Pre‐ and post‐treatment <scp>FDG PET‐CT</scp> as a predictor of patient outcomes in anal squamous cell carcinoma: A systematic review and <scp>meta‐analysis</scp>
Bibliographic record
Abstract
Anal squamous cell carcinoma (ASCC) has a generally acceptable outlook in terms of survival. 18-fluorodeoxyglucose-positron emission tomography/computer tomography (FDG PET-CT) is not recommended for routine monitoring post-ASCC treatment. We examine herein if FDG PET-CT has a use in the prognostic evaluation of patients with ASCC, what FDG PET-CT metrics are of value and if a pre- or post-chemo/radiotherapy scan is more prognostic of outcomes. PubMed, EMBASE and Cochrane Central Registry of Controlled Trials were comprehensively searched until 3 May, 2023. A modified Newcastle Ottawa scale was used to assess for study bias. We present our systematic review alongside pooled hazard ratios (HR) for maximum standardised uptake values (SUV) as a predictor of overall survival (OS) and progression-free survival (PFS). Seven studies including 523 patients were included in our systematic review. Current evidence suggests that SUV maximum and median, metabolic tumour volume, total lesion glycolysis and complete and partial metabolic response may be prognostic when considering overall or progression-free survival (OS)/(PFS) along with local recurrence (LR). Pooled HR from two included studies indicate SUV max is prognostic of OS, HR 1.179, CI (1.039-1.338), P = 0.011 and PFS 1.176, CI (1.076-1.285), P < 0.01. FDG PET-CT may have a role to play in the prognostic evaluation of ASCC patients. Current evidence suggests post-treatment scanning may hold superior prognostic value at this time.
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.022 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".