METHODS: All 5616 patients, diagnosed with breast cancer in University Malaya Medical Centre from 1999 to 2013 were included. In 945 elderly patients (aged 65 years and above), multivariable logistic regression was performed to identify factors associated with treatment, following adjustment for age, ethnicity, tumor, and other treatment characteristics. The impact of lack of treatment on survival of the elderly was assessed while accounting for comorbidities.
RESULTS: One in five elderly patients had comorbidities. Compared to younger patients, the elderly had more favorable tumor characteristics, and received less loco-regional treatment and chemotherapy. Within stage I-IIIa elderly breast cancer patients, 10 % did not receive any surgery. These patients were older, more likely to be Malays, have comorbidities, and bigger tumors. In elderlies with indications for adjuvant radiotherapy, no irradiation (30 %) was associated with increasing age, comorbidity, and the absence of systemic therapy. Hormone therapy was optimal, but only 35 % of elderly women with ER negative tumors received chemotherapy. Compared to elderly women who received adequate treatment, those not receiving surgery (adjusted hazard ratio: 2.30, 95 %CI: 1.10-4.79), or radiotherapy (adjusted hazard ratio: 1.56, 95 %CI: 1.10-2.19), were associated with higher mortality. Less than 25 % of the survival discrepancy between elderly women receiving loco-regional treatment and no treatment were attributed to excess comorbidities in untreated patients.
CONCLUSION: While the presence of comorbidities significantly influenced loco-regional treatment decisions in the elderly, it was only able to explain the lower survival rates in untreated patients up to a certain extent, suggesting missed opportunities for treatment.
METHOD: A total of 2937 newly diagnosed patients with stage I and stage II breast cancer in University Malaya Medical Centre between Jan 1993 to Dec 2012 were included in the study. Multinomial logistic regression analysis allowing death to compete with CBC as a study outcome was used; patients with unilateral breast cancer who were alive were taken as reference. A stepwise backward regression analysis including age at diagnosis, ethnicity, family history of breast cancer, TNM stage, hormonal receptor status, HER2 status, chemotherapy, radiotherapy, and hormone therapy was conducted.
RESULTS: Fifty women developed CBC, over a median follow-up of 6 years. The 5- and 10-year cumulative risk of contralateral breast cancer was 1.0% (95% CI 0.6-1.4%) and 2.8% (95% CI 2.0-3.6%), respectively. Young age at diagnosis of first cancer, positive family history, and stage I disease were independent predictors of CBC.
DISCUSSION: The current study suggests that the risk of CBC is very low in a Southeast Asian setting. Any recommendations or practice of CRRM should be reviewed with caution and patients must be counseled appropriately.
Methods: A cross-sectional study was conducted on 745 women who presented with breast symptoms in a university breast clinic in Malaysia. Participants were instructed to respond to self-report questionnaires on depression, trait anxiety, and social support while they were waiting for assessment of their suspected BC. The final diagnoses of these patients were traced one month after examining their medical records. Descriptive statistics were performed to examine the socio-demographic and clinical characteristics of all participants. A multiple regression analysis was carried out to determine the association of the abovementioned factors with the diagnosis of BC.
Results: The analysis showed that BC was diagnosed in 109 (14.6%), benign breast disease (BBD) in 550 (73.8%), and healthy breast (HB) in 86 (11.5%) women. The prevalence of depression was 53.2% in women with BC, 53.6% in women with BBD, and 60.5% in women with HB prior to diagnosis. The prevalence of trait anxiety was 33%. Mean scores for trait anxiety were 42.2 ± 9.0 and 41.8 ± 9.1 for the BC group and BBD group, respectively. The level of perceived social support was similar in all three groups.
Conclusion: We found no significant difference in depression, trait anxiety, and social support among women with newly diagnosed BC, BBD, and HB in women with breast symptoms while undergoing diagnostic evaluation. A longitudinal study is essential to establish the association between chronic mental stress and BC.
OBJECTIVE: Our aim was to evaluate the nutritional status of BC survivors at 1 year after diagnosis.
DESIGN: This was a cross-sectional study of 194 participants from the MyBCC study, recruited within 1 year of their diagnosis. Participants completed a 3-day food diary.
PARTICIPANTS: Malaysian women (aged 18 years and older) who were newly diagnosed with primary BC, managed at the University Malaya Medical Center, and able to converse either in Malay, English, or Mandarin were included.
MAIN OUTCOME MEASURES: Dietary intake and prevalence of overweight or obesity among participants 1 year after diagnosis were measured.
STATISTICAL ANALYSES PERFORMED: Student's t test and analysis of variance or its equivalent nonparametric test were used for association in continuous variables.
RESULTS: About 66% (n=129) of participants were overweight or obese and >45% (n=86) had high body fat percentage 1 year after diagnosis. The participants' diets were low in fiber (median=8.7 g/day; interquartile range=7.2 g/day) and calcium (median=458 mg/day; interquartile range=252 mg/day). Ethnicity and educational attainment contributed to the differences in dietary intake among participants. Higher saturated fat and lower fiber intake were observed among Malay participants compared with other ethnic groups.
CONCLUSIONS: Overweight and obesity were highly prevalent among BC survivors and suboptimal dietary intake was observed. Provision of an individualized medical nutrition therapy by a qualified dietitian is crucial as part of comprehensive BC survivorship care.
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: 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 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.
RESULTS: Quality Implementation Framework (QIF) was adopted to develop the breast cancer module as part of the in-house EMR system used at UMMC, called i-Pesakit©. The completion of the i-Pesakit© Breast Cancer Module requires management of clinical data electronically, integration of clinical data from multiple internal clinical departments towards setting up of a research focused patient data governance model. The 14 QIF steps were performed in four main phases involved in this study which are (i) initial considerations regarding host setting, (ii) creating structure for implementation, (iii) ongoing structure once implementation begins, and (iv) improving future applications. The architectural framework of the module incorporates both clinical and research needs that comply to the Personal Data Protection Act.
CONCLUSION: The completion of the UMMC i-Pesakit© Breast Cancer Module required populating EMR including management of clinical data access, establishing information technology and research focused governance model and integrating clinical data from multiple internal clinical departments. This multidisciplinary collaboration has enhanced the quality of data capture in clinical service, benefited hospital data monitoring, quality assurance, audit reporting and research data management, as well as a framework for implementing a responsive EMR for a clinical and research organization in a typical middle-income country setting. Future applications include establishing integration with external organization such as the National Registration Department for mortality data, reporting of institutional data for national cancer registry as well as data mining for clinical research. We believe that integration of multiple clinical visit data sources provides a more comprehensive, accurate and real-time update of clinical data to be used for epidemiological studies and audits.
METHOD: A prospective test-retest design was employed on Malaysian women with early breast cancer (N = 105). Data were analyzed using SPSS version 24.
RESULTS: The results showed overall Cronbach alpha values were .92 and .93 for test-retest, respectively. Intraclass correlation coefficient (ICC) values ranged between .62 and .75. This study accepted three factors and two factors for test-retest, respectively. Individual factors showed Cronbach alpha average ranged from .71 to .91.
CONCLUSION: The Malay version RS-14 tool was found to be statistically valid, reliable, and reproducible. It was able to measure resilience level in those women under study.