Long-Term Total Neoadjuvant Therapy Leads to Impressive Response Rates in Rectal Cancer: Results of a German Single-Center Cohort
Bibliographic record
Abstract
Intensified preoperative chemotherapy after (chemo)radiotherapy, (Total Neoadjuvant Therapy–TNT), increases pathological complete response (pCR) rates and local control. In cases of clinically complete response (cCR) and close follow-up, non-operative management (NOM) is feasible. We report early outcomes and toxicities of a long-term TNT regime in a single-center cohort. Fifteen consecutive patients with distal or middle-third locally advanced rectal cancer (UICC stage II–III) were investigated, who received neoadjuvant chemoradiotherapy (total adsorbed dose: 50.4 Gy in 28 fractions and two concomitant courses 5-fluorouracil (250 mg/m2/d)/oxaliplatin (50 mg/m2), followed by consolidating chemotherapy (nine courses of FOLFOX4). NOM was offered if staging revealed cCR 2 months after TNT, with resection performed otherwise. The primary endpoint was complete response (pCR + cCR). Treatment-related side effects were quantified for up two years after TNT. Ten patients achieved cCR, of whom five opted for NOM. Ten patients (five cCR and five non-cCR) underwent surgery, with pCR confirmed in the five patients with cCR. The main toxicities comprised leukocytopenia (13/15), fatigue (12/15) and polyneuropathy (11/15). The most relevant CTC °III + IV events were leukocytopenia (4/15), neutropenia (2/15) and diarrhea (1/15). The long-term TNT regime resulted in promising response rates that are higher than the response rates of short TNT regimes. Overall tolerability and toxicity were comparable with the results of prospective trials.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".