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• W4386648367 abstract "Abstract Introduction Worldwide, pancreatic cancer has a poor prognosis. Earlier diagnosis may improve survival by enabling curative treatment. However, non-specific symptoms and a lack of suitable biomarkers make this challenging. Statistical and machine learning prediction models using risk factors such as patient demographics, symptoms and blood tests are being developed for clinical use to improve earlier diagnosis. One example is the Enriching New-onset Diabetes for Pancreatic Cancer (ENDPAC) model, which employs patients’ age, blood glucose and weight changes to provide pancreatic cancer risk scores. However, ENDPAC has yet to be used in clinical settings. In the United Kingdom (UK), blood tests and weight measurements are routinely collected in primary care which, given primary care’s central role in assessing and addressing patients’ cancer risk, makes it an ideal setting to assess ENDPAC’s feasibility. Methods and analysis DEFEND PRIME will be a multi-centre observational study determining the feasibility of extracting data from primary care providers in the UK to calculate ENDPAC scores. After developing the data extraction methods, 20 UK GP practices will provide anonymised data on participants aged 50+ years, with a glycated haemoglobin (HbA1c) test result of ≥ 48 mmol/mol and no previous abnormal HbA1c results. ENDPAC scores will be calculated, and descriptive statistics used to summarise the cohort’s demographics and assess data quality. Findings will inform the development of a future clinical study, in which ENDPAC scores will be calculated and participants with elevated scores will be invited for clinical workup. Ethics and dissemination This project has been reviewed by the University of Surrey University Ethics Committee and received a favourable ethical opinion (FHMS 22-23 151 EGA). Study findings will be presented at scientific meetings and published in international peer-reviewed journals. Participating GP practices, clinical leads and policy makers will be provided with summaries of the findings. Strengths and limitations of this study’s methods Early computerisation of UK primary care, incorporating linkage to pathology systems combined with pay-for-performance for chronic disease management including diabetes, helps to ensure population-wide data. The extraction methods will permit validation of the extracted data by GP practice staff prior to transfer to the research team. Using HbA1c results only to define new-onset diabetes means this study is not impacted by the quality of diabetes diagnosis coding in primary care. This study will raise awareness of new-onset diabetes’ association with pancreatic cancer within the primary care community. The study period includes the COVID-19 pandemic, thus the data within this period may not reflect data obtained before or after the pandemic." @default.
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• W4386648367 date "2023-09-12" @default.
• W4386648367 modified "2023-09-27" @default.
• W4386648367 title "Determining the feasibility of calculating pancreatic cancer risk scores for people with new-onset diabetes in primary care (DEFEND PRIME): study protocol" @default.
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• W4386648367 doi "https://doi.org/10.1101/2023.09.12.23295372" @default.
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