Clinical Validation of the Myelofibrosis Transplant Scoring System in an Independent Series of Myelofibrosis Patients Undergoing Allogeneic Hematopoietic Transplantation

Introduction: Allogeneic hematopoietic cell transplantation (allo-HCT) constitutes the only curative treatment for myelofibrosis (MF), but its associated toxicity remains high. Prognostic risk models are widely used in clinical practice to select those MF patients who are more likely to benefit from transplantation. Recently, a new prognostic model, the Myelofibrosis Transplant Scoring System (MTSS), has been developed to predict the outcome of MF patients undergoing allo-HCT (Gagelmann N et al, Blood 2019). We aimed to evaluate the performance of such model in an independent series of patients. Methods: This is a retrospective study that included all adult patients who underwent first allo-HCT for MF between January 2005 and May 2019 in 8 Spanish hospitals. Patients transplanted after leukemic transformation were excluded. Survival probability from the time of HCT was estimated by the method of Kaplan-Meier and compared by the log-rank test. Each parameter of the MTSS was tested for its potential association with survival in univariate analysis. Cumulative incidence functions were used to estimate incidence of Graft-versus-Host-Disease (GVHD), Relapse Incidence (RI), and Non-Relapse Mortality (NRM) within a competing risk setting. Statistical analyses were performed with SPSS 19 (SPSS Inc./IBM, Armonk, NY) and R. Results: Demographics and transplant characteristics of the overall series of 107 MF patients are shown in Table 1. After a median follow-up from allo-HCT of 5.3 years, 49 patients (46%) had died. The survival probability at 1, 3, and 5-years was 64.5%, 52%, and 50%, respectively. Transplantation outcome improved over the years. Thus, the survival probability at 3-years was 35% (95% CI: 12-58), 50% (95% CI: 33-67), and 65% (95% CI: 50-80) during the time periods 2005-2009 (n=17), 2010-2014 (n=34), and 2015-2019 (n=56), respectively (P=0.038). The cumulative incidence of grade II-IV acute GVHD at day 100 was 45%. The cumulative incidence of relapse at 1, 3, and 5-years was 16%, 19.5%, and 19.5%, respectively. NRM probability at 1, 3, and 5-years was 24%, 29%, and 31%, respectively. In univariate analysis, the only parameter included in the MTSS that was significantly associated with survival was the Karnofsky performance status < 90% (HR: 1.9, 95% CI: 1.1-3.4; P=0.031). Neither age > 57 years (P=0.68), platelets <150 x 109/L (P=0.79), leukocytes >25 x 109/L (P=0.38), ASXL1 mutations (P=0.34), non-CALR/MPL driver mutation (P=0.57) nor HLA-mismatched unrelated donor (P=0.22) correlated with survival. Among other classical risk factors for transplant outcome, only a comorbidity index >= 3 was significantly associated with shorter survival (HR: 2.1, 95% CI: 1.1-4; P=0.017). A total of 64 cases had all required clinical and molecular data to calculate the MTSS. Figure 1 shows the survival curves of the different risk groups as defined by the MTSS. As can be seen, the prognostic model was not able to discriminate four risk groups. We then pooled together patients assigned to the low (n=26) and intermediate risk (n=23) groups, and those within the high (n=9) and very high risk (n=6) groups. On this basis, two-categories could be identified: standard risk (n=49 [77% of patients]) and high risk (n=15 [23%]). The 3-year overall survival was 65% (95% CI: 51-79) in the standard risk and 17% (95% CI: 0-46) in the high risk categories (P=0.060)(Figure 2). Conclusions: the MTSS did not discriminate four different risk categories in our series. Both, the limited number of cases and the differences in patients and transplant characteristics in our series as compared to those of the original MTSS cohort might account for this finding. Nevertheless, the MTSS was able to identify a subset of patients with a very poor prognosis after transplantation. Such information could be useful to assist on transplant decision-making. Disclosures Sanchez-Guijo: Novartis: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Amgen: Honoraria; Roche: Honoraria. Hernandez Boluda:Incyte: Other: Travel expenses paid.

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Applying the Hematopoietic Cell Transplantation-Comorbidity Index (HCT-CI) in Myeloablative MUD Transplants Predicts NRM and OS Using a Modified 2-Tier Scoring System.

Blood ◽

10.1182/blood.v110.11.1988.1988 ◽

2007 ◽

Vol 110 (11) ◽

pp. 1988-1988

Author(s):

Tibor Kovacsovics ◽

Byung Park ◽

Brandon Hayes-Lattin ◽

Jose F. Leis ◽

Peter T. Curtin ◽

...

Keyword(s):

