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Collins, S, Peek, N, Riley, RD ORCID: https://orcid.org/0000-0001-8699-0735 and Martin, G (2021) Sample sizes of prediction model studies in prostate cancer were rarely justified and often insufficient. Journal of Clinical Epidemiology, 133. pp. 53-60.
Zghebi, SS, Mamas, MA ORCID: https://orcid.org/0000-0001-9241-8890, Ashcroft, DM, Rutter, MK, VanMarwijk, H, Salisbury, C, Mallen, CD ORCID: https://orcid.org/0000-0002-2677-1028, Chew-Graham, CA ORCID: https://orcid.org/0000-0002-9722-9981, Qureshi, N, Weng, SF, Holt, T, Buchan, I, Peek, N, Giles, S, Reeves, D and Kontopantelis, E (2021) Assessing the severity of cardiovascular disease in 213 088 patients with coronary heart disease: a retrospective cohort study. Open Heart, 8 (1).
Jenkins, DA, Martin, GP, Sperrin, M, Riley, RD ORCID: https://orcid.org/0000-0001-8699-0735, Debray, TPA, Collins, GS and Peek, N (2021) Continual updating and monitoring of clinical prediction models: time for dynamic prediction systems? Diagnostic and Prognostic Research, 5 (1). 1 - ?.
Zghebi, SS, Mamas, MA ORCID: https://orcid.org/0000-0001-9241-8890, Ashcroft, DM, Salisbury, C, Mallen, CD ORCID: https://orcid.org/0000-0002-2677-1028, Chew-Graham, CA ORCID: https://orcid.org/0000-0002-9722-9981, Reeves, D, Van Marwijk, H, Qureshi, N, Weng, S, Holt, T, Buchan, I, Peek, N, Giles, S, Rutter, MK and Kontopantelis, E (2020) Development and validation of the DIabetes Severity SCOre (DISSCO) in 139 626 individuals with type 2 diabetes: a retrospective cohort study. BMJ Open Diabetes Research and Care, 8 (1).
Nowakowska, M, Zghebi, SS, Ashcroft, DM, Buchan, I, Chew-Graham, C ORCID: https://orcid.org/0000-0002-9722-9981, Holt, T, Mallen, CD ORCID: https://orcid.org/0000-0002-2677-1028, Van Marwijk, H, Peek, N, Perera-Salazar, R, Reeves, D, Rutter, MK, Weng, SF, Qureshi, N, Mamas, MA ORCID: https://orcid.org/0000-0001-9241-8890 and Kontopantelis, E (2020) Correction to: The comorbidity burden of type 2 diabetes mellitus: patterns, clusters and predictions from a large English primary care cohort. BMC Medicine, 18 (1). 22 - ?.
Barrowman, MA, Peek, N, Lambie, M, Martin, GP and Sperrin, M (2019) How unmeasured confounding in a competing risks setting can affect treatment effect estimates in observational studies. BMC Medical Research Methodology, 19 (1). 166 -166.
Nowakowska, M, Zghebi, SS, Ashcroft, DM, Buchan, I, Chew-Graham, C, Holt, T, Mallen, C, Van Marwijk, H, Peek, N, Perera-Salazar, R, Reeves, D, Rutter, MK, Weng, SF, Qureshi, N, Mamas, MA and Kontopantelis, E (2019) The comorbidity burden of type 2 diabetes mellitus: patterns, clusters and predictions from a large English primary care cohort. BMC Medicine, 17 (1). 145 - ?.
Zghebi, S, Panagioti, M, Rutter, M, Ashcroft, D, van Marwijk, H, Salisbury, C, Chew-Graham, CA, Buchan, I, Qureshi, N, Peek, N, Mallen, CD ORCID: https://orcid.org/0000-0002-2677-1028, Mamas, M ORCID: https://orcid.org/0000-0001-9241-8890 and Kontopantelis, E (2019) Assessing the Severity of Type 2 Diabetes Using Clinical Data Based Measures: a Systematic Review. Diabetic Medicine, 36 (6). pp. 688-701.
Zghebi, SS, Rutter, MK, Ashcroft, DM, Salisbury, C, Mallen, CD ORCID: https://orcid.org/0000-0002-2677-1028, Chew-Graham, CA, Reeves, D, Van Marwijk, H, Qureshi, N, Weng, S, Peek, N, Planner, C, Nowakowska, M, Mamas, M ORCID: https://orcid.org/0000-0001-9241-8890 and Kontopantelis, E (2018) Using electronic health records to quantify and stratify the severity of type 2 diabetes in primary care in England: rationale and cohort study design. BMJ Open, 8 (6).
Martin, GP, Mamas, M ORCID: https://orcid.org/0000-0001-9241-8890, Peek, N, Buchan, I and Sperrin, M (2018) A Multiple-Model Generalisation of Updating Clinical Prediction Models. Statistics in Medicine, 37 (8). pp. 1343-1358.
Martin, G, Mamas, M ORCID: https://orcid.org/0000-0001-9241-8890, Peek, N, Buchan, I and Sperrin, M (2017) Clinical Prediction in Defined Populations: a simulation study investigating when and how to aggregate existing models. BMC Medical Research Methodology, 17 (1). pp. 1-11.
Fraccaro, P, Kontopantelis, E, Sperrin, M, Peek, N, Mallen, C, Urban, P, Buchan, I and Mamas, M ORCID: https://orcid.org/0000-0001-9241-8890 (2016) Predicting Mortality from Change-over-time in the Charlson Comorbidity Index: A retrospective cohort study in a data-intensive UK health system. Medicine, 95 (43). e4973.
Mamas, M ORCID: https://orcid.org/0000-0001-9241-8890, Fath-Ordoubadi F, F, Danzi, G, Spaepen, E, Kwok, CS ORCID: https://orcid.org/0000-0001-7047-1586, Buchan, I, Peek, N, Debelder, M, Ludman, P, Paunovic, D and Urban, P (2015) Prevalence and Impact of Co-morbidity Burden as Defined by the Charlson Co-morbidity Index on 30-Day and 1- and 5-Year Outcomes After Coronary Stent Implantation (from the Nobori-2 Study). American Journal of Cardiology, 116 (3). pp. 364-371.
Book Section
Akbarov, A, Williams, R, Brown, B, Mamas, M ORCID: https://orcid.org/0000-0001-9241-8890, Peek, N, Buchan, I and Sperrin, M (2015) A Two-stage Dynamic Model to Enable Updating of Clinical Risk Prediction from Longitudinal Health Record Data: illustrated with Kidney Function. In: Medinfo 2015: Proceedings of the 15th World Congress on Health and Biomedical Informatics. Studies in Health Technology and Informatics, 216 . IOS Press, pp. 696-700.