Professor Sue Mallett

Sue Mallett is a Professor in diagnostic and prognostic medical statistics, specialising in clinical trials design, methodology and systematic reviews. She works closely with clinical teams to improve diagnostic pathways, by designing studies and identifying best methods and evidence to inform NHS practice and future NICE guidelines. Sue brings expertise from several disciplinary areas - medical statistics, immunology, virology and genetics.

Sue Mallett trained for her DPhil in molecular immunology with Alan F. Williams and Neil Barclay. Sue retrained in medical statistics from 2000, including working with Roy Anderson, Neil Ferguson, Mike Clarke, Sally Hopewell, Doug Altman, Rafael Perera and Jon Deeks. Following over 15 years of productive ongoing research collaborations with Steve Halligan and Stuart Taylor, Sue joined CMI in 2020.

Sue has developed new diagnostic clinical trial designs in collaboration with Stuart Taylor and Steve Halligan to include patient management decisions, time to diagnosis and comparison of diagnostic pathways. She has helped to design and analyse studies on computer assisted detection in CT colonography as well as eye tracking of radiologists reading 3D videos of colorectal cancer. Sue collaborates with Seena Fazel at Oxford on risk prediction tools in forensic pyschiatry (OxRISK) and ongoing studies into implementation in clinical practice.

Sue has a strong track record of methodology research including as a steering group member for development of internationally important risk of bias tools PROBAST and QUADAS for prognosis and diagnosis.

She is currently senior statistician on a number of ongoing clinical trials in CMI through NCITA, ACED and ongoing collaborations. She is lead statistician and methodologist on diagnostic and prognostic systematic reviews including recently on RT-PCR testing for SARS-CoV-2, Crohn's prognostic markers, hernia recurrence, Coeliac disease, prostate cancer and HIV. Sue has published over 100 papers.

View: Scopus | Google Scholar

Summary of current research projects

Position	Project Title	Funder	Duration (Months)	Year	Grant Award
Co-I	A prognostic model to identify ventral hernia recurrence	NIHR RFPB	24	2018	£145,926
Co-I	Biomarkers in Crohn's disease	NIHR HTA	24	2016	£248,773
Co-I	MRI enterography as a predictor of disabling disease in newly diagnosed Crohn's disease	NIHR HTA	60	2016	£358K
Co-I	Comprehensive staging of newly diagnosed lung and colorectal cancer: Prospective multicentre comparison of whole body Magnetic Resonance Imaging	NIHA HTA	72	2012	£1,057K
Co-I	Multi-centre comparison of MRI and ultrasound in the diagnosis and staging of crohn’s disease	NIHA HTA	60	2013	£920K
Co-I	ROCKETS-GEN: Earlier detection of ovarian cancer using novel genomic technology.	CRUK	36	2019	£376K
Co-I	What is the optimum strategy for identifying adults and children with coeliac disease? A systematic review and economic models (NIHR129020)	NIHR	18	2020
Co-I	Real World Evidence Driving Changes in Crohn’s Disease Management Using Quantitative Imaging Analysis (NIHR201000)	NIHR EME	24	2022	£500K
Co-I	TEST - Test Evaluation Using Structured Tool	MRC	36	2020	£442K

Selected Publications

1. Mallett S, Allen AJ, Graziadio S, Taylor SA, Sakai NS, Green K, Suklan J, Hyde C, Shinkins B, Zhelev Z, Peters J, Turner PJ, Roberts NW, di Ruffano LF, Wolff R, Whiting P, Winter A, Bhatnagar G, Nicholson BD, Halligan S. (2020) At what times during infection is SARS-CoV-2 detectable and no longer detectable using RT-PCR-based tests? A systematic review of individual participant data. BMC Med. 18(1):346. doi: 10.1186/s12916-020-01810-8

2. Wolff, R. F., Moons, K. G., Riley, R. D., Whiting, P. F., Westwood, M., Collins, G. S., Reitsma, J. B., Kleijnen, J., & Mallett, S. (2019). PROBAST: A tool to assess the risk of bias and applicability of prediction model studies. Annals of Internal Medicine, 170(1), 51-58.

3. Moons, K. G., Wolff, R. F., Riley, R. D., Whiting, P. F., Westwood, M., Collins, G. S., Reitsma, J. B., Kleijnen, J., & Mallett, S. (2019). PROBAST: a tool to assess risk of bias and applicability of prediction model studies – explanation and elaboration. Annals of Internal Medicine, 170(1), W1-W33.