High Risk ◽

Cell Transplantation ◽

Cumulative Incidence ◽

Scoring System ◽

Clinical Decision Making ◽

Hematopoietic Cell Transplantation ◽

Disease Risk ◽

Risk Groups ◽

Hematopoietic Stem ◽

Gvhd Prophylaxis

Abstract Background: The HCT-CI is a recently developed comorbidity score which has been adapted to hematopoietic stem cell transplantation, and identified 3 risk groups with increased non-relapse mortality (NRM) and lower overall survival (OS) (Blood2005;106:2912). We determined the HCT-CI score in a cohort of patients who underwent myeloablative MUD transplantation in a single arm, institutional trial assessing the efficacy of a combination of cyclosporine, methotrexate and prednisone for GVHD prophylaxis. Methods: The analysis included all patients undergoing MUD transplant from 1996–2006 who received GVHD prophylaxis with cyclosporine 2 mg/kg iv BID from day −2, methotrexate 15 mg/m2 iv on day +1 and 10 mg/m2 iv on days +3 and +6, and methylprednisolone 0.25 mg/kg iv BID beginning on day +7 and tapering from day +28. Patients were stratified by disease risk per CIBMTR classification. The comorbidities were obtained by retrospective chart review and scored according to the HCT-CI score. Results: 150 patients (median age 40) received the 3 drug-regimen, including 38% with low-, 34% with intermediate- and 28% with high-risk disease. Diagnoses included acute leukemia in 50%, MDS in 12%, CML in 15%, lymphoma in 18%, and multiple myeloma in 3.0%. Conditioning regimens included Cy-TBI in 64% and Bu-Cy in 21%. Source of stem cells was PBSC in 47.3% and marrow in 50.7%. HCT-CI scores of 0, 1–2 or ≥3 were found in 17%, 30% and 53% of patients evaluated. The majority of comorbidities were pulmonary (72%). With a median follow-up of 46 weeks, day 100 and 5-year OS were 82.7 and 33%, with a 23% and 50.4% cumulative incidence of NRM. Five year relapse-related mortality was 15.8%. Although higher HCT-CI scores were associated with increased NRM and decreased OS, no statistically significant differences were detected when using the published HCT-CI grouping of 0, 1–2 and ≥3. Unadjusted hazard ratio (HR) for inferior survival were 0.9 (CI 0.47–1.85, P=.79) and 1.65 (CI 0.885–3.090, P=.11) for scores 1–2 and ≥3, respectively. We then determined an alternate prognostic model based on 2 groups. Statistical modeling separated patients with a score of 0–3 (n=97, 64%) and ≥4 (n=53, 35.6%), with a 3 month and 5 year OS of 84% and 45% versus 52% and 10%, respectively (P<.0001). Cumulative incidence of day 100 and 5-year NRM was 16% and 38% versus 43% and 73%, respectively. Unadjusted HR for inferior survival was 2.77 (CI 1.816–4.225, P<.0001) for a score of ≥4. By multivariate analysis, only the HCT-CI score (P<.0001) and the disease risk per CIBMTR (P=.0058) were predictive of OS and NRM, but not age, CMV positivity, sex- or HLA-mismatch, or regimen. Conclusions: While our data confirm that the HCT-CI score is predictive of NRM and OS in a high-risk MUD transplant cohort, we were unable to detect statistically significant differences between the 3 risk groups defined in the original score. A modified 2-group scoring system readily stratified the patient population into low-risk and high-risk risk groups with scores of 0–3 and ≥4, respectively, that was predictive of OS and NRM. This simplified, 2-tiered scoring system will have utility in clinical decision-making and in defining patient populations eligible for clinical trials. Additional single and multi-institutional analyses will ultimately determine the optimal applications of the HCT-CI score.

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Validation of a Prognostic Model and the Impact of SF3B1, DNMT3A, and Other Mutations in 289 Genetically Characterized Lower Risk MDS Patient Samples

Blood ◽

10.1182/blood.v118.21.969.969 ◽

2011 ◽

Vol 118 (21) ◽

pp. 969-969 ◽

Cited By ~ 3

Author(s):

Rafael Bejar ◽

Kristen Stevenson ◽

Bennett Caughey ◽

Omar Abdel-Wahab ◽

Naomi Galili ◽

...

Keyword(s):

