Out-of-Pocket Costs in the Year After Early Breast Cancer Among Canadian Women and Spouses
Bibliographic record
Abstract
BACKGROUND: We lack comprehensive information about the extent of out-of-pocket costs after diagnosis of early breast cancer and their effects on the family's financial situation. METHODS: This longitudinal study assessed out-of-pocket costs and wage losses during the first year after diagnosis of early breast cancer among Canadian women and spouses. Out-of-pocket costs for treatments and follow-up, consultations with other practitioners, home help, clothing, and natural health products were estimated, with information collected from telephone interviews. Generalized linear models were used to identify women at risk of having higher costs and the effects of out-of-pocket costs on perceptions of the family's financial situation. RESULTS: Overall, 829 women (participation, 86.2%) and 391 spouses participated. Women's median net out-of-pocket costs during the year after diagnosis were $1002 (2003 Canadian dollars; mean = $1365; SD = $1238), and 74.4% of these costs resulted from treatments and follow-up. Spouses' median costs were $111 (mean = $234; SD = $320), or 9% of couples' total expenses. In multivariable analyses, the percentage of women with out-of-pocket costs of $1773 or more (upper quartile) was statistically significantly associated with higher education, working at diagnosis, living more than 50 km from the hospital where surgery was performed, and having two and three different types of adjuvant treatment (all 2-sided P values ≤ .01). However, when considered simultaneously with wage losses, out-of-pocket costs were not associated with perceived deterioration in the family's financial situation; rather, wage losses were the driving factor. CONCLUSIONS: Overall, out-of-pocket costs from breast cancer for the year after diagnosis are probably not unmanageable for most women. However, some women were at higher risk of experiencing financial burden resulting from these costs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".