Sexual health outcomes after colorectal cancer diagnosis in females: a population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Colorectal cancer (CRC) affects a growing number of females. Our objective was to evaluate the impact of CRC on sexual health outcomes among females, while controlling for age. METHODS: We conducted a cohort study using administrative health data from the province of British Columbia (BC) including linked health visits and cancer registry from 1985 to 2017. The cohort included females with CRC (n = 25 402; mean age [SD]: 69.0 [13.1]) and matched controls without CRC (n = 254 020; 69.0 [13.1]) in a 1:10 ratio by age, further stratified by age groups (≤39 years and ≥40 years). Multivariable Cox regression models assessed the associations between CRC and 5 sexual health outcomes (dyspareunia, pelvic inflammatory disease, endometriosis, abnormal bleeding, and premature ovarian failure), adjusting for covariates. Sensitivity analyses focused on females with CRC to explore associations between sociodemographic and cancer-related factors and sexual health outcomes. Tests were 2-sided (statistical significance P <.05). RESULTS: Females with CRC had higher risks of dyspareunia (HR 1.67; 95% CI = 1.62 to 1.73), pelvic inflammatory disease (HR 3.42; 95% CI = 3.07 to 3.81), and endometriosis (HR 1.95; 95% CI = 1.69 to 2.25) compared to controls. In the ≥40-year group, these associations persisted, while in the ≤39-year group, endometriosis was not associated with CRC, but premature ovarian failure was (HR 1.75; 95% CI = 1.40 to 2.19). In sensitivity analyses, we also observed associations with cancer treatments (surgery, chemotherapy, radiation) and sexual health outcomes. CONCLUSIONS: This population-based study identified associations between CRC and adverse sexual health outcomes among female patients, highlighting the need for targeted interventions and support.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".