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Evaluation of a New Prognostic Index for Peripheral T-Cell Lymphoma, Unspecified (PTCL-US).

2005· article· en· W2594366765 on OpenAlexaff
Heather L. McArthur, Mukesh Chhanabhai, Gascoyne D. Randy, Connors M. Joseph, Savage J. Kerry

Bibliographic record

VenueBlood · 2005
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsInternational Prognostic IndexMedicineInternal medicineLymphomaPeripheral T-cell lymphomaProportional hazards modelStage (stratigraphy)CancerDiffuse large B-cell lymphomaNot Otherwise SpecifiedOncologyGastroenterologyT cellImmunologyImmune systemBiology

Abstract

fetched live from OpenAlex

Abstract Background: Peripheral T-cell lymphoma, unspecified (PTCL-US) represents the largest subtype of PTCLs among Western populations. The prognosis of this heterogeneous group is poor with a 5-year overall survival (OS) of approximately 30%. The biological diversity of this subtype has prompted various attempts at refining clinical risk groups. For instance, the International Prognostic Index (IPI), first validated in DLBCL, has also been validated in PTCL-US in several studies. Recently, however, a new Prognostic Index for PTCL-US (PIT) has been proposed (Gallamini et al Blood103 (7): 2004). The purpose of this study was to apply the PIT to all patients with PTCL-US diagnosed and treated at the British Columbia Cancer Agency (BCCA) and to compare its prognostic utility with the IPI. Methods: The BCCA Lymphoid Cancer Database was screened to identify all patients over 18 y diagnosed with PTCL-US by the World Health Organization classification system between January 1981 and June 2004. Patients were excluded if the diagnosis occurred outside of British Columbia or if the pertinent prognostic information was incomplete. Five year OS estimates were calculated for each variable in both the IPI (age >60 y, LDH> normal, PS ≥2, Stage III/IV and >1 extranodal sites) and PIT models (age, LDH> normal, PS ≥2 and bone marrow involvement). Five year OS estimates were then calculated for IPI groups 1, 2 and 3 (0/1, 2/3 and 4/5 factors, respectively) as well as PIT groups 1 through 4 (0, 1, 2 and 3/4 factors, respectively). Results: Of the 134 patients identified, the median age was 61 y and the male to female ratio was 1.6. The predominant sites of extranodal involvement were bone marrow (10%), bone (6%), liver (4%), skin (4%), soft tissue (4%), lung (3%) and GI (3%). As demonstrated in figure 1, 5 year OS estimates were 73%, 24% and 22% for IPI groups 1, 2 and 3 (p=10−4), respectively and 76%, 35%, 25% and 19% for PIT groups 1 through 4, respectively (p=10−4 ). There was no difference between the prognostic models in the subset of 107 (80%) patients treated with CHOP-based chemotherapy. Conclusions: Although the PIT was as effective as the IPI in defining clinical risk groups among PTCL-US patients, it did not provide any additional information in this study. Since the IPI is a well-established, familiar tool with similar prognostic capacity, it is reasonable to continue to apply this model in PTCL-US. With ongoing advances in gene expression profiling, it is likely that new biological models will emerge which may be used in combination with the IPI to better prognosticate this heterogeneous group. Figure Figure

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)0.002
metaresearch head score (Gemma)0.006
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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.035
GPT teacher head0.292
Teacher spread0.256 · 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

Citations1
Published2005
Admission routes1
Has abstractyes

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