Guidance for protocol content and reporting of factorial randomised trials: explanation and elaboration of the CONSORT 2010 and SPIRIT 2013 extensions.

This report presents the explanation and elaboration paper for the CONSORT (Consolidated Standards of Reporting Trials) 2010 and SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) 2013 extensions for factorial trials. Factorial trials involve randomising participants to more than one intervention, often with the aim of evaluating multiple interventions in one study or assessing whether treatments interact. The CONSORT and SPIRIT statements have been extended to allow for the unique features of the factorial design.

SPIRIT-DEFINE explanation and elaboration: recommendations for enhancing quality and impact of early phase dose-finding clinical trials protocols.

Unlabelled: Transparent and accurate reporting in early phase dose-finding (EPDF) clinical trials is crucial for informing subsequent larger trials. The SPIRIT statement, designed for trial protocol content, does not adequately cover the distinctive features of EPDF trials. Recent findings indicate that the protocol contents in past EPDF trials frequently lacked completeness and clarity.

CONSORT-DEFINE explanation and elaboration: recommendations for enhancing reporting quality and impact of early phase dose-finding clinical trials.

Unlabelled: Early phase dose-finding (EPDF) trials are key in the development of novel therapies, with their findings directly informing subsequent clinical development phases and providing valuable insights for reverse translation. Comprehensive and transparent reporting of these studies is critical for their accurate and critical interpretation, which may improve and expedite therapeutic development. However, quality of reporting of design characteristics and results from EPDF trials is often variable and incomplete.

TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods.

The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) statement was published in 2015 to provide the minimum reporting recommendations for studies developing or evaluating the performance of a prediction model. Methodological advances in the field of prediction have since included the widespread use of artificial intelligence (AI) powered by machine learning methods to develop prediction models. An update to the TRIPOD statement is thus needed.