Varying Importance of Prognostic Factors in Subgroups of Myelodysplastic Syndromes Defined by Blast Count, Cytogenetic Risk Group, or WHO Classification.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 2776-2776
Author(s):  
Andrea Kuendgen ◽  
Corinna Strupp ◽  
Kathrin Nachtkamp ◽  
Barbara Hildebrandt ◽  
Rainer Haas ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Prognostic Factors ◽  
High Risk ◽  
Research Funding ◽  
Risk Group ◽  
Univariate Analysis ◽  
Risk Groups ◽  
High Risk Group ◽  
Intermediate Risk ◽  
Blast Count

Abstract Abstract 2776 Poster Board II-752 Introduction: We wondered whether prognostic factors have similar relevance in different subpopulations of MDS patients. Methods: Our analysis was based on patients with primary, untreated MDS, including 181 RA, 169 RARS, 649 RCMD, 322 RSCMD, 79 5q-syndromes, 290 RAEB I, 324 RAEB II, 266 CMML I, 64 CMML II, and 209 RAEB-T. The impact of prognostic variables in univariate analysis was compared in subpopulations of patients defined by medullary blast count, namely <5%, ≥5% (table), ≥10%, and ≥20% (not shown), as well as 3 subpopulations defined by the cytogenetic risk groups according to IPSS (table). Multivariate analysis of prognostic factors was performed for cytogenetically defined subgroups and WHO-subtypes. Results: Strong prognostic factors in all blast-defined subgroups were hemoglobin, transfusion dependency, increased WBC, age, and LDH. However, all variables became less important in patients with ≥20% blasts (RAEB-T) and increased WBC was rare. Platelet count and cytogenetic risk groups were relevant in patients with <5%, ≥5%, and ≥10% marrow blasts, but not in RAEB-T. Marrow fibrosis was important in patients with <5% or ≥5% blasts, but not ≥10%. Gender and ANC <1000/μl were significant only in patients with a normal blast count. Furthermore, we looked for the effect of the karyotypes, relevant for IPSS scoring (-Y, del5q, del20q, others, del7q/-7, complex), and found a comparable influence on survival, irrespective whether patients had < or ≥5% marrow blasts. In subpopulations defined by cytogenetic risk groups, several prognostic factors were highly significant in univariate analysis, if patients had a good risk karyotype. These included hemoglobin, sex, age, LDH, increased WBC, transfusion need, and blast count (cut-offs 5%, 10%, and 20%). In the intermediate risk group only LDH, platelets, WBC, and blasts were significant prognostic factors, while in the high risk group only platelets and blast count remained significant. Multivariate analysis was performed for the cytogenetic risk groups and for subgroups defined by WHO subtypes. The analysis considered blast count (</≥5%), hemoglobin, platelets, ANC, cytogenetic risk group, transfusion need, sex, and age. In the subgroup including RA, RARS, and 5q-syndrome, LDH, transfusion, and age in descending order were independent prognostic parameters. In the RCMD+RSCMD group, karyotype, age, transfusion, and platelets were relevant factors. In the RAEB I+II subgroup, the order was hemoglobin, karyotype, age, and platelets, while in CMML I+II only hemoglobin had independent influence. In RAEB-T none of the factors examined was of independent significance. Looking at cytogenetic risk groups, in the favorable group, several variables independently influenced survival, namely transfusion, blasts, age, sex, and LDH (in this order). Interestingly, in the intermediate and high risk group, only blast count and platelets retained a significant impact. Conclusion: Univariate analysis showed prognostic factors (except ANC) included in IPSS and WPSS are relevant in most subgroups defined by marrow blast percentage. However, they all lose their impact if the blast count exceeds 20%. Regarding cytogenetic risk groups, several prognostic factors lose their influence already in the intermediate risk group. This underscores the prognostic importance of MDS cytogenetics. Multivariate analysis showed MDS subpopulations defined by WHO types also differ with regard to prognostic factors. In particular, CMML and RAEB-T stand out against the other MDS types. Disclosures: Kuendgen: Celgene: Honoraria. Hildebrandt:Celgene: Research Funding. Gattermann:Novartis: Honoraria, Participation in Advisory Boards on deferasirox clinical trials. Germing:Novartis, Celgene: Honoraria, Research Funding.

