In vitro Anti-Tumor Effects of Statins on Head and Neck Squamous Cell Carcinoma: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Statins are commonly used against arteriosclerotic disease, but recent retrospective analyses have suggested that statins also prevent cancer. The aim of this systematic review is to verify the vitro anti-tumor effects of statins on head and neck squamous cell carcinoma. METHODS: Studies were gathered by searching Cochrane, MEDLINE, EMBASE, LILACS, and PubMed, up until May 9, 2015, with no time or language restrictions. Only in vitro studies that discuss the effect of statins on head and neck carcinoma were selected. RESULTS: Of 153 identified papers, 14 studies met the inclusion criteria. These studies demonstrated that statins had a significant effect on head and neck squamous cell carcinoma cell lines and influenced cell viability, cell cycle, cell death, and protein expression levels involved in pathways of carcinogenesis, which corroborates with the potential in vitro anti-tumor effects. It provides highlights about the biological mechanisms of statins used alone or associated with traditional therapy for cancer. CONCLUSIONS: Though there are few studies on the topic, currently available evidence suggests that statins shows that preclinical experiments supports the potentiality of statin as an adjuvant agent in chemotherapy and/or radiotherapy approaches routinely used in the management of HNSCC and should undergo further clinical assessment.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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".