Prediagnosis lifestyle exposures and survival of patients with gastric cancer
Bibliographic record
Abstract
The relation between lifestyles and gastric cancer has been investigated thoroughly; however few studies have addressed the impact of these exposures on prognosis. Therefore, we quantified the association between prediagnosis smoking, alcohol intake and other dietary exposures and the survival of gastric cancer patients through a systematic review and meta-analysis. We searched Pubmed and EMBASE up to April 2011 and computed summary hazard ratio estimates and respective 95% confidence intervals (95% CIs) through a random-effects meta-analysis (DerSimonian and Laird). Heterogeneity was quantified using the I2 statistic. Seven articles, providing data from 6856 cases evaluated in seven countries (Canada, Japan, Italy, USA, Korea, Iran and Sweden), were eligible for meta-analysis. The summary hazard ratio was 1.08 (95% CI: 0.90-1.30) for smoking (current vs. never smokers, seven studies; I2=56.2%) and 1.13 (95% CI: 1.00-1.28) for alcohol consumption (drinkers vs. nondrinkers, five studies; I2=13.2%). Only two studies assessed the effect of other dietary factors. This study summarizes the best evidence available on the relation between prediagnosis lifestyles and the survival of gastric cancer patients. Alcohol drinkers have lower survival, but results on the effect of smoking lack consistency and there is almost no information on the effects of dietary factors.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".