Bibliographic record
Abstract
BACKGROUND: Gastric cancer is a disease with different management approaches in different regions, especially between Western and Asian countries. Surgery is the mainstay of treatment for non-metastatic disease. Perioperative chemotherapy or adjuvant radio-chemotherapy is recommended, since recurrences are common after curative resection. Unfortunately, advanced or metastatic gastric cancer constitutes the majority of patients in clinical practice. For these patients systemic chemotherapy is the standard treatment, to provide palliation and prolong survival; however, prognosis remains poor. Several molecular targeting agents are under evaluation in international randomized studies. OBJECTIVE: To review chemotherapy and targeted therapies for gastric cancer, chemical and pharmacological characteristics of trastuzumab, and evidence for its clinical use in gastric cancer. METHODS: Examination of relevant literature. RESULTS/CONCLUSIONS: HER-2 is overexpressed/amplified in approximately 22% of gastric cancer patients. Trastuzumab, a recombinant humanized anti-HER-2 monoclonal antibody, is, to our knowledge, the first biological therapy that has showed a survival improvement by nearly 3 months (reduced risk of death by 26%), thus trastuzumab in combination with chemotherapy is a treatment option for patients with HER2-positive advanced gastric cancer. Trastuzumab's role in curative gastric cancer treatment needs to be studied, as well as monotherapy, maintenance therapy and second line treatment in the palliative setting.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".