METHODS: Cross sectional analyses of N = 345 adult cancer survivors (5 years post cancer diagnosis) attending follow-ups at University Malaya Medical Centre, Malaysia. Face-to face-interviews were conducted using the 30-item Cancer Health Literacy Test and the Patient-Practitioner Orientation Scale to determine preference for patient-centered care.
RESULTS: Cancer survivors' preference for patient-centered care was associated with a higher cancer health literacy score, higher educational level, being employed, breast cancer diagnosis, and not desiring psychological support [F (14, 327) = 11.25, p
METHODS: A total of 160 breast cancer survivors from the University of Malaya Medical Centre (UMMC) participated in this cross-sectional study. Their QoL was evaluated with the Malay version of the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire Core 30 (QLQ-C30) version 3.0. Cognitive functioning and psychological distress were evaluated using the Malay version of the Montreal Cognitive Assessment (MoCA-BM) and Hospital Anxiety and Depression Scale (HADS), respectively. Data analysis was performed with Pearson's correlation and multiple regression analyses.
RESULTS: At 1- to 3-year post-chemotherapy, the mean EORTC QLQ-C30 global health status of the breast cancer survivors was relatively low (60.5 over 100, SD = 10.88). One-third (31.9%) of them demonstrated cognitive impairment, and another 3.2% showed moderate to severe anxiety levels. The significant predictors for global health status and functioning included age, psychological distresses, cognitive performance, fatigue, appetite loss, insomnia, pain, and constipation.
CONCLUSION: Our breast cancer survivors demonstrated poor global health status. Health care providers and policymakers must strive to provide holistic intervention strategies to improve the multiple dimensions of QoL and the cognitive and psychological functioning of this vulnerable population.
METHODS: A large hospital-based breast cancer dataset retrieved from the University Malaya Medical Centre, Kuala Lumpur, Malaysia (n = 8066) with diagnosis information between 1993 and 2016 was used in this study. The dataset contained 23 predictor variables and one dependent variable, which referred to the survival status of the patients (alive or dead). In determining the significant prognostic factors of breast cancer survival rate, prediction models were built using decision tree, random forest, neural networks, extreme boost, logistic regression, and support vector machine. Next, the dataset was clustered based on the receptor status of breast cancer patients identified via immunohistochemistry to perform advanced modelling using random forest. Subsequently, the important variables were ranked via variable selection methods in random forest. Finally, decision trees were built and validation was performed using survival analysis.
RESULTS: In terms of both model accuracy and calibration measure, all algorithms produced close outcomes, with the lowest obtained from decision tree (accuracy = 79.8%) and the highest from random forest (accuracy = 82.7%). The important variables identified in this study were cancer stage classification, tumour size, number of total axillary lymph nodes removed, number of positive lymph nodes, types of primary treatment, and methods of diagnosis.
CONCLUSION: Interestingly the various machine learning algorithms used in this study yielded close accuracy hence these methods could be used as alternative predictive tools in the breast cancer survival studies, particularly in the Asian region. The important prognostic factors influencing survival rate of breast cancer identified in this study, which were validated by survival curves, are useful and could be translated into decision support tools in the medical domain.
METHODS: A cross-sectional study was performed at two chemotherapy providers. Patients were questioned about use of three categories of CAM, mind-body practices (MBPs), natural products (NPs) and traditional medicine (TM). PFH was also examined separately from CAM to better characterise the patterns of CAM and PFH used during chemotherapy.
RESULTS: A total of 546 eligible patients participated in the study; 70.7% (n = 386) reported using some form of CAM, and 29.3% (n = 160) were non-CAM users. When PFH was excluded as a CAM, fewer patients reported the use of CAM (66.1%; n = 361). The total number of patients who used MBPs decreased from 342 to 183. The most common CAM use category was NPs (82.8%), followed by MBPs (50.7%), and TM (35.7%). CAM users were more likely to have a tertiary education (OR 2.11, 95% CI 1.15-3.89 vs. primary/lower), have household incomes > RM 3,000 (≈944 USD) per month (OR 2.32, 95% CI 1.40-3.84 vs. ≤RM 3,000 (≈944 USD)), and have advanced cancer (OR 1.75, 95% CI 1.18-2.59 vs. early stage cancer), compared with non-CAM users. The CAM users were less likely to have their chemotherapy on schedule (OR 0.24, 95% CI 0.10-0.58 vs. chemotherapy postponed) than non-CAM users. Most MBPs were perceived to be more helpful by their users, compared with the users of NPs and TM.
CONCLUSION: CAM use was prevalent among breast cancer patients. Excluding PFH from the definition of CAM reduced the prevalence of overall CAM use. Overall, CAM use was associated with higher education levels and household incomes, advanced cancer and lower chemotherapy schedule compliance. Many patients perceived MBP to be beneficial for improving overall well-being during chemotherapy. These findings, while preliminary, clearly indicate the differences in CAM use when PFH is included in, and excluded from, the definition of CAM.
METHODS: We conducted a cross-sectional study of 2,377 Malaysian women aged 40-74 years. Physical activity information was obtained at screening mammogram and mammographic density was measured from mammograms by the area-based STRATUS method (n = 1,522) and the volumetric Volpara™ (n = 1,200) method. Linear regression analyses were performed to evaluate the association between physical activity and mammographic density, adjusting for potential confounders.
