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Record W3015876203 · doi:10.1080/16078454.2020.1749473

Up to half of patients diagnosed with chronic lymphocytic leukemia in México may not require treatment

2020· article· en· W3015876203 on OpenAlexaff
Antonio Cruz-Mora, Iván Murrieta-Álvarez, Juan Carlos Olivares‐Gazca, Andrés A. León‐Peña, Yahveth Cantero‐Fortiz, Yarely Itzayana García-Navarrete, Luisa Fernanda Sánchez-Valledor, Dina Khalaf, Guillermo J. Ruiz‐Delgado, Guillermo J. Ruíz‐Argüelles

Bibliographic record

VenueHematology · 2020
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsChronic lymphocytic leukemiaMedicineLeukemiaInternal medicineOncologyCancer researchImmunology

Abstract

fetched live from OpenAlex

Introduction: Although therapeutic choices for patients with chronic lymphocytic leukemia (CLL) were once limited, treatment of this disease has vastly improved in the last decades.Patients and methods: Consecutive CLL patients diagnosed in a single institution were analyzed. Treatment was withheld in persons with CLL Rai stage 0 or 1, until progression and in persons with stages 2–4, with a negative expression of ZAP-70 until progression. Between 1983 and 1991, patients were give chlorambucil and prednisone (CP); after 1991 fludarabine and cyclophosphamide (FC) and after 1998, rituximab and FC (FCR).Results: 98 patients with CLL were identified; 49 were followed for >3 months. 21 persons (43%) did not require treatment nor progressed; 14 received CP, 6 FC, 7 FCR and one rituximab. Median overall survival (OS) has not been reached, being above 247 months; median OS for patients given CP was 115 months, for FC above 132 months and for FCR above 136 months (p > 0.5).Conclusion: CLL seems to be less aggressive in Mexican mestizos than in Caucasians; 43% of patients do not need treatment at all.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

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)0.0090.001

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 head0.034
GPT teacher head0.305
Teacher spread0.271 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2020
Admission routes1
Has abstractyes

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