MétaCan
Menu
Back to cohort

Current Trends in the Treatment of Human Epidermal Growth Factor Receptor-2 Negative Breast Cancer

2020· article· en· W4235292000 on OpenAlexvenueno aff
Palanisamy Sivanandy, Suresh Kumar Shanmugam, Rui Ying Lau, Jonathan Yvong Syen Chin, Xiao Xiang Lee, Yun Yun Lau, Wai Ching Lee, Iqbal Danial Said, Jing Ying Lee, Karthikayini Krishnasamy

Bibliographic record

VenueJournal of Pharmacy and Nutrition Sciences · 2020
Typearticle
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOlaparibBreast cancerOncologyCancerInternal medicineDrugPharmacology

Abstract

fetched live from OpenAlex

Breast cancer affect almost 1 in 8 women and it is highest in developed and developing countries. There are many drugs exist for the treatment of breast cancer, but still the incidence of mortality and morbidity are high among all cancer types in most countries. Even though the conventional therapies play a major role in the management of breast cancer, its complications are obvious and unavoidable. The newer targeted drug therapy came in place to reduce complications in some extent, but not fully. Hence, a review was aimed to analyse the efficacy and safety of newer anticancer drugs that approved for the treatment of breast cancer by US-FDA from 2017 to 2019. The Olaparib, Talazoparib, and Ribociclib are the newly approved drugs for the treatment of breast cancer during this review period. Among these new drugs, Olaparib and Talazoparib alone or in combination with other anticancer drugs considered as safe and efficacious. Patients with Olaparib or Talazoparib as monotherapy have median progression-free survival of 2.8 to 8.6 months longer and has 42-46% lower risk of death (P

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 score0.746
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.104
GPT teacher head0.427
Teacher spread0.323 · 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".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Pharmacy and Nutrition SciencesSame topicAdvanced Breast Cancer TherapiesFrench-language works237,207