Genetic variant predicts bevacizumab-induced hypertension in ECOG-5103 and ECOG-2100
Bibliographic record
Abstract
BACKGROUND: Bevacizumab has broad anti-tumour activity, but substantial risk of hypertension. No reliable markers are available for predicting bevacizumab-induced hypertension. METHODS: A genome-wide association study (GWAS) was performed in the phase III bevacizumab-based adjuvant breast cancer trial, ECOG-5103, to evaluate for an association between genotypes and hypertension. GWAS was conducted in those who had experienced systolic blood pressure (SBP) >160 mm Hg during therapy using binary analysis and a cumulative dose model for the total exposure of bevacizumab. Common toxicity criteria (CTC) grade 3-5 hypertension was also assessed. Candidate SNP validation was performed in the randomised phase III trial, ECOG-2100. RESULTS: When using the phenotype of SBP>160 mm Hg, the most significant association in SV2C (rs6453204) approached and met genome-wide significance in the binary model (P=6.0 × 10(-8); OR=3.3) and in the cumulative dose model (P=4.7 × 10(-8); HR=2.2), respectively. Similar associations with rs6453204 were seen for CTC grade 3-5 hypertension but did not meet genome-wide significance. Validation study from ECOG-2100 demonstrated a statistically significant association between this SNP and grade 3/4 hypertension using the binary model (P-value=0.037; OR=2.4). CONCLUSIONS: A genetic variant in SV2C predicted clinically relevant bevacizumab-induced hypertension in two independent, randomised phase III trials.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".