4. Taylor, S. A., Mallett, S., Beare, S., Bhatnagar, G., Blunt, D., Boavida, P., Bridgewater, J., Clarke, C. S., Duggan, M., Ellis, S., Glynne-Jones, R., Goh, V., Groves, A. M., Hameeduddin, A., Janes, S. M., Johnston, E. W., Koh, D. M., Miles, A., Morris, S., Morton, A., Navani, N., O'Donohue, J., Oliver, A., Padhani, A. R., Pardoe, H., Patel, U., Punwani, S., Quinn, L., Rafiee, H., Reczko, K., Rockall, A. G., Shahabuddin, K., Sidhu, H. S., Teague, J., Thaha, M. A., Train, M., van Ree, K., Wijeyekoon, S., Halligan, S., & Streamline, i. (2019). Diagnostic accuracy of whole-body MRI versus standard imaging pathways for metastatic disease in newly diagnosed colorectal cancer: the prospective Streamline C trial. Lancet Gastroenterol Hepatol, 4(7), 529-537. doi:10.1016/S2468-1253(19)30056-1

5. Taylor, S. A., Mallett, S., Ball, S., Beare, S., Bhatnagar, G., Bhowmik, A., Boavida, P., Bridgewater, J., Clarke, C. S., Duggan, M., Ellis, S., Glynne-Jones, R., Goh, V., Groves, A. M., Hameeduddin, A., Janes, S. M., Johnston, E. W., Koh, D. M., Lock, S., Miles, A., Morris, S., Morton, A., Navani, N., Oliver, A., O'Shaughnessy, T., Padhani, A. R., Prezzi, D., Punwani, S., Quinn, L., Rafiee, H., Reczko, K., Rockall, A. G., Russell, P., Sidhu, H. S., Strickland, N., Tarver, K., Teague, J., Halligan, S., & Streamline, i. (2019). Diagnostic accuracy of whole-body MRI versus standard imaging pathways for metastatic disease in newly diagnosed non-small-cell lung cancer: the prospective Streamline L trial. Lancet Respir Med, 7(6), 523-532. doi:10.1016/S2213-2600(19)30090-6

6. Taylor, S. A., Mallett, S., Bhatnagar, G., Baldwin-Cleland, R., Bloom, S., Gupta, A., Hamlin, P. J., Hart, A. L., Higginson, A., Jacobs, I., McCartney, S., Miles, A., Murray, C. D., Plumb, A. A., Pollok, R. C., Punwani, S., Quinn, L., Rodriguez-Justo, M., Shabir, Z., Slater, A., Tolan, D., Travis, S., Windsor, A., Wylie, P., Zealley, I., Halligan, S., & investigators, M. s. (2018). Diagnostic accuracy of magnetic resonance enterography and small bowel ultrasound for the extent and activity of newly diagnosed and relapsed Crohn's disease (METRIC): a multicentre trial. Lancet Gastroenterol Hepatol, 3(8), 548-558. doi:10.1016/S2468-1253(18)30161-4

7. Halligan, S., Mallett, S., Altman, D. G., McQuillan, J., Proud, M., Beddoe, G., Honeyfield, L., & Taylor, S. A. (2011). Incremental benefit of computer-aided detection when used as a second and concurrent reader of CT colonographic data: multiobserver study. Radiology, 258(2), 469-476. doi:10.1148/radiol.10100354

8. Mallett, S., Phillips, P., Fanshawe, T. R., Helbren, E., Boone, D., Gale, A., Taylor, S. A., Manning, D., Altman, D. G., & Halligan, S. (2014). Tracking eye gaze during interpretation of endoluminal three-dimensional CT colonography: visual perception of experienced and inexperienced readers. Radiology, 273(3), 783-792. doi:10.1148/radiol.14132896

9. Fazel, S., Wolf, A., Larsson, H., Lichtenstein, P., Mallett, S., & Fanshawe, T. R. (2017). Identification of low risk of violent crime in severe mental illness with a clinical prediction tool (Oxford Mental Illness and Violence tool [OxMIV]): a derivation and validation study. Lancet Psychiatry, 4(6), 461-468. doi:10.1016/S2215-0366(17)30109-8

10. Wijedoru, L., Mallett, S., & Parry, C. M. (2017). Rapid diagnostic tests for typhoid and paratyphoid (enteric) fever. Cochrane Database Syst Rev, 5, CD008892.doi:10.1002/14651858.CD008892.pub2

11. Fazel, S., Chang, Z., Fanshawe, T., Langstrom, N., Lichtenstein, P., Larsson, H., & Mallett, S. (2016). Prediction of violent reoffending on release from prison: derivation and external validation of a scalable tool. Lancet Psychiatry, 3(6), 535-543. doi:10.1016/S2215-0366(16)00103-6

12. Ratnavelu, N. D., Brown, A. P., Mallett, S., Scholten, R. J., Patel, A., Founta, C., Galaal, K., Cross, P., & Naik, R. (2016). Intraoperative frozen section analysis for the diagnosis of early stage ovarian cancer in suspicious pelvic masses. Cochrane Database Syst Rev, 3, CD010360. doi:10.1002/14651858.CD010360.pub2

Professor Sue Mallett

Contact