Association of cancer with the risk of developing hypertension
Bibliographic record
Abstract
BACKGROUND AND AIMS: Although the importance of hypertension in patients with cancer is widely recognized, little is known about the risk of developing hypertension in patients with a history of cancer. METHODS AND RESULTS: This retrospective observational cohort study analysed data from the JMDC Claims Database between 2005 and 2022, including 78 162 patients with a history of cancer and 3692 654 individuals without cancer. The primary endpoint was the incidence of hypertension.During a mean follow-up period of 1208 ± 966 days, 311 197 participants developed hypertension. The incidence of hypertension was 364.6 [95% confidence interval (CI) 357.0-372.2] per 10 000 person-years among those with a history of cancer, and 247.2 (95% CI 246.3-248.1) per 10 000 person-years in those without cancer. Individuals with a history of cancer had an elevated risk of developing hypertension, according to multivariable Cox regression analyses [hazard ratio (HR) 1.17, 95% CI 1.15-1.20]. Both cancer patients requiring active antineoplastic therapy (HR 2.01, 95% CI 1.85-2.20), and those who did not require active antineoplastic therapy (HR 1.14, 95% CI 1.12-1.17) had an increased risk of hypertension. A multitude of sensitivity analyses confirmed the robustness of the relationship between cancer and incident hypertension. Patients with certain types of cancer were found to have a higher risk of developing hypertension than those without cancer, with varying risks dependent on the type of cancer. CONCLUSION: Our analysis of a nationwide epidemiological database revealed that individuals with a history of cancer have a higher risk of developing hypertension, and this finding applies to both cancer patients who require active antineoplastic therapy and those who do not.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".