Hypertension as a predictor of outcome and treatment response to cetuximab: A retrospective analysis of NCIC CTG CO.17.
Bibliographic record
Abstract
256 Background: Adrenergic receptor stimulation is involved in development of hypertension (HTN), and is implicated in progression and dissemination of metastases in tumour types such as colon cancer (CRC). Adrenergic antagonists, such as beta-blockers (BB), demonstrate inhibition of invasion and migration in CRC cell lines and have been associated with decreased mortality in advanced CRC. We examined the association of baseline HTN (BHTN) and use of BB on overall (OS) or progression-free survival (PFS) of pts with pre-treated, chemotherapy refractory, metastatic CRC (mCRC). We also examined BHTN and BB use as predictors of Cetuximab (CET) efficacy. Methods: Using data from NCIC CO.17 (CET vs. BSC), we coded BHTN and use of anti-HTN meds (Rx), including BB, for 572 pts. Chi-square test assessed association between these variables and baseline characteristics. Univariate and multivariate analyses of OS and PFS by BHTN diagnosis and BB use were performed using Cox regression models. Results: Pts with BHTN (149/572) and those using BB (60/572) were older, had diminished performance status, and higher creatinine levels. BHTN, BB use and anti-HTN Rx were not prognostic for OS and PFS, though a trend was noted between BB use and improved PFS (HR 1.38 [0.97- 1.96], p= 0.077). BHTN and BB use were not significant predictors of CET benefit. However, pts with BHTN tended to have a stronger treatment effect in PFS from CET (interaction p = 0.074). Conclusions: In chemo-refractory mCRC, BHTN and BB use are not significant prognostic factors. BHTN and BB use are also not predictive of CET benefit, though pts with baseline HTN may benefit from a stronger treatment effect with CET. Patients with chemo-refractory mCRC may be biologically selected and the impact of BB use in earlier lines may therefore still warrant investigation. [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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".