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Record W2893126727 · doi:10.1016/j.onsig.2018.09.003

Novel agents in the Canadian therapeutic landscape of chronic lymphocytic leukemia

2018· article· en· W2893126727 on OpenAlexaffabout
Anthea Peters, Andrei Fagarasanu

Bibliographic record

VenueOncology Signaling · 2018
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsAlberta Cancer FoundationUniversity of Alberta
Fundersnot available
KeywordsChronic lymphocytic leukemiaLeukemiaMedicineGeographyImmunology

Abstract

fetched live from OpenAlex

In this brief commentary, we discuss oral novel agents within in the armementarium of therapeutic options for Canadian patients with chronic lymphocytic leukemia (CLL). Previously limited to chemotherapy, the Canadian patient with relapsed or refractory CLL has the option of treatment with B-cell receptor inhibitors ibrutinib or idelalisib (combined with rituximab), both individually showing superiority to anti-CD20 monoclonal antibody comparators regardless of high-risk deletion 17p (del(17p)) status in phase 3 clinical trials . BCL2-inhibitor venetoclax shows impressive efficacy for previously-treated patients with del(17p), but though approved, it is not yet funded. For treatment-naïve patients, ibrutinib has proven superior to chemotherapy for those over 65 with comorbidities, but its role remains to be seen for the young and/or fit. Whereas oral novel agents are generally well-tolerated, some side effects , such as infection, hemorrhage , cardiac arrhythmias and tumour lysis syndrome , can be severe, therefore expert clinical vigilance is essential. Regarding sequencing of these agents, most patients failing ibrutinib or idelalisib do respond to venetoclax . While future studies using combinations of novel agents may eventually obviate the use of chemotherapy for CLL, regimens that can be stopped when minimal residual disease is achieved, such as venetoclax, are particularly relevant for our publicly-funded health care system. For Canadian CLL patients, the availability of oral novel agents has greatly expanded treatment options and is improving outcomes.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.896

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.069
GPT teacher head0.363
Teacher spread0.294 · 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 designSimulation or modeling
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

Citations1
Published2018
Admission routes2
Has abstractyes

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