External validation and comparison of multiple prognostic scores in allogeneic hematopoietic stem cell transplantation.
Roni ShouvalJoshua Alexander FeinAniela ShouvalIvetta DanyleskoNoga Shem-TovMaya ZlotnikRonit YerushalmiAvichai ShimoniArnon NaglerPublished in: Blood advances (2020)
Clinical decisions in allogeneic hematopoietic stem cell transplantation (allo-HSCT) are supported by the use of prognostic scores for outcome prediction. Scores vary in their features and in the composition of development cohorts. We sought to externally validate and compare the performance of 8 commonly applied scoring systems on a cohort of allo-HSCT recipients. Among 528 patients studied, acute myeloid leukemia was the leading transplant indication (44%) and 46% of patients had a matched sibling donor. Most models successfully grouped patients into higher and lower risk strata, supporting their use for risk classification. However, discrimination varied (2-year overall survival area under the receiver operating characteristic curve [AUC]: revised Pretransplantation Assessment of Mortality [rPAM], 0.64; PAM, 0.63; revised Disease Risk Index [rDRI], 0.62; Endothelial Activation and Stress Index [EASIx], 0.60; combined European Society for Blood and Marrow Transplantation [EBMT]/Hematopoietic Cell Transplantation-specific Comorbidity Index [HCT-CI], 0.58; EBMT, 0.58; Comorbidity-Age, 0.58; HCT-CI, 0.55); AUC ranges from 0.5 (random) to 1.0 (perfect prediction). rPAM and PAM, which had the greatest predictive capacity across all outcomes, are comprehensive models including patient, disease, and transplantation information. Interestingly, EASIx, a biomarker-driven model, had comparable performance for nonrelapse mortality (NRM; 2-year AUC, 0.65) but no predictive value for relapse (2-year AUC, 0.53). Overall, allo-HSCT prognostic systems may be useful for risk stratification, but individual prediction remains a challenge, as reflected by the scores' limited discriminative capacity.
Keyphrases
- allogeneic hematopoietic stem cell transplantation
- acute myeloid leukemia
- end stage renal disease
- ejection fraction
- newly diagnosed
- acute lymphoblastic leukemia
- chronic kidney disease
- prognostic factors
- risk factors
- machine learning
- cardiovascular events
- cardiovascular disease
- patient reported outcomes
- case report
- endothelial cells
- healthcare
- mesenchymal stem cells
- bone marrow
- coronary artery disease
- cell proliferation
- cell death
- stress induced
- weight loss
- cell cycle arrest
- patient reported
- clinical evaluation