Simple imaging biomarker predicts survival in anal squamous cell cancer treated with curative intent: a UK cohort study
Bibliographic record
Abstract
AIM This study aimed to determine the prognostic significance of length of tumour (mrT stage) and depth of extramural spread (mrEMS) in anal squamous cell cancer (SCC) treated by chemoradiation with curative intent. Locally advanced anal SCC (T3-4 N+) have poorer prognosis, but it is unknown whether the lateral spread of the tumour (extramural spread beyond the bowel wall) also confers poor prognosis in anal SCC, as it does for rectal cancer. T stage and mrEMS can be readily assessed by pelvic magnetic resonance imaging (MRI) routinely undertaken to stage anal SCC. MATERIALS AND METHODS 125 patients were included. Baseline mrT, mrN and mrEMS were assessed with response to chemoradiation and outcomes. Receiver operating curve (ROC) curve was used to determine a binary cut-off for mrEMS according to 3-year progression- free survival (PFS). Results 43% were mrT3-4 and 38% were mrEMS poor at baseline. 87% achieved mrCR. 3-year PFS and overall survival (OS) were 70.6% and 82%. On univariate analysis worse 3-year PFS was seen for mrT3-4 (HR 3.105), mrEMS poor (HR 4.924) and failure to achieve mrCR (HR 20.591). By univariate analysis, worse 3-year OS was seen for mrT3-4 (HR 4.134), mrEMS poor (HR 10.251) and failure to achieve mrCR (HR 19.289). On multivariate analysis, only mrEMS poor and failure to achieve mrCR remained prognostic. mrN was not prognostic. Conclusion MrEMS poor is a simple prognostic imaging biomarker for poorer survival which can be readily assessed by radiologists on routine imaging. mrEMS should be considered as a future stratification variable to identify high-risk SCC and consider escalation of treatment and surveillance strategies.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".