Publications by authors named "A Lemanska"

Tackling inequities in cancer outcomes is a global health priority. One avenue for improving early diagnosis of cancer is to ensure people know when and how to seek help for cancer symptoms and that this knowledge (and behaviour) is equitably distributed across the population. In this perspective piece we highlight the challenges in understanding sociodemographic differences in help-seeking behaviour (for example, how help-seeking is defined / conceptualised and subsequently assessed), as well as challenges with using existing datasets that are now more readily accessible than ever.

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Article Synopsis
  • The study evaluated the accuracy and completeness of prostate cancer diagnosis records in two UK primary care databases (CPRD GOLD and Aurum) compared to linked Cancer Registry (CR) and Hospital Episode Statistics (HES) data from 2000-2016.
  • Results showed that Aurum had higher accuracy (87%) and completeness (77%) than GOLD (86% accurate, 65% complete), while both databases improved in date concordance over the years.
  • The study concluded that using linked CR or HES data is recommended to enhance case capture, highlighting the importance of understanding each data source's limitations for reliable cancer research.
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Objectives: In the UK, guidelines recommend pancreatic enzyme replacement therapy (PERT) to all people with unresectable pancreatic cancer. In 2023, we published a national audit of PERT which showed suboptimal prescribing and wide regional variation in England. The aim of this manuscript was to describe how we used the PERT audit to drive improvements in healthcare.

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Objectives: To investigate the effect of the COVID-19 pandemic on prostate cancer incidence, prevalence, and mortality in England.

Patients And Methods: With the approval of NHS England and using the OpenSAFELY-TPP dataset of 24 million patients, we undertook a cohort study of men diagnosed with prostate cancer. We visualised monthly rates in prostate cancer incidence, prevalence, and mortality per 100 000 adult men from January 2015 to July 2023.

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Introduction: Worldwide, pancreatic cancer has a poor prognosis. Early diagnosis may improve survival by enabling curative treatment. Statistical and machine learning diagnostic prediction models using risk factors such as patient demographics and blood tests are being developed for clinical use to improve early diagnosis.

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