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Record W3080816877 · doi:10.1136/esmoopen-2020-000842

Endocrine therapy-based treatments in hormone receptor-positive/HER2-negative advanced breast cancer: systematic review and network meta-analysis

2020· review· en· W3080816877 on OpenAlexaff
Mariana Brandão, Christian Maurer, Patrícia Klarmann Ziegelmann, Noam Falbel Pondé, Arlindo R. Ferreira, Samuel Martel, Martine Piccart, Evandro de Azambuja, Márcio Debiasi, Matteo Lambertini

Bibliographic record

VenueESMO Open · 2020
Typereview
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsCentre intégré de santé et de services sociaux de Chaudière-AppalachesCentre Intégré de Santé et de Services Sociaux des LaurentidesHôpital Charles-Le Moyne
FundersSeagenServierG1 TherapeuticsAmgenPfizerGenomic HealthGenentechAstraZenecaEli Lilly and Company
KeywordsMeta-analysisBreast cancerHormone receptorOncologyMedicineInternal medicineCancerHER2 negativeHormone therapyEndocrine systemHormoneMetastatic breast cancer

Abstract

fetched live from OpenAlex

BACKGROUND: Several endocrine therapy (ET)-based treatments are available for patients with advanced breast cancer. We assessed the efficacy of different ET-based treatments in patients with hormone receptor-positive/HER2-negative advanced breast cancer with endocrine-sensitive or endocrine-resistant disease. METHODS: We searched Medline and Cochrane Central Register of Controlled Trials up to 15 October 2019 and abstracts from major conferences from 2016 to October 2019. We included phase II/III randomised trials, comparing ≥2 ET-based treatments. Progression-free survival (PFS) and overall survival (OS) were analysed by network meta-analyses using MTC Bayesian models based on both fixed-effect and random-effect models; relative treatment effects were measured as HRs and 95% credibility intervals (CrI). All statistical tests were two-sided. Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed and this systematic review is registered in the PROSPERO database. RESULTS: 55 publications reporting on 32 trials (n=12 293 patients) were included. Regarding PFS in the endocrine sensitive setting (n=5200; 12 trials), the combination of cyclin-dependent kinases (CDK)4/6-inhibitors (CDK4/6i)+fulvestrant 500 mg (F500) was likely the most effective treatment (surface under the cumulative ranking curve (SUCRA)=97.3%), followed by CDK4/6i+aromatase inhibitor ±goserelin; there was no significant difference between them (HR 0.82; 95% CrI 0.54-1.25). Regarding OS (n=2157; five trials), the most effective treatment was probably CDK4/6i+F500 (SUCRA=97.3%); comparing CDK4/6i+F500 versus F500 held a HR of 0.77 (95% CrI 0.63-0.95). Regarding PFS in the endocrine-resistant setting (n=6635; 20 trials), CDK4/6i+F500 was likely the most effective treatment (SUCRA=95.7%), followed by capivasertib+F500, without significant difference between them (HR 0.91; 95% CrI 0.60-1.36). For OS (n=4377; 11 trials), the most effective treatments were capivasertib+F500 (SUCRA=84.7%) and CDK4/6i+F500 (SUCRA=69.9%). Comparing CDK4/6i+F500 versus F500 held a HR of 0.77 (95% CrI 0.67-0.89). CONCLUSIONS: CDK4/6i+F500 is likely the best treatment option in both endocrine-sensitive and endocrine-resistant diseases for PFS, and in endocrine-sensitive patients for OS. Concerning OS in endocrine-resistant patients, capivasertib+F500 and CDK4/6i+F500 are likely the best treatments. PROSPERO REGISTRATION NUMBER: CRD42018104628.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.041
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0170.032
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.080
GPT teacher head0.395
Teacher spread0.315 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations32
Published2020
Admission routes1
Has abstractyes

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