Scoring System ◽

Lower Risk ◽

Prognostic Model ◽

Point Mutations ◽

Gene Mutations ◽

Risk Groups ◽

Appropriate Therapy ◽

Md Anderson ◽

Risk Categories ◽

Independent Cohort

Abstract Abstract 969 Selection of the appropriate therapy for patients with myelodysplastic syndromes (MDS) depends heavily on the predicted prognosis of each afflicted individual. Prognostic scoring systems help stratify patients into risk groups, but outcomes can be highly variable even within these groups. Of particular concern are patients predicted to have lower risk disease that go on to progress more rapidly than expected. Such patients may not be offered risk-appropriate therapy at a time when it might be of greatest benefit. A prognostic model that better predicts survival in patients believed to have lower risk disease has been proposed by investigators at the MD Anderson Cancer Center, but not yet validated in an independent cohort. Acquired genetic mutations can also identify patients with higher-than-predicted disease risk. We have previously demonstrated that mutations in any of five genes (TP53, EZH2, ETV6, RUNX1, and ASXL1) predict a poorer prognosis independently of the International Prognostic Scoring System (IPSS). In this study, we examined 289 MDS patients with Low or Intermediate-1 IPSS risk for mutations in 21 genes, including two genes that have recently been reported to be frequently mutated in MDS: DNMT3A and SF3B1. We validate the ability of the Lower-Risk MD Anderson Prognostic Scoring System (LR-PSS) to more finely risk-stratify patients using an independent cohort and identify gene mutations independently associated with clinical features and overall survival. Patients were stratified into one of three risk categories using the LR-PSS shown in the Table. The 58 patients (20%) assigned to Category 1 had a median survival of 5.19 years (95% confidence interval in years [CI] 3.05–10.34), compared to 2.65 years (CI 2.18–3.30) for the 160 patients (55%) in Category 2, and 1.11 (CI 0.82–1.51) for the 71 patients (25%) in Category 3. Differences in survival were significant between all three categories (p < 0.001 for all comparisons). Point mutations were identified in 63% of samples, including 64% of those with a normal karyotype. The 10 most frequently mutated genes were TET2 (23% of cases), SF3B1 (21%), ASXL1 (15%), DNMT3A (14%), RUNX1 (9%), EZH2 (8%), JAK2 (3%), NRAS (3%), TP53 (2%), and ETV6 (2%). Mutations of SF3B1 were highly enriched in cases of refractory anemia with ring sideroblasts (RARS; 32 out of 43, 74%), associated with normal blast percentages (p = 0.04) and neutrophil counts (p = 0.002), and more likely to be present in cases with platelet counts greater than 450,000/μl (p < 0.001). We extended our analysis of SF3B1 mutations by adding a separate cohort of 98 RARS patients with Low or Intermediate-1 IPSS risk for a total of 141 cases. In this extended RARS set, SF3B1 mutations were associated with improved survival even after adjustment for IPSS risk group or LR-PSS category (hazard ratio [HR]=0.49; CI 0.29–0.81, HR=0.35; CI 0.21–0.58, respectively). SF3B1 is the first gene mutation independently associated with a favorable prognosis in non-CMML MDS. In contrast, DNMT3A mutations were not associated with differences in overall survival in the 289 patients with lower IPSS risk MDS. In a model generated from stepwise Cox regression analysis that considered LR-PSS risk categories and the mutation status of the 13 most frequently mutated genes as candidates, only EZH2 mutations emerged as a LR-PSS-independent risk factor associated with a poor prognosis (HR=2.90; CI 1.86–4.53). In a similar model using IPSS risk groups, EZH2 (HR=2.85; CI 1.78–4.57), NRAS (HR=2.78; CI 1.35–5.72), and ASXL1 (HR=1.60; CI 1.09–2.34) were significant IPSS-independent risk factors. Mutations in genes such as ASXL1, RUNX1, NRAS, and ETV6, which are associated with poor survival in unselected MDS patients, were most common in patients assigned to the LR-PSS risk Category 3, indicating that this prognostic model may capture more clinically relevant information associated with adverse gene mutations. In conclusion, this study validates the LR-PSS 's ability to identify higher risk MDS patients among those with lower IPSS risk and demonstrates that point mutations are common in this cohort, associate with specific clinical features, and independently provide both favorable and adverse prognostic information.Table:Table:. The Lower-Risk MD Anderson Prognostic Scoring System (LR-PSS) Disclosures: No relevant conflicts of interest to declare.

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A Novel Prognostic Marker for Primary CNS Lymphoma: Lactate Dehydrogenase-to-Lymphocyte Ratio Improves Stratification of Patients Within the Low and Intermediate MSKCC Risk Groups

Frontiers in Oncology ◽

10.3389/fonc.2021.696147 ◽

2021 ◽

Vol 11 ◽

Author(s):

Yuting Gao ◽

Li Wei ◽

Seok Jin Kim ◽

Liang Wang ◽

Yingzhi He ◽

...

Keyword(s):

Lactate Dehydrogenase ◽

Survival Data ◽

Scoring System ◽

Prognostic Model ◽

Group Performance ◽

Univariate Analysis ◽

Eastern Cooperative Oncology Group ◽

Risk Groups ◽

Neutrophil To Lymphocyte Ratio ◽

Lymphocyte Ratio

BackgroundPrimary central nervous system lymphoma (PCNSL) is a highly aggressive and rare extranodal non-Hodgkin lymphoma (NHL). The MSKCC and the IELSG scores represent the most widely used prognostic models, but many changes have occurred in therapeutic protocols since their development. Moreover, many PCNSL patients cannot be classified using the IELSG score. We thus aimed to create a novel, effective and feasible prognostic model for PCNSL.MethodsWe included 248 PCNSL patients diagnosed with PCNSL. Our primary endpoint was the overall survival (OS) and we used the receiver operating characteristic (ROC) analysis to determine the optimal prognostic cut-off value for LLR (lactate dehydrogenase-to-lymphocyte ratio), neutrophil-to-lymphocyte ratio (NLR) and derived neutrophil-to-lymphocyte ratio (dNLR). Variable associated with OS were evaluated by univariate and multivariate analyses. 124 out of 248 patients were randomly selected as the internal validation cohort.ResultsBy univariate analysis, an age >60 years, Eastern Cooperative Oncology Group performance status (ECOG PS) >1, treatment with radiotherapy alone, high-risk groups of Memorial Sloan Kettering Cancer Center (MSKCC) score, NLR >4.74, dNLR >3.29, and LLR >166.8 were significantly associated with a worse OS. By multivariate analysis, the MSKCC score and LLR were confirmed as independent prognostic parameters for poorer OS. OS, however, was not significantly different between low- and intermediate-risk groups according to the MSKCC score, while LLR proved to be prognostically relevant and was thus used to develop a novel, effective three-tier PCNSL scoring system. Of 124 patients, 84 patients with survival data and LLR data were successfully validated by newly established PCNSL LLR scoring system.ConclusionsIn the present study, we demonstrate that a high LLR represents an independent unfavorable prognostic parameter in PCNSL patients which can be integrated into an effective prognostic model.

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Improved Outcome in High Risk and Very High Risk ALL by Risk Adapted SCT and in Standard Risk ALL by Intensive Chemotherapy in 713 Adult ALL Patients Treated According to the Prospective GMALL Study 07/2003.

