MATERIALS AND METHODS: This retrospective review concerned data for patients diagnosed with colorectal cancer in the years 1995 to 2011 collected from the Wilayah Persekutuan Health Office, taken from the cancer notification form (NCR-2), and patient medical records from the Surgical Department, Universiti Kebangsaan Malaysia Medical Centre (UKMMC). A total of 146 cases were analyzed. All the data collected were analysed using ArcGIS version 10.0 and SPSS version 19.0.
RESULTS: Patients aged 60 to 69 years accounted for the highest proportion of cases (34.2%) and males slightly predominated 76 (52.1%), Chinese had the highest number of registered cases at 108 (74.0%) and staging revealed most cases in the 3rd and 4th stages. Kernel density analysis showed more cases are concentrated up in the northern area of Petaling and Kuala Lumpur subdistricts. Spatial global pattern analysis by average nearest neighbour resulted in nearest neighbour ratio of 0.75, with Z-score of -5.59, p value of <0.01 and the z-score of -5.59. Spatial autocorrelation (Moran's I) showed clustering significant with p<0.01, Z score 3.14 and Moran's Index of 0.007. When mapping clusters with hotspot analysis (Getis-Ord Gi), hot and cold spots were identified. Hot spot areas fell on the northeast side of KL.
CONCLUSIONS: This study demonstrated significant spatial patterns of cancer incidence in KL. Knowledge about these spatial patterns can provide useful information to policymakers in the planning of screening of CRC in the targeted population and improvement of healthcare facilities to provide better treatment for CRC patients.
MATERIALS AND METHODS: A cross-sectional study was conducted among breast cancer patients at University Kebangsaan Malaysia Medical Center (UKMMC), Kuala Lumpur. A total of 205 patients who were diagnosed between 2007 until 2010 were interviewed using the questionnaires of Hospital Anxiety and Depression (HADS). The associated factors investigated concerned socio-demographics, socio economic background and the cancer status. Descriptive analysis, chi-squared tests and logistic regression were used for the statistical test analysis.
RESULTS: The prevalence of anxiety was 31.7% (n=65 ) and of depression was 22.0% (n=45) among the breast cancer patients. Age group (p= 0.032), monthly income (p=0.015) and number of visits per month (p=0.007) were significantly associated with anxiety. For depression, marital status (p=0.012), accompanying person (p=0.041), financial support (p-0.007) and felt burden (p=0.038) were significantly associated. In binary logistic regression, those in the younger age group were low monthly income were 2 times more likely to be associated with anxiety. Having less financial support and being single were 3 and 4 times more likely to be associated with depression.
CONCLUSIONS: In management of breast cancer patients, more care or support should be given to the young and low socio economic status as they are at high risk of anxiety and depression.
METHODS: This study consisted of 3 steps; the formulation of ASMaQ draft, content validation and construct validity. A total of 110 questions were drafted with 5-point Likert scale answers. From the list, 31 were selected and subsequently tested on 158 participants. The results were analysed and validated using exploratory factor analysis on SPSS. Components were extracted and questions with low factor loading were removed. The internal consistency was then measured with Cronbach's alpha.
RESULTS: Following analysis, 3 components were extracted and named as general stroke knowledge, hyperacute stroke care and advanced stroke management. Two items were deleted leaving 29 out of 31 questions for the final validated ASMaQ. Internal consistency showed high reliability with Cronbach's alpha of 0.82. Our respondents scored a total cumulative mean of 113.62 marks or 66.6%. A sub analysis by occupation showed that medical assistants scored the lowest in the group with a score of 57% whilst specialists including neurologists scored the highest at 79.4%.
CONCLUSION: The ASMaQ is a newly developed and validated questionnaire consisting of 29 questions testing the respondents' acute stroke management knowledge.