Antihypertensive drugs and survival outcomes in oropharyngeal squamous cell carcinoma patients
Bibliographic record
Abstract
BACKGROUND: Radiation therapy is commonly used to treat head and neck cancer patients, and response may be improved by combining radiation with preexisting medications. Based on recent preclinical and retrospective patient data, we hypothesized that antihypertensive drugs may improve radiotherapy outcomes. METHODS: Retrospective analyses were conducted on 1077 oropharyngeal squamous cell carcinoma and 608 nasopharyngeal carcinoma patients, all of whom received radiation therapy. Univariate and multivariate analyses were conducted to assess overall survival, disease-specific survival, and locoregional control for cancer patients taking angiotensin receptor blockers (ARBs), angiotensin-converting enzyme inhibitors, calcium channel blockers, or beta blockers compared with propensity score-matched groups of patients not taking these medications. RESULTS: Oropharyngeal squamous cell carcinoma patients taking antihypertensive medications were statistically older and had higher Charlson Comorbidity Indices at diagnosis. However, these patients had statistically significant improved overall survival, disease-specific survival, and locoregional control compared with propensity score-matched oropharyngeal squamous cell carcinoma patients who were not taking antihypertensive medications, with ARB users showing the greatest improvements. Antihypertensive drugs did not affect outcomes in the nasopharyngeal carcinoma patient cohort. CONCLUSION: The use of antihypertensive medications, and particularly ARBs, was associated with improved outcomes in oropharyngeal squamous cell carcinoma patients who had more advanced age and higher Charlson Comorbidity Indices at diagnosis. This study supports future prospective testing of ARBs in conjunction with radiation therapy in this group of higher risk oropharyngeal squamous cell carcinoma patients. Additionally, this study illustrates the need to use propensity score matching to identify patient subgroups that may benefit from a given treatment in retrospective analyses.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".