Disease Risk Index Predicts Relapse in Children Undergoing Allogeneic Hematopoietic Cell Transplantation (HCT)
Bibliographic record
Abstract
Relapse is most common cause of death after HCT. However, given the heterogeneity of diseases and disease states among patients (pts), risk for relapse is often difficult to manage in clinical trials when survival is the endpoint. The Disease Risk Index (DRI) predicts overall survival (OS) based on pre-HCT disease characteristics such as type of disease, remission status, and cytogenetic abnormalities and can be used to group heterogeneous diseases into 4 risk strata: very high risk [VHR, 1% of pts], high risk [HR, 23%], intermediate risk [IR, 64%], and low risk [LR, 12%] (Armand, Blood, 2014). OS for each of these strata is distinctly different. The DRI has been validated for adults, but not for children. Furthermore, the DRI cannot be calculated for some pediatric diseases like juvenile myelomonocytic leukemia (JMML). To determine its validity for children we calculated the DRI for 280 pediatric pts transplanted between 2008 and 2018 at Mount Sinai Acute GVHD International Consortium centers. The median age was 8.9 years (range, 0.4 - 17). The most common indications for HCT were ALL (51%), AML (31%), MDS (10%), and JMML (4%). Donors were adult unrelated donors (48%), unrelated cord blood (20%), haploidentical donors (17%), and matched siblings (15%). We first determined 2y survival by DRI for the 270 pts without JMML. Survival for JMML was closest to the VHR strata and we grouped JMML with VHR for all further analyses. The size of each of the risk strata were different for children compared to adults, VHR (n=32, 11%), HR (n=108, 39%), IR (n=128, 46%), and LR (n=12, 4%). Given the small number of LR pts, we excluded them from further analyses. We then determined that DRI effectively stratified pts into distinct strata for relapse (FIG 1A) and disease-free survival (FIG 1B). Because transplant practices are different for children compared to adults (e.g., more myeloablative conditioning), we examined whether DRI remained predictive of outcomes after adjustment for age, donor type, stem cell source, and conditioning intensity. We used IR as the reference group for these multivariate analyses. Children with HR DRI were significantly more likely to relapse (HR 2.1, 95% CI 1.2-3.7) and have worse DFS (HR 1.6, 95% CI 1.0-2.5). The risks for relapse and worse DFS were even greater for children with VHR DRI (relapse, HR 3.4, 95% CI 1.6-7.3, DFS 3.59, 95% CI 2.0-6.5). There were no significant differences in 2y non-relapse mortality by DRI. VHR pts had significantly worse 2y OS (HR 3.2, 95% CI 1.6-6.4) but HR pts were not significantly different for 2y OS than IR pts (HR 1.3, 95% CI 0.7-2.2). OS for HR and IR pts may diverge with longer follow-up. In summary, the LR strata is small and more pts are needed to determine their outcomes. However, for >95% of children the DRI creates 3 distinct risk strata. The DRI can be used in pediatric clinical trials to stratify for risk of relapse.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".