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P53 protein over-expression but not <i>p53</i> gene mutation is a poor prognostic marker and a predictive marker for survival benefit from adjuvant chemotherapy in non-small cell lung cancer (NSCLC) in the JBR.10 Trial

2007· article· en· W2260261261 on OpenAlexaff
Ming‐Sound Tsao, Sarit Aviel‐Ronen, Keyue Ding, Denise Lau, N. Liu, M. Whitehead, Lesley Seymour, T. Winton, Frances A. Shepherd

Bibliographic record

VenueJournal of Clinical Oncology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsAlberta HealthUniversity of AlbertaHealth Sciences CentreUniversity Health Network
Fundersnot available
KeywordsMedicineImmunohistochemistryOncologyInternal medicineERCC1ChemotherapyCisplatinVinorelbineHazard ratioLung cancerCancer researchGeneDNA repairBiologyNucleotide excision repair

Abstract

fetched live from OpenAlex

7577 Background: JBR.10, a phase III inter-group trial randomized 482 patients with resected stage IB & II NSCLC to receive 4 cycles of adjuvant cisplatin + vinorelbine or observation alone. Chemotherapy patients had an overall survival (OS) benefit (Hazard Ratio [HR] 0.69, p=0.04). P53 has important regulatory roles in cell cycle progression, apoptosis, gene transcription and DNA repair. We evaluated the prognostic and predictive value of p53 in JBR.10. Methods: P53 protein expression was evaluated by immunohistochemistry (IHC) on tissue micro-arrays (282 available blocks). We used the DO7 antibody, and defined ≥15% nuclear staining as the cutoff for over- expression. Mutations in exons 5–9 were determined by denaturing high performance liquid chromatography (446 available samples), followed by sequencing of aberrant PCR products. Results: Successful assays: p53 mutation, 403/446 patients; p53 IHC, 254/282 patients. P53 gene mutations were found in 126/403 (31%) patients. In the observation arm, mutations were not prognostic of poorer survival (HR = 1.18, 95% CI 0.77–1.81; p= 0.45). Adjuvant chemotherapy effect was not significantly different in p53 mutated and wild type patients (interaction p = 0.66), the estimated HR was 0.68 (95% CI 0.46–1, p=0.047) for patients with wild type p53, and 0.79 (95% CI 0.47–1.33, p=0.37) for mutated patients. P53 protein over-expression was found in 133/254 (52%) patients. Patients with over-expression in the observation arm had a higher risk of death than patients with low expression (HR 1.89, 95% CI 1.07–3.34, p=0.03). However, the adjuvant chemotherapy effect was significantly better in p53 over-expressing patients (interaction p= 0.018), with an estimated HR of 0.53 (95% C.I. 0.31–0.90, p=0.03) for p53 over-expressing patients, and 1.40 (95% C.I. 0.78–2.52, p=0.26) for low expressing patients. Conclusions: P53 protein overexpression but not p53 gene mutation is both a significant prognostic marker of poorer survival in the JBR 10 population and a significant predictive marker for the benefit of adjuvant chemotherapy. [Table: see text]

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.361
Teacher spread0.334 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2007
Admission routes1
Has abstractyes

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