An Automated and Quantitative Protein Expression-Based Classification System to Identify High Risk Multiple Myeloma Patients

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 735-735
Author(s):  
Alex Klimowicz ◽  
Paola Neri ◽  
Adnan Mansoor ◽  
Anthony Magliocco ◽  
Douglas A. Stewart ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
High Risk ◽  
Protein Expression ◽  
Classification System ◽  
Risk Group ◽  
Univariate Analysis ◽  
High Risk Group ◽  
Group Classification ◽  
Low Risk ◽  
High Expression

Abstract Background: Autologous stem cell transplantation (ASCT) has dramatically improved the survival of myeloma patients; however, this approach has significant toxicities and nearly 25% of MM patients progress within one year from their transplant. While gene expression profiling-based (GEP) molecular classification has permitted the identification of unresponsive high-risk patients, these approaches have proven too costly and complex to translate into clinical practice. Less expensive and more readily available methods are needed clinically to identify, at the time of diagnosis, MM patients who may benefit from more aggressive or experimental therapies. While protein-based tissue arrays offer such alternative, biases introduced by the “observer-dependent” scoring methods have limited their wide applicability. Methods: We have designed a simplified, fully automated and quantitative protein expression based-classification system that will allow us to accurately predict survival post ASCT in a cost effective and “observer-independent” manner. We constructed tissue microarrays using diagnostic bone marrow biopsies of 82 newly diagnosed MM patients uniformly treated with a dexamethasone based induction regimen and frontline ASCT. Using the HistoRx PM-2000 quantitative immunohistochemistry platform, coupled with the AQUA analysis software, we have examined the expression of the following proteins: FGFR3 which is associated with t(4;14), cyclin B2 and Ki-67 which are associated with cellular proliferation, TACI which is associated with maf deregulation, and phospho-Y705 STAT3 and p65NF-κB, which are associated with myeloma cell growth and survival. For FGFR3, patients were divided into FGFR3 positive and negative groups based on hierarchical clustering of their AQUA score. For all other proteins examined, based on AQUA scores, the top quartiles or quintiles of patients were classified as high expression groups. Based on the univariate analysis, patients were further classified as “High Risk” MM if they had been identified as high expressers of either TACI, p65NF-κB or FGFR3. The Kaplan-Meier method was used to estimate time to progression and overall survival. Multivariate analysis was performed using the Cox regression method. Results: 82 patients were included in this study. In univariate analysis, FGFR3 and p65NF-κB expression were associated with significantly shorter TTP (p=0.018 and p=0.009) but not OS (p=0.365 and p=0.104). TACI expression levels predicted for worse OS (p=0.039) but not TTP (p=0.384). High expression of Ki67 or phospho-Y705 STAT3 did not affect survival. Of the 82 cases, 67 were included in the multivariate analysis since they had AQUA scores available for all markers: 26 (38.8%) were considered as High Risk by their AQUA scores and had significantly shorter TTP (p=0.014) and OS (p=0.006) compared to the Low Risk group. The median TTP for the Low and High Risk groups was 2.9 years and 1.9 years, respectively. The 5-years estimates for OS were 60.6% for the High Risk group versus 83.5% for the Low Risk group. Multivariate analysis was performed using del13q and our risk group classification as variables. Both our risk group classification and del13q were independent predictors for TTP, having 2.4 and 2.3 greater risk of relapse, respectively. Our risk group classification was the only independent predictor of OS with the High Risk group having a 5.9 fold greater risk of death. Conclusions: We have found that the expression of FGFR3, TACI, and p65NF-κB, in an automated and fully quantitative tissue-based array, is a powerful predictor of survival post-ASCT in MM and eliminates the “observer-dependent” bias of scoring TMAs. A validation of this “High Risk” TMA based signature is currently underway in larger and independent cohorts. Figure Figure

Application of a Validated Predictive Model for Venous Thromboembolism in Cancer to Patients with Multiple Myeloma

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 534-534
Author(s):  
Natasha Catherine Edwin ◽  
Jesse Keller ◽  
Suhong Luo ◽  
Kenneth R Carson ◽  
Brian F. Gage ◽  
...  
Keyword(s):  
High Risk ◽  
Research Funding ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Intermediate Risk ◽  
Discriminative Ability ◽  
Blood Institute ◽  
C Statistic

