JOURNAL ARTICLE

Impact of oncology pharmacy services on the management of chemotherapy-induced nausea and vomiting: A systematic review and meta-analysis.

  • Published In: American Journal of Health-System Pharmacy, 2025, v. 82, n. 3. P. e131 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Shin, Yejin; Shin, Sangyoon; Ryu, Heejeong; Lee, Jooyi; Lee, Eunkyung Euni 3 of 3

Abstract

This article systematically reviews and meta-analyzes the impact of clinical pharmacy services on managing chemotherapy-induced nausea and vomiting (CINV) in cancer patients. The findings indicate that pharmacist-led interventions significantly reduce the incidence of nausea and vomiting, particularly during the delayed phase (2 to 5 days post-chemotherapy), and improve secondary outcomes such as medication adherence, patient satisfaction, quality of life, emergency department visits, hospitalizations, and healthcare costs. The interventions typically include patient counseling, identification and management of medication-related problems, and supportive care tailored to individual needs. Despite heterogeneity among studies and a predominance of quasi-experimental designs, the evidence supports the valuable role of oncology pharmacists in enhancing CINV control and overall treatment experiences. The authors recommend further randomized controlled trials with standardized pharmacist services to strengthen these findings.

Additional Information

  • Source:American Journal of Health-System Pharmacy. 2025/02, Vol. 82, Issue 3, pe131
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2025
  • ISSN:1079-2082
  • DOI:10.1093/ajhp/zxae237
  • Accession Number:182437281
  • Copyright Statement:Copyright of American Journal of Health-System Pharmacy is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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