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Record W3134027539 · doi:10.2217/fon-2020-1264

CDK4/6 Inhibitors in HR+/HER2- Advanced/metastatic Breast Cancer: A Systematic Literature Review of Real-World Evidence Studies

2021· review· en· W3134027539 on OpenAlexaff
Nadia Harbeck, Meaghan Bartlett, Dean Spurden, Becky Hooper, Lin Zhan, Emily Rosta, Chris Cameron, Debanjali Mitra, Anna Zhou

Bibliographic record

VenueFuture Oncology · 2021
Typereview
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsEVERSANA (Canada)
FundersPfizer
KeywordsMedicineOncologyMetastatic breast cancerInternal medicineBreast cancerTrastuzumabReal world evidenceCancerGynecology

Abstract

fetched live from OpenAlex

Background: This review aims to qualitatively summarize the published real-world evidence (RWE) for CDK4/6 inhibitors (CDK4/6i) approved for treating HR+, HER2-negative advanced/metastatic breast cancer (HR+/HER2- a/mBC). Materials & methods: A systematic literature review was conducted to identify RWE studies of CDK4/6i in HR+/HER2- a/mBC published from 2015 to 2019. Results: This review identified 114 studies, of which 85 were only presented at scientific conferences. Most RWE studies investigated palbociclib and demonstrated improved outcomes. There are limited long-term and comparative data between CDK4/6i and endocrine monotherapy, and within the CDK4/6i class. Conclusion: Available RWE suggests that CDK4/6i are associated with improved outcomes in HR+/HER2- a/mBC, although additional studies with longer follow-up periods are needed.

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)0.007
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.007
Bibliometrics0.0090.009
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.062
GPT teacher head0.456
Teacher spread0.394 · 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 designSystematic review
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

Citations75
Published2021
Admission routes1
Has abstractyes

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