Aims: Medication-taking behaviours of breast cancer survivors undergoing adjuvant hormone therapy have received considerable attention. This study aimed to determine factors affecting medication-taking behaviours in people with breast cancer using data mining.
Design: A longitudinal observational retrospective cohort study with a hospital-based survey.
Methods: A total of 385 subjects were surveyed, analysing existing data from January 2010 to December 2017 in Taiwan. Three data mining approaches-multiple logistic regression, decision tree and artificial neural network-were used to build the prediction models and rank the importance of influencing factors. Accuracy, specificity and sensitivity were used as assessment indicators for the prediction models.
Results: Multiple logistic regression was the most effective approach, achieving an accuracy of 96.37%, specificity of 96.75% and sensitivity of 96.12%. The duration of adjuvant hormone therapy discontinuation, duration of adjuvant hormone therapy use and age at diagnosis by data mining were the three most critical factors influencing the medication-taking behaviours of people with breast cancer.
Keywords: adherence; breast cancer; data mining; medication-taking behaviours; persistence.
© 2021 The Authors. Nursing Open published by John Wiley & Sons Ltd.