Systematic review of the diagnostic accuracy of 18F-fluorodeoxyglucose positron emission tomography in melanoma patients
Bibliographic record
Abstract
BACKGROUND. Positron emission tomography (PET) with 18F-fluorodeoxyglucose (FDG) is a rapidly developing new imaging technique in the diagnosis and staging of melanoma. The objective of the current study was to determine the diagnostic accuracy of FDG-PET in patients with melanoma. METHODS. A systematic review and meta-analysis of clinical studies regarding FDG-PET and cutaneous melanoma was conducted. Studies were identified by a comprehensive search of the MEDLINE, EMBASE, and Current Contents databases, without any language restrictions. Eleven studies were selected. The methodologic quality of these studies was assessed independently by two reviewers. Levels of evidence and grades of recommendation were determined for each study. Six studies could be included in the statistical pooling. Sources of heterogeneity were studied by meta-regression of the diagnostic odds ratio (DOR). A summary receiver operating characteristic curve was calculated. RESULTS. The pooled sensitivity and specificity of FDG-PET in the detection of melanoma metastases were 0.79 (95% confidence interval [95% CI], 0.66-0.93) and 0.86 (95% CI, 0.78-0.95), respectively. The pooled DOR of 33.1 (95% CI, 21.9-54.0) suggests a high diagnostic accuracy for PET. Subgroup analysis revealed that PET is more accurate for systemic staging (DOR of 36.4) than for regional staging (DOR of 19.5). When used for regional staging, PET performed better in patients with American Joint Committee on Cancer Stage III disease, compared with patients with Stage I and Stage II disease. However, the methodologic quality of the studies was limited. Major problems were verification, review, and selection bias. CONCLUSIONS. Due to the poor methodologic quality of the available studies, to the authors' knowledge it is yet not possible to develop guidelines for the effective use of PET in patients with melanoma. Future accuracy studies should meet the methodologic criteria outlined in the current review.
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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 | 0.019 | 0.077 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.014 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".