P53 mutation compared with Ki67 marker in metastasis of breast cancer in western Iran
Bibliographic record
Abstract
Objective: To investigate and compare the prognostic value of P53 and Ki67 markers with age and metastasis and survival in patients with breast cancer in Kermanshah, western Iran. Methods: In our study on 116 patients with breast cancer that all of them were women and kind of pathology was invasive ductal carcinoma and patients had Her2 positive. The expression of ki67 marker and p53 genes were determined by immunohistochemistry. Statistical analysis was performed with SPSS version IBM 19 and Disease free survival was calculated using the Kaplan-Meier method and log-rank test. Patients were followed up to 5 years. Results: The age mean of patients was 46.5±10.75.Of 116 patients, 23 patients (19.8%) had breast cancer with metastasis and 93(80.2%) without metastasis. expression of P53 (50%) in 58 patients was positive and 58(50%) was negative. there is a statistically significant relationship between the p53 and metastasis ( P <0.05), but no for Ki67. The over expression of p53 protein and Ki67 had no significant relationship with survival rate ( P >0.05). Conclusions: The results showed that the Ki67 marker and P53 protein are important factors in the breast cancer patients with emphasis on therapeutic agents. Normal 0 false false false EN-US X-NONE AR-SA
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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 | 0.000 |
| 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) | 0.001 | 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".