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Record W4405850856 · doi:10.1111/ejh.14376

Underrepresentation of Small Lymphocytic Lymphoma in Clinical Trials for Chronic Lymphocytic Leukemia

2024· article· en· W4405850856 on OpenAlexaff
Robert Puckrin, Carolyn Owen, Anthea Peters

Bibliographic record

VenueEuropean Journal Of Haematology · 2024
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsUniversity of AlbertaUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsChronic lymphocytic leukemiaChemoimmunotherapyMedicineClinical trialFollicular lymphomaInternal medicineOncologyLymphomaCancerLeukemia

Abstract

fetched live from OpenAlex

BACKGROUND: Although chronic lymphocytic leukemia (CLL) and small lymphocytic lymphoma (SLL) are the same biologic disease entity and warrant identical treatment approaches, patients with SLL have frequently been excluded from clinical trials in CLL. METHODS: This study assessed the representation of patients with SLL among Phase II or III clinical trials cited in the 2024 National Comprehensive Cancer Network (NCCN) treatment guidelines. RESULTS: Patients with SLL were explicitly eligible for only 21 (38%) of the 56 clinical trials for CLL, comprising 222 (6%) of the 3440 enrolled patients. Notably, 380 patients with SLL were enrolled in 16 separate non-CLL clinical trials alongside patients with indolent B-cell lymphomas such as follicular lymphoma. In CLL trials, patients with SLL were included in a greater proportion of studies evaluating BTK inhibitors (67%) or BTK/BCL2 inhibitor combinations (67%) compared to BCL2 inhibitors (0%) or chemoimmunotherapy (0%). CONCLUSIONS: Although recent and upcoming trials show a promising trend toward the inclusion of patients with SLL, further advocacy is needed to raise awareness of the biological similarities between CLL and SLL and to promote the representation of patients with SLL in CLL/SLL clinical research.

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)0.016
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.249
GPT teacher head0.468
Teacher spread0.219 · 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 designOther design
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

Citations3
Published2024
Admission routes1
Has abstractyes

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