Abstract Background Patients with multiple myeloma (MM) have a 9-fold increased risk of developing venous thromboembolism (VTE). Current guidelines recommend pharmacologic thromboprophylaxis in patients with MM receiving an immunomodulatory agent in the presence of additional VTE risk factors (NCCN 2015, ASCO 2014, ACCP 2012). However, putative risk factors vary across guidelines and no validated VTE risk tool exists for MM. Khorana et al. developed a VTE risk score in patients with solid organ malignancies and lymphoma (Blood, 2008). We sought to apply the Khorana et al. score in a population with MM. Methods We identified patients diagnosed with MM within the Veterans Health Administration (VHA) between September 1, 1999 and December 31, 2009 using the International Classification of Diseases (ICD)-03 code 9732/3. We followed the cohort through October 2014. To eliminate patients with monoclonal gammopathy of undetermined significance and smoldering myeloma, we excluded patients who did not receive MM-directed therapy within 6 months of diagnosis. We also excluded patients who did not have data for hemoglobin (HGB), platelet (PLT) count, white blood count (WBC), height and weight, as these are all variables included in the Khorana et al. risk model. Height and weight were assessed within one month of diagnosis and used to calculate body mass index (BMI). We measured HGB, PLT count, and WBC count prior to treatment initiation: within two months of MM diagnosis. A previously validated algorithm, using a combination of ICD-9 code for VTE plus pharmacologic treatment for VTE or IVC filter placement, identified patients with incident VTE after MM diagnosis (Thromb Res, 2015). The study was approved by the Saint Louis VHA Medical Center and Washington University School of Medicine institutional review boards. We calculated VTE risk using the Khorana et al. score: We assigned 1 point each for: PLT ≥ 350,000/μl, HGB < 10 g/dl, WBC > 11,000/μl, and BMI ≥ 35 kg/m2. Patients with 0 points were at low-risk, 1-2 points were considered intermediate-risk and ≥3 points were termed high-risk for VTE. We assessed the relationship between risk-group and development of VTE using logistic regression at 3- and 6-months. We tested model discrimination using the area under the receiver operating characteristic curve (concordance statistic, c) with a c-statistic range of 0.5 (no discriminative ability) to 1.0 (perfect discriminative ability). Results We identified 1,520 patients with MM: 16 were high-risk, 802 intermediate-risk, and 702 low-risk for VTE using the scoring system in the Khorana et al. score. At 3-months of follow-up, a total of 76 patients developed VTE: 27 in the low-risk group, 48 in the intermediate-risk group, and 1 in the high-risk group. At 6-months of follow-up there were 103 incident VTEs: 41 in the low-risk group, 61 in the intermediate-risk group, and 1 in the high-risk group. There was no significant difference between risk of VTE in the high- or intermediate-risk groups versus the low-risk group (Table 1). The c-statistic was 0.56 at 3-months and 0.53 at 6-months (Figure 1). Conclusion Previously, the Khorana score was developed and validated to predict VTE in patients with solid tumors. It was not a strong predictor of VTE risk in MM. There is a need for development of a risk prediction model in patients with MM. Figure 1. Figure 1. Disclosures Carson: American Cancer Society: Research Funding. Gage:National Heart, Lung and Blood Institute: Research Funding. Kuderer:Janssen Scientific Affairs, LLC: Consultancy, Honoraria. Sanfilippo:National Heart, Lung and Blood Institute: Research Funding.

High Prevalence of Relapse in Australian Children with Ph-like Acute Lymphoblastic Leukemia Despite Risk Adapted Treatment

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1419-1419 ◽  
Author(s):  
Susan L Heatley ◽  
Teresa Sadras ◽  
Eva Nievergall ◽  
Chung Hoow Kok ◽  
Phuong Dang ◽  
...  
Keyword(s):  
High Risk ◽  
Research Funding ◽  
Risk Group ◽  
Lymphoblastic Leukemia ◽  
Risk Groups ◽  
High Risk Group ◽  
Event Free Survival ◽  
Free Survival ◽  
Kaplan Meier ◽  
Medium Risk

