Cost-effectiveness of pembrolizumab compared with chemotherapy in the US for women with previously treated deficient mismatch repair or high microsatellite instability unresectable or metastatic endometrial cancer
Bibliographic record
Abstract
AIMS: There is limited published evidence for the cost-effectiveness of treatments for unresectable or metastatic endometrial cancer (mEC). The objective of this analysis was to assess the cost-effectiveness of pembrolizumab versus chemotherapy for previously treated unresectable or mEC, in women whose tumors have deficient mismatch repair (dMMR) or high microsatellite instability (MSI-H). The analysis was carried out from a US healthcare payer perspective. MATERIALS AND METHODS: A lifetime partitioned survival model comprising three health states (progression-free, progressed disease and death) was constructed. Chemotherapy was represented by single-agent paclitaxel or doxorubicin. Overall survival, progression-free survival and time on treatment data for pembrolizumab were obtained from a Phase II clinical study that included women with previously treated dMMR/MSI-H unresectable or mEC (KEYNOTE-158, NCT02628067). Survival data for chemotherapy were obtained from a published Phase III study for previously treated advanced endometrial cancer. Costs included were drug acquisition and administration, health-state, end-of-life, and adverse event management. Costs were presented in 2019 US$. Outcomes were calculated as quality-adjusted life-years (QALYs), using EQ-5D data from KEYNOTE-158. Model results were tested extensively in deterministic and probabilistic sensitivity analyses. RESULTS: Results demonstrated that pembrolizumab is a highly cost-effective treatment option when compared with chemotherapy, with estimated deterministic and probabilistic incremental cost-effectiveness ratios (ICERs) of $58,165 and $57,668 per QALY gained, respectively. Pembrolizumab was associated with a large QALY and life-year gain per person versus chemotherapy over the model time horizon (deterministic 4.68 life year gain, 3.80 QALYs), with the majority of QALYs accrued in the progression-free health state. LIMITATIONS: The key limitation of the analysis was the lack of comparative effectiveness data for pembrolizumab versus chemotherapy. CONCLUSIONS: Pembrolizumab is a highly cost-effective treatment option when compared with chemotherapy for women with previously treated dMMR/MSI-H unresectable or mEC. Results were robust to the changes in parameters and assumptions explored.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".