Polymorphisms and Clinical Outcome in Recurrent Ovarian Cancer Treated with Cyclophosphamide and Bevacizumab
Bibliographic record
Abstract
PURPOSE: This study was designed to evaluate the associations between angiogenesis gene polymorphisms and clinical outcome in ovarian cancer patients treated with low-dose cyclophosphamide and bevacizumab. EXPERIMENTAL DESIGN: Seventy recurrent/metastatic epithelial ovarian cancer patients were enrolled in a phase II clinical trial. Genomic DNA was available from 53 blood samples. Polymorphisms were analyzed using the PCR-RFLP protocol. A 5' end 33P gammaATP-labeled PCR protocol was used to analyze dinucleotide repeats. RESULTS: Patients genotyped A/A or A/T for the IL-8 T-251A gene polymorphism had a statistically significant lower response rate (19%; 0%) than those homozygous T/T (50%; P = 0.006, Fisher's exact test). Patients carrying a minimum one C allele (C/C; C/T) of the CXCR2 C+785T polymorphism showed a median progression-free survival (PFS) of 7.4 months compared with the PFS of 3.7 months for those homozygous T/T (P = 0.026, log-rank test). Patients with the VEGF C+936T polymorphism C/T genotype had a longer median PFS of 11.8 months, compared with those with the C/C and T/T genotype, which had median PFS of 5.5 months and 3.2 months, respectively (P = 0.061, log-rank test). Patients carrying both AM 3'end alleles < 14 CA repeats had the shortest median PFS of 3.4 months; patients with at least one allele > 14 repeats or both alleles > 14 repeats showed a median PFS of 6.4 months and 7.2 months, respectively (P = 0.008, log-rank test). CONCLUSION: Our data suggest that the IL-8 A-251T polymorphism may be a molecular predictor of response to bevacizumab-based chemotherapy. The CXCR2 C+785T, VEGF C+936T single nucleotide polymorphisms and the AM 3' dinucleotide repeat polymorphisms may be molecular markers for PFS in ovarian cancer patients.
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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 | 0.000 | 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) | 0.001 | 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".