RESULTS: We observed that recent physical activity was associated with area-based mammographic density measures among postmenopausal women, but not premenopausal women. In the fully adjusted model, postmenopausal women with the highest level of recent physical activity had 8.0 cm2 [95% confidence interval: 1.3, 14.3 cm2] lower non-dense area and 3.1% [0.1, 6.3%] higher area-based percent density, compared to women with the lowest level of recent physical activity. Physical activity was not associated to volumetric mammographic density.
CONCLUSIONS: Our findings suggest that the beneficial effects of physical activity on breast cancer risk may not be measurable through mammographic density. Future research is needed to identify appropriate biomarkers to assess the effect of physical activity on breast cancer risk.
METHODS: This study is from the MyBCC cohort study. Two hundred and twenty one female breast cancer patients were included into the study. They were assessed at the time of diagnosis, 6 months and 12 month using Hospital Anxiety and Depression Scale (HADS) and distress thermometer. The information on age, ethnicity, treatment types and staging of cancer were collected.
RESULTS: 50.2%, 51.6% and 40.3% of patients had perceived high level of distress at baseline, 6 months and 1 year after diagnosis. Those with high perceived level of distress had significant higher anxiety scores even after adjusted for the underlying depressive scores (Adjusted OR at baseline = 1.28, 95% CI = 1.13-1.44; adjusted OR at 6 months = 1.27, 95% CI = 1.11-1.45; adjusted OR at 12 months = 1.51, 95% CI = 1.29-1.76). There were no significant differences in the depressive scores between the subjects with either low or high distress level. There was reduction in perceived level of distress, anxiety and depression scores at 12 months after the diagnosis. The decrease of distress was positively correlated with the reduction of anxiety scores but not the changes of depressive scores (r' = 0.25).
CONCLUSION: Anxiety is a more significant psychological state that contributed to the feeling of distress in breast cancer as compared with depression. Levels of anxiety at diagnosis in this study would justify screening for anxiety, early identification and therapy for maintaining the psychological well-being of breast cancer patients. Further studies will be needed to measure the effectiveness of therapeutic interventions.
METHODS: Breast cancer patients were recruited from three Malaysian hospitals between June and November 2017. We compared the proportion of patients who rated PROs as very important (scored 7-9 on a 9-point Likert scale) between Malaysian patients and data collected from patients in HICs via the ICHOM questionnaire development process, using logistic regression. A two-step cluster analysis explored differences in PROs among Malaysian patients.
RESULTS: The most important PROs for both cohorts were survival, overall well-being, and physical functioning. Compared with HIC patients (n = 1177), Malaysian patients (n = 969) were less likely to rate emotional (78% vs 90%), cognitive (76% vs 84%), social (72% vs 81%), and sexual (30% vs 56%) functioning as very important outcomes (P
OBJECTIVE: To characterize tumors associated with BC susceptibility genes in large-scale population- or hospital-based studies.
DESIGN, SETTING, AND PARTICIPANTS: The multicenter, international case-control analysis of the BRIDGES study included 42 680 patients and 46 387 control participants, comprising women aged 18 to 79 years who were sampled independently of family history from 38 studies. Studies were conducted between 1991 and 2016. Sequencing and analysis took place between 2016 and 2021.
EXPOSURES: Protein-truncating variants and likely pathogenic missense variants in ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53.
MAIN OUTCOMES AND MEASURES: The intrinsic-like BC subtypes as defined by estrogen receptor, progesterone receptor, and ERBB2 (formerly known as HER2) status, and tumor grade; morphology; size; stage; lymph node involvement; subtype-specific odds ratios (ORs) for carrying protein-truncating variants and pathogenic missense variants in the 9 BC susceptibility genes.
RESULTS: The mean (SD) ages at interview (control participants) and diagnosis (cases) were 55.1 (11.9) and 55.8 (10.6) years, respectively; all participants were of European or East Asian ethnicity. There was substantial heterogeneity in the distribution of intrinsic subtypes by gene. RAD51C, RAD51D, and BARD1 variants were associated mainly with triple-negative disease (OR, 6.19 [95% CI, 3.17-12.12]; OR, 6.19 [95% CI, 2.99-12.79]; and OR, 10.05 [95% CI, 5.27-19.19], respectively). CHEK2 variants were associated with all subtypes (with ORs ranging from 2.21-3.17) except for triple-negative disease. For ATM variants, the association was strongest for the hormone receptor (HR)+ERBB2- high-grade subtype (OR, 4.99; 95% CI, 3.68-6.76). BRCA1 was associated with increased risk of all subtypes, but the ORs varied widely, being highest for triple-negative disease (OR, 55.32; 95% CI, 40.51-75.55). BRCA2 and PALB2 variants were also associated with triple-negative disease. TP53 variants were most strongly associated with HR+ERBB2+ and HR-ERBB2+ subtypes. Tumors occurring in pathogenic variant carriers were of higher grade. For most genes and subtypes, a decline in ORs was observed with increasing age. Together, the 9 genes were associated with 27.3% of all triple-negative tumors in women 40 years or younger.
CONCLUSIONS AND RELEVANCE: The results of this case-control study suggest that variants in the 9 BC risk genes differ substantially in their associated pathology but are generally associated with triple-negative and/or high-grade disease. Knowing the age and tumor subtype distributions associated with individual BC genes can potentially aid guidelines for gene panel testing, risk prediction, and variant classification and guide targeted screening strategies.