Increased circulating vascular endothelial growth factor in acute myeloid leukemia patients: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Vascular endothelial growth factor (VEGF) is one of the angiogenesis regulators, which plays an important role in tumor angiogenesis and tumor progression. Current studies have found that VEGF plays an important role in hematologic diseases including acute myeloid leukemia (AML). However, the circulating levels of VEGF in AML were still controversial among published studies. Methods Three databases including PubMed, EMBASE, and Cochrane Library databases were searched up to February 2020. All articles included in the meta-analysis met our inclusion and exclusion criteria. Studies will be screened and data extracted by two independent investigators. The Newcastle-Ottawa Scale (NOS) and the Risk of Bias In Non-randomized Studies of Interventions (ROBINS-I) tool were applied to evaluate the quality of the included studies. A random-effects model was applied to pool the standardized mean difference (SMD). Heterogeneity test was performed by the Q statistic and quantified using I 2 . All statistical analysis was conducted in Stata 12.0 software. Results Fourteen case-control studies were finally included in this systematic review and meta-analysis. Heterogeneity was high in our included studies ( I 2 = 91.1%, P < 0.001). Sensitivity analysis showed no significant change when any one study was excluded using random-effect methods ( P > 0.05). Egger’s linear regression test showed that no publication bias existed ( P > 0.05). Patients with AML, mainly those newly diagnosed and untreated, have higher VEGF levels (SMD = 0.85, 95% CI 0.28–1.42). Moreover, AML patients in n ≥ 40 group, plasma group, Asia and Africa group, and age ≥ 45 group had higher circulating VEGF levels (all P < 0.05). Conclusions Compared to healthy controls, our meta-analysis shows a significantly higher level of circulating VEGF in AML patients, and it is associated with sample size, sample type, region, and age.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.024 | 0.009 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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; both teacher heads agree on what is shown here.
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".