Abstract Introduction: While remission rates for childhood acute lymphoblastic leukemia (ALL) now exceed 80%, relapsed ALL remains the leading cause of non-traumatic death in children. Recently, a high-risk group of B-progenitor ALL patients has been identified. Such cases exhibit a gene expression profile similar to that of BCR-ABL1 positive (Ph+) ALL but are BCR-ABL1 negative, and also experience poor treatment outcomes. This subset, termed Ph-like ALL, is characterised by a range of genetic alterations that activate cytokine receptor and kinase signalling, allowing potential targeting by available tyrosine kinase inhibitors (TKI). The frequency of Ph-like ALL in the Australian community and the prognosis in the setting of the first MRD (minimal residual disease) intervention trial by the Australian and New Zealand Children's Haematology/Oncology Group (ANZCHOG ALL8) is unknown. Method: We retrospectively screened 250 unselected samples that were available from children diagnosed with B-ALL, for Ph-like ALL. The children, aged between 1 and 18 years, were enrolled on the ANZCHOG ALL8 trial and recruited from 2002-2011. The criteria for stratification to the high-risk group, based upon Berlin-Frankfurt-Munster (BFM) protocols, were BCR-ABL1 or MLL t(4;11) translocation; poor prednisolone response at day 8; failure to achieve remission by day 33 or high MRD (>5 x10-4) at day 79. MRD was measured by RQ-PCR for patient-specific immunoglobulin and T-cell receptor rearrangements. All patients received a standard BFM four drug induction chemotherapy regimen including a prednisolone pre-phase and intrathecal methotrexate. High-risk patients received a further three novel intensive blocks of chemotherapy followed by transplant in most cases. Patients were screened for Ph-like ALL using a custom Taqman Low Density Array (TLDA) based upon previous reports. Fusions were then confirmed by RT-PCR for 30 known fusions, Sanger sequencing, mRNA sequencing and/or FISH. Results: Ten percent (25/250) of children in this cohort were identified as having Ph-like ALL, with most fusions converging on kinase activating pathways (Table 1). Three Ph-like ALL patients were considered high-risk, the remaining 22 (88%) were medium risk. Five children with Ph-like ALL, that did not have a fusion identified by RT-PCR, are currently under further investigation. Furthermore, 15 of the 20 (75%) of rearrangements involved CRLF2 with 10 (66%) of these children relapsing. Strikingly, 56% (14/25) of children in the ALL8 cohort who were identified as Ph-like subsequently relapsed compared to 16% (36/225) who were not, with significantly worse event free survival (p<0.0001) (Figure 1). Conclusion: Here we demonstrate a significantly higher frequency of relapse amongst Australian children with Ph-like ALL compared to non Ph-like disease despite a MRD-adjusted intensification regimen. In this cohort, these children should be classified as high-risk due to high treatment failure rates with standard/medium risk regimens. Importantly, rapid identification of these patients may guide future intervention with targeted therapies, such as TKI, matched to the causative genetic lesion in this high-risk group. Figure 1. Fusions identified in Ph-like ALL from ANZCHOG ALL8 cohort. Figure 1. Fusions identified in Ph-like ALL from ANZCHOG ALL8 cohort. Figure 2. Kaplan-Meier estimates of event free survival for patients with Ph-like ALL and non Ph-like ALL (all risk groups). Figure 2. Kaplan-Meier estimates of event free survival for patients with Ph-like ALL and non Ph-like ALL (all risk groups). Disclosures Hughes: ARIAD: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Mullighan:Incyte: Consultancy, Honoraria; Cancer Science Institute: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Speakers Bureau; Loxo Oncology: Research Funding. White:Novartis: Honoraria, Research Funding; BMS: Honoraria, Research Funding.

The Combination of SKY92 and ISS Provides a Powerful Tool to Identify Both High Risk and Low Risk Multiple Myeloma Cases, Validation in Two Independent Cohorts

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 2970-2970 ◽  
Author(s):  
Martin van Vliet ◽  
Joske Ubels ◽  
Leonie de Best ◽  
Erik van Beers ◽  
Pieter Sonneveld
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Research Funding ◽  
Prognostic Markers ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Low Risk ◽  
Kaplan Meier ◽  
Standard Risk

