Helicobacter pylori Infection Predicts Favorable Outcome in Patients with Gastric Cancer
Bibliographic record
Abstract
BACKGROUND: Recent studies have suggested a controversial role of Helicobacter pylori infection in gastric cancer prognosis. The aim of the present study was to investigate the potential impact of H. pylori status on the prognosis of patients with gastric cancer in a Chinese prospective cohort. METHODS: Between 2007 and 2009, 261 patients with curatively resected gastric cancer were enrolled in the study. H. pylori status was defined by means of immunohistochemical staining in tumour and non-neoplastic tissues. Treatment prognosis was measured in terms of cancer-specific survival and disease-free survival (dfs). Univariate and multivariate Cox regression models were used to assess the association between H. pylori status and patient prognosis. RESULTS: Positivity for H. pylori infection was observed in 188 of the 261 patients (72.0%). In patients positive for H. pylori, mean cancer-specific survival was 55.2 months [95% confidence interval (ci): 53.4 to 56.9 months] and mean dfs was 53.9 months (95% ci: 51.8 to 56.0 months); the same survivals were, respectively, 45.1 months (95% ci: 42.2 to 47.9 months) and 43.7 months (95% ci: 40.4 to 47.0 months) in patients negative for H. pylori. In univariate analysis, positive H. pylori status was associated with better cancer-specific survival [hazard ratio (hr): 0.486; 95% ci: 0.271 to 0.870; p = 0.015] and dfs (hr: 0.540; 95% ci: 0.307 to 0.950; p = 0.033). In multivariate analysis, H. pylori was an independent prognostic factor for cancer-specific survival (hr: 0.485; 95% ci: 0.265 to 0.889; p = 0.019). CONCLUSIONS: Our study demonstrates that positive H. pylori status is a beneficial prognostic indicator in patients with gastric cancer and might suggest possible therapeutic approaches for gastric cancer. Further research is required to better understand inflammation mechanisms and cancer progression.
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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 | 0.000 | 0.002 |
| 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".