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Abstract P3-12-01: Value-based approach to treatment of HER2-positive breast cancer: Examining the evidence

2017· article· en· W2593434036 on OpenAlexaffabout
NA Nixon, Malek B. Hannouf, S. Verma

Bibliographic record

VenueCancer Research · 2017
Typearticle
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicinePertuzumabTrastuzumabCapecitabineLapatinibMetastatic breast cancerNiceBreast cancerOncologyInternal medicineRegimenCancerCost effectivenessColorectal cancer

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.841
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.245
GPT teacher head0.469
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2017
Admission routes2
Has abstractyes

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