Determinants of delay in diagnosis and end stage at presentation among breast cancer patients in Iran: a multi-center study
Bibliographic record
Abstract
One of the reasons for high mortality of breast cancer (BC) is long delay in seeking medical care and end stage at presentation. This study was designed to measure the association between a wide range of socio-demographic and clinical factors with diagnostic delay in BC and stage at presentation among Iranian patients. From June 2017 to December 2019, 725 patients with newly diagnosed BC in Shiraz and Kermanshah were selected and information on BC diagnosis delay was obtained from the patient's medical record. Data on socio-economic status was obtained via a structured interview. Our findings suggest that 45.8% of the patients were diagnosed at a late stage (stage 3 or higher). A total of 244 (34%) patients had more than 3 months delay in diagnosis. We found a significant association between stage at diagnosis and place of residence (adjusted odds ratio (aOR rural vs. urban = 1.69, 95% CI 1.49-1.97), marital status (aOR 1.61, 95% CI 1.42-1.88), family history of BC (aOR 1.46, 95% CI 1.01-2.13), and history of benign breast disease (BBD) (aOR 1.94, 95% CI 1.39-2.72) or unaware of breast self-examination (BSE) (aOR 1.42, 95% CI 1.42-1.85), delay time (aOR 3.25, 95% CI 1.04-5.21), and left breast tumor (aOR right vs. left 2.64, 95% CI 1.88-3.71) and smoking (aOR no vs. yes 1.59, 95% CI 1.36-1.97). Also, delay in diagnosis was associated with age, family income, health insurance, place of residence, marital status, menopausal status, history of BBD, awareness of breast self-examination, type of first symptoms, tumor histology type, BMI and comorbidity (p < 0.05 for all). Factors including history of BBD, awareness of BSE, and suffering from chronic diseases were factors associated with both delay in diagnosis and end stage of disease. These mainly modifiable factors are associated with the progression of the disease.
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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 | 0.000 | 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 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".