Use of complementary traditional phytotherapy to manage cancer in Morocco: A decade-long review of ethnopharmacological studies

• Published in: Journal of herbal medicine 2021-10, Vol.29, p.100494, Article 100494
• Main Authors: Aboufaras, Mohamed, Selmaoui, Karima, Ouzennou, Nadia
• Format: Article
• Language: English
• Subjects: Cancer; Complementary and alternative medicine; Herbal medicine; Medicinal plants; Morocco
• ISSN: 2210-8033
• DOI: 10.1016/j.hermed.2021.100494

•First review of the literature summarizing data from the studies on the prevalence of traditional herbal medicine use by Moroccan cancer patients.•31.16% of Moroccan cancer patients traditionally use medicinal plants.•Almost 100 medicinal plants are used by Moroccan cancer patients.•The most widely used and cited by studies are: Aristolochia longa L. Nigella Sativa L. and Trigonella foenum-graecum L.•The profile of users is destitute women aged 40–60 years. To synthesize data on prevalence of herbal medicine use by this group, the determinants and predictors of use, and its results as well as to list the medicinal plants used. A systematic review was carried out on the three indexed databases Scopus, Web of sciences and Pubmed, in addition to the Google Scholar database. The works included were observational studies of medicinal plants use prevalence performed within Moroccan cancer patients. The prevalence of medicinal plant use ranged from 11 % to 39 % between 2011 and 2019 with an average of 31.16 %. The user's characteristics were female, low income and aged between 41 and 60 years. The quantity of plants used overall was 94. The most widely used and cited studies were: Aristolochia longa L. (Aristolochia), Nigella Sativa L. (Black seed) and Trigonella foenum-graecum L. (Fenugreek). This research includes data on medicinal plants used by cancer patients followed and treated at the level of Moroccan oncology centers where Education and information guides on the most widely used herbal medicines are needed. Research in this field should adopt a reliable methodology based on theoretical models to standardize the analysis.