Prognostic value of pretreatment standardized uptake value of F-18-fluorodeoxyglucose PET in patients with gastric cancer: a meta-analysis
Bibliographic record
Abstract
F-18- fluorodeoxyglucose Positron emission tomography (18FDG-PET) has been widely used in clinical practice. However, the prognostic value of the pretreatment standardized uptake value (SUV) for patients with gastric cancer remains controversial. Major databases were systematically searched. The quality of the included studies was assessed using the Newcastle–Ottawa scale; the PET protocols were also evaluated. The pooled hazard ratio (HR) for overall survival (OS) and recurrence-free survival (RFS) were used to estimate the effect size. Data from the included studies were analyzed using Review Manager Software version 5.2. Eight studies with 1080 patients were included. The pooled HR for OS of six studies including 672 patients was 1.72 (95% CI [1.28–2.3], p = 0.0004, I2 = 0%), indicating that patients with high SUVs may have poor prognosis. The pooled HR for RFS was 1.70 (95% CI [1.20–2.39], p = 0.003, I2 = 0%). Subgroup analysis based on the cutoff values determining method indicated that the receiver operating characteristic (ROC) method could better define the cutoff value. Subgroup analysis based on the therapeutic strategies used subsequently indicated the significant prognostic value of SUV. In conclusion, our meta-analysis indicated that pretreatment SUV in primary lesions can be an important prognostic factor for overall survival and recurrence-free survival in patients with gastric cancer. High SUVs may indicate poor prognosis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| 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 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".