Blood ◽

10.1182/blood.v110.11.12.12 ◽

2007 ◽

Vol 110 (11) ◽

pp. 12-12 ◽

Cited By ~ 13

Author(s):

Nicola Gökbuget ◽

Renate Arnold ◽

Angelika Böhme ◽

Rainer Fietkau ◽

Mathias Freund ◽

...

Keyword(s):

Risk Factors ◽

High Risk ◽

Residual Disease ◽

Univariate Analysis ◽

Early Death ◽

Risk Groups ◽

Prognostic Impact ◽

Standard Risk ◽

Very High ◽

Improved Outcome

Abstract In 2003 the German Multicenter ALL Study Group (GMALL) initiated the trial GMALL 07/2003. Major aims were improvement of outcome by shortened, intensified induction, intensified consolidation, risk adapted and extended SCT indication and minimal residual disease (MRD) based treatment stratification. 8drug-induction was followed by uniform 1st consolidation based on HDARAC and HDMTX. Further treatment was stratified according to the following risk factors (RF): WBC > 30.000 in B-prec. ALL, late CR (>3wks), proB-, earlyT and mature T-ALL, Ph/BCR-ABL and t(4;11)/ALL1-AF4. The risk groups were defined as follows: standard risk (SR, no RF), high risk (HR,>= 1RF) and very high risk (VHR,Ph/BCR-ABL). HR and VHR pts were scheduled for SCT in CR1 with the following priorities: allo sibling, allo matched unrelated and autologous. VHR pts mostly received Imatinib according to different schedules. SR pts received 5 consolidation cycles (HDMTX/ASPx3, VP16/ARAC, CYCLO/ARAC) and reinduction. SR pts with high MRD after consolidation I were allocated to SCT. In the remaining SR pts decision on maintenance therapy was based on MRD. Between 04/03-12/06 713 evaluable (15–55 yrs) pts were included. The median age was 34 yrs. The CR rate after induction was 89% with 5% early death and 6% failure. 50%, 33% and 17% were allocated to SR (N=353), HR (N=235) and VHR (N=117) with similar CR rates of 92%, 88% and 85%. CR rate was not different in pts < vs > 35 yrs (90% vs 89%). 5 year overall survival (OS) was 54% and survival of CR (S-CR) pts was 59%. HR and VHR pts obtained 55% and 49% S-CR at 3 yrs resp. HR subgroups showed different S-CR for early T (58%), mature T (70%), pro B (66%) and other B-lineage ALL (37%). 68% and 71% of HR and VHR pts received SCT in CR1 as scheduled which thus contributed substantially to improved outcome. In SR- ALL S-CR was 69% (68% c/preB, 66% thymicT). The CCR probability was 52% at 3 yrs. CNS prophylaxis was very effective since only 2% of the CR pts had CNS involvement at relapse. Univariate analysis confirmed a significant prognostic impact of immunphenotype, WBC in B-lin ALL, time to CR and Ph/BCR-ABL. WBC was no prognostic factor in T-lin-ALL. Age was highly significant for survival with 64% survival < 35 yrs vs 48% above 35 yrs. In adolescents below 25 years the most favourable survival of 67% was achieved. In standard risk pts below 35 yrs the survival was 73% without SCT in CR1. Overall the study yielded improved CR rates (89%) and survival (54%). Risk adapted SCT indication was feasible (realised in 70% of HR/VHR pts) and lead to improved survival particularly in early/mature T-ALL and pro B-ALL. In standard risk (SR) the survival is favourable, even above 70% in young pts; however, the relapse rate is still high. Further intensification of therapy during the first year seems required. By definition of new risk factors additional SR patients could be allocated to SCT in CR1. There is however no intention to transfer all SR patients to SCT. Future improvement will be attempted by further inclusion of subtype specific and targeted therapies.

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Validation of German High-Grade Non-Hodgkin's Lymphoma (DSHNHL) Prognostic Model and the Impact of Treatment on Secondary Central Nervous System (CNS) Relapse in Diffuse Large B-Cell Lymphoma (DLBCL) in a Developing Country: Report from the Nationwide Multi-Institutional Registry of Thai Lymphoma Study Group (TLSG)

Blood ◽

10.1182/blood.v126.23.1471.1471 ◽

2015 ◽

Vol 126 (23) ◽

pp. 1471-1471

Author(s):

Kitsada Wudhikarn ◽

Udomsak Bunworasate ◽

Arnuparp Lekhakula ◽

Jakrawadee Julamanee ◽

Chittima Sirijerachai ◽

...

Keyword(s):

