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Minimum sample size calculations for external validation of a clinical prediction model with a time-to-event outcome. (2021)
Journal Article
Riley, R. D., Collins, G. S., Ensor, J., Archer, L., Booth, S., Mozumder, S. I., …Snell, K. I. E. (2022). Minimum sample size calculations for external validation of a clinical prediction model with a time-to-event outcome. Statistics in Medicine, 41(7), 1280-1295. https://doi.org/10.1002/sim.9275

Previous articles in Statistics in Medicine describe how to calculate the sample size required for external validation of prediction models with continuous and binary outcomes. The minimum sample size criteria aim to ensure precise estimation of key... Read More about Minimum sample size calculations for external validation of a clinical prediction model with a time-to-event outcome..

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.

A prognostic model, including quantitative fetal fibronectin, to predict preterm labour: the QUIDS meta-analysis and prospective cohort study (2021)
Journal Article
Stock, S. J., Horne, M., Bruijn, M., White, H., Heggie, R., Wotherspoon, L., …Norrie, J. (2021). A prognostic model, including quantitative fetal fibronectin, to predict preterm labour: the QUIDS meta-analysis and prospective cohort study. Health Technology Assessment, 25(52), 1-168. https://doi.org/10.3310/hta25520

BACKGROUND: The diagnosis of preterm labour is challenging. False-positive diagnoses are common and result in unnecessary, potentially harmful treatments (e.g. tocolytics, antenatal corticosteroids and magnesium sulphate) and costly hospital admissio... Read More about A prognostic model, including quantitative fetal fibronectin, to predict preterm labour: the QUIDS meta-analysis and prospective cohort study.

External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database: an individual participant data meta-analysis. (2021)
Journal Article
Allotey, J., Whittle, R., Snell, K. I. E., Smuk, M., Townsend, R., von Dadelszen, P., …Thangaratinam, S. (2021). External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database: an individual participant data meta-analysis. Ultrasound in Obstetrics & Gynecology, 59(2), 209-219. https://doi.org/10.1002/uog.23757

OBJECTIVE: Stillbirth is a potentially preventable complication of pregnancy. Identifying women at risk can guide decisions on closer surveillance or timing of birth to prevent fetal death. Prognostic models have been developed to predict the risk of... Read More about External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database: an individual participant data meta-analysis..

A tutorial on individualized treatment effect prediction from randomized trials with a binary endpoint (2021)
Journal Article
Hoogland, J., IntHout, J., Belias, M., Rovers, M. M., Riley, R. D., Harrell Jr, F. E., …Reitsma, J. B. (2021). A tutorial on individualized treatment effect prediction from randomized trials with a binary endpoint. Statistics in Medicine, 40(26), 5961-5981. https://doi.org/10.1002/sim.9154

Randomized trials typically estimate average relative treatment effects, but decisions on the benefit of a treatment are possibly better informed by more individualized predictions of the absolute treatment effect. In case of a binary outcome, these... Read More about A tutorial on individualized treatment effect prediction from randomized trials with a binary endpoint.

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.

Developing more generalizable prediction models from pooled studies and large clustered data sets (2021)
Journal Article
de Jong, V. M. T., Moons, K. G. M., Eijkemans, M. J. C., Riley, R. D., & Debray, T. P. A. (2021). Developing more generalizable prediction models from pooled studies and large clustered data sets. Statistics in Medicine, 40(15), 3533-3559. https://doi.org/10.1002/sim.8981

Prediction models often yield inaccurate predictions for new individuals. Large data sets from pooled studies or electronic healthcare records may alleviate this with an increased sample size and variability in sample characteristics. However, existi... Read More about Developing more generalizable prediction models from pooled studies and large clustered data sets.

Prognostic models for predicting relapse or recurrence of major depressive disorder in adults (2021)
Journal Article
Moriarty, A. S., Meader, N., Snell, K. I., Riley, R. D., Paton, L. W., Chew-Graham, C. A., …McMillan, D. (2021). Prognostic models for predicting relapse or recurrence of major depressive disorder in adults. Cochrane Database of Systematic Reviews, 2021(5), Article ARTN CD013491. https://doi.org/10.1002/14651858.cd013491.pub2

BACKGROUND: Relapse (the re-emergence of depressive symptoms after some level of improvement but preceding recovery) and recurrence (onset of a new depressive episode after recovery) are common in depression, lead to worse outcomes and quality of lif... Read More about Prognostic models for predicting relapse or recurrence of major depressive disorder in adults.

Individual participant data meta-analysis for external validation, recalibration, and updating of a flexible parametric prognostic model. (2021)
Journal Article
Ensor, J., Snell, K. I. E., Debray, T. P. A., Lambert, P. C., Look, M. P., Mamas, M. A., …Riley, R. D. (2021). Individual participant data meta-analysis for external validation, recalibration, and updating of a flexible parametric prognostic model. Statistics in Medicine, 40(13), 3066-3084. https://doi.org/10.1002/sim.8959

Individual participant data (IPD) from multiple sources allows external validation of a prognostic model across multiple populations. Often this reveals poor calibration, potentially causing poor predictive performance in some populations. However, r... Read More about Individual participant data meta-analysis for external validation, recalibration, and updating of a flexible parametric prognostic model..

Community-based complex interventions to sustain independence in older people, stratified by frailty: a protocol for a systematic review and network meta-analysis (2021)
Journal Article
Crocker, T. F., Clegg, A., Riley, R. D., Lam, N., Bajpai, R., Jordão, M., …Gladman, J. R. F. (2021). Community-based complex interventions to sustain independence in older people, stratified by frailty: a protocol for a systematic review and network meta-analysis. BMJ Open, 11(2), Article ARTN e045637. https://doi.org/10.1136/bmjopen-2020-045637

INTRODUCTION: Maintaining independence is a primary goal of community health and care services for older people, but there is currently insufficient guidance about which services to implement. Therefore, we aim to synthesise evidence on the effective... Read More about Community-based complex interventions to sustain independence in older people, stratified by frailty: a protocol for a systematic review and network meta-analysis.

Association between antihypertensive treatment and adverse events: systematic review and meta-analysis (2021)
Journal Article
Albasri, A., Hattle, M., Koshiaris, C., Dunnigan, A., Paxton, B., Emma Fox, S., …Sheppard, J. P. (2021). Association between antihypertensive treatment and adverse events: systematic review and meta-analysis. BMJ, 372, https://doi.org/10.1136/bmj.n189

OBJECTIVE: To examine the association between antihypertensive treatment and specific adverse events. DESIGN: Systematic review and meta-analysis. ELIGIBILITY CRITERIA: Randomised controlled trials of adults receiving antihypertensives compare... Read More about Association between antihypertensive treatment and adverse events: systematic review and meta-analysis.