Combination of the Centre for International Blood and Marrow Transplant Registry Risk Score and the Global Severity Score Enhances Prognostic Risk Stratification in Patients Receiving Frontline Therapy for Chronic Graft-versus-Host Disease
Bibliographic record
Abstract
The Centre for International Blood and Marrow Transplant Registry (CIBMTR) score has been shown to be prognostic for overall survival (OS) and nonrelapse mortality (NRM) but has been shown in several single-center studies to classify a large proportion of patients with chronic graft-versus-host disease (cGVHD) in the lower risk groups (RG1 to RG2), thereby limiting its prognostic utility for those patients. We evaluate the CIBMTR score, the Global Severity Score (GSS), and a novel risk score developed to improve on the limitations of the CIBMTR with respect to clinically relevant outcomes, including failure-free survival (FFS), in patients receiving frontline systemic treatment for cGVHD. We identified 277 patients between 2002 and 2012 at the Princess Margaret Cancer Centre in Toronto, Canada, who developed cGVHD and were treated with at least 1 line of systemic therapy. cGVHD was graded by GSS, and patients were stratified by CIBMTR. We evaluated OS, NRM, relapse, and FFS within GSS grade groups, as well as CIBMTR RGs, and used a novel prognostic risk score. The median FFS duration was 164 days in the severe GSS group versus 238 days in the moderate-grade group and 304 days in mild-grade group (P= .001). The median FFS duration was 501 days in CIBMTR RG1 versus 291 days in RG2 and 166 days in RG3 to RG6 (P = .003). A novel risk score combining the GSS and CIBMTR scores was prognostic of OS, NRM, and FFS and was able to subdivide patients with cGVHD in CIBMTR RG1 to RG2 into distinct prognostic risk categories. The CIBMTR risk score and the GSS are well correlated with FFS, OS, and NRM following frontline systemic treatment for cGVHD. A new risk score model combining the CIBMTR risk score and the GSS could enhance risk stratification in the lower CIBMTR risk groups.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".