ArticleBioMed research international2018
Discovering Associations of Adverse Events with Pharmacotherapy in Patients with Non-Small Cell Lung Cancer Using Modified Apriori Algorithm.
Article in BioMed research international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Use of Electronic Health Record Data for Drug Safety Signal Identification: A Scoping Review.Drug safety · 2023Article
- Medical Information Mining-Based Visual Artificial Intelligence Emergency Nursing Management System.Journal of healthcare engineering · 2021Article
- Different Data Mining Approaches Based Medical Text Data.Journal of healthcare engineering · 2021Review
- Aidi Injection, a Traditional Chinese Medicine Injection, Could Be Used as an Adjuvant Drug to Improve Quality of Life of Cancer Patients Receiving Chemotherapy: A Propensity Score Matching Analysis.Integrative cancer therapiesArticle
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimTo explore the associations between adverse events and pharmacotherapy in patients with non-small cell lung cancer.
methods16,527 patients with non-small cell lung cancer admitted to the Cancer Hospital, Chinese Academy of Medical Sciences, between January 1, 2010, and December 31, 2016, were included in the study. Their medication and laboratory examinations data were extracted from the medical records. Common Terminology Criteria for Adverse Events Version 4.03 were utilized for adverse events reporting. A new association algorithm was developed based on Apriori algorithm and used to investigate the associations between drugs and adverse events. In addition, a statistical comparison was conducted to compare the modified Apriori algorithm with the conventional Apriori algorithm.
resultsDifferent types and levels of adverse events were identified from the abnormal laboratory findings. The three most common adverse events were hypocalcemia, elevated creatine phosphokinase, and hypertriglyceridemia. In addition, using the modified Apriori algorithm, 380 association rules were found between adverse events and chemotherapy. Moreover, the statistical comparison of the two methods demonstrated that the modified Apriori algorithm was more advantageous in analyzing the correlation between drugs and adverse events than the conventional Apriori algorithm.
conclusionsThe modified Apriori algorithm can be used to more efficiently associate pharmacotherapy with adverse events. Based on the modified Apriori algorithm, meaningful association rules between drugs and adverse events were found, demonstrating a promising way to reveal the risk factors of adverse events during cancer treatment.
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