High Risk ◽

Cumulative Incidence ◽

Prognostic Model ◽

Risk Group ◽

Univariate Analysis ◽

High Grade ◽

Extranodal Involvement ◽

Cns Relapse ◽

Baseline Characteristics ◽

Lymphoma Study Group

Abstract Introduction: Despite improved treatment outcome of DLBCL in the immunochemotherapy era, secondary CNS relapse remains a serious and fatal complication. Several prognostic models were reported in order to define high-risk patients for CNS relapse and provide proper prophylactic strategies. There is no standard approach for CNS prophylaxis in DLBCL with more data suggesting lack of efficacy of intrathecal chemoprophylaxis. In 2013, the DSHNHL introduced a prognostic model including each international prognostic index (IPI) factor (age, lactate dehydrogenase (LDH), stage, performance status (PS), extranodal involvement (EN) and kidney/adrenal involvement) to stratify patients into 3 groups. Herein, we applied and validated DSHNHL model to DLBCL patients treated at nationwide University hospitals in Thailand including analyzing an impact of rituximab and intrathecal chemoprophylaxis on CNS relapse. Method: From the nationwide multicenter registry of 4,371 newly diagnosed lymphoma patients in Thailand between 2007 and 2014, there were a total of 2,399 DLBCL patients. We looked at the incidence and clinical predictors of CNS relapse, the effect of immunotherapy and intrathecal chemoprophylaxis on CNS relapse in DLBCL who were treated with at least one cycle of CHOP-like or intensive chemotherapy regimens. Result: After excluding patients with CNS/ocular involvement at diagnosis, 2,034 DLBCL patients were included in the analysis. Table 1 summarizes baseline characteristics of DLBCL patients. The median follow up time for living patients was 51 months (interquartile range, 22-75 months). A total of 565 patients (27.8%) progressed or relapsed after first-line induction therapy and 61 patients (3.0%) developed CNS relapse. Median time to CNS relapse was relatively shorter than non-CNS relapse (8.4 vs 10.5 months, P=0.07). A total of 729 (35.8%), 1,024 (50.3%) and 281 (13.8%) patients were classified as low-, intermediate- and high-risk groups based on DSHNHL risk model for CNS relapse. Of high DSHNHL risk group, 45 patients (16%) received intrathecal chemotherapy for CNS prophylaxis along with induction treatments. Using the competing risk regression analysis, 2-year cumulative incidence of CNS relapse was 2.7% (1.5%, 3.1%, and 4.6% for low-, intermediate- and high-risk DSHNHL group respectively). Univariate analysis showed elevated LDH, poor PS, stage III/IV, presence of B symptoms, higher risk IPI and DSHNHL risk group as risk factors of CNS relapse (Table 2). Presence of concurrent EN involvement more than one site and elevated LDH was a significant predictor of CNS relapse (Hazard Ratio [HR] 2.39, P =0.004). Kidney/adrenal gland and gonadal involvement were not associated with higher risk of CNS relapse whereas breast involvement showed a trend toward higher incidence of CNS relapse (HR 2.46, P=0.07). Either immunochemotherapy or intrathecal chemoprophylaxis was not associated with lower risk of CNS relapse; in fact patients who received intrathecal chemotherapy had more CNS relapse though this could be due to selection bias. Median survival of patients with CNS relapse was 13.2 months which was significantly worse than patients without CNS relapse (81.8 months, P<0.001). Conclusion: The 2-year cumulative incidence of CNS relapse in DLBCL in this analysis was 2.7% which was comparable to other series. Using the DSHNHL prognostic model was able to define DLBCL patients into low, intermediate and high risk for CNS relapse. The high-risk group in our series had lower incidence of CNS relapse compared to German and recently reported British Columbia cohorts. Our study confirms poor survival outcome of DLBCL patients with CNS relapse and no protective effect of immunochemotherapy or intrathecal chemoprophylaxis on the incidence of CNS relapse. Novel risk-adapted CNS prophylaxis strategies are warranted to be further investigated in prospective studies. Figure 1. Baseline characteristics of DLBCL patients based on pattern of CNS relapse IQR: Interquartile Range Figure 1. Baseline characteristics of DLBCL patients based on pattern of CNS relapse. / IQR: Interquartile Range Figure 2. Univariate analysis for factors associated with risk of CNS relapse DSHNHL: The German High Grade Non-Hodgkin's Lymphoma Study Group, R:Rituximab Figure 2. Univariate analysis for factors associated with risk of CNS relapse. / DSHNHL: The German High Grade Non-Hodgkin's Lymphoma Study Group, R:Rituximab Figure 3. 1A shows cumulative incidence (CI) of CNS relapse. 1B shows CI of CNS relapse stratified by the presence of > 1 extranodal involvement and elevated LDH. 1C shows CI of CNS relapse stratified by DSHNHL risk group. 1D shows overall survival based on relapse status. Figure 3. 1A shows cumulative incidence (CI) of CNS relapse. 1B shows CI of CNS relapse stratified by the presence of > 1 extranodal involvement and elevated LDH. 1C shows CI of CNS relapse stratified by DSHNHL risk group. 1D shows overall survival based on relapse status. Disclosures Khuhapinant: Roche: Honoraria.

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Comprehensive Clinical-Molecular Transplant Risk Model for Myelofibrosis Undergoing Allogeneic Stem Cell Transplantation

Blood ◽

10.1182/blood-2018-99-114636 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 689-689 ◽

Cited By ~ 1

Author(s):

Nico Gagelmann ◽

Markus Ditschkowski ◽

Rashit Bogdanov ◽

Marie Robin ◽

Bruno Cassinat ◽

...

Keyword(s):