Abstract Introduction Multiple Myeloma (MM) is a heterogeneous disease with a strong need for robust markers for prognosis. Frequently occurring chromosomal abnormalities, such as t(4;14), gain(1q), and del(17p) etc. have some prognostic power, but lack robustness across different cohorts. Alternatively, gene expression profiling (GEP) studies have developed specific high risk signatures such as the SKY92 (EMC92, Kuiper et al. Leukemia 2012), which has shown to be a robust prognostic factor across five different clinical datasets. Moreover, studies comparing prognostic markers have indicated that the SKY92 signature outperforms all other markers for identifying high risk patients, both in single and multivariate analyses. Similarly, when assessing the prognostic value of combinations of various prognostic markers, the SKY92 combined with ISS was the top performer, and also enables detection of a low risk group (Kuiper et al. ASH 2014). Here, we present a further validation of the low and high risk groups identified by the SKY92 signature in combination with ISS on two additional cohorts of patients with diverse treatment backgrounds, containing newly diagnosed, previously treated, and relapsed/refractory MM patients. Materials and Methods The SKY92 signature was applied to two independent datasets. Firstly, the dataset from the Total Therapy 6 (TT6) trial, which is a phase 2 trial for symptomatic MM patients who have received 1 or more prior lines of treatment. The TT6 treatment regime consists of VTD-PACE induction, double transplant with Melphalan + VRD-PACE, followed by alternating VRD/VMD maintenance. Affymetrix HG-U133 Plus 2.0 chips were performed at baseline for n=55 patients, and OS was made available previously (Gene Expression Omnibus identifier: GSE57317). However, ISS was not available for this dataset. Secondly, a dataset of patients enrolled at two hospitals in the Czech Republic, and one in Slovakia (Kryukov et al. Leuk&Lymph 2013). Patients of all ages, and from first line up to seventh line of treatment were included (treatments incl Bort, Len, Dex). For n=73 patients Affymetrix Human Gene ST 1.0 array, OS (n=66), and ISS (n=58) was made available previously (ArrayExpress accession number: E-MTAB-1038). Both datasets were processed from .CEL files by MAS5 (TT6), and RMA (Czech), followed by mean variance normalization per probeset across the patients. The SKY92 was applied as previously described (Kuiper et al. Leukemia 2012), and identifies a High Risk and Standard Risk group. In conjunction with ISS, the SKY92 Standard Risk group is then further stratified into low and intermediate risk groups (Kuiper et al. ASH 2014). Kaplan-Meier plots were created, and the Cox proportional hazards model was used to calculate Hazard Ratios (HR), and associated 1-sided p-values that assess whether the SKY92 High Risk group has worse survival than SKY92 Standard Risk group (i.e. HR>1). Results Figure 1 shows the Kaplan Meier plots of the SKY92 High Risk and Standard Risk groups on the TT6 and Czech cohorts. On the TT6 dataset, the SKY92 signature identifies 11 out of 55 patients (20%) as High Risk. In both datasets, the SKY92 High Risk group has significantly worse overall survival, HR=10.3, p=7.4 * 10-6 (TT6), and HR=2.6, p=2.2 * 10-2 (Czech). In addition, the combination of SKY92 with ISS on the Czech dataset identifies a low risk group of 14 out of 61 patients (23%), with a five year overall survival estimate of 100% versus 28.7% in the SKY92 High Risk group (HR=inf). Robustness of the SKY92 signature is further demonstrated by the fact that it validates on both datasets, despite different microarray platforms being used. Conclusions The SKY92 high risk signature has been successfully validated on two independent datasets generated using different microarray platforms. In addition, on the Czech data, the low risk group (SKY92 Standard Risk combined with ISS 1) has been successfully validated. Together, this signifies the robust nature of the SKY92 signature for high and low risk prediction, across treatments, and with applicability in newly diagnosed, treated, and relapsed/refractory MM patients. Figure 1. Kaplan-Meier plots showing a significantly poorer overall survival in patients identified as SKY92 High Risk (red curves), relative to SKY92 Standard Risk, on both the TT6 (left), and Czech (middle) datasets, as well as a low risk group by SKY92 & ISS1 on the Czech dataset (green curve, right). Figure 1. Kaplan-Meier plots showing a significantly poorer overall survival in patients identified as SKY92 High Risk (red curves), relative to SKY92 Standard Risk, on both the TT6 (left), and Czech (middle) datasets, as well as a low risk group by SKY92 & ISS1 on the Czech dataset (green curve, right). Disclosures van Vliet: SkylineDx: Employment. Ubels:SkylineDx: Employment. de Best:SkylineDx: Employment. van Beers:SkylineDx: Employment. Sonneveld:Celgene: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Karyopharm: Research Funding; SkylineDx: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Research Funding.

scholarly journals A novel hyperinflammation clinical risk tool, HI5-NEWS2, predicts mortality following early dexamethasone use in an observational cohort of hospitalised COVID-19 patients.

