Association between continuous decrease of plasma VEGF-A levels and the efficacy of chemotherapy in combination with anti-programmed cell death 1 antibody in non-small cell lung cancer patients
Bibliographic record
Abstract
OBJECTIVES: Vascular endothelial growth factor-A (VEGF-A) plays important roles in tumor immune suppression and thus correlates with the efficacy of anti-programmed cell death-1/ligand 1 (anti-PD-1/PD-L1) antibodies. We aimed to determine the association between change in plasma VEGF-A levels and the efficacy of chemotherapy combined with anti-PD-1/PD-L1 antibodies (chemo-PD1) in non-small cell lung cancer (NSCLC) patients. METHODS: We included NSCLC patients treated with chemo-PD1. Plasma VEGF-A levels were measured at baseline (Pre) and days 7 (D7) and 14 (D14) after the initiation of chemo-PD1. Continuous VEGF-A decrease was determined by comparing Pre with the median value of maximum change rate of posttreatment VEGF-A as cutoff. Patients whose change rates of VEGF-A at both D7 and D14 were consistently lower than the cutoff value were classified into the VEGF-A decrease group, whereas those whose VEGF-A at D7 or D14 were higher than the cutoff level were classified into the VEGF-A no-decrease group. The primary outcome was progression-free survival (PFS). RESULTS: A total of 32 patients were evaluated. The median Pre VEGF-A levels was 49 (range, 13-257). The median change rate of VEGF-A at D7 and D14 was -25.6% (range, -77.5-376.9) and -42.3% (range, -100-138.5) respectively. The cutoff value of posttreatment VEGF-A change rate was -9.3%. The PFS was significantly longer in the VEGF-A decrease group than that in the VEGF-A no-decrease group (median, not reached vs 2.4 months; p = 0.017). CONCLUSIONS: Continuous decrease of plasma VEGF-A levels during treatment may be associated with the efficacy of chemo-PD1.
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".