High Risk ◽

Scoring System ◽

Research Funding ◽

Triple Negative ◽

Cox Regression ◽

Univariate Analysis ◽

Risk Groups ◽

Karnofsky Performance Score ◽

Very High ◽

Reduced Intensity

Abstract Background The dynamic International Prognostic Scoring System (DIPSS) is commonly applied to predict survival among patients with primary myelofibrosis (PMF) but has been shown to perform less precisely in secondary myelofibrosis (SMF) and after transplantation. Furthermore, the prognostic relevance of mutation profile resulted in the mutation-enhanced IPSS (MIPSS) in PMF, as well as in a model specific to SMF (MYSEC-PM) after essential thrombocythemia (ET) or polycythemia vera (PV). The aim of the current study was to develop a comprehensive prognostic system including clinical and molecular information, specifically in myelofibrosis undergoing transplantation. Methods Previously published methods were used to sequence myelofibrosis-associated genes (i.a. CALR1/2, JAK2, MPL,ASXL1, SRSF2, EZH2, IDH1/2, DNMT3A, TET2, TP53). Outcome was calculated from date of transplant (95% confidence interval). Variables associated with overall survival (OS) constructed a Cox regression with a stepwise selection procedure. Hazard ratios (HR) were used as weights for model development. Validation was done using repeated random subsampling. Performance of the model was verified via Harrel's concordance index C and was also tested in predefined cohorts: disease (PMF, SMF), conditioning, and ruxolitinib pretreatment. Results Population. The total cohort consisted of 361 patients from four different centers in Germany and France (260 PMF, 101 SMF). Median age at transplant was 57 years (range, 22-75), 58% were male and 42% had a Karnofsky performance score (KPS) <90. The median follow-up was 62 months and was similar between PMF and SMF (p=0.50). Overall 5-year OS was 60% (54-67) being similar in PMF (63%) and SMF after ET (59%) and slightly lower after PV (45%). Most frequent mutations were: JAK2 V617F (57%), CALR (20%; types 1/2/other 66%/23%/11%), MPL (5%), ASXL1 (31%), TET2 (19%), SRSF2 (9%), DNMT3A (6%), TP53 (6%). Two or more mutations were present in 60%. Most transplants were received from matched unrelated (46%), mismatched unrelated donors (MMUD, 27%), identical siblings (27%), and mismatched siblings (1%). Reduced intensity was given more frequently (64%) than myeloablative conditioning (36%). Frequencies at transplant were 9% (low), 29% (intermediate-1), 48% (intermediate-2), 14% (high) according to DIPSS and 3% (low), 40% (intermediate), and 57% (high) for MIPSS. Factors on outcome. In univariate analysis, mutations in CALR and MPL showed better OS (79% and 76%) vs. JAK2 (53%) and triple negative (50%; p=0.001). Outcome was similar according to CALR type (p=0.99). ASXL1 and DNMT3A mutations also entered the multivariate model. The following eight clinical, molecular and transplant-related variables were identified (corresponding HR): leukocytes >25x109/l (1.71), platelets <150x109/l (1.53), KPS <90 (1.63), age >57 years (1.69), recipient/donor CMV serostatus (+/- vs. other, 1.68), ASXL1 (1.74), JAK2/triple negative (2.10), and MMUD (2.11). Myelofibrosis Transplant Scoring System (MTSS). A weighted score of 1 was assigned to leukocytosis, thrombocytopenia, KPS <90, age >57, recipient/donor CMV serostatus (+/-), and ASXL1 mutation, whereas 2 points were assigned to JAK2/triple negative and MMUD. Four risk groups constructed the MTSS: low (score 0-2), intermediate (score 3-4), high (score 5-6), and very high (score 7-9). The 5-year OS according to risk groups was 88%, 71%, 50%, and 20% (Figure 1). The hazard for death (with low-risk as reference) was 2.36 for intermediate-risk, 4.65 for high-risk, and 9.72 for very high-risk. The score was predictive of OS overall as well as for PMF and SMF (p<0.001, respectively). The MTSS showed overall C statistics of 0.718 (0.707-0.730) after cross-validation yielding a median of 0.727 in PMF and 0.708 in SMF indicating improved performance and replicability vs. DIPSS (0.572), MIPSS (0.577), and MYSEC-PM (0.601). The system was also predictive of OS in different conditioning settings (reduced intensity and myeloablative) and in patients with ruxolitinib pretreatment (p<0.001, respectively). Conclusions The new MTSS includes modern disease- and transplant-associated risk variables pertinent to both PMF and SMF. This proposed system consistently predicts outcome facilitating posttransplant decision-making and can be applied to different conditioning settings and to patients receiving ruxolitinib pretreatment. Figure 1. Figure 1. Disclosures Beelen: Medac: Consultancy, Other: Travel Support. Kroeger:Novartis: Honoraria, Research Funding; Riemser: Honoraria, Research Funding; Neovii: Honoraria, Research Funding; Sanofi: Honoraria; JAZZ: Honoraria; Celgene: Honoraria, Research Funding.

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MD Anderson Scoring System (MDACC) Predicts Outcomes After Hematopoietic Stem Cell Transplantation (HSCT) Better Than Other Prognostic Classifications In MDS

Blood ◽

10.1182/blood.v122.21.3340.3340 ◽

2013 ◽

Vol 122 (21) ◽

pp. 3340-3340

Author(s):

Piyanuch Kongtim ◽

Uday R Popat ◽

Marcos de Lima ◽

Guillermo Garcia-Manero ◽

Elias J. Jabbour ◽

...

