Development of a dynamic type 2 diabetes risk prediction tool: a UK Biobank study

• URL: http://arxiv.org/abs/2104.10108v1
• Date: Tue, 20 Apr 2021 16:37:26 GMT
• Title: Development of a dynamic type 2 diabetes risk prediction tool: a UK Biobank study
• Authors: Nikola Dolezalova, Massimo Cairo, Alex Despotovic, Adam T.C. Booth, Angus B. Reed, Davide Morelli, David Plans
• Abstract summary: We developed a predictive 10-year type 2 diabetes risk score using 301 features from the UK Biobank dataset. A Cox proportional hazards model slightly overperformed a DeepSurv model trained using the same features. This tool can be used for clinical screening of individuals at risk of developing type 2 diabetes and to foster patient empowerment.
• Score: 0.8620335948752806
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Diabetes affects over 400 million people and is among the leading causes of morbidity worldwide. Identification of high-risk individuals can support early diagnosis and prevention of disease development through lifestyle changes. However, the majority of existing risk scores require information about blood-based factors which are not obtainable outside of the clinic. Here, we aimed to develop an accessible solution that could be deployed digitally and at scale. We developed a predictive 10-year type 2 diabetes risk score using 301 features derived from 472,830 participants in the UK Biobank dataset while excluding any features which are not easily obtainable by a smartphone. Using a data-driven feature selection process, 19 features were included in the final reduced model. A Cox proportional hazards model slightly overperformed a DeepSurv model trained using the same features, achieving a concordance index of 0.818 (95% CI: 0.812-0.823), compared to 0.811 (95% CI: 0.806-0.815). The final model showed good calibration. This tool can be used for clinical screening of individuals at risk of developing type 2 diabetes and to foster patient empowerment by broadening their knowledge of the factors affecting their personal risk.

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