Abstract PS19-04: Exploring the broad societal value of pembrolizumab in triple-negative breast cancer in Canada
Bibliographic record
Abstract
Abstract Background: The impact of breast cancer is multifaceted; for each patient there are personal, social, and financial consequences which have wider societal and economic consequences. Cost-effectiveness analyses for health technology assessment (HTA) purposes are predominantly conducted from the traditional payer perspective and often do not capture these wider impacts. Pembrolizumab, a programmed death receptor-1 (PD-1)-blocking antibody indicated for the treatment of triple-negative breast cancer (TNBC), has demonstrated substantial survival benefits to patients. Our study analyzes the traditional societal and broader societal net monetary benefit (NMB) of pembrolizumab-based therapies for early TNBC (eTNBC) and metastatic TNBC (mTNBC) in a Canadian setting. We incorporate novel elements of value described in the third ISPOR Special Task Force Report alongside new elements considered relevant to the disease. METHODS: Two validated and HTA approved cost-effectiveness models for pembrolizumab in eTNBC and mTNBC were expanded to include elements constituting the broad societal perspective. For the traditional societal perspective, this included productivity. For the broad societal perspective, the additional elements included caregiver burden, insurance value, value of hope, real option value, severity of disease, out-of-pocket expenses, and fertility treatment costs. A targeted literature review was conducted to identify inputs for each element. A standard of care comparator, consisting of chemotherapy, was generated for each indication; formed of a weighted average of the various chemotherapy comparators by indication based on market share. Canadian list prices were used for all treatment acquisition costs. An overall NMB was generated across indications by weighting individual results by prevalence and using a willingness to pay threshold of CAD$100,000. Probabilistic sensitivity analysis (PSA) and scenario analyses were implemented to analyze the robustness of results to plausible variation. Results: The results showed that adopting a broad societal perspective resulted in more favourable cost-effectiveness results. Specifically, the overall broad societal NMB was CAD$1,113,858, almost four times greater than the traditional payer (CAD$282,644) and traditional societal NMB (CAD$279,534). For mTNBC, the NMB was positive for the broad societal perspective whereas the two traditional perspectives yielded a negative NMB. For eTNBC, pembrolizumab consistently resulted in a positive NMB for all three perspectives, however the broad societal perspective resulted in a substantially higher NMB. This was largely driven by the substantial insurance value impact on quality-adjusted life years. The next most influential element was the value of hope. PSA was consistent with deterministic results. Scenario analysis demonstrated that the choice of input source used to inform the broad elements of value had a substantial impact on NMB. Discussion: The inclusion of broader societal elements of value resulted in a significantly higher NMB than the traditional payer perspective for both indications, indicating that society as a whole may place a substantially greater value on access to treatment than suggested from a traditional payer perspective. However, the paucity of disease-specific input data and the uncertain estimation of some of the broad societal perspective elements of value result in challenges with interpretation. Overall, the research highlights the importance of considering alternative and broader perspectives of analysis in health technology evaluation, but more research is needed to robustly parameterize novel elements of value. Notably, this study indicates that the traditional payer and societal perspectives commonly used for HTA may be missing key elements of value, and thus underestimate the value that general societal places on access to innovative therapies. Citation Format: Kate Young Brook E, Madin-Warburton M; Wijenayake N; Mishkin K; Meilleur M-C; Davies A. Exploring the broad societal value of pembrolizumab in triple-negative breast cancer in Canada [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2024; 2024 Dec 10-13; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(12 Suppl):Abstract nr PS19-04.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.014 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 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".