Selecting Lung Cancer Patients from UK Primary Care Data: A Longitudinal Study of Feature Trends

Abeer Alzubaidi, Jaspreet Kaur, Mufti Mahmud, David J. Brown, Jun He, Graham Ball, David R. Baldwin, Emma O’Dowd, Richard B. Hubbard

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

A high proportion of lung cancer cases are detected at a late cancer stage when they present with symptoms to general practitioners (GP). Early diagnosis is a challenge because many symptoms are also common in other diseases. Therefore, this study aims to assess UK primary care data of patients one, two and three years prior to lung cancer diagnosis to capture trends in clinical features of patients with the goal of early diagnosis and thus potentially curative treatment. This longitudinal study utilises data from the Clinical Practice Research Datalink (CPRD) with linked data from the National Cancer Registration and Analysis Service (NCRAS). A comprehensive list of Read codes is created to select features of interest to establish if a patient has experienced a certain medical condition or not. The comparison of the relative frequencies of the identified predictors associated with cases and controls reveals the importance of the following groups of features: ‘Cough Wheeze’ and ‘Bronchitis unspecified’, ‘Dyspnoea’ and ‘Upper Respiratory Infection’, which are frequent events for lung cancer cases, where a high proportion of cases were also identified using ‘Haemoptysis’ and ‘Peripheral vascular disease’.

Original languageEnglish
Title of host publicationApplied Intelligence and Informatics - 1st International Conference, AII 2021, Proceedings
EditorsMufti Mahmud, M. Shamim Kaiser, Nikola Kasabov, Khan Iftekharuddin, Ning Zhong
PublisherSpringer Science and Business Media Deutschland GmbH
Pages43-59
Number of pages17
ISBN (Print)9783030822682
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event1st International Conference on Applied Intelligence and Informatics, AII 2021 - Virtual, Online
Duration: 30 Jul 202131 Jul 2021

Publication series

NameCommunications in Computer and Information Science
Volume1435
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference1st International Conference on Applied Intelligence and Informatics, AII 2021
CityVirtual, Online
Period30/07/2131/07/21

Keywords

  • Bronchitis unspecified
  • Cough
  • Dyspnoea
  • Lung cancer
  • Machine learning
  • Upper respiratory infection

ASJC Scopus subject areas

  • Computer Science (all)
  • Mathematics (all)

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