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When: Wednesday, September 30, 2020 at 4 pm
Where: Online virtual seminars during the COVID-19 pandemic
Presenter: Richard Riley, Professor of Biostatistics at Keele University
Topic: Improving prognosis and prediction research: PROGRESS in sample size calculations and estimation of treatment effect modifiers
There is a growing demand to personalise treatment and healthcare for individuals based on their prognosis and/or predicted response to treatment. For this reason, prognosis and prediction research has never been more important. Sadly, empirical evidence has shown that prognosis and prediction studies are often poorly designed, badly analysed, and selectively reported. The Prognosis Research Strategy (PROGRESS) framework was established to help address such shortcomings. In this talk, I will describe the PROGRESS framework, and highlight two areas that warrant particular improvement: (i) sample size for developing risk prediction models, and (ii) estimation of treatment effect modifiers (treatment-covariate interactions). In terms of sample size for model development, current “rules of thumb” are based on having at least 10 events per predictor variable, but I will propose a more scientific approach based on minimising expected overfitting and ensuring precise parameter estimation. In terms of treatment effect modifiers, I will describe why individual participant data (IPD) meta-analyses are needed to increase statistical power, and plead for researchers to stop categorising continuous variables and to consider non-linear relationships. Real are examples used to illustrate the concepts. The talk is intended for a wide audience.
To Register: Contact firstname.lastname@example.org to receive the link
The presentation will be delivered in English.