Pathological Responses of the Primary Tumor and Locoregional Lymph Nodes After Neoadjuvant Immunochemotherapy in Esophageal Squamous Cell Cancer
Bibliographic record
Abstract
Background: The current study attempted to describe the specific patterns of pathological tumor response and locoregional node metastases from surgically resected esophageal squamous cell carcinoma after neoadjuvant immunochemotherapy (NAIC), as well as to explore the association between clinicopathological characteristics and such oncological patterns. Methods: Fifty-one patients with cT3 or deeper esophageal squamous cell cancer underwent subtotal esophagectomy after NAIC. The NAIC regimen included intravenous administration of platinum-based and docetaxel- and taxane-based chemotherapeutics along with a 200 mg fixed dose of one programmed death 1 (PD-1) inhibitor, given every 3 weeks. We divided patients into tumor/nodal good-responders and poor-responders based on the pathological observation of the tumor or nodal responses. We also examined the association between clinicopathological factors and tumor/nodal responses. Further, significant baseline predictors for tumor and nodal good-responders were identified using multivariate binary logistic regression. Results: Of the 51 patients, 68.6% achieved marked primary tumor response. Notably, 21.6% of patients achieved complete pathological response. Significant differences in treatment cycles between tumor good-responders and tumor poor-responders (P = 0.019) were observed. For locoregional nodal responses, only 33.3% of patients achieved down-staged nodal disease. Of the investigated variables, neoadjuvant cycles (odds ratio (OR): 5.271, 95% confidence interval (CI): 1.278 - 21.740, P = 0.022) and pretreatment platelets (OR: 0.979, 95% CI: 0.962 - 0.996, P = 0.017) were identified as independent predictors for good tumor and nodal responses. Conclusions: We conclusively noted that most patients receiving NAIC were tumor good-responders, whereas only one-third of patients were nodal good-responders. Furthermore, we identified that treatment cycle number and baseline platelet counts were independent predictors of combined tumor and nodal responses.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".