[Breast Cancer With Synchronous Metastases At The Gabriel Toure University Hospital: Frequency And Prognosis].
Bibliographic record
Abstract
Breast cancer is a public health issue worldwide. One of the main causes of death due to this disease is metastasis, which is understudied in our context. Thus, the objectives of this work were to: (1) estimate the frequency of synchronous metastatic breast cancer; (2) determine the overall survival rate; and (3) identify the main factors associated with metastatic breast cancer death in Malian women. PATIENTS AND METHODS: , 2021. We included all pathologically confirmed of breast cancer with synchronous metastases. Descriptive statistics were used to analyze sociodemographic and clinical data. Identification of factors associated with metastatic breast cancer death was performed using univariate and multivariate Cox regression models to produce adjusted hazard ratios (AHR) with their 95% confidence intervals. RESULTS: During the study period, a total of 231 cases of breast cancer were diagnosed in our department; among them, 60 cases were synchronous metastatic breast cancer (26%). The mean age of these cases was 45.3 ±12.1 years old. The most common histological form was non-specific infiltrating carcinoma, 55 cases (91.7%). The main metastatic sites were lung alone, 26 cases (43.3%), liver alone, 12 cases (20.0%) and 16 cases (26.6%) had more than one metastatic sites. The overall 2-year survival was less than 20%. Factor associated with the risk of death was lung metastases; AHR = 4.22 [95% CI: 1.13 - 15.79]. CONCLUSION: Synchronous metastatic breast cancer was very common in our setting and a poor prognosis was observed in patients with lung metastasis.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".