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The NIH Chronic Gvhd Global Score and the CIBMTR Risk Score Correlate Well with Failure Free Survival Following Frontline Systemic Corticosteroid Therapy for Chronic Gvhd

2014· article· en· W2521713921 on OpenAlexaffabout
Jieun Uhm, Nada Hamad, Elizabeth Shin, Vikas Gupta, John Kuruvilla, Jeffrey H. Lipton, Hans A. Messner, Matthew D. Seftel, Dennis Dong Hwan Kim

Bibliographic record

VenueBlood · 2014
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineSystemic therapyInternal medicineClinical endpointOncologyCancerClinical trialBreast cancer

Abstract

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Abstract Introduction: While the National Institutes of Health (NIH) consensus criteria (NCC) on diagnosis and staging of cGVHD are now widely used, minimal attempts have been made to validate its ability to predict the outcomes of cGVHD treatment. Arora et al. analyzed data from the Center for International Blood and Marrow Transplant Registry (CIBMTR) and suggested that the CIBMTR risk score is a predictive factor for overall survival (OS) and non-relapse mortality (NRM). The failure free survival (FFS) has been recently proposed as an endpoint for clinical trials on treatment of cGVHD. With this study we aimed to evaluate if the cGVHD global score by the NCC and the CIBMTR risk groups (RG) could predict the treatment outcomes of frontline systemic steroid therapy for cGVHD. Method: We retrospectively reviewed 668 consecutive patients who underwent allo-HCT between 2004 and 2012 at the Princess Margaret Cancer Centre, Toronto, Canada. We then identified 312 patients who had a diagnosis of cGVHD and received at least one systemic treatment for this. Thirty-five patients were excluded from the analysis as they were not treated with systemic corticosteroids and the remaining 277 patients were included in the final analysis. Chronic GVHD was reclassified and graded using the NCC. The CIBMTR risk score was also calculated and patients were stratified into 3 RGs accordingly. We evaluated the treatment outcomes including OS, NRM, relapse and FFS. FFS was defined as time to a switch in systemic therapy (i.e. failure of the treatment), NRM or relapse. The Kaplan-Meier method was used for OS and FFS. The cumulative incidences of NRM and relapse were calculated considering competing risks. Multivariate analysis was performed using the Cox proportional hazard regression model for OS and FFS. The Fine-Gray method was used for the incidences of NRM and relapse in multivariate analysis. Results: With a median follow-up duration of 26 months among survivors, the median to onset of cGVHD was 140 days (range, 45-381). One hundred and two patients (36.9%) were classified as classical cGVHD and 175 patients (63.1%) as overlap syndrome. At the onset of cGVHD 90 patients (32.5%) had mild cGVHD by the NIH global score (NIH GS), moderate in 143 patients (51.6%) and severe in 44 patients (15.9%). Thirty-three patients (11.9%) presented with progressive type onset (PTO). The CIBMTR risk score was available in 227 patients and we were able to stratify them into those with RG1 (score 0-2; n=32, 14.1%), RG2 (score 3-6; n=162; 71.4%) and RG3-6 (score ≥7; n=33, 14.5%). The median FFS of the 277 patients was 255 days. A severe GS correlated with the worst FFS: median FFS duration was 164 days in severe vs 238 days in moderate vs 304 days in mild (p=0.001). The CIBMTR RG also reflected the prognosis of patients after cGVHD treatment: the higher the RG the shorter the median duration of FFS: 166 days in RG3-6 vs 291 days in RG2 vs 501 days in RG1 (p=0.003). The OS at 2 years from the onset of cGVHD was 74.3%. A severe GS was associated with a worse OS: 55.1% in severe vs 79.9% in moderate vs 76% in mild grade (p<0.001). The CIBMTR RG was predictive of OS: 92% in RG1 vs 81.5% in RG2 vs 38.9% in RG3-6 (p<0.001). The cumulative incidence of NRM was 7.6% at 2 years. The NIH GS was predictive of NRM. The 2-year NRM rate was lowest with a mild GS at 2.4%, intermediate with a score of moderate at 4.8%, but significantly higher with a severe score at 27.5% (p<0.001). The CIBMTR RGs were also predictive of NRM: 0% for RG1, 6.1% for RG2 and 21.9% for RG3-6 (p=0.001). The cumulative incidence of relapse at 2 years was 9.2% and it was not associated with either the NIH GS or CIBMTR RGs.. Multivariate analysis confirmed that an NIH GS of severe and the CIBMTR RG3-6 and the overlap syndrome were associated with worse FFS: A severe NIH GS hazard ratio (HR) 1.65, p=0.011; CIBMTR RG3-6, HR 2.39, p=0.006; overlap syndrome, HR 1.38, p=0.058. A NIH GS of severe and CIBMTR RG3-6 were verified as adverse risk factors for NRM: A severe NIH GS, HR 6.31, p=0.001; CIBMTR RG3-6, HR 3.44, p=0.0081. CIBMTR RG3-6 and PTO were identified as unfavorable factors for OS: CIBMTR RG3-6, HR 5.14, p=0.002; PTO, HR 3.20, p<0.001. Conclusion: The NIH GS and CIBMTR RG for cGVHD correlated well with FFS and NRM following first line systemic treatment for cGVHD with corticosteroid-based regimens. Disclosures No relevant conflicts of interest to declare.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.009
GPT teacher head0.233
Teacher spread0.224 · 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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