The crosstalk between Stroke and Cancer: Incidence of cancer after a first-ever cerebrovascular event in a population-based study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Objectives: To determine the cancer incidence after the first-ever cerebrovascular event (CVE) and compare it to the cancer incidence in the population from the same region. Methods: We evaluated 1069 patients with a first-ever CVE (Ischaemic or haemorrhagic stroke and Transient Ischaemic Attack) from a prospective population registry of stroke and transient focal neurological attacks, diagnosed between 2009 and 2011. We conducted a structured search to identify cancer-related variables and case-fatality for a period of 8 years following CVE. Cancer incidence in CVE patients was compared to the North Region Cancer Registry (RORENO). Results: We found that 90/1069 (8.4%) CVE patients developed cancer after a first-ever CVE. Overall cancer annual incidence rate was higher after a CVE (820/100,000, 95%CI: 619–1020) than in general population (513/100,000, 95%CI: 508–518). In the 45–54 age group cancer incidence post-CVE was 3.2-fold (RR, 95%CI: 1.6–6.4) higher compared to the general population, decreasing gradually in older age-groups. Median time between CVE and cancer was 3.2 years (IQR = 1.4–5.2). Lower respiratory tract and colorectal were the most frequent cancer types. In univariable models, male sex (sHR = 1.78, 95%CI: 1.17–2.72, p = 0.007), tobacco use (sHR = 2.04, 95%CI: 1.31–3.18, p = 0.002) and peripheral artery disease (sHR = 2.37, 95%CI: 1.10–5.13, p = 0.028) were associated to higher cancer risk after CVE. After adjustment, tobacco use (sHR = 1.84, 95%CI: 1.08–3.14, p = 0.026) remained associated to a higher risk of cancer. Conclusions: At the population level, patients presenting a first-ever CVE have higher cancer incidence, that is particularly prominent in younger age-groups. Higher cancer incidence, delayed cancer diagnosis and increased mortality post-CVE warrants further research on long-term cancer surveillance in first-ever CVE survivors.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 it