Complementary and alternative medicine (CAM) is widely used among the breast cancer patients in Malaysia. Delays in presentation, diagnosis and treatment have been shown to impact the disease prognosis. There is considerable use of CAM amongst breast cancer patients. CAM use has been cited as a cause of delay in diagnosis and treatments in qualitative studies, however there had not been any confirmatory study that confirms its impact on delays. The purpose of this study was to evaluate whether the use of CAM among newly diagnosed breast cancer patients was associated with delays in presentation, diagnosis or treatment of breast cancer. This multi-centre cross-sectional study evaluating the time points of the individual breast cancer patients' journey from first visit, resolution of diagnosis and treatments was conducted in six public hospitals in Malaysia. All newly diagnosed breast cancer patients from 1st January to 31st December 2012 were recruited. Data were collected through medical records review and patient interview by using a structured questionnaire. Complementary and alternative medicine (CAM) was defined as the use of any methods and products not included in conventional allopathic medicine before commencement of treatments. Presentation delay was defined as time taken from symptom discovery to first presentation of more than 3 months. The time points were categorised to diagnosis delay was defined as time taken from first presentation to diagnosis of more than 1 month and treatment delay was defined as time taken from diagnosis to initial treatment of more than 1 month. Multiple logistic regression was used for analysis. A total number of 340 patients participated in this study. The prevalence of CAM use was 46.5% (n = 158). Malay ethnicity (OR 3.32; 95% CI: 1.85, 5.97) and not interpreting symptom as cancerous (OR 1.79; 95% CI: 1.10, 2.92) were significantly associated with CAM use. The use of CAM was associated with delays in presentation (OR 1.65; 95% CI: 1.05, 2.59), diagnosis (OR 2.42; 95% CI: 1.56, 3.77) and treatment of breast cancer (OR 1.74; 95% CI: 1.11, 2.72) on univariate analyses. However, after adjusting with other covariates, CAM use was associated with delays in presentation (OR 1.71; 95% CI: 1.05, 2.78) and diagnosis (OR 2.58; 95% CI: 1.59, 4.17) but not for treatment of breast cancer (OR 1.58; 95% CI: 0.98, 2.55). The prevalence of CAM use among the breast cancer patients was high. Women of Malay ethnicity and not interpreting symptom as cancerous were significantly associated with CAM use. The use of CAM is significantly associated with delay in presentation and resolution of diagnosis. This study suggests further evaluation of access to breast cancer care is needed as poor access may cause the use of CAM. However, since public hospitals in Malaysia are heavily subsidized and readily available to the population, CAM use may impact delays in presentation and diagnosis.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5407802 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0176394 | PLOS |
Pharm Dev Technol
January 2025
Department of Pharmacy, School of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian 116029, China.
In this paper, the pH-sensitive targeting functional material NGR-poly(2-ethyl-2-oxazoline)-cholesteryl methyl carbonate (NGR-PEtOz-CHMC, NPC) modified quercetin (QUE) liposomes (NPC-QUE-L) was constructed. The structure of NPC was confirmed by infrared spectroscopy (IR) and nuclear magnetic resonance hydrogen spectrum (H-NMR). Pharmacokinetic results showed that the accumulation of QUE in plasma of the NPC-QUE-L group was 1.
View Article and Find Full Text PDFJ Med Econ
January 2025
UNESCO-TWAS, The World Academy of Sciences, Trieste, Italy.
Aim: Dynamic cancer control is a current health system priority, yet methods for achieving it are lacking. This study aims to review the application of system dynamics modeling (SDM) on cancer control and evaluate the research quality.
Methods: Articles were searched in PubMed, Web of Science, and Scopus from the inception of the study to November 15th, 2023.
Int J Surg
January 2025
Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China.
Detection of biomarkers of breast cancer incurs additional costs and tissue burden. We propose a deep learning-based algorithm (BBMIL) to predict classical biomarkers, immunotherapy-associated gene signatures, and prognosis-associated subtypes directly from hematoxylin and eosin stained histopathology images. BBMIL showed the best performance among comparative algorithms on the prediction of classical biomarkers, immunotherapy related gene signatures, and subtypes.
View Article and Find Full Text PDFInt J Gen Med
December 2024
Department of Thyroid and Breast Surgery, Quzhou People's Hospital, Quzhou, 324000, People's Republic of China.
Objective: This study aims to demonstrate the impact of sarcopenia on the prognosis of early breast cancer and its role in early multimodal intervention.
Methods: The clinical data of patients (n=285) subjected to chemotherapy for early-stage breast cancer diagnosed pathologically between January 1, 2016, and December 31, 2020, in our hospital were retrospectively analyzed. Accordingly, the recruited subjects were divided into sarcopenia (n=85) and non-sarcopenia (n=200) groups according to CT diagnosis correlating with single-factor and multifactorial logistic regression analyses.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!