Development and validation of a disease risk stratification system for patients with haematological malignancies: a retrospective cohort study of the European Society for Blood and Marrow Transplantation registry

Abstract

Background Diagnosis and remission status at the time of allogeneic haematopoietic stem-cell transplantation (HSCT) are the principal determinants of overall survival following transplantation. We sought to develop a contemporary disease-risk stratification system (DRSS) that accounts for heterogeneous transplantation indications.Methods In this retrospective cohort study we included 55 histology and remission status combinations across haematological malignancies, including acute leukaemia, lymphoma, multiple myeloma, and myeloproliferative and myelodysplastic disorders. A total of 47 265 adult patients (aged ≥18 years) who received an allogeneic HSCT between Jan 1, 2012, and Dec 31, 2016, and were reported to the European Society for Blood and Marrow Transplantation registry were included. We divided EBMT patients into derivation (n=25 534), tuning (n=18 365), and geographical validation (n=3366) cohorts. Disease combinations were ranked in a multivariable Cox regression for overall survival in the derivation cohort, cutoff for risk groups were evaluated for the tuning cohort, and the selected system was tested on the geographical validation cohort. An independent single-centre US cohort of 660 patients transplanted between Jan 1, 2010, and Dec 31, 2015 was used to externally validate the results. Findings The DRSS model stratified patients in the derivation cohort (median follow-up was 2•1 years [IQR 1•0-3•2]) into five risk groups with increasing mortality risk: low risk (reference group), intermediate-1 (hazard ratio for overall survival 1•26 [95% CI 1•17-1•36], p<0•0001), intermediate-2 (1•53 [1•42-1•66], p<0•0001), high (2•03 [1•86-2•22], p<0•0001), and very high (2•87 [2•63-3•13], p<0•0001). DRSS levels were also associated with a stepwise increase in risk across the tuning and geographical validation cohort. In the external validation cohort (median follow-up was 5•7 years [IQR 4•5-7•1]), the DRSS scheme separated patients into 4 risk groups associated with increasing risk of mortality: intermediate-2 risk (hazard ratio [HR] 1•34 [95% CI 1•04-1•74], p=0•025), high risk (HR 2•03 [95% CI 1•39-2•95], p=0•00023) and very-high risk (HR 2•26 [95% CI 1•62-3•15], p<0•0001) patients compared with the low risk and intermediate-1 risk group (reference group). Across all cohorts, between 64% and 65% of patients were categorised as having intermediate-risk disease by a previous prognostic system (ie, the diseaserisk index [DRI]). The DRSS reclassified these intermediate-risk DRI patients, with 855 (6%) low risk, 7111 (51%) intermediate-1 risk, 5700 (41%) intermediate-2 risk, and 375 (3%) high risk or very high risk of 14 041 patients in a subanalysis combining the tuning and internal geographic validation cohorts. The DRI projected 2-year overall survival was 62•1% (95% CI 61•2-62•9) for these 14 041 patients, while the DRSS reclassified them into finer prognostic groups with overall survival ranging from 45•7% (37•4-54•0; very high risk patients) to 73•1% (70•1-76•2; low risk patients).Interpretation The DRSS is a n...

Donor Age and Non-Relapse Mortality: Study of Their Association after HLA-Matched Allogeneic Hematopoietic Cell Transplantation for Acute Myeloid Leukemia and Myelodysplastic Syndrome

“…Multivariate analyses using the Cox proportional hazards model and Fine–Gray model for cumulative incidences were used to study the association of pre-aHCT characteristics, including DA, with outcomes. DA, patient-age-adjusted HCT-comorbidity index (aaHCT-CI), Karnofsky performance status (KPS), donor type (matched related (MRD) or unrelated (MUD)), conditioning regimen intensity, sex mismatch (female donor to male recipient versus other), recipient CMV status, disease relapse risk (using the EBMT Disease Risk Stratification System), anti-thymocyte globulin (ATG) use and cell source (peripheral blood or bone marrow grafts) [ 13 ] were used as covariates when appropriate for the study outcomes. DA groups using decades were used to better define the association between DA and NRM.…”

Integrating artificial intelligence into haematology training and practice: Opportunities, threats and proposed solutions

“…A novel disease-risk stratification tool incorporating disease features related to histology, genetics and treatment response was validated in a retrospective study of >47 000 adult patients who underwent allogeneic HSCT for various haematological malignancies. 18 The potential benefits of this model in facilitating the analysis and interpretation of clinical trial results from heterogeneous cohorts are discussed.…”

“…Machine learning may be used to automate various HSCT steps, such as donor selection, identification of biomarkers for early diagnosis of complications, and modelling of graft‐versus‐host disease risk stratification. A novel disease‐risk stratification tool incorporating disease features related to histology, genetics and treatment response was validated in a retrospective study of >47 000 adult patients who underwent allogeneic HSCT for various haematological malignancies 18 . The potential benefits of this model in facilitating the analysis and interpretation of clinical trial results from heterogeneous cohorts are discussed.…”

Repetitively Administered Low-Dose Donor Lymphocyte Infusion for Prevention of Relapse after Allogeneic Stem Cell Transplantation in Patients with High-Risk Acute Leukemia

“…Disease recurrence is the major obstacle to the success of allo-SCT as patients with high-risk acute leukemia and MDS have a high risk of relapse after allo-SCT [ 3 , 4 ]. The outcome of patients with acute leukemia who relapse after allo-SCT is extremely poor.…”