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Record W3104194802 · doi:10.14740/jh730

Prognostic Role of Lymphocyte/Monocyte Ratio in Chronic Lymphocytic Leukemia

2020· article· en· W3104194802 on OpenAlexvenueno aff
Osman Yokuş, Esma Nur Saglam, Hasan Göze, Fettah Sametoğlu, İstemi Serin

Bibliographic record

VenueJournal of Hematology · 2020
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineChronic lymphocytic leukemiaLymphocyteStage (stratigraphy)Internal medicineLymphoproliferative disordersMonocyteGastroenterologyLeukemiaDiseaseImmunologyOncologyPathologyLymphoma

Abstract

fetched live from OpenAlex

BACKGROUND: Chronic lymphocytic leukemia (CLL) is a B-lymphoproliferative disease with varying clinical characteristics, which occurs mostly in older ages. In studies from literature, we see that different parameters are examined to determine the prognosis of CLL. The main purpose of our study is to determine the relationship of lymphocyte/monocyte ratio (LMR) value in CLL, which has been previously shown to be a prognostic factor in various solid organ tumors and some hematological malignancies. METHODS: A total of 173 patients who were followed up between 2005 and 2019 were retrospectively analyzed. The diagnostic age, gender, laboratory, absolute lymphocyte and monocyte count, LMR and overall survival (OS), treatment and responses, recurrence, cytogenetic subtype and mortality rates were examined. RESULTS: The median LMR was 26.7 and it was considered as cut-off value of 26. A positive correlation was found between LMR and Rai Stage. LMR was significantly higher in patients who have an indication for treatment or who died. CONCLUSIONS: In our study, in CLL, LMR has been shown to be over 26 in advanced stages, in relapse or with indication of a treatment. With the increase of LMR, it was found that survival and disease-free gap decreased.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.022
GPT teacher head0.296
Teacher spread0.274 · 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 designBench or experimental
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

Citations6
Published2020
Admission routes1
Has abstractyes

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