Intellectual or developmental disabilities and curative female breast cancer treatment: A population-based retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Adults with intellectual or developmental disabilities (IDD) diagnosed with breast cancer are more likely to die than those without IDD. Differences in breast cancer treatment among individuals with and without IDD could contribute to survival disparities. We compared breast cancer treatment receipt among adults with and without IDD. METHODS: A population-based retrospective cohort study was conducted using administrative data. We included adult females diagnosed with stage I-III breast cancer in Ontario (2007-2018). IDD status was identified using an established algorithm. We estimated associations between IDD and surgical resection, adjuvant chemotherapy, and radiation using cause-specific hazards models in four distinct cohorts determined by stage and treatment eligibility. Unadjusted and adjusted hazard ratios (HR; adjusted for region, rurality, previous cancer, stage and year of diagnosis) with 95 % confidence intervals are reported, accounting for the competing event of death. Cancer subtype was not adjusted for as about 25 % of participants were missing this information. Effect modification by age, stage and comorbidity was explored. RESULTS: The four cohorts included 100,679 (IDD = 369), 12,526 (IDD = 57), 60,279 (IDD = 167), and 7891 individuals (IDD = 22), respectively. Relative to those without IDD, people with IDD were less likely to receive surgical resection (HR = 0.84; 0.76-0.94), breast conserving surgery (HR = 0.69; 0.60-0.80), adjuvant chemotherapy (HR = 0.49; 0.32-0.74), and radiation (HR = 0.58; 0.46-0.73). People with IDD were as likely to receive mastectomy (HR = 1.13; 0.97-1.33). Significant interactions by age and IDD were detected for receipt of mastectomy (interaction p-value = 0.03) and breast conserving surgery (interaction p-value = 0.02). CONCLUSIONS: Research to understand treatment decision-making, the accessibility of breast cancer treatment, and to examine potential pathways to improve receipt of guideline-recommended care are needed to inform targeted improvements in care delivery.
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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 | 0.002 |
| 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".