Demographic, tumour, and treatment characteristics of female patients with breast cancer in Sri Lanka; results from a hospital-based cancer registry
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".