Hypertension (HTN) in National Cancer Institute of Canada Clinical Trials Group study BR.24: A randomized, double-blind phase II trial of carboplatin (C) and paclitaxel (P) with either daily oral cediranib (CED), an inhibitor of vascular endothelial growth factor receptors, or placebo, in patients with advanced non-small cell lung cancer
Bibliographic record
Abstract
3527 Background: CED 30 mg/d with C+P increased response rate (RR: 38 vs 16% p < 0.0001) and median progression free survival (PFS: 5.6 vs 5 m, hazard ratio [HR] 0.77) over C+P alone. HTN is a known effect of angiogenesis inhibitors (AI). For BR.24, we describe the incidence of HTN, effects on drug delivery, predictors of its development/worsening, and assess the predictive effect of HTN on efficacy. Methods: Pts received C+P plus either placebo (n =146) or CED (n = 148). HTN as an adverse event (HTN AE: defined as either new onset HTN, or worsening grade HTN in a previously hypertensive pt), was managed with a protocol-defined algorithm. Exploratory analyses characterized the relationship between HTN AE and baseline characteristics and treatment arm. Kaplan Meier curves summarized time to event outcomes and Cox regression models with time dependent covariates correlated HTN AE to outcomes. Results: Rate of pts with a history of HTN were similar: CED 26 %, placebo 33 %. CED pts had significantly higher HTN AE (any: 38 vs 12%, p < 0.0001; grade 3 or 4: 19 vs 2 %). With the treatment algorithm, HTN AE had minimal impact on drug delivery (1 pt interrupted C+P, 11 pts [3.7%] reduced /discontinued CED / placebo). Headache was the only other AE that correlated with HTN AE. Predictors of HTN AE included: CED arm (p < 0.0001), good ECOG (p = 0.02), female (p = 0.006), history of HTN (p = 0.06). CED pts with HTN AE had significantly higher RR (51.8 vs 32.6%, p = 0.025) and PFS (8.5 vs 5.1 m; HR 0.45, 95% CI 0.29 to 0.72, p = 0.0007); similar but not significant findings were observed with placebo (RR 35.3 vs 17.2%, p= 0.098; PFS 5.6 vs 4.9 m; HR 0.84, 95 % CI 0.45–1.54); the interaction term by treatment arm was not significant. Conclusions: CED pts had greater HTN AE, but this did not impact drug delivery. Certain baseline characteristics predicted HTN AE in all pts. Unexpectedly, development of on-study HTN predicted improved outcome in all pts, although to a greater extent for those on CED. Additional evaluation of the role of HTN AE as a predictor of efficacy of both AI and cytotoxics is warranted. [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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".