Self-Medication during and after Cancer: A French Nation-Wide Cross-Sectional Study.
Julie MaraudSabrina BedhommeBruno PereiraSophie TrévisMarine JaryDavid BalayssacPublished in: Cancers (2023)
(1) Background: Little data are available in Western countries regarding self-medication practices in the context of cancer. The aim of this study was to describe the prevalence of self-medication practices during (cancer patients) and after cancer (cancer survivors). (2) Methods: This multicenter, cross-sectional, and online study was designed to assess self-medication prevalence. Other objectives were explored, notably the medication types, the perceived risks, and the relation with symptoms and quality of life. (3) Results: Among the 518 patients analyzed, 56.4% declared they practiced self-medication. Dietary supplements and pain medications were used by more than half of the patients. Self-medication was practiced in order to manage the adverse effects of anticancer therapies (63.8%), for which pain was the leading indication (39%), and to improve the efficacy of anticancer therapies (43.8%, cancer patients). Patients believed that self-medication could not lead to drug interactions with anticancer therapies (84.9%, cancer patients), or to adverse effects (84.6%, cancer patients and survivors). Self-medication practices were associated with altered social functioning, pain, insomnia, and financial difficulties. (4) Conclusions: Self-medication was performed by more than half of the responders (ongoing or past cancer) and could be a marker of the undermanagement of cancer and treatment-related adverse effects.
Keyphrases
- healthcare
- adverse drug
- end stage renal disease
- papillary thyroid
- ejection fraction
- chronic kidney disease
- newly diagnosed
- cross sectional
- primary care
- peritoneal dialysis
- squamous cell
- chronic pain
- young adults
- emergency department
- prognostic factors
- depressive symptoms
- patient reported outcomes
- childhood cancer
- squamous cell carcinoma
- risk factors
- mental health
- electronic health record
- clinical trial
- machine learning
- social media
- artificial intelligence
- patient reported