Estimation of treatment effects in short-term depression studies. An evaluation based on the ICH E9(R1) estimands framework.

Estimands aim to incorporate intercurrent events in design, data collection and estimation of treatment effects in clinical trials. Our aim was to understand what estimands may correspond to efficacy analyses commonly employed in clinical trials conducted before publication of ICH E9(R1). We re-analysed six clinical trials evaluating a new anti-depression treatment.

The Impact of COVID-19 on the Initiation of Clinical Trials in Europe and the United States.

The coronavirus disease 2019 (COVID-19) pandemic has a major impact not only on public health and daily living, but also on clinical trials worldwide. To investigate the potential impact of the COVID-19 pandemic on the initiation of clinical trials, we have descriptively analyzed the longitudinal change in phase II and III interventional clinical trials initiated in Europe and in the United States. Based on the public clinical trial register EU Clinical Trials Register and clinicaltrials.

A narrative review of estimands in drug development and regulatory evaluation: old wine in new barrels?

Background: An estimand defines the target of estimation for a clinical trial through specification of the treatment, target population, variable, population-level summary and of the strategies for intercurrent events. A carefully defined estimand aligns the clinical trial design and analysis with the scientific question of interest and adequately accounts for so-called intercurrent events. The ICH E9(R1) addendum suggests five estimand strategies.

FAIR data sharing: The roles of common data elements and harmonization.

The value of robust and responsible data sharing in clinical research and healthcare is recognized by patients, patient advocacy groups, researchers, journal editors, and the healthcare industry globally. Privacy and security concerns acknowledged, the act of exchanging data (interoperability) along with its meaning (semantic interoperability) across studies and between partners has been difficult, if not elusive. For shared data to retain its value, a recommendation has been made to follow the Findable, Accessible, Interoperable, Reusable (FAIR) principles.