated with COVID-19 in patients who were hospitalised for the disease between January and 15 November 2020.

Design: Observational cohort study.

Setting: COVID-19 subset of the Optum deidentified electronic health records, including more than 1.

A qualitative exploration of nurse-physician collaboration in intensive care units.

Background: Effective nurse-physician collaboration is associated with superior patient outcomes and improved job satisfaction for both nurses and physicians.

Objectives: This qualitative study explored factors that contribute to nurse-physician collaboration in critical care. Using a qualitative descriptive design, in-depth interviews were conducted with intensive care unit physicians and nurses.

Machine learning applications for therapeutic tasks with genomics data.

Thanks to the increasing availability of genomics and other biomedical data, many machine learning algorithms have been proposed for a wide range of therapeutic discovery and development tasks. In this survey, we review the literature on machine learning applications for genomics through the lens of therapeutic development. We investigate the interplay among genomics, compounds, proteins, electronic health records, cellular images, and clinical texts.

A Novel Case Study of the Use of Real-World Evidence to Support the Registration of an Osteoporosis Product in China.

On June 23, 2020, Prolia (denosumab) was approved by the National Medical Products Administration (NMPA) in the People's Republic of China as the first monoclonal antibody for the treatment of postmenopausal women with osteoporosis at high risk of fractures. Its brand name in Chinese is , a transliteration from the English name "Prolia", which has an implied meaning of "to give strength to everyone"- a suitable name for a potent anti-resorptive therapy. The approval was supported by a novel marketing authorization application (MAA) that included data from Prolia's global clinical trial program establishing favorable efficacy and safety, augmented by results from a real-world evidence (RWE) study confirming the effectiveness and safety of Prolia in clinical practice within Taiwan and Hong Kong.