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
Bibliographic record
Abstract
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]
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".