Keyword(s):

High Risk ◽

Scoring System ◽

Risk Group ◽

Univariate Analysis ◽

Scoring Systems ◽

Risk Groups ◽

High Risk Group ◽

Risk Scores ◽

Hematopoietic Stem ◽

Very High

Abstract MDS is a heterogeneous group of hematopoietic stem cell disorders. Various prognostic models have been established to categorize patients with MDS including the International Prognostic Scoring System (IPSS), the Revised-IPSS (r-IPSS) and MDACC Scoring System. In this analysis, we compared those three classification schemas for their outcome predictability after HSCT. We analyzed 291 MDS patients with a median age of 55 (interquartile range (IQR) 47-60.7 years) who underwent HSCT between January 2001 and December 2011. Histology by WHO classification included RA/RARS 48 (16.5%), RCMD 28 (9.6%), RAEB-1 59 (20.2%), RAEB-2 63 (21.7%), MDS unclassified 67 (23%), and CMML 26 (9%). Of 291, 117 patients (40.2%) had therapy related MDS (t-MDS). Conditioning regimen was myeloablative in 201 patients (69.1%) and reduced intensity in 90 patients (30.9%). Donors were matched related (MRD), matched unrelated (MUD), mismatched (MMD) in 131 (45%), 114 (39.2%) and 46 (15.8%) patients respectively. Risk categorization was performed by IPSS, r-IPSS and MDACC scoring systems at the time of diagnosis. IPSS, r-IPSS and MDACC scoring systems could be assessed in 239 (82.1%), 241 (82.8%) and 231 (79.4%) patients respectively. The median follow up time of 109 survivors was 45 months. The median time from diagnosis to HSCT was 7.3 months (IQR 4.6-12.4 months). Three-year overall survival (OS) was 38.1% (95%CI 32.3-43.9) with 3-year event free survival (EFS) of 34.2% (95%CI 28.4-40). Cumulative relapse incidence (RI) at 3-year was 28.8% (95%CI 23.3-34.5). Cumulative incidence of treatment related mortality (TRM) at 3 year post-transplant was 27.9% (95%CI 22.6-33.6). In univariate analysis, IPSS and r-IPSS were able to differentiate 2 risk groups for OS and EFS. High risk group per IPSS and very high risk group per r-IPSS had lower OS with hazard ratio (HR) of 2.4 to 3.1, lower EFS with HR of 2.2 to 2.7. While IPSS could not predict RI, very high risk group by r-IPSS had higher RI with HR of 3.6 compared with lower risk groups. Both IPSS and r-IPSS did not identify different risk groups for TRM. On the other hand, MDACC scoring system was able to identify 4 different risk groups for EFS and OS in univariate analysis. Three-year OS was 68%, 46.1%, 30.3% and 11.4% for patients with MDACC risk score of 0-4, 5-6, 7-8 and ≥9 respectively (p<0.001) (figure1). Three-year EFS with MDACC risk score of 0-4, 5-6, 7-8 and ≥9 was 61.7%, 40.8%, 28.1% and 7.4% respectively (p<0.001). For RI and TRM, only MDACC risk scores of ≥9 was associated with poor outcomes with 3-year RI of 38.9% and 3-year TRM of 41.7% compared with 13.3% and 15.5% in risk scores of 0-4 (p=0.01 and p=0.01 respectively). In multivariate analysis, MDACC score, matched unrelated and mismatched donors were associated with inferior OS (table1). As a summary, MDACC risk scoring system for MDS better differentiates prognostic groups than IPSS or r-IPSS. Considering the high frequency of t-MDS among transplanted MDS patients, we propose that MDACC scoring system should be used for prognostic classification for hematopoietic transplantation. Disclosures: No relevant conflicts of interest to declare.

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The Prognostic Value of the New Combined Hemo-Eosinophil Inflammation Index (HEI Index): A Multicenter Analysis of Anal Cancer Patients Treated with Concurrent Chemo-Radiation

Cancers ◽

10.3390/cancers13040671 ◽

2021 ◽

Vol 13 (4) ◽

pp. 671

Author(s):

Margherita Rimini ◽

Pierfrancesco Franco ◽

Berardino De Bari ◽

Maria Giulia Zampino ◽

Stefano Vagge ◽

...

Keyword(s):

High Risk ◽

Cancer Patients ◽

Anal Cancer ◽

Prognostic Score ◽

Univariate Analysis ◽

External Validation ◽

Risk Groups ◽

Anal Squamous Cell Carcinoma ◽

Predictors Of Response ◽

Risk Patients

Anal squamous cell carcinoma (SCC) is a rare tumor, and bio-humoral predictors of response to chemo-radiation (CT-RT) are lacking. We developed a prognostic score system based on laboratory inflammation parameters. We investigated the correlation between baseline clinical and laboratory variables and disease-free (DFS) and overall (OS) survival in anal SCC patients treated with CT-RT in five institutions. The bio-humoral parameters of significance were included in a new scoring system, which was tested with other significant variables in a Cox’s proportional hazard model. A total of 308 patients was included. We devised a prognostic model by combining baseline hemoglobin level, SII, and eosinophil count: the Hemo-Eosinophils Inflammation (HEI) Index. We stratified patients according to the HEI index into low- and high-risk groups. Median DFS for low-risk patients was not reached, and it was found to be 79.5 months for high-risk cases (Hazard Ratio 3.22; 95% CI: 2.04–5.10; p < 0.0001). Following adjustment for clinical covariates found significant at univariate analysis, multivariate analysis confirmed the HEI index as an independent prognostic factor for DFS and OS. The HEI index was shown to be a prognostic parameter for DFS and OS in anal cancer patients treated with CT-RT. An external validation of the HEI index is mandatory for its use in clinical practice.

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Derivation and validation of a lipid-covered prognostic model for mature T-cell lymphomas

Cancer Cell International ◽

10.1186/s12935-021-02042-3 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Tiange Lu ◽

Lei Shi ◽

Guanggang Shi ◽

Yiqing Cai ◽

Shunfeng Hu ◽

...

