Real-World Efficacy and Safety of Disitamab Vedotin (RC48-ADC) in the Treatment of HER2-Overexpressing Advanced Gastric/Gastroesophageal Junction Cancer
Bibliographic record
Abstract
Objective: To evaluate the real-world efficacy and safety of disitamab vedotin (RC48-ADC) in patients with human epidermal growth factor receptor 2 (HER2) overexpression (immunohistochemistry [IHC] 2+ or 3+), advanced gastric/gastroesophageal junction cancer (GC/GEJC) with metastases who had received at least one line of prior systemic therapy. Patients and methods: Patients with HER2-overexpressing advanced or metastatic GC/GEJC who had previously received the anti-HER2 antibody-drug conjugate disitamab vedotin between December 2022 and April 2024 were enrolled in this study. The patients’ baseline characteristics, treatment procedures, and laboratory or imaging examinations were retrospectively collected and analyzed. The observation items included the objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and treatment-related adverse events (TRAEs). Results: Of the 38 enrolled patients in the study, 27 were found to be HER2-positive. Most patients (29/38) received disitamab vedotin therapy as a third-line or subsequent treatment. A total of 68.4% of patients had previously received anti-HER2 therapy, and 13 patients underwent immunotherapy concurrently. The overall ORR and DCR were 31.6% and 65.8%, respectively. A higher ORR was observed in patients with a single metastatic site compared to those with multiple sites (53.3% vs. 17.4%, p = 0.022). In the general population, the median PFS was 6.5 months (95% confidence interval [CI] 3.3–9.8 months), and OS was 13.5 months (95% CI 9.0–17.9 months). The most common adverse event was anemia (89.5%), and eight patients suffered severe toxicities of grade ≥3. Conclusions: Disitamab vedotin exhibited encouraging anti-tumor effectiveness with a tolerable safety profile for advanced GC/GEJC patients with HER2 overexpression who had failed at least one line of systemic therapy in a real-world setting.
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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 | 0.000 |
| 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 | 0.001 |
| 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".