Protective effect of metformin in lung cancer patients
Bibliographic record
Abstract
e22063 Background: Over the past decade, dozens of studies have shown that metformin not only decreases mortality in diabetics, it also significantly reduces CRP and reduces the risks of cancer in rodent and human cell lines. We report on the survival of lung cancer patients concomitantly exposed to metformin in our community-based program. Methods: 850 patients undergoing treatment from a prospectively collected pulmonary oncology database of the SMBD-Jewish General Hospital over an 8-year period were analyzed. Pilot observational study of survival was performed using Cox regression model. The factors that were included in the model were age, gender, stage, histology and metformin use. Results: 850 patients (F: M=375:475; mean age of 66) were diagnosed since 2000 and followed in pulmonary oncology outpatient clinic for NSCLC. 523 (62%) of those patients were diagnosed with adenocarcinoma; 488 (57%) were stage IIIB with pleural effusion/IV. 79(9%) patients were receiving treatment with metformin for their comorbid type 2 diabetes. The Cox regression analysis demonstrated that age, gender, stage and use of metformin were significant prognostic factors for survival. The use of metformin is associated with a 37% (HR 1.37; CI 1.01–1.84) (p=0.039) increase in survival. Conclusions: Thus, the result obtained from our model suggests that use of metformin may be associated with better survival of lung cancer patients. As this is a pilot study, we will consider alternative explanations. No significant financial relationships to disclose.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.006 | 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".