2021 ◽  
Author(s):  
Michael R Ardern-Jones ◽  
Hang T.T. Phan ◽  
Florina Borca ◽  
Matthew Stammers ◽  
James Batchelor ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Low Risk ◽  
Intermediate Risk ◽  
Dexamethasone Treatment ◽  
Dexamethasone Therapy ◽  
Risk Patients ◽  
Anti Inflammatory

Background The success of early dexamethasone therapy for hospitalised COVID-19 cases in treatment of Sars-CoV-2 infection may predominantly reflect its anti-inflammatory action against a hyperinflammation (HI) response. It is likely that there is substantial heterogeneity in HI responses in COVID-19. Methods Blood CRP, ferritin, neutrophil, lymphocyte and platelet counts were scored to assess HI (HI5) and combined with a validated measure of generalised medical deterioration (NEWS2) before day 2. Our primary outcome was 28 day mortality from early treatment with dexamethasone stratified by HI5-NEWS2 status. Findings Of 1265 patients, high risk of HI (high HI5-NEWS2) (n=367, 29.0%) conferred a strikingly increased mortality (36.0% vs 7.8%; Age adjusted hazard ratio (aHR) 5.9; 95% CI 3.6-9.8, p<0.001) compared to the low risk group (n= 455, 36.0%). An intermediate risk group (n= 443, 35.0%) also showed significantly higher mortality than the low risk group (17.6% vs 7.8%), aHR 2.2, p=0.005). Early dexamethasone treatment conferred a 50.0% reduction in mortality in the high risk group (36.0% to 18.0%, aHR 0.56, p=0.007). The intermediate risk group showed a trend to reduction in mortality (17.8% to 10.3%, aHR 0.82, p=0.46) which was not observed in the low risk group (7.8% to 9.2%, aHR 1.4, p =0.31). Interpretation The HI5-NEWS2 measured at COVID-19 diagnosis, strongly predicts mortality at 28 days. Significant reduction in mortality with early dexamethasone treatment was only observed in the high risk group. Therefore, the HI5-NEWS2 score could be utilised to stratify randomised clinical trials to test whether intensified anti-inflammatory therapy would further benefit high risk patients and whether alternative approaches would benefit low risk groups. Considering its recognised morbidity, we suggest that early dexamethasone should not be routinely prescribed for HI5-NEWS2 low risk individuals with COVID-19 and clinicians should cautiously assess the risk benefit of this intervention. Funding No external funding.

scholarly journals Allotransplants for Patients 65 Years or Older with High-Risk Acute Myeloid Leukemia

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 4667-4667
Author(s):  
Paul Lin ◽  
Lauren Westfall Veltri ◽  
Katy Rezvani ◽  
Betul Oran ◽  
Sairah Ahmed ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Prognostic Factors ◽  
High Risk ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Risk Group ◽  
Morphological Evidence ◽  
Consolidation Chemotherapy ◽  
Medical Event ◽  
History Of

