Class III beta tubulin expression and benefit from adjuvant cisplatin/vinorelbine chemotherapy in operable non-small cell lung cancer: Analysis of the National Cancer Institute of Canada Clinical Trials Group (NCIC CTG) study JBR.10
Bibliographic record
Abstract
7051 Background: Biomarkers may be useful to select patients who will benefit from a particular chemotherapy regimen. High class III beta tubulin (bTubIII) expression in advanced NSCLC is known to correlate with reduced response rates and inferior survival with the anti-microtubule agents vinorelbine or paclitaxel. JBR.10 demonstrated a 12% and 15% improvement in 5-year recurrence-free (RFS) and overall survival (OS) respectively with the addition of cisplatin and vinorelbine following resection of stage IB-II NSCLC. We sought to determine the impact of bTubIII on patient outcome and benefit from adjuvant chemotherapy in the JBR.10 trial. Methods: We performed an immunohistochemical assay for bTubIII on primary tumor tissue available from 265 of the 482 patients in JBR.10. A validated, numerical bTubIII score was assigned by two observers based on the intensity and frequency of tumour cell staining. Tumours were classified as bTubIII “low” or “high” based on the median score. We examined the prognostic impact of bTubIII in patients treated with or without chemotherapy, and the survival benefit from chemotherapy in low versus high bTubIII subgroups. Results: High bTubIII expression was associated with poorer RFS (HR = 1.9, p = 0.01) in patients treated with surgery alone, but not in patients treated with adjuvant chemotherapy (HR = 1.1, p = .75). In the low bTubIII subgroup, the improvement in RFS with chemotherapy was non-significant (HR = 0.78, p = 0.4), while the improvement in RFS with chemotherapy was significant in the high bTubIII subgroup (HR = 0.45, p = 0.002). With Cox regression, the interaction between bTubIII status and chemotherapy treatment in predicting RFS did not reach statistical significance (p = 0.15). Results for OS were similar. Conclusions: Chemotherapy appeared to overcome the negative prognostic impact of high bTubIII expression. Greater benefit from adjuvant chemotherapy was seen in patients with high bTubIII expression. This is contrary to what has been seen in the setting of advanced disease; possible reasons for this difference are being explored. No significant financial relationships to disclose.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".