Akahoshi, Yu and Spyrou, Nikolaos and Weber, Daniela and Aguayo-Hiraldo, Paibel and Ayuk, Francis and Chanswangphuwana, Chantiya and Choe, Hannah K. and Eder, Matthias and Etra, Aaron M. and Grupp, Stephan A. and Hexner, Elizabeth O. and Hogan, William J. and Kitko, Carrie L. and Kraus, Sabrina and Malki, Monzr M. Al and Merli, Pietro and Qayed, Muna and Reshef, Ran and Schechter, Tal and Ullrich, Evelyn and Vasova, Ingrid and Woelfl, Matthias and Zeiser, Robert and Baez, Janna and Beheshti, Rahnuma and Eng, Gilbert and Gleich, Sigrun and Katsivelos, Nikolaos and Kowalyk, Steven and Morales, George and Young, Rachel and Chen, Yi-Bin and Nakamura, Ryotaro and Levine, John E. and Ferrara, James L. M. (2024) Novel MAGIC composite scores using both clinical symptoms and biomarkers best predict treatment outcomes of acute GVHD. BLOOD, 144 (9). ISSN 0006-4971, 1528-0020
Full text not available from this repository. (Request a copy)Abstract
Acute graft-versus-host disease (GVHD) grading systems that use only clinical symptoms at treatment initiation such as the Minnesota risk identify standard and high-risk categories but lack a low-risk category suitable to minimize immunosuppressive strategies. We developed a new grading system that includes a low-risk stratum based on clinical symptoms alone and determined whether the incorporation of biomarkers would improve the model's prognostic accuracy. We randomly divided 1863 patients in the Mount Sinai Acute GVHD International Consortium (MAGIC) who were treated for GVHD into training and validation cohorts. Patients in the training cohort were divided into 14 groups based on similarity of clinical symptoms and similar nonrelapse mortality (NRM); we used a classification and regression tree (CART) algorithm to create three Manhattan risk groups that produced a significantly higher area under the receiver operating characteristic curve (AUC) for 6-month NRM than the Minnesota risk classification (0.69 vs 0.64, P = .009) in the validation cohort. We integrated serum GVHD biomarker scores with Manhattan risk using patients with available serum samples and again used a CART algorithm to establish 3 MAGIC composite scores that significantly improved prediction of NRM compared to Manhattan risk (AUC, 0.76 vs 0.70, P = .010). Each increase in MAGIC composite score also corresponded to a significant decrease in day 28 treatment response (80% vs 63% vs 30%, P < .001). We conclude that the MAGIC composite score more accurately predicts response to therapy and long-term outcomes than systems based on clinical symptoms alone and may help guide clinical decisions and trial design.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | VERSUS-HOST-DISEASE; HEMATOPOIETIC-CELL TRANSPLANTATION; MARROW-TRANSPLANTATION; INITIAL TREATMENT; RISK-FACTORS; SURVIVAL; CYCLOPHOSPHAMIDE; PREVENTION; ALGORITHM; PHASE-2; |
| Subjects: | 600 Technology > 610 Medical sciences Medicine |
| Divisions: | Medicine > Lehrstuhl für Innere Medizin III (Hämatologie und Internistische Onkologie) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 06 Aug 2025 06:22 |
| Last Modified: | 06 Aug 2025 06:22 |
| URI: | https://pred.uni-regensburg.de/id/eprint/65690 |
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