Keyword(s):

Lipid Metabolism ◽

T Cell ◽

Scoring System ◽

Serum Lipid ◽

Prognostic Model ◽

Validation Cohort ◽

Univariate Analysis ◽

Prognostic Significance ◽

Cox Regression Analysis ◽

T Cell Lymphomas

Abstract Background Mature T-cell lymphomas (MTCLs), a group of diseases with high aggressiveness and vulnerable prognosis, lack for the accurate prognostic stratification systems at present. Novel prognostic markers and models are urgently demanded. Aberrant lipid metabolism is closely related to the tumor progression but its prognostic significance in MTCLs remains unexplored. This study aims to investigate the relationship between dysregulated lipid metabolism and survival prognosis of MTCLs and establish a novel and well-performed prognostic scoring system for MTCL patients. Methods A total of 173 treatment-naive patients were enrolled in this study. Univariate and multivariate Cox regression analysis were performed to assess the prognostic significance of serum lipid profiles and screen out independent prognostic factors, which constituted a novel prognostic model for MTCLs. The performance of the novel model was assessed in the training and validation cohort, respectively, by examining its calibration, discrimination and clinical utility. Results Among the 173 included patients, 115 patients (01/2006–12/2016) constituted the training cohort and 58 patients (01/2017–06/2020) formed the validation cohort. Univariate analysis revealed declined total cholesterol (TC, P = 0.000), high-density lipoprotein cholesterol (HDL-C, P = 0.000) and increased triglycerides (TG, P = 0.000) correlated to inferior survival outcomes. Multivariate analysis revealed extranodal involved sites ≥ 2 (hazard ratio [HR]: 2.439; P = 0.036), β2-MG ≥ 3 mg/L (HR: 4.165; P = 0.003) and TC < 3.58 mmol/L (HR: 3.338; P = 0.000) were independent predictors. Subsequently, a novel prognostic model, EnBC score, was constructed with these three factors. Harrell’s C-index of the model in the training and validation cohort was 0.840 (95% CI 0.810–0.870) and 0.882 (95% CI 0.822–0.942), respectively, with well-fitted calibration curves. The model divided patients into four risk groups with distinct OS [median OS: not available (NA) vs. NA vs. 14.0 vs. 4.0 months, P < 0.0001] and PFS (median PFS: 84.0 vs. 19.0 vs. 8.0 vs. 1.5 months, P < 0.0001). Time-dependent receiver operating characteristic curve and decision curve analysis further revealed that EnBC score provided higher diagnostic capacity and clinical benefit, compared with International Prognostic Index (IPI). Conclusion Firstly, abnormal serum lipid metabolism was demonstrated significantly related to the survival of MTCL patients. Furthermore, a lipid-covered prognostic scoring system was established and performed well in stratifying patients with MTCLs.

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A prognostic model based on seven immune-related genes predicts the overall survival of patients with hepatocellular carcinoma

BioData Mining ◽

10.1186/s13040-021-00261-y ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Qian Yan ◽

Wenjiang Zheng ◽

Boqing Wang ◽

Baoqian Ye ◽

Huiyan Luo ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

High Risk ◽

Risk Score ◽

Immune Cells ◽

Prognostic Model ◽

Risk Groups ◽

Low Risk ◽

Prognostic Performance ◽

Immune Related Genes

Abstract Background Hepatocellular carcinoma (HCC) is a disease with a high incidence and a poor prognosis. Growing amounts of evidence have shown that the immune system plays a critical role in the biological processes of HCC such as progression, recurrence, and metastasis, and some have discussed using it as a weapon against a variety of cancers. However, the impact of immune-related genes (IRGs) on the prognosis of HCC remains unclear. Methods Based on The Cancer Gene Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort) datasets, we integrated the ribonucleic acid (RNA) sequencing profiles of 424 HCC patients with IRGs to calculate immune-related differentially expressed genes (DEGs). Survival analysis was used to establish a prognostic model of survival- and immune-related DEGs. Based on genomic and clinicopathological data, we constructed a nomogram to predict the prognosis of HCC patients. Gene set enrichment analysis further clarified the signalling pathways of the high-risk and low-risk groups constructed based on the IRGs in HCC. Next, we evaluated the correlation between the risk score and the infiltration of immune cells, and finally, we validated the prognostic performance of this model in the GSE14520 dataset. Results A total of 100 immune-related DEGs were significantly associated with the clinical outcomes of patients with HCC. We performed univariate and multivariate least absolute shrinkage and selection operator (Lasso) regression analyses on these genes to construct a prognostic model of seven IRGs (Fatty Acid Binding Protein 6 (FABP6), Microtubule-Associated Protein Tau (MAPT), Baculoviral IAP Repeat Containing 5 (BIRC5), Plexin-A1 (PLXNA1), Secreted Phosphoprotein 1 (SPP1), Stanniocalcin 2 (STC2) and Chondroitin Sulfate Proteoglycan 5 (CSPG5)), which showed better prognostic performance than the tumour/node/metastasis (TNM) staging system. Moreover, we constructed a regulatory network related to transcription factors (TFs) that further unravelled the regulatory mechanisms of these genes. According to the median value of the risk score, the entire TCGA cohort was divided into high-risk and low-risk groups, and the low-risk group had a better overall survival (OS) rate. To predict the OS rate of HCC, we established a gene- and clinical factor-related nomogram. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve showed that this model had moderate accuracy. The correlation analysis between the risk score and the infiltration of six common types of immune cells showed that the model could reflect the state of the immune microenvironment in HCC tumours. Conclusion Our IRG prognostic model was shown to have value in the monitoring, treatment, and prognostic assessment of HCC patients and could be used as a survival prediction tool in the near future.

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