[Inflammatory Breast Cancers: Epidemiological Aspects At The Gabriel Touré University Hospital In Bamako, Mali].
Bibliographic record
Abstract
INTRODUCTION: Inflammatory breast cancer (IBC) is very rare worldwide. The objectives of the present study were to determine the frequency, to describe the socio-demographic and clinical characteristics according to the type of CIS (primary and secondary), and to establish the prognosis. METHOD: We conducted a retrospective cohort study in the Gynecology-Obstetrics unit of CHU Gabriel Touré (2015 - 2021). Data were analyzed using descriptive statistics and the Kaplan Meier method was used to produce survival curves. RESULTS: We identified 100 cases of IBC among 588 breast cancer cases including 23 cases of primary IBC (3.59%) and 77 cases of secondary IBC (13.1%). The two types of IBC appeared in a relatively younger and peaked between 35 and 40 years old. Contrary to primary IBC, secondary IBC exhibited a second peak between 55 and 60 years old (Wilcoxon rank, test p > 0.05). The time between symptom onset to disease progression was significantly shorter in primary IBC cases versus secondary one (p < 0.001). Overall survival and specific survival according to the type of IBC were less than 40% after 60 months of followed up. CONCLUSION: The incidence of IBC was high in our setting but dominated by secondary IBC. Whatever the type of IBC, the prognosis was poor.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".