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Meta-analysis of risk prediction studies

Ahmed, Ikhlaaq (2015)
Ph.D. thesis, University of Birmingham.

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This thesis identifies and demonstrates the methodological challenges of meta-analysing risk prediction models using either aggregate data or individual patient data (IPD).

Firstly, a systematic review of published breast cancer models is performed, to summarise their content and performance using aggregate data. It is found that models were not available for comparison. To address this issue, a systematic review is performed to examine articles that develop and/or validate a risk prediction model using IPD from multiple studies. This identifies that most articles only use the IPD for model development, and thus ignore external validation, and also ignore clustering of patients within studies. In response to these issues, IPD is obtained from an article which uses parathyroid hormone (PTH) assay (a continuous variable) to predict postoperative hypocalcaemia after thyroidectomy. It is shown that ignoring clustering is inappropriate, as it ignores potential between-study heterogeneity in discrimination and calibration performance.

This dataset was also used to evaluate an imputation method for dealing with missing thresholds when IPD are unavailable, and the simulation results indicate the approach performs well, though further research is required.

This thesis therefore makes a positive contribution towards meta-analysis of risk prediction models to improve clinical practice.

Type of Work:Ph.D. thesis.
Supervisor(s):Deeks, Jon and Riley, Richard and Billingham, Lucinda
School/Faculty:Colleges (2008 onwards) > College of Medical & Dental Sciences
Department:School of Health and Population Sciences
Additional Information:

Publications resulting from research:

Meads, Catherine, Ikhlaaq Ahmed, and Richard D. Riley. "A systematic review of breast cancer incidence risk prediction models with meta-analysis of their performance." Breast cancer research and treatment 132.2 (2012): 365-377.

Ahmed, Ikhlaaq, et al. "Developing and validating risk prediction models in an individual participant data meta-analysis." BMC medical research methodology 14.1 (2014): 3.

Riley, Richard D., et al. "Summarising and validating test accuracy results across multiple studies for use in clinical practice." Statistics in medicine 34.13 (2015): 2081-2103.

Riley, Richard D., et al. "Meta-analysis of test accuracy studies: an exploratory method for investigating the impact of missing thresholds." Systematic reviews 4.1 (2015): 1-13.

Subjects:RA0421 Public health. Hygiene. Preventive Medicine
RC0254 Neoplasms. Tumors. Oncology (including Cancer)
Institution:University of Birmingham
ID Code:6376
This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder.
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