Event

Meta-research, or “research on research”, is an emerging discipline focused on understanding and improving the current research enterprise. This field offers statisticians new opportunities to apply their technical expertise and propose improvements to how research is planned, conducted and reported.

This seminar will provide an overview of meta-research projects led by the Statistics and Data Analysis group at the Australian Centre for Health Services Innovation (QUT). Our recent work has explored publication trends in clinical prediction modelling. Widespread interest in clinical prediction modelling has been driven by its potential to enhance clinical decision-making, to inform decisions that may delay the onset of disease, optimise access to life-saving treatments, and ultimately improve health outcomes. Yet, of the thousands of models being published each year, few are of sufficient quality to be used in practice. I will discuss the methods and results of two studies: trends in reporting prediction model performance using the Area Under the receiving operating Curve (AUC) and publication rates for prediction model studies registered on clinicaltrials.gov. Lessons learned and opportunities for statisticians to contribute to meta-research will also be discussed.

Nicole White is a mid-career biostatistician and Senior Research Fellow at the Australian Centre for Health Services Innovation, QUT. She has collaborated with academics and clinicians across a range of health and medical research areas. Her clinical collaborations have centred on the analysis of patient registries in critical care, and randomised trials targeting infection control and prevention. Outside of this work, Nicole has been building a meta-research program focused on improving statistical reporting in health and medical research.

This presentation will be held via Zoom and will be recorded.

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Meeting ID: 815 5226 5044

Passcode: 087311