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Validation of Favourable Impact of Large Granular Lymphocytosis after Allogeneic Hematopoietic Cell Transplantation

2014· article· en· W2553095985 on OpenAlexaffabout
Marc Poch Martell, Jieun Uhm, Naheed Alam, Vikas Gupta, Jeffrey H. Lipton, John Kuruvilla, Matthew D. Seftel, Hans A. Messner, Dennis Kim

Bibliographic record

VenueBlood · 2014
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsLeukemia & Lymphoma Society of CanadaPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsLymphocytosisMedicineCumulative incidenceTransplantationIncidence (geometry)Internal medicineHematopoietic stem cell transplantationHematopoietic cellImmunologyGastroenterologyHaematopoiesisBiologyStem cell

Abstract

fetched live from OpenAlex

Abstract Introduction: We previously reported on the incidence of large granular lymphocytosis (LGL) following allogeneic hematopoietic cell transplantation (allo-HCT), its favorable impact on outcome and the predictive factors associated with its development (D Kim, BMT, 2013). In the current study we aimed to validate our previous findings in an independent set of patients. Methods:All 408 patients undergoing allo-HCT at Princess Margaret Cancer Centre, Toronto, from 2007 to 2012 (replication set) were included retrospectively. Data from the previously reported set of patients undergoing allo-HCT from 2000 to 2007 (n = 418) (original set) were updated. Results:There were significant differences between original and replication sets in baseline characteristics (age, underlying disease, conditioning, GvHD prophylaxis, graft source, donor type, and incidences of GvHD and CMV viremia) in accordance to the changes over a decade in allo-HCT procedures. The cumulative incidence of LGL lymphocytosis at 3 years was 21.8% in the original set and 11.7% in the replication set (P<0.001). The median onset of LGL lymphocytosis was 362 days after HCT in the original set and 223 days in the replication set. Patients with LGL lymphocytosis showed a persistent elevation of lymphocyte count compared to patients without LGL lymphocytosis (P<0.001). Patients with LGL lymphocytosis showed a higher overall survival (OS) (86.4% vs 46.1%, P<0.001, Fig. A) and lower non-relapse mortality (NRM) (10.5% vs 36.3%, P<0.001, Fig. B) at 3 years. No significant difference was found in relapse incidence according to the development of LGL lymphocytosis (13.9% vs 19.6%, P=0.25). Multivariable analysis confirmed the favorable impact of LGL lymphocytosis on OS (HR 0.30, P=0.02) and a trend towards lower NRM (HR 0.27, P<0.001, original set; HR 0.50, P=0.22, replication set). No effect of LGL lymphocytosis on relapse incidence was demonstrated (HR 1.24, P=0.37, original set; HR 0.53, P=0.29, replication set). Patients with LGL lymphocytosis showed a trend towards a higher incidence of IST cessation after cGvHD: 63.6% at 7 years vs 53.4% in patients without LGL lymphocytosis, P=0.07. The previously identified predictive factors for the development of LGL lymphocytosis were replicated: higher incidence of LGL lymphocytosis with 1) CMV seropositive recipients (29.6% vs 5.1%, P < 0.001); 2) CMV viremia (31.0% vs 8.9%, P<0.001) and 3) chronic GvHD (28.2%, vs 5.0%, P<0.001). Conclusions: The favorable impact of LGL lymphocytosis following allo-HCT in OS and NRM, as well as the predictive factors for the development of LGL lymphocytosis were successfully validated in an independent cohort of patients. No impact of LGL lymphocytosis on relapse incidence was noted. The difference in transplantation procedures between the two cohorts, such as GvHD prophylaxis/T-cell depletion, may explain the lower incidence of LGL lymphocytosis in the replication cohort. Patients with LGL lymphocytosis showed a trend towards a higher incidence of IST cessation after cGvHD, which may explain the lower NRM. Patients with LGL lymphocytosis showed a persistent elevation of lymphocyte count and had an indolent course. OS and NRM according to the development of LGL lymphocytosis Disclosures No relevant conflicts of interest to declare.

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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)0.004
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 score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.008
GPT teacher head0.250
Teacher spread0.242 · 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".

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Citations0
Published2014
Admission routes2
Has abstractyes

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