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Background: Although breast cancer is the most common cancer among Sri Lankan women, there is little published data on patient characteristics and treatment in the local context. We aimed to describe disease characteristics and management in a large contemporary cohort of women with breast cancer at the National Cancer Institute of Sri Lanka (NCISL).Methods: All women with invasive primary breast cancers diagnosed during 2016-2020 were identified from the NCISL breast cancer registry. The NCISL sees approximately 40% of all cancer patients in Sri Lanka. Cancer stage at diagnosis was defined according to the Tumour, Node, and Metastasis (TNM) staging system and the Estrogen (ER) and progesterone (PR) receptor status was determined based on the results of immunohistochemistry tests. Descriptive statistics were used to describe the study cohort and treatment patterns.Results: Over 5100 patients were diagnosed with breast cancer during the study period at the NCISL. The mean age of the women was 56 (SD 12) years. Common co-morbidities were hypertension (n = 1566, 30%) and diabetes mellitus (n = 1196, 23%). Two thirds (66%) of the cancers were early stage (stage I & II) at diagnosis. ER/PR positivity rate was 72% and HER-2 positivity rate was 22%. Two thirds of the women had undergone mastectomy while 68% had undergone axillary clearance. The rate of chemotherapy delivery was 91% for women with node positive disease while 77% of eligible women (i.e., after wide local excision or with > 3 positive lymph nodes) had received adjuvant radiotherapy. Endocrine therapy was initiated in 88% of eligible women with hormone receptor positive disease while rate of trastuzumab use was 59% among women with HER2 positive breast cancer.Conclusions: High percentage of advanced breast cancer at diagnosis and high prevalence of comorbidities are some of the major challenges faced in the management of breast cancer in Sri Lanka. Given that stage at diagnosis is the most important prognostic factor determining survival, greater efforts are needed to promote early diagnosis of breast cancer. Considerable lapses in the concordance between guideline recommendations and the delivery of cancer care warrants closer assessment and intervention. [ABSTRACT FROM AUTHOR]

Background: Prescription medication use, which is common among long-term care facility (LTCF) residents, is routinely used to describe quality of care and predict health outcomes. Data sources that capture medication information, which include surveys, medical charts, administrative health databases, and clinical assessment records, may not collect concordant information, which can result in comparable prevalence and effect size estimates. The purpose of this research was to estimate agreement between two population based electronic data sources for measuring use of several medication classes among LTCF residents: outpatient prescription drug administrative data and the Resident Assessment Instrument Minimum Data Set (RAI-MDS) Version 2.0. Methods: Prescription drug and RAI-MDS data from the province of Saskatchewan, Canada (population 1.1 million) were linked for 2010/11 in this cross-sectional study. Agreement for anti-psychotic, anti-depressant, and anti-anxiety/ hypnotic medication classes was examined using prevalence estimates, Cohen's κ, and positive and negative agreement. Mixed-effects logistic regression models tested resident and facility characteristics associated with disagreement. Results: The cohort was comprised of 8,866 LTCF residents. In the RAI-MDS data, prevalence of anti-psychotics was 35.7%, while for anti-depressants it was 37.9% and for hypnotics it was 27.1%. Prevalence was similar in prescription drug data for anti-psychotics and anti-depressants, but lower for hypnotics (18.0%). Cohen's κ ranged from 0.39 to 0.85 and was highest for the first two medication classes. Diagnosis of a mood disorder and facility affiliation was associated with disagreement for hypnotics. Conclusions: Agreement between prescription drug administrative data and RAI-MDS assessment data was influenced by the type of medication class, as well as selected patient and facility characteristics. Researchers should carefully consider the purpose of their study, whether it is to capture medication that are dispensed or medications that are currently used by residents, when selecting a data source for research on LTCF populations. [ABSTRACT FROM AUTHOR]