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Record W2072374359 · doi:10.5430/jst.v4n3p4

P53 mutation compared with Ki67 marker in metastasis of breast cancer in western Iran

2014· article· en· W2072374359 on OpenAlexvenueno aff
Mehrdad Payandeh, Masoud Sadeghi, Adel Fekri, Edris Sadeghi

Bibliographic record

VenueJournal of Solid Tumors · 2014
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBreast cancerMetastasisImmunohistochemistryOncologyInternal medicineP53 expressionCancerDistant metastasisP53 protein

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.278
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2014
Admission routes1
Has abstractyes

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