Study of PD-1 Inhibitors in Combination with Chemoradiotherapy/Chemotherapy in Patients with Esophageal Squamous Carcinoma
Bibliographic record
Abstract
In this study, we aimed to evaluate the efficacy of PD-1 inhibitors in combination with concurrent CRT/CT for patients with inoperable ESCC in the real world and to find predictors for the efficacy of PD-1 inhibitors. Patients with unresectable ESCC were evaluated at baseline. The clinical data of patients with ESCC who received CRT/CT with or without PD-1 inhibitor were collected and retrospectively reviewed. The objective response rate (ORR), overall survival (OS), and progression-free survival (PFS) were analyzed statistically. A total of 96 patients with ESCC were included. As compared with a control group (n = 48), the PFS (6.0 months vs. 5.0 months, p = 0.025) and 6-month OS (70.8% vs. 47.9%, p < 0.001) were significantly longer in the ICIs group (n = 48). There were no significant differences in ORR and 12-month OS between the two groups. In addition, we found that body mass index (BMI) was associated with PFS (HR 0.85, 95% CI 0.76−0.95, and p = 0.004) and OS (HR 0.82, 95% CI 0.69−0.98, and p = 0.033) in the ICIs group. PD-1 inhibitors combined with CRT/CT is safe with acceptable complications and improved survival for patients with inoperable ESCC. CRT plus PD-1 inhibitor has superior antitumor efficacy. BMI was positively correlated with the efficacy of PD-1 inhibitors.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".