Healthcare costs associated with prostate cancer: estimates from a population‐based study
Bibliographic record
Abstract
STUDY TYPE: Health Economic (multiway sensitivity analyses). LEVEL OF EVIDENCE: 2b. OBJECTIVE: To estimate the total healthcare costs and costs attributable to prostate cancer across all stages of disease, and to determine the predictors of those costs, as describing the cost of care for patients with prostate cancer is useful to understand the economic burden of illness, explore patterns of care, and provide reliable cost data for economic evaluations. METHODS: We estimated direct medical costs for 42 484 men diagnosed with prostate cancer in Ontario, Canada between 1995 and 2002 using linked administrative data. The observation time was divided into five phases: (I) before diagnosis (6 months before); (II) initial care (12 months after diagnosis); (III) continuing care; (IV) pre-terminal care (from 18 to 6 months before death); and (V) terminal care (6 months before death). Attributable costs were estimated by comparing costs in cases to matched controls. RESULTS: The total direct costs per 100 days (in $Canadian, 2004) were: Phase I $1297; II $3289; III $1495; IV $5629; and V $16 020. Prostate cancer-attributable costs accounted for 72% of total costs in the 12-month period after diagnosis (II, $2366), but <35% of total costs in phases III to V ($398, $1977 and $3140, respectively). An advanced stage at diagnosis, being older at diagnosis, and higher comorbidity were associated with increased costs. CONCLUSION: Prostate cancer is associated with increased direct healthcare costs over the natural history of the disease. Costs are highest around two events, cancer diagnosis and cancer death. Future research should evaluate costs borne by private insurers and patients, evaluate the effects of patient and system variables on lifetime costs, and explore differences in end-of-life healthcare costs across countries.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".