Effect of beta-blockers on survival of lung cancer patients: a systematic review and meta-analysis
Bibliographic record
Abstract
The recent interest in beta-blockers as possible agents for drug repurposing in oncology arises from many pre-clinical and epidemiologic studies suggesting a possible clinically relevant antitumour effect. In lung cancer, given the contradictory results obtained, it is crucial to further study its effects. A systematic review of the literature was planned to evaluate a possible beneficial effect of beta-blocker on overall survival in lung cancer patients. Medline and Embase databases were searched from inception until 1 May 2018 to identify published studies that assessed the effect beta-blocker use on overall survival in lung cancer patients. Risk of bias was evaluated by Newcastle-Ottawa scale. Hazard ratios and 95% confidence intervals for overall survival were estimated using a random-effects model. Of 920 studies, seven (all retrospective and observational, six cohort and one case-control), including 7448 patients, met the inclusion criteria. Beta-blocker users with lung cancer had no increased overall survival compared to non-users (hazard ratio = 1.00; 95% confidence interval = 0.91-1.10; I = 45%). Similarly, beta-blocker users with non-small cell lung cancer had no increased overall survival compared to beta-blocker non-users (hazard ratio = 0.96; 95% confidence interval = 0.80-1.17; I = 56%). Our findings do not suggest an overall survival advantage in patients with lung cancer using beta-blocker therapy when compared to non-users. Further prospective cohort studies, designed to overcome the intrinsic limitations of retrospective observational studies are warranted to definitively clarify any possible beneficial effect of beta-blockers on lung cancer overall survival.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.006 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".