Neoadjuvant programmed cell death 1 blockade combined with chemotherapy for resectable esophageal squamous cell carcinoma
Bibliographic record
Abstract
Background Programmed cell death 1 (PD-1) blockade induces tumor regression in patients with advanced esophageal squamous cell carcinoma (ESCC); however, little is known about the efficacy of PD-1 blockade as neoadjuvant therapy in resectable ESCC. We aim to assess the safety and feasibility of using the combination of neoadjuvant PD-1 blockade with chemotherapy in patients with ESCC. Methods Patients with previously untreated, resectable (stage II or III) ESCC were enrolled. Each patient received two 21-day cycles of neoadjuvant treatment with camrelizumab, nab-paclitaxel, and carboplatin before undergoing surgical resection approximately 6–9 weeks after the first cycle. Results Between January 2020 and September 2020, 37 patients were screened, of whom 23 were enrolled. The neoadjuvant therapeutic regimen had an acceptable side effect profile, and no delays in surgery were observed. Severe (grade 3–4) treatment-related adverse events included neutropenia (9 of 23, 39.1%) and leukopenia (2 of 23, 8.7%). The objective response and disease control rates were 90.5% and 100%, respectively. Twenty patients received surgery, and R0 resection was achieved in all cases. Five (25%) patients had a pathological complete response (PCR) and 10 (50%) patients had a major pathological response. The proportion of patients with a high tumor mutation burden and a high expression of programmed death-ligand 1 (PD-L1) in primary tumor was significantly higher in the PCR group than in the non-PCR group (p=0.044). The number of infiltrating PD-L1 + CD163 + cells was significantly lower in the PCR group than in the non-PCR group after treatment (p=0.017). Conclusions Neoadjuvant camrelizumab plus carboplatin and nab-paclitaxel had manageable treatment-related adverse effects and induced an objective response in 90.5% of patients, demonstrating its antitumor efficacy in resectable ESCC. Trial registration number ChiCTR2000028900.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 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".