Affiliations 

  • 1 Harvard Medical School and Harvard Pilgrim Healthcare Institute, 401 Park Drive, Suite 401 East, Boston, MA 02215 United States of America
  • 2 IQVIA, London, England
  • 3 School of Pharmaceutical Sciences, Peking University, Beijing, China
Bull World Health Organ, 2020 Jul 01;98(7):467-474.
PMID: 32742032 DOI: 10.2471/BLT.19.243998

Abstract

OBJECTIVE: To assess sales of anti-cancer medicines in the 2017 World Health Organization's WHO Model list of essential medicines in China, Indonesia, Kazakhstan, Malaysia, Philippines and Thailand from 2007 (2008 for Kazakhstan and Malaysia) to 2017.

METHODS: We extracted sales volume data for 39 anti-cancer medicines from the IQVIA database. We divided the total quantity sold by the reference defined daily dose to estimate the total number of defined daily doses sold, per country per year, for three types of anti-cancer therapies (traditional chemotherapy, targeted therapy and endocrine therapy). We adjusted these data by the number of new cancer cases in each country for each year.

FINDINGS: We observed an increase in sales across all types of anti-cancer therapies in all countries. The largest number of defined daily doses of traditional chemotherapy per new cancer case was sold in Thailand; however, the largest relative increase per new cancer case occurred in Indonesia (9.48-fold). The largest absolute and relative increases in sales of defined daily doses of targeted therapies per new cancer case occurred in Kazakhstan. Malaysia sold the largest number of adjusted defined daily doses of endocrine therapies in 2017, while China and Indonesia more than doubled their adjusted sales volumes between 2007 and 2017.

CONCLUSION: The use of sales data can fill an important knowledge gap in the use of anti-cancer medicines, particularly during periods of insurance coverage expansion. Combined with other data, sales volume data can help to monitor efforts to improve equitable access to essential medicines.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.