Neoadjuvant chemotherapy among patients treated for nonmetastatic breast cancer in a population with a high HIV prevalence in Johannesburg, South Africa
Bibliographic record
Abstract
Background: Neoadjuvant (primary) chemotherapy (NACT) is the standard of care for locally advanced breast cancer. It also allows for the short-term assessment of chemotherapy response; a pathological complete responses correspond to improved long-term breast cancer outcomes. In sub-Saharan Africa, many patients are diagnosed with large nonresectable tumors. We examined NACT use in breast cancer patients who visited public hospitals in Johannesburg, South Africa. Methods: We assessed demographic characteristics, tumor stage and grade, hormone receptor status, and human immunodeficiency virus (HIV) status of female patients diagnosed with nonmetastatic invasive carcinoma of the breast at Chris Hani Baragwanath Academic Hospital between January 1, 2009, and December 31, 2011. The patients received neoadjuvant, adjuvant, or no chemotherapy. Trastuzumab was unavailable. We developed logistic regression models to analyze the factors associated with NACT receipt in these patients. Results: Of 554 women with nonmetastatic breast cancer, the median age at diagnosis was 52 years (range: 28–88 years). Only 5.8% of patients were diagnosed with stage I disease; 49.3% and 44.9% were diagnosed with stages II and III, respectively. Most patients had hormone-responsive tumors: luminal A, 38.1%; luminal B 1 (human epidermal growth factor receptor 2 [HER2]-negative and high grade), 12.5%, and luminal B 2 (HER2-positive any grade), 11.6%; 11.6% had a HER2-enriched tumor and 20.6% a triple-negative tumor. Eighty (14.4%) patients were HIV-positive. In total, 195 patients (35.2%) received NACT, 264 (47.7%) patients received adjuvant chemotherapy, and 95 patients (17.1%) received no chemotherapy, including 62 (11.2%) patients who received only hormonal therapy. Of patients receiving NACT, 125 (64.1%) were evaluable for clinical response. Eighty (64.0%) patients had a clinically significant response; 19 (15.2%) patients had a stable disease, and 26 (20.8%) patients had a progressive disease. Multivariate analysis showed age <40 years and disease stage to be independently associated with the receipt of NACT. Conclusion: Most women receiving NACT with available response data showed a clinical benefit. Stage III disease at diagnosis and age <40 years were predictors of neoadjuvant versus adjuvant chemotherapy treatment. Keywords: breast cancer, chemotherapy, neoadjuvant, South Africa, HIV, LMICs
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".