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Record W4379802500 · doi:10.3390/curroncol30060415

Safety of CDK4/6 Inhibitors Combined with Radiotherapy in Patients with Metastatic Breast Cancer: A Review of the Literature

2023· review· en· W4379802500 on OpenAlexafffundvenue
Rejane Franco, Jeffrey Cao, Michael Yassa, Tarek Hijal

Bibliographic record

VenueCurrent Oncology · 2023
Typereview
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsCentre intégré universitaire de santé et de services sociaux de l'Est-de-l'Île-de-MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalHôpital Maisonneuve-RosemontUniversity of CalgaryMcGill University Health Centre
FundersPfizer CanadaPfizer
KeywordsMedicineMetastatic breast cancerRadiation therapyOncologyBreast cancerInternal medicineCancerClinical trialPalbociclib

Abstract

fetched live from OpenAlex

Recent evidence suggests that cyclin-dependent kinase 4/6 (CDK4/6) inhibitors significantly improve progression-free survival and overall survival among metastatic breast cancer patients. However, given the effects on cell cycle arrest, there is potential for CDK4/6 inhibitors and radiotherapy (RT) to work synergistically, enhancing the effect and toxicities of RT. A comprehensive review of the literature on the combination of RT and CDK4/6 inhibitors was performed with 19 eligible studies included in the final analysis. A total of 373 patients who received radiotherapy combined with CDK4/6 inhibitors were evaluated across 9 retrospective studies, 4 case reports, 3 case series, and 3 letters to the editor. The CDK4/6 inhibitor used, RT target, and RT technique were assessed in terms of toxicities. This literature review demonstrates generally limited toxicities with the combination of CDK4/6 inhibitors and palliative radiotherapy to metastatic breast cancer patients. The current evidence is nonetheless limited, and further results of ongoing prospective clinical trials will help clarify whether these treatments can be safely combined.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.775
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.048
GPT teacher head0.402
Teacher spread0.354 · 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.

Study designOther design
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

Citations11
Published2023
Admission routes3
Has abstractyes

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