588 Dostarlimab + chemotherapy for the treatment of primary advanced or recurrent endometrial cancer (pA/rEC) in the RUBY trial: post hoc analysis of the costs of grade ≥3 adverse events (AEs)
Bibliographic record
Abstract
Background In the RUBY trial ( NCT03981796), dostarlimab + carboplatin-paclitaxel (CP) significantly increased progression-free survival (PFS) compared with placebo+CP in patients with pA/rEC. Grade ≥3 AEs were more frequent with dostarlimab+CP vs placebo+CP. This analysis estimated the difference in per-patient costs of grade ≥3 AEs with dostarlimab+CP vs placebo+CP.Methods This AE cost model used grade ≥3 treatment-emergent AE (TEAE) and treatment-related AE (TRAE) data from RUBY part 1. Grade ≥3 AEs are likely to require specialized clinical treatment and/or hospitalization; as a surrogate, management costs were extracted from the US Healthcare Cost and Utilization Project using 2020 inpatient hospitalization data. In the base-case analysis, mean per-patient costs for each AE were calculated by multiplying management cost by the number of AEs observed and dividing by the number of participants. In a scenario analysis, number needed to treat to harm (NNTH) or benefit (NNTB) was derived from the risk difference for each AE, and mean per-patient cost differences were calculated by dividing management cost by NNTH or NNTB. All analyses were performed in the mismatch repair-deficient (dMMR)/microsatellite instability-high (MSI-H) and intention-to-treat (ITT) populations.Results In the base-case analysis in the dMMR/MSI-H group, aggregate per-patient costs were $26,968 (US$) with dostarlimab+CP vs $35,862 with placebo+CP (difference: −$8,894) for TEAEs ( figure 1) and $19,775 vs $26,005, respectively, (difference: −$6,230) for TRAEs (figure 2). Lower predicted AE costs for dostarlimab+CP vs placebo+CP were driven by higher costs of managing decreases in neutrophil and white cell counts, which occurred more frequently in the placebo arm. In the ITT population, aggregate per-patient costs were $28,199 with dostarlimab+CP vs $25,219 with placebo+CP (difference: $2,980) for TEAEs and $19,375 vs $19,156, respectively, (difference: $219) for TRAEs. The higher predicted costs for dostarlimab+CP in the ITT population were driven by comparatively smaller differences in costs of neutrophil and white cell count decreases but higher costs of anemia, sepsis, peripheral neuropathy, and metabolic enzyme derangements. AE cost differences were qualitatively similar in the scenario analysis.Conclusions In the dMMR/MSI-H population, grade ≥3 TEAE and TRAE costs were predicted to be substantially lower for dostarlimab+CP. In the ITT population, grade ≥3 TEAE costs were predicted to be somewhat higher for dostarlimab+CP, while grade ≥3 TRAE costs were similar between arms. Together with the significant PFS benefits, these results further support the use of dostarlimab+CP as a new standard of care, especially in patients with dMMR/MSI-H pA/rEC.Acknowledgements This study was funded by GSK. Medical editorial assistance was provided by ArticulateScience, LLC, and was funded by GSK.Trial Registration U.S. National Library of Medicine ClinicalTrials.gov, NCT03981796Abstract 588 Figure 1Grade 23 TEAEs in the (A) dMMR/MSI-H and (B) ITT populations. In each panel, the 5 biggest positive (higher costs for placebo+CP) and negative (higher costs for dostarlimab+CP) contributors are shown.Abstract 588 Figure 2Grade 23 TRAEs in the (A) dMMR/MSI-H and (B) ITT populations. In each panel, the 5 biggest positive (higher costs for placebo+CP) and negative (higher costs for dostarlimab+CP) contributors are shown.
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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 | 0.011 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.011 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".