ReviewFrontiers in oncology2025
Prospects for the application of pathological response rate in neoadjuvant therapy for gastric cancer.
Review in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Global hotspots and trends in the application of neoadjuvant therapy for gastric cancer: a bibliometric analysis.Frontiers in oncology · 2026Pooled it
- Prognosis-predicting factor of gastrectomy after systemic cancer therapy for cStage IVB gastric cancer.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2026Article
- Gastric cancer-secreted galectin-1 promotes peritoneal mesothelial-mesenchymal transition to prime peritoneal metastasis soil.iScience · 2026Article
- Alteration of tumor characteristics following neoadjuvant treatment in gastric adenocarcinoma: a case report.Frontiers in oncology · 2026Article
- Global research trends on the association between gastric cancer and chronic atrophic gastritis: a bibliometric analysis.Discover oncology · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the annual increase in the incidence and mortality rates of gastric cancer, it has gradually become one of the significant threats to human health. Approximately 90% of gastric cancer patients are diagnosed with adenocarcinoma. Although the 5-year survival rate for early-stage gastric cancer can exceed 90%, due to its concealed symptoms, less than half of the patients are eligible for radical surgical treatment upon diagnosis. For gastric cancer patients receiving palliative treatment, the current expected survival time is only about one year. In China, the majority of gastric cancer patients, accounting for about 80% of the total, are in the locally advanced stage. For these patients, radical surgery remains the primary treatment option; however, surgery alone is often inadequate in controlling tumor progression. In the pivotal MAGIC study, the recurrence rate was as high as 75%, and similar results were obtained in the French ACCORD07-FFCD9703 study. Numerous clinical trials are currently exploring preoperative neoadjuvant therapy for patients with locally advanced gastric cancer. Data indicates that preoperative neoadjuvant therapy can not only reduce the size of the local tumor but also shrink surrounding lymph nodes, thereby downstaging the tumor and improving the R0 resection rate. Additionally, it can decrease tumor cell activity and eliminate potential micrometastases. The emergence of various immunotherapies has ushered in a new era for neoadjuvant treatment options for gastric cancer.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.