Early MRI predictors of disease-free survival in locally advanced rectal cancer from the GRECCAR 4 trial
Bibliographic record
Abstract
BACKGROUND: Tailored neoadjuvant treatment of locally advanced rectal cancer (LARC) may improve outcomes. The aim of this study was to determine early MRI prognostic parameters with which to stratify neoadjuvant treatment in patients with LARC. METHODS: All patients from a prospective, phase II, multicentre randomized study (GRECCAR4; NCT01333709) were included, and underwent rectal MRI before treatment, 4 weeks after induction chemotherapy and after completion of chemoradiotherapy (CRT). Tumour volumetry, MRI tumour regression grade (mrTRG), T and N categories, circumferential resection margin (CRM) status and extramural vascular invasion identified by MRI (mrEMVI) were evaluated. RESULTS: A total of 133 randomized patients were analysed. Median follow-up was 41·4 (95 per cent c.i. 36·6 to 45·2) months. Thirty-one patients (23·3 per cent) developed tumour recurrence. In univariable analysis, mrEMVI at baseline was the only prognostic factor associated with poorer outcome (P = 0·015). After induction chemotherapy, a larger tumour volume on MRI (P = 0·019), tumour volume regression of 60 per cent or less (P = 0·002), involvement of the CRM (P = 0·037), mrEMVI (P = 0·026) and a poor mrTRG (P = 0·023) were associated with poor outcome. After completion of CRT, the absence of complete response on MRI (P = 0·004), mrEMVI (P = 0·038) and a poor mrTRG (P = 0·005) were associated with shorter disease-free survival. A final multivariable model including all significant variables (baseline, after induction, after CRT) revealed that Eastern Cooperative Oncology Group performance status (P = 0·011), sphincter involvement (P = 0·009), mrEMVI at baseline (P = 0·002) and early tumour volume regression of 60 per cent or less after induction (P = 0·007) were associated with relapse. CONCLUSION: Baseline and early post-treatment MRI parameters are associated with prognosis in LARC. Future preoperative treatment should stratify treatment according to baseline mrEMVI status and early tumour volume regression.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".