589 RUBY trial post hoc analysis of number needed to treat and incremental costs per outcome of dostarlimab + carboplatin-paclitaxel (CP) vs placebo + CP for primary advanced/recurrent endometrial cancer
Bibliographic record
Abstract
Background In the RUBY trial (NCT03981796), dostarlimab+CP was associated with a statistically significant improvement in progression-free survival (PFS) by investigator assessment (IA) vs placebo+CP, driven predominantly by longer duration of response (DOR) in patients with primary advanced or recurrent endometrial cancer (pA/rEC).1 Durability of responses led to an early positive trend in overall survival. This study aimed to estimate the number needed to treat (NNT; number of treated patients needed to achieve 1 positive outcome/prevent 1 adverse outcome) and incremental cost associated with achieving these outcomes. Methods NNT estimates were calculated based on PFS (by IA) and DOR at 6, 12, 18, and 24 months and on objective response rate at 6, 12, 18, 24, 30, and 36 months. Mean treatment costs (in 2023 US$) were estimated by applying the wholesale acquisition costs for each drug to the average dose and proportion of patients treated at each cycle. Incremental costs per outcome were then calculated by multiplying the difference in mean treatment costs of dostarlimab+CP and placebo+CP by the NNT and normalizing by the number of months at each time point. Analyses were performed for patients with mismatch repair-deficient/microsatellite instability-high (dMMR/MSI-H) disease and the intention-to-treat (ITT) population to align with the populations assessed in the RUBY primary analysis. Results The estimated NNT to observe on average 1 additional patient alive and progression free (by IA) at 24 months for dostarlimab+CP vs placebo+CP in the dMMR/MSI-H and ITT populations was 3 and 6 patients, respectively (figure 1A); incremental costs per additional progression-free life-month were $36,124 and $91,973, respectively (table 1). The NNT associated with maintaining 1 additional patient in 24-month response was 3 and 7 in the dMMR/MSI-H and ITT populations, respectively (figure 1B); the incremental costs per additional month of response were $44,334 and $105,112, respectively (table 1). For all endpoints, the NNT and incremental costs generally decreased with longer follow-up; NNT and costs were lower in the dMMR/MSI-H population than in the ITT population. Conclusions NNT estimates show dostarlimab+CP is a highly effective treatment for patients with pA/rEC. Incremental cost per outcome is in line with immunotherapies reimbursed by payers and represents a good value for money treatment. As chemotherapy is associated with high response rates, cost-per-responder analyses suggest that the value of dostarlimab+CP is largely derived from maintaining patients in response. These results support dostarlimab+CP as a new standard of care for patients with pA/rEC. Acknowledgements This study was funded by GSK. Medical editorial assistance was provided by ArticulateScience, LLC, and was funded by GSK. Trial Registration ClinicalTrials.gov, NCT03981796 References Mirza MR, et al. N Engl J Med. 2023;388:2145−2158. Ethics Approval This study used clinical trial data from the RUBY trial (NCT03981796). The trial adhered to the principles of the Declaration of Helsinki, Good Clinical Practice guidelines, and all local laws under the auspices of an independent data and safety monitoring committee. All patients provided written informed consent. Institutional Review Board approval was obtained from all study sites
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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 | 0.021 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.011 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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".