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Record W3129284555 · doi:10.14740/wjon1351

Epidemiology and Clinical Characteristics of Non-Hodgkin Lymphoma in Mexico

2021· article· en· W3129284555 on OpenAlexvenueno aff
Eleazar Hernández-Ruiz, Martha Alvarado‐Ibarra, Lourdes Esthela Juan Lien-Chang, Luisa I. Banda-García, Jorge Luis Aquino-Salgado, Gabriel Barragán-Ibáñez, Eva Fabiola Ramirez-Romero, Cesar Nolasco-Cancino, Wilfrido Herrera-Olivares, Javier de Jesús Morales-Adrián, Eugenia Patricia Paredes-Lozano, María Eugenia Espitia-Ríos, Maria de Monserrat Gonzalez Lopez-Elizalde, José L. López-Arroyo, Jorge Trejo-Gómora, José A. de la Peña-Celaya, José L. Álvarez-Vera, Luara L. Arana-Luna, Annel Martínez‐Ríos, Rodrigo Reséndiz-Olea, Lucero Jazmin Rodriguez-Velasquez, Nidia Zapata-Canto, Juan Manuel Pérez-Zúñiga

Bibliographic record

VenueWorld Journal of Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLymphomaEpidemiologyFollicular lymphomaInternal medicineDiseaseStage (stratigraphy)Hodgkin lymphomaRegimenOncology

Abstract

fetched live from OpenAlex

BACKGROUND: There is no epidemiological registry in Mexico. The information about the epidemiology in our country is obtained by these types of studies, such as multicentric studies. A lot of improvements in the survival in non-Hodgkin lymphoma patients had occurred in the last 20 years. The access to treatment in these types of pathology could change the prognostic factors in Mexican Mestizos patients. The primary objective of the study was to learn what the most frequent histological varieties of non-Hodgkin lymphoma in Mexico are. The secondary objectives included clinical characteristics, treatments used, treatment response, disease-free survival and overall survival. METHODS: A retrospective, descriptive study of consecutive cases was carried out in 14 hospitals across 14 Mexican states with patients diagnosed with non-Hodgkin lymphoma using the World Health Organization (WHO) 2008 criteria. Inclusion criteria included: ≥ 18 years of age, male or female, any clinical stage at diagnosis, who had received any chemotherapy regimen, with a known outcome. Descriptive statistics was performed for all variables, and survival was assessed using Kaplan-Meier curves. RESULTS: Totally, 609 patients were enrolled, of which 545 were B-cell lymphomas and 64 were T-cell lymphomas. Median ages were 61 and 50, respectively. B-cell lymphomas were more common in males with 52.1%, and 65.5% of T-cell lymphomas occurred in females. For B-cell lymphomas, the two most frequent histological subtypes were diffuse large B-cell lymphoma in 63.9%, followed by follicular lymphoma at 18%. Meanwhile, 50% of T-cell lymphomas were of the T/natural killer (NK) subtype, and 87.1% of the patients received a CHOP-like regimen. Radiotherapy was given to 31% of B-cell Lymphomas and 46.9% of T-cell lymphomas. Overall survival at 9 years was 84.6% for B-cell lymphomas, and 73.4% for T-cell lymphomas. CONCLUSIONS: Diffuse large B-cell lymphoma constitutes the most frequent subtype for B-cell lymphomas in Mexico. The most frequent T-cell lymphoma is the NK/T histological subtype.

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)0.001
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.053
GPT teacher head0.408
Teacher spread0.355 · 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

Citations21
Published2021
Admission routes1
Has abstractyes

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