Suzie Cro is a Research Fellow at Imperial Clinical Trials Unit (ICTU), School of Public Health.
She has a broad range of experience in the design and analysis of clinical trials and other interventional studies. Currently she is the statistician on a variety of clinical trials including; APRICOT - a two-staged randomised placebo controlled trial with an adaptive element for treatment of Pustular Psoriasis with the IL-1 receptor antagonist anakinra; and ASCOT – a randomised controlled trial of adjunctive intraocular and periocular steroid (triamcinolone acetonide) versus standard treatment in eyes undergoing vitreoretinal surgery for open globe trauma. She is the statistician on an international individual participant data meta-analysis of skin care interventions for the prevention of eczema and food allergy (SCiPAD).
Her statistical research interests include relevant accessible methods for:
- Handling missing data in randomised controlled trials
- Accounting for post-randomisation events, such as rescue medication and non-compliance in randomised controlled trials
- Transparency in the statistical analysis of clinical trials
She has been an Associate Editor for the journal Trials and reviews articles for various other journals. She serves as a member of IDMCs and TSCs.
Suzie obtained a BSc in Mathematics with statistics in 2008 and an MSc in Statistics with applications in medicine in 2010 from the University of Southampton. Following this she joined the MRC Clinical Trials Unit at UCL as a statistician, where she worked in collaboration with the Royal National Orthopaedic Hospital on a variety of musculoskeletal trials and other research projects. In 2013, alongside her position at the MRC CTU at UCL, she joined the London School of Hygiene and Tropical Medicine to undertake a PhD supervised by Professor James Carpenter. After completing her thesis on sensitivity analysis for randomised controlled trials with missing data, she joined Imperial College in October 2016.
et al., 2020, A four-step strategy for handling missing outcome data in randomised trials affected by a pandemic, BMC Medical Research Methodology, ISSN:1471-2288
et al., 2020, Evidence of unexplained discrepancies between planned and conducted statistical analyses: a review of randomized trials, BMC Medicine, Vol:18, ISSN:1741-7015
et al., 2020, Sensitivity analysis for clinical trials with missing continuous outcome data using controlled multiple imputation: a practical guide, Statistics in Medicine, ISSN:0277-6715
et al., 2020, Treatment effect of omalizumab on severe pediatric atopic dermatitis: The ADAPT randomized clinical trial, Jama Pediatrics, Vol:174, ISSN:2168-6203, Pages:29-37
Kahan B, Forbes G, Cro S, 2019, How to design a pre-specified statistical analysis approach to limit p-hacking in clinical trials: the Pre-SPEC framework, BMC Medicine, ISSN:1741-7015
Cro S, Carpenter JR, Kenward MG, 2019, Information-anchored sensitivity analysis: theory and application, The Authors Journal of the Royal Statistical Society: Series a (statistics in Society)