Responses by Breast and Prostate Cancer Patients to Out-Of-Pocket Costs in Newfoundland and Labrador
Bibliographic record
Abstract
PURPOSE: Cancer patients face substantial care-related out-of-pocket (oop) costs that may influence treatment decisions, attitudes, and use of drug- or appointment-related cost-saving strategies. We examined the relationship between oop costs and care-related responses by patients. METHODS: We surveyed 170 prostate and 131 breast cancer patients presenting at clinics or support groups, or listed on the cancer registry in Newfoundland and Labrador. RESULTS: In the 3-month period before the survey, 18.8% of prostate and 25.2% of breast cancer patients had oop costs greater than $500. Those oop costs consumed more than 7.5% of quarterly household income for 15.9% of prostate and 19.1% of breast cancer patients. Few patients (8.8% prostate, 15.3% breast) ever adopted any drug- or appointment-related cost-saving strategy. Few patients (7.2% prostate, 9.6% breast) said oop costs influenced treatment decisions, told their physicians about their oop costs (27.0% prostate, 21.1% breast), or were aware of available financial assistance programs (27.3% prostate, 36.9% breast). Compared with patients having low or moderate oop costs (22.9% prostate, 16.7% breast, and 25.7% prostate, 58.3% breast respectively), a larger proportion of prostate (56.0%) and breast (58.3%) cancer patients with high oop costs said that those costs created stress. Among prostate cancer patients, a larger proportion of those having high oop costs (compared with low or moderate costs) used drug-related (22.2% vs. 3.3% and 9.6% respectively) and appointment-related (11.1% vs. 1.1% and 3.8% respectively) cost-saving strategies, said oop costs created an unusual amount of stress (48.0% vs. 18.4% and 10.4%), and had difficulty paying those costs (29.2% vs. 6.2% and 10.4%). CONCLUSIONS: For a small group of breast and prostate cancer patients, oop costs are high, but rarely lead to the use of care-related cost-saving strategies or influence care decisions.
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 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".