Diagnostic and referral intervals for Manitoba women with epithelial ovarian cancer - the Manitoba Ovarian Cancer Outcomes (MOCO) study group: a retrospective cross-sectional study
Bibliographic record
Abstract
Background: Epithelial ovarian cancer has the highest mortality of all gynecologic cancers. The poor survival rates are often attributed to the advanced stage at which most of these cancers are detected. We sought to examine the effects of patient demographics, comorbidities and presenting symptoms on diagnostic and referral intervals by location of first presentation (emergency department v. elsewhere) and to identify factors that affect these intervals. Methods: We performed a retrospective analysis of chart and medical record data for ovarian cancers, with the exceptions of sex cord and germ cell tumours, diagnosed between 2004 and 2010 in Manitoba, Canada. Data were collected on baseline characteristics, time to diagnosis and referral, number and type of physician visits and emergency department visits. Results: The final cohort consisted of 601 patients. Sixty-three percent of patients received their diagnosis within 60 days of initial presentation, and 75.2% had their cancer diagnosed within 2 physician encounters. The median diagnostic interval for all stages of patients presenting to the emergency department was 7 days, compared with 55 days for patients presenting elsewhere. Early stage patients not presenting to the emergency department had their diagnosis a median of 34.0 days later than patients with advanced disease (95% confidence interval [CI] 22.22 to 45.69, p < 0.0001). The presence of some symptoms was associated with shortened diagnostic intervals. Patients with serous, clear-cell or endometrioid histotypes were less likely to have first presentation beginning in the emergency department (odds ratio [OR] 0.40, 95% CI 0.24 to 0.64, p = 0.0001; OR 0.28, 95% CI 0.14 to 0.59, p = 0.007) than those with unclassified epithelial histotype. Interpretation: For this group of patients, the main factor associated with diagnostic and referral intervals is presentation to the emergency department. These patients likely required more urgent attention for their more symptomatic disease, leading to quicker diagnosis and referral patterns, despite poorer prognosis.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".