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Abstract P6-10-03: Comparative efficacy of everolimus in combination with exemestane and chemotherapy for advanced breast cancer in terms of progression-free survival

2013· article· en· W1984252859 on OpenAlexaff
Shannon Cope, J Zhang, Brielan Smiechowski, Surampalli Gurunath, Stephen Saletan, JP Jansen, P. Schmid

Bibliographic record

VenueCancer Research · 2013
Typearticle
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsNovartis (Canada)
Fundersnot available
KeywordsEverolimusMedicineExemestaneOncologyInternal medicineBreast cancerRandomized controlled trialProgression-free survivalHazard ratioCancerMeta-analysisChemotherapyTamoxifenConfidence interval

Abstract

fetched live from OpenAlex

Abstract Background: For hormone receptor-positive (HR+) advanced breast cancer (ABC), guidelines recommend endocrine therapy as the preferred option even in the presence of visceral disease. If there is evidence of endocrine resistance or rapidly progressive disease requiring a fast response then chemotherapy is recommended. The randomized controlled trial (RCT) BOLERO-2 demonstrated that everolimus plus exemestane (EVE+EXE) more than doubled median progression-free survival (PFS) compared with placebo+EXE while still maintaining quality of life in HR+/HER2- ABC patients who recurred or progressed during or after non-steroidal aromatase inhibitors (NSAIs). EVE+EXE offers a viable new line of therapy which can delay treatment with chemotherapy. Therefore, comparative evidence of EVE+EXE versus chemotherapies is relevant. In addition, such data will provide useful information for health technology assessment. Objective: 1) Assess the feasibility of network-meta-analysis (NMA) to compare the efficacy of EVE+EXE with chemotherapies in ABC in terms of PFS. 2) If feasible, to conduct the NMA. Methods: A systematic review of EMBASE, Medline, and Cochrane was performed to identify RCTs concerning the efficacy of everolimus, alternative hormonal therapies, and alternative chemotherapies for ABC in terms of PFS in order to facilitate an indirect comparison of everolimus versus chemotherapy. PFS data from published Kaplan-Meier curves for each treatment and RCT were synthesized and indirectly compared with random effects Bayesian Weibull network-meta-analysis (NMA) models. Analyses were performed assuming treatment effects as expressed with hazard ratios vary over time. Results: Based on a search of 6271 citations 24 RCTs were included. Differences across RCTs were identified in terms of age, post-menopausal status, receptor status, prior exposure to hormonal and chemotherapy, and types of hormonal therapies, visceral metastases, and performance status. Despite the limitations due to these differences, a NMA was performed to provide a broad estimate regarding comparative PFS for everolimus versus chemotherapy to inform current practice. Results of NMA in terms of mean PFS (i.e. area under the curve) up to 20 months are presented in Table 1. Sensitivity analyses will be performed to explore the impact of these differences on the robustness of the results. Table 1. Mean PFS until 20 months as obtained with NMATreatmentMean PFS time up to 20 months95% Credible Interval95% Credible IntervalEpirubicin6.162.5312.17Liposomal doxorubicin6.663.1212.00Paclitaxel7.103.7811.90Pegylated liposomal doxorubicin7.143.0913.56Doxorubicin7.353.9612.09Vinorelbine7.552.9914.28Docetaxel7.924.3712.45Capecitabine9.905.0316.67Nab paclitaxel10.105.4215.75Exemestane+ Everolimus12.216.2116.98 Conclusions: It is feasible to conduct NMA, however, differences in patient characteristics identified among studies are likely to have resulted in over or underestimation of the relative treatment effects. Based on the NMA, EVE+EXE is expected to be at least as efficacious as selected chemotherapies regarding PFS. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P6-10-03.

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)0.000
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 score0.702
Threshold uncertainty score0.560

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.051
GPT teacher head0.428
Teacher spread0.377 · 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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Citations1
Published2013
Admission routes1
Has abstractyes

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