FDG-PET parameters predict for recurrence in anal cancer – results from a prospective, multicentre clinical trial
Bibliographic record
Abstract
BACKGROUND: To investigate the prognostic significance of positron emission tomography (PET) parameters from F-18 fluorodeoxyglucose (FDG) PET scans performed pre- and post- chemo-radiotherapy (CRT) for squamous cell carcinoma of the anal canal (AC). METHODS: From January 2013 to January 2017, 19 patients with non-metastatic AC enrolled on a prospective trial underwent FDG-PET/CT imaging before and 12 weeks following CRT. A computer-generated volume of interest (VOI) was snapped around the primary tumour using six different standard uptake value (SUV) thresholds and the following parameters were extracted: SUV max, mean, median, standard deviation and peak as well as metabolic tumour volume (MTV) and total lesion glycolysis. Exact logistic regression and ROC AUC analyses were performed for each metric at each timepoint. RESULTS: With a median follow up of 15.8 months, 3/19 patients had a local recurrence and 5/19 had any recurrence. On post-CRT PET, the median SUV within a VOI bounded by an SUV of 3 correlated with local recurrence (p < 0.01) and demonstrated excellent discrimination (ROC AUC 1.00, perfect separation was achieved at a median SUV of 3.38). The mean SUV at this threshold did not quite reach significance for prediction of local recurrence (p = 0.06) but demonstrated excellent discrimination (ROC AUC 0.91). The MTV bounded by a threshold of 41% SUVmax on the pre-CRT PET predicted for any recurrence (p = 0.03) and showed excellent discrimination (ROC AUC 0.89). CONCLUSIONS: FDG-PET parameters are predictive of recurrence in AC. FDG-PET may represent a valuable tool for prognostication and response assessment in AC. TRIAL REGISTRATION: ANZCTR, ACTRN12614001219673 . Registered 19 November 2014 - Retrospectively registered.
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 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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".