Health Care Costs for Prostate Cancer Patients Receiving Androgen Deprivation Therapy: Treatment and Adverse Events
Bibliographic record
Abstract
BACKGROUND: Serious adverse events have been associated with androgen deprivation therapy (adt) for prostate cancer (pca), but few studies address the costs of those events. METHODS: All pca patients (ICD-9-CM 185) in Ontario who started 90 days or more of adt or had orchiectomy at the age of 66 or older during 1995-2005 (n = 26,809) were identified using the Ontario Cancer Registry and drug and hospital data. Diagnosis dates of adverse events-myocardial infarction, acute coronary syndrome, congestive heart failure, stroke, deep vein thrombosis or pulmonary embolism, any diabetes, and fracture or osteoporosis-before and after adt initiation were determined from administrative data. We excluded patients with the same diagnosis before and after adt, and we allocated each patient's time from adt initiation to death or December 31, 2007, into health states: adt (no adverse event), adt-ae (specified single adverse event), Multiple (>1 event), and Final (≤180 days before death). We used methods for Canadian health administrative data to estimate annual total health care costs during each state, and we examined monthly trends. RESULTS: Approximately 50% of 21,811 patients with no pre-adt adverse event developed 1 or more events after adt. The costliest adverse event state was stroke ($26,432/year). Multiple was the most frequent (n = 2,336) and the second most costly health state ($24,374/year). Costs were highest in the first month after diagnosis (from $1,714 for diabetes to $14,068 for myocardial infarction). Costs declined within 18 months, ranging from $784 per 30 days (diabetes) to $1,852 per 30 days (stroke). Adverse events increased the costs of adt by 100% to 265%. CONCLUSIONS: The economic burden of adverse events is relevant to programs and policies from clinic to government, and that burden merits consideration in the risks and benefits of adt.
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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 | 0.005 |
| 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 | 0.000 | 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".