Results of multivariable analysis.

Background

Complementary and alternative medicine (CAM) is a commonly used approach among cancer patients, with a reported prevalence of 14.8 to 73.1% depending on multiple factors. Even though a typical patient-reported reason for using CAM is symptom control, no conclusive evidence could be established for specific symptoms being a predictor for CAM use. Symptom clusters are a novel approach for assessing a multidimensional symptom burden, reflecting the impact of diseases on the patient’s quality of life and considering the tendency of symptoms to occur in groups.

Material and methods

A single-center cross-sectional study on cancer patients during oncological or palliative care was conducted to identify socio-demographical and clinical characteristics, including symptom clusters of CAM users and non-users. Symptom clusters were defined using latent profile analysis, and multivariable analyses were performed to assess significant factors influencing CAM use.

Results

Of 171 cancer patients in this study, 63.7% used CAM alongside oncological treatment or palliative care. The most common CAM therapies were biological and physical therapies, including homeopathy (30.3%), supplements (27.4%), herbs (26.6%), massage (24.8%), and acupuncture (22.0%). Four distinct symptom clusters were identified, of which the cluster drowsiness-depression-anxiety was associated with a 3.83-fold increased chance of using CAM compared to low-symptomatic cancer patients. Multivariate analysis did not show any additional significant predictors of socio-demographical factors.

Conclusion

Using the concept of symptom clusters revealed a significant predictor for CAM use, suggesting to be a more conclusive method for assessing symptom burden in cancer patients. In addition, understanding why and how cancer patients turn to CAM can enhance the quality of multidisciplinary communication about its use.