Development and external validation of a risk prediction model for falls in patients with an indication for antihypertensive treatment: retrospective cohort study. (2022)
Journal Article
Archer, L., Koshiaris, C., Lay-Flurrie, S., Snell, K. I. E., Riley, R. D., Stevens, R., …Ogden, M. (2022). Development and external validation of a risk prediction model for falls in patients with an indication for antihypertensive treatment: retrospective cohort study. BMJ, 379, e070918. https://doi.org/10.1136/bmj-2022-070918

OBJECTIVE: To develop and externally validate the STRAtifying Treatments In the multi-morbid Frail elderlY (STRATIFY)-Falls clinical prediction model to identify the risk of hospital admission or death from a fall in patients with an indication for a... Read More about Development and external validation of a risk prediction model for falls in patients with an indication for antihypertensive treatment: retrospective cohort study..

Developing clinical prediction models when adhering to minimum sample size recommendations: The importance of quantifying bootstrap variability in tuning parameters and predictive performance (2021)
Journal Article
Martin, G. P., Riley, R. D., Collins, G. S., & Sperrin, M. (2021). Developing clinical prediction models when adhering to minimum sample size recommendations: The importance of quantifying bootstrap variability in tuning parameters and predictive performance. Statistical Methods in Medical Research, 30(12), 2545-2561. https://doi.org/10.1177/09622802211046388

Recent minimum sample size formula (Riley et al.) for developing clinical prediction models help ensure that development datasets are of sufficient size to minimise overfitting. While these criteria are known to avoid excessive overfitting on average... Read More about Developing clinical prediction models when adhering to minimum sample size recommendations: The importance of quantifying bootstrap variability in tuning parameters and predictive performance.

Development and validation of a risk prediction model of preterm birth for women with preterm labour symptoms (the QUIDS study): A prospective cohort study and individual participant data meta-analysis. (2021)
Journal Article
Stock, S. J., Horne, M., Bruijn, M., White, H., Boyd, K. A., Heggie, R., …Norrie, J. (2021). Development and validation of a risk prediction model of preterm birth for women with preterm labour symptoms (the QUIDS study): A prospective cohort study and individual participant data meta-analysis. PLoS Medicine, e1003686 - ?. https://doi.org/10.1371/journal.pmed.1003686

BACKGROUND: Timely interventions in women presenting with preterm labour can substantially improve health outcomes for preterm babies. However, establishing such a diagnosis is very challenging, as signs and symptoms of preterm labour are common and... Read More about Development and validation of a risk prediction model of preterm birth for women with preterm labour symptoms (the QUIDS study): A prospective cohort study and individual participant data meta-analysis..

Minimum sample size for external validation of a clinical prediction model with a binary outcome (2021)
Journal Article
Riley, R. D., Debray, T. P. A., Collins, G. S., Archer, L., Ensor, J., van Smeden, M., & Snell, K. I. E. (2021). Minimum sample size for external validation of a clinical prediction model with a binary outcome. Statistics in Medicine, 40(19), 4230-4251. https://doi.org/10.1002/sim.9025

In prediction model research, external validation is needed to examine an existing model's performance using data independent to that for model development. Current external validation studies often suffer from small sample sizes and consequently imp... Read More about Minimum sample size for external validation of a clinical prediction model with a binary outcome.

Protocol for a systematic review on the methodological and reporting quality of prediction model studies using machine learning techniques (2020)
Journal Article
Andaur Navarro, C. L., Damen, J. A. A. G., Takada, T., Nijman, S. W. J., Dhiman, P., Ma, J., …Hooft, L. (2020). Protocol for a systematic review on the methodological and reporting quality of prediction model studies using machine learning techniques. BMJ Open, 10(11), Article e038832. https://doi.org/10.1136/bmjopen-2020-038832

INTRODUCTION: Studies addressing the development and/or validation of diagnostic and prognostic prediction models are abundant in most clinical domains. Systematic reviews have shown that the methodological and reporting quality of prediction model s... Read More about Protocol for a systematic review on the methodological and reporting quality of prediction model studies using machine learning techniques.

Minimum sample size for developing a multivariable prediction model: Part II-binary and time-to-event outcomes (2018)
Journal Article
Riley, R. D., Snell, K. I. E., Ensor, J., Burke, D. L., Harrell, F. E., Moons, K. G. M., & Collins, G. S. (2019). Minimum sample size for developing a multivariable prediction model: Part II-binary and time-to-event outcomes. Statistics in Medicine, 38(7), 1276-1296. https://doi.org/10.1002/sim.7992

When designing a study to develop a new prediction model with binary or time-to-event outcomes, researchers should ensure their sample size is adequate in terms of the number of participants (n) and outcome events (E) relative to the number of predic... Read More about Minimum sample size for developing a multivariable prediction model: Part II-binary and time-to-event outcomes.