Preclinical assessment for translation to humans: The PATH approach for assessing supporting evidence for early-phase trials and innovative care.

Early-phase trials and innovative care draw support from basic science, preclinical studies, and clinical research. Such evidential diversity presents a challenge for traditional ways of synthesizing evidence. In what follows, we review the limitations of existing approaches for communicating supporting evidence for early-phase trials.

Trials that turn from retrospectively registered to prospectively registered: a cohort study of "retroactively prospective" clinical trial registration using history data.

Background: Prospective registration of clinical trials is mandated by various regulations. However, clinical trial registries like ClinicalTrials.gov allow registry entries to be updated at any time, and key study elements, including the start date, may change before the first patient is enrolled.

Probability of Regulatory Approval Over Time: A Cohort Study of Cancer Therapies.

Purpose: New cancer therapies are frequently evaluated in multiple disease indications. We evaluated whether the probability of achieving US Food and Drug Administration (FDA) approval for a new cancer therapy changes with time.

Methods: We identified a cohort of anticancer drugs with a first registered efficacy trial from 2007 to 2011 on ClinicalTrials.

Frequency of multiple changes to prespecified primary outcomes of clinical trials completed between 2009 and 2017 in German university medical centers: A meta-research study.

Background: Clinical trial registries allow assessment of deviations of published trials from their protocol, which may indicate a considerable risk of bias. However, since entries in many registries can be updated at any time, deviations may go unnoticed. We aimed to assess the frequency of changes to primary outcomes in different historical versions of registry entries, and how often they would go unnoticed if only deviations between published trial reports and the most recent registry entry are assessed.

Artificial Intelligence for Clinical Decision Support in Acute Ischemic Stroke: A Systematic Review.

Background: Established randomized trial-based parameters for acute ischemic stroke group patients into generic treatment groups, leading to attempts using various artificial intelligence (AI) methods to directly correlate patient characteristics to outcomes and thereby provide decision support to stroke clinicians. We review AI-based clinical decision support systems in the development stage, specifically regarding methodological robustness and constraints for clinical implementation.

Methods: Our systematic review included full-text English language publications proposing a clinical decision support system using AI techniques for direct decision support in acute ischemic stroke cases in adult patients.

Institutional dashboards on clinical trial transparency for University Medical Centers: A case study.

Background: University Medical Centers (UMCs) must do their part for clinical trial transparency by fostering practices such as prospective registration, timely results reporting, and open access. However, research institutions are often unaware of their performance on these practices. Baseline assessments of these practices would highlight where there is room for change and empower UMCs to support improvement.

Competition for recruitment in SARS-CoV-2 Trials in the United States: a longitudinal cohort analysis.

Objective: Competition among trials for patient enrollment can impede recruitment. We hypothesized that this occurred early in the COVID-19 pandemic, when an unprecedented number of clinical trials were launched. We performed a simple and multivariable regression analysis evaluating the relationship between the proportion of SARS-CoV-2 investigational trial sites within each USA state with unsuccessful patient-participant recruitment and: (i) the proportion of cases required to reach state recruitment goals; (ii) state population based on data from the US Census; and, (iii) number of trial sites per state.

Analysis of clinical trial registry entry histories using the novel R package cthist.

Historical clinical trial registry data can only be retrieved by manually accessing individual clinical trials through registry websites. This limits the feasibility, accuracy and reproducibility of certain kinds of research on clinical trial activity and presents challenges to the transparency of the enterprise of human research. This paper presents cthist, a novel, free and open source R package that enables automated scraping of clinical trial registry entry histories and returns structured data for analysis.

Results publications are inadequately linked to trial registrations: An automated pipeline and evaluation of German university medical centers.

Background/aims: Informed clinical guidance and health policy relies on clinicians, policymakers, and guideline developers finding comprehensive clinical evidence and linking registrations and publications of the same clinical trial. To support the finding and linking of trial evidence, the World Health Organization, the International Committee of Medical Journal Editors, and the Consolidated Standards of Reporting Trials ask researchers to provide the trial registration number in their publication and a reference to the publication in the registration. This practice costs researchers minimal effort and makes evidence synthesis more thorough and efficient.

How informative were early SARS-CoV-2 treatment and prevention trials? a longitudinal cohort analysis of trials registered on ClinicalTrials.gov.

Background: Early in the SARS-CoV-2 pandemic, commentators warned that some COVID trials were inadequately conceived, designed and reported. Here, we retrospectively assess the prevalence of informative COVID trials launched in the first 6 months of the pandemic.

Methods: Based on prespecified eligibility criteria, we created a cohort of Phase 1/2, Phase 2, Phase 2/3 and Phase 3 SARS-CoV-2 treatment and prevention efficacy trials that were initiated from 2020-01-01 to 2020-06-30 using ClinicalTrials.

Patient burden and clinical advances associated with postapproval monotherapy cancer drug trials: a retrospective cohort study.

Objectives: After regulatory approval, drug companies, public funding agencies and academic researchers often pursue trials aimed at extending the uses of a new drug by testing it in new non-approved indications. Patient burden and clinical impact of such research are not well understood.

Design And Setting: We conducted a retrospective cohort study of postapproval clinical trials launched within 5 years after the drug's first approval, testing anticancer drugs in monotherapy in indications that were first pursued after a drug's first Food and Drug Administration (FDA) license, for all 12 anticancer drugs approved between 2005 and 2007.

Benefit, burden, and impact for a cohort of post-approval cancer combination trials.

Background: After approval, drug developers often pursue trials aimed at extending the uses of a new drug by combining it with other drugs. Little is known about the risk and benefits associated with such research.

Methods: To establish a historic benchmark of risk and benefit, we searched Medline and Embase for clinical trials testing anti-cancer drugs in combination within 5 years of approval by the Food and Drug Administration of 12 anti-cancer "index" drugs first licensed 2005-2007 inclusive.