Abstract P3-12-01: Value-based approach to treatment of HER2-positive breast cancer: Examining the evidence
Bibliographic record
Abstract
Abstract Outcomes of HER2-positive breast cancer have improved significantly with use of targeted therapies. Survival in both early (EBC) and metastatic breast cancer (MBC) has improved along with gains in quality of life. With increasing costs of cancer care, it became imperative that health systems evaluate cost-effectiveness and value provided by new therapies. Methods: We conducted a review of 'value' utilizing the ASCO 2015, ASCO 2016 (revised) and ESMO framework for all currently available HER2 targeted therapies. We performed a systematic review of cost-effectiveness analyses (CEAs) of these therapies across the neoadjuvant, adjuvant, and metastatic disease settings. We included economic evaluations from published literature and government agencies involved in drug-approval assessments from NICE (UK), pCODR (Canada), and PBAC (Australia). Results: 22 studies evaluating 1-year of trastuzumab (H) in EBC were identified. Of these, 17 found the regimen cost-effective (CE). Three of 22 plus an additional 1 evaluated 9 weeks H, all of which found it CE. NICE and PBAC determined adjuvant H to be CE, consistent with clinical benefit (Table 1). There are currently no academic CEAs of neoadjuvant pertuzumab (P). It has been evaluated in drug-approval processes by NICE and pCODR, both finding cost-effectiveness highly uncertain. In MBC, 6 studies evaluating H for first line were identified. The combination with chemotherapy was CE in 3 of 4 studies, whereas monotherapy and combination with anastrazole were not. A total of 9 studies evaluating lapatinib for MBC were identified. While it was CE combined with capecitabine for second line, in all other combinations it was not. Two studies evaluating P for MBC did not find the regimen CE, despite significant clinical benefit. However, PBAC considers the regimen CE and pCODR recommended funding based on net clinical benefit, whereas NICE did not. No academic CEAs of trastuzumab emtansine (T-DM1) in the literature were identified however cost-effectiveness in second line has been evaluated by pCODR, NICE and PBAC. All groups found it not CE, even with very high clinical benefit (Table 1). Table 1: ASCO Net Health Benefit (NHB), modified NHB (mNHB) and ESMO Magnitude of Clinical Benefit Score (MCBS) for landmark trials in HER2+ breast cancer compared with cost-effectivenessStudySettingRegimenNHBmNHBMCBSCost-EffectiveNeoSphereEBC (Neoadjuvant)DH+/- P->surgery->FECNA*NA*NA*-TRYPHAENA"DCH+P->surgeryNANANA-NSABP-B31/NCCTGN9831EBC (Adjuvant)AC-based chemo +/- H4828AYFinHer"FEC based chemo +/- H x 9 weeksNA*NA*NA*YHERA"Chemo +/- 1y H3226AYSlamon et alMBC (1st line)TH vs T1617.72YCLEOPATRA"DHP vs. DH32324NTanDEM"Anastrozole +/- H2213.93NJohnston et al"Letrozole +/- Lapatinib5513.61NEMILIAMBC (2nd line)T-DM1 vs. lapatinib + cape4246.45NEGF100151MBC (>/=2nd line)Cape + lapatinib vs. cape alone1629.44N* = Not significant Conclusion: While there is consistent value provided by Her2 targeted therapies, there is generally lack of support for these in MBC based on cost-effectiveness analysis. We need to work towards a model that integrates value, clinical benefit and cost to implement new therapies in cancer, including HER2 positive breast cancer. Citation Format: Nixon NA, Hannouf M, Verma S. Value-based approach to treatment of HER2-positive breast cancer: Examining the evidence [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P3-12-01.
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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 | 0.026 | 0.107 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".