Abstract P4-12-08: Palbociclib in hormone receptor positive advanced breast cancer: A cost-utility analysis
Bibliographic record
Abstract
Abstract Introduction The addition of palbociclib to letrozole improves progression free survival (PFS) and response rates compared to letrozole alone in the 1st line treatment of hormone receptor positive advanced breast cancer. However palbociclib increases toxicity (i.e. neutropenia) and costs more than $6,250 per month in Canada. This study assesses the cost-utility of palbociclib from the Canadian healthcare payer perspective. Methods To evaluate the cost-utility of palbociclib, a probabilistic discrete event simulation model was developed. The model was parameterized with data from the phase 2 and 3 PALOMA 1 and 2 trials and other sources. The incremental cost per quality-adjusted life-month (QALM) gained for palbociclib was calculated. A time horizon of 15 years was used in the base case with costs and effectiveness discounted 5% annually. The time to progression and death were derived from a Weibull and exponential distribution. Expected costs were based on Ontario fees and other sources. Probabilistic sensitivity analyses were conducted to account for parameter uncertainty. Results Compared to letrozole alone, the addition of palbociclib provided an additional 14.7 QALM at an incremental cost of $161,508. The resulting incremental cost-effectiveness ratio was $10,999 per QALM gained. Assuming a willingness to pay (WTP) of $4,167 per QALM, the addition of palbociclib was not cost-effective and the probability of palbociclib to be cost-effective was 0%. Cost-effectiveness acceptability curves derived from a probabilistic sensitivity analysis showed that at a WTP of $11,667 per QALM gained, the probability of palbociclib to be cost-effective was 50%. Conclusion Compared with letrozole alone, the addition of palbociclib is unlikely to be cost-effective for the treatment of advanced breast cancer from a Canadian healthcare perspective with its current price. While advanced breast cancer patients derive a meaningful clinical benefit from palbociclib, considerations should be given to increase the WTP threshold and reduce the drug pricing, to render this strategy more affordable. Citation Format: Raphael J, Helou J, Naimark DM. Palbociclib in hormone receptor positive advanced breast cancer: A cost-utility analysis [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P4-12-08.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".