The relationships between antihypertensive medications and the overall survival of patients with pancreatic cancer: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Antihypertensive medications may have some impacts on cancer. The influence of antihypertensive medications, including angiotensin converting enzyme inhibitors (ACEIs)/angiotensin II receptor blockers (ARBs), beta-blockers, calcium channel blockers (CCBs) and diuretics, on patients with pancreatic cancer (PC) remains controversial. This meta-analysis was conducted to investigate whether antihypertensive medications had a negative effect on the prognosis of patients with PC. METHODS: The PubMed, Embase, Web of Science and the Cochrane Library databases were searched up to 30 November 2021. The Newcastle-Ottawa scale was used to evaluate the quality of each study. This meta-analysis was registered with PROSPERO (CRD42021279169) and was carried out by using RevMan 5.3. RESULTS: Twelve studies with 120,549 patients were included in this study. ACEIs/ARBs [HR = 0.89, 95% CI (0.70-1.14)], CCB (HR = 0.69, 95% CI (0.47-0.99)], beta-blockers [HR = 0.95, 95% CI (0.84-1.07)] and diuretics [HR = 1.08, 95% CI (0.91-1.29)] use had no effects on overall survival among patients with PC (all P ≥ 0.05). CONCLUSION: Antihypertensive medication will not have a negative effect on overall survival in patients with PC. PC patients with hypertension should continue to use antihypertensive medications to reduce the morbidity and mortality of cardiovascular events.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.016 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".