Proteomic Pattern-Based Risk Stratification of Outcome Shows Significant Higher Accuracy Compared to HCT-CI in Patients with AML and MDS,
Authors: Dobbelstein Christiane E , Metzger Jochen , Dammann Elke , Borchert Uwe , Buchholz Stefanie , Stadler Michael , Eder Matthias , Krauter Juergen , Ganser Arnold , Mischak-Weissinger Eva 
Published: October 2019

Abstract
Abstract 4128

Objectives:
Allogeneic stem cell transplantation (SCT) is an established treatment for many severe disorders of hematopoiesis. Although SCT has considerable curative potential, its application is limited by transplant-related complications such as infections and graft-versus host disease (GvHD) which could lead to high mortality rates especially in older or less fit patients. Therefore, a careful pre-SCT assessment of risk and benefit is mandatory and different scores have recently emerged as helpful tools. We have previously applied proteomics to identify a specific urinary polypeptide patterns (PP) predictive for developing acute GvHD (aGvHD) (Weissinger EM et al, Blood 2007;109:5511–5519). The aim of this study was to investigate whether the PPs can predict overall outcome after allo-SCT and to compare these findings to those of the hematopoietic cell transplantation comorbidity index (HCT-CI) (Sorror M et al, Blood 2005;106:2912–2919).

Methods:
In this retrospective analysis from Hannover Medical School, the datasets from all patients (pts) with acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS), who were allo-transplanted from a fully matched donor (matched related/unrelated donor (MRD/MUD)) between 2003–2008 and for whom relevant PP data were available, were included. Pts with a pt-donor HLA-mismatch constellation were excluded from this study. PP data from urine samples which were prospectively collected by day ≥ +7 after allo-SCT were correlated with overall survival (OS), aGvHD, non-relapse mortality (NRM), relapse rate and mortality (RM), and compared to the predictive value of the HCT-CI.

Results:
PP data were available from 111 pts (97 pts with AML, 14 with MDS; median age 52y; median EBMT score 4; 59 male/52 female; 69 MUD/42 MRD). They were grouped in high (PP-HRG), low (PP-LRG) or intermediate risk groups (PP-IRG). Forty-three pts (39%) belonged to the PP-LRG for aGvHD compared to 47 pts (42%) who were classified PP-HRG. Patient characteristics of PP-LRG and PP-HRG were similar in terms of age, sex and EBMT score (median 4 in both groups).
OS compared favorably for the PP-LRG with an OS of 72% vs. 49% for the PP-HRG (p=0.03), also if only reduced intensity conditioning (RIC) was considered (73% vs 42%; p=0.01), respectively. There was a trend for higher incidence of NRM in the PP-HRG compared to PP-LRG (30% vs 14%, p=0.07) for the whole cohort, and a significant higher NRM rate, if only RIC was evaluated (35% vs 11%, p=0.01).
However, if risk stratification was based on the HCT-CI, there was no significant difference between high risk (S-HRG) and low risk group (S-LRG) in terms of OS and NRM regardless of intensity of conditioning (OS for whole cohort: 57% vs 45%, p=0.4; OS for RIC: 56% vs 36%, p=0.2; NRM for whole cohort: 20% vs 23%, p=0.8; NRM for RIC: 18% vs 29%, p=0.4).
Concerning the PP-IRG, there was a difference in OS between PP-IRG and PP-LRG (38% vs 73%, p=0.02). However, there was no significant difference in OS of the PP-IRG compared to the other PP-based risk groups nor between the HCT-CI based risk groups. Further, NRM did not show a significant difference neither for PP-based nor HCT-CI-based intermediate risk group compared to the other risk groups.
Thirty vs 15 pts developed aGvHD in PP-HRG and PP-LRG (64% vs 35%, p<0.01) compared to 48% vs 64% (p=0.2) for S-HRG and S-LRG of the whole cohort, respectively. Incidence of aGvHD differed also significantly in the RIC cohort for PP-HRG and PP-LRG (65% vs 32%, p=0.01), but not for HCT-CI-based risk groups (47% vs 64%, p=0.1). Relapse rates and RM were not significantly different between high and low risk groups, neither for PP-based nor HCT-CI based (whole cohort and RIC subgroup), respectively.

Conclusion:
Risk stratification according to GvHD-match based PP, which has previously been shown to predict aGvHD, now also allows the identification of patient groups with significantly different OS and NRM. In comparison to the HCT-CI, PP-based prediction shows significantly higher accuracy in this rather homogeneous cohort of patients. Since proteomics is a new method which has been available only at a few centers, further multicenter analyses are essential to determinate the value of PP-based prediction of complications and outcome in SCT.

Disclosures:
Metzger: Mosaiques Diagnostics GmbH: Employment.