Abstract Outcome of persons >65 years with acute myeloid leukemia (AML) is poor. Allogeneic transplant can cure some of these patients but is associated with substantial transplant-related mortality (TRM) and high relapse risk. We analyzed 185 consecutive patients >65 years with high-risk AML between 2010 and 2015 who had measurable residual disease (MRD) and molecular risk assessments and who received myeloablative conditioning (MAC, n=42) or reduced-intensity conditioning (RIC, n=143) and a transplant from an HLA-identical sibling (n=66) or a 10/10 loci HLA-matched unrelated donor (MUD, n=119) in order to identify patients who would benefit from allotransplant. MRD was assessed by flow cytometry in bone marrow samples. AML cytogenetic and molecular risk were defined using the 2017 European Leukemia Net genetic risk stratification. The patients who were MRD-negative at time of transplant had a better 2-year cumulative incidence of relapse (CIR 17.6%) and a 2-year overall survival (OS, 69.4%) as compared to the patients in remission but MRD-positive (55.6% CIR, 21.5% OS) or the patients who had morphological evidence of leukemia prior to transplant (48.7% CIR, 19.9% OS), (p<0.0001). Multivariate analysis for 2-year CIR showed that having detectable leukemia at time of SCT (defined as MRD-positive or morphological evidence of leukemia) (HR=14.5, CI=3.4-61.4, p<0.0001), having received <3 cycles of chemotherapy prior to SCT (HR=1.8, CI=1.1-2.8 p=0.01), and high-risk genetics were independent predictors of relapse. However, high-risk genetics only had a deleterious effect on outcomes for MRD-negative patients (HR=9.4, CI=2.0-43.6, p=0.004), and did not affect the outcome of patients with detectable leukemia (HR=1.1, CI=0.7-1.9, p=0.61). Patients who received RIC (Flu-Mel-RIC or Bu-Flu-RIC) or MAC (Bu-Flu-MAC) had similar proportion of MRD-negative patients (p=1.0). However, MRD-negative patients who received Flu-Mel-RIC had a superior OS than patients who received Bu-Flu-RIC (adjusted HR=1 vs 5.3, p=0.02) or patients who received Bu-Flu-MAC (HR=1 vs 5.093, p=0.04), which is explained by a significantly lower relapse rate in patients receiving Flu-Mel-RIC (adjusted HR=1 vs 4.8, p=0.03) and a significantly lower TRM as compared to patients receiving Bu-Flu-MAC (adjusted HR= 5.1, p=0.01). Patients who had major medical complications (MMC), defined as a medical event requiring admission to the intensive care unit for ventilatory or inotropic support or a medical event that prolonged the patient hospitalization for more than 2 weeks, during induction or consolidation chemotherapy preceding the transplant, had a higher day +100 mortality (30.6% vs 6.0%, p<0.0001), 2-year TRM (55.6% vs 16.8%, p<0.0001) and lower 2-year OS (8.3% vs 44.6%, p<0.0001). Multivariate analysis for 2-year OS showed that history of delayed hematological recovery during induction or consolidation chemotherapy prior to transplantation (HR=1.5, CI=1.0-2.3, p=0.04), high risk genetics (HR=1.8 CI:1.2-2.6, p=0.006), donor-recipient HLA-DRβ3/4/5-DP mismatch (HR=2.2, CI=1.3-3.6, p=0.001), history of cardiovascular disease (HR=1.7, CI=1.1-2.6, p=0.02) were independent predictors for OS. Other variables such as secondary leukemia, CMV sero-status, FEV1 or creatinine clearance prior to SCT, sex mismatch, ABO group mismatch, donor type, or stem cell source did not have a significant impact on OS or TRM. Outcomes were also similar between patients transplanted in CR1 or in ≥ CR2 or in CR or CRi. We sought to identify those patients who may clearly benefit from a SCT. To that end, we classified patients according to the MRD status prior to transplantation and the presence or absence of the other prognostic factors identified in the multivariate analysis. As seen in the Figure, the High risk group which includes patients with detectable leukemia and >1 additional adverse prognostic factors (or a MMC), had a 2-year OS of 7.7% (CI=3.1-17.8). In comparison, the Low risk group which includes MRD-negative patients with ≤3 other prognostic factors (and no MMC), had a 2-year OS of 76.2% (CI=63.3-85.6). Finally, the Intermediate risk group which constituted the remaining patients, had a 2-year OS of 32.2% (CI=22.1-44.3, p<0.00001). These data indicate the possibility to identify persons >65 years with high-risk AML likely to benefit from an allotransplant. Figure. Figure. Disclosures Rezvani: Affirmed GmbH: Research Funding. Oran:ASTEX: Research Funding; Celgene: Consultancy, Research Funding; AROG pharmaceuticals: Research Funding. Shpall:Affirmed GmbH: Research Funding. Champlin:Otsuka: Research Funding; Sanofi: Research Funding.

Differences In Clinical Characteristics and Prognostic Features Between Patients with Myelodysplastic Syndromes (MDS) From Korea, Japan, and Germany

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 1882-1882
Author(s):  
Andrea Kuendgen ◽  
Je-Hwan Lee ◽  
Akira Matsuda ◽  
Kyoo Hyung Lee ◽  
Jung-Hee Lee ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Clinical Characteristics ◽  
Risk Group ◽  
Risk Groups ◽  
Low Risk ◽  
Intermediate Risk ◽  
Asian Countries ◽  
Cell Counts ◽  
Blast Count ◽  
K 12

Abstract Abstract 1882 Evidence exists for differences between eastern and western type MDS. However, for the development of the IPSS Score, 6 of the participating study groups were European or US, while only one group originated from Japan. In order to find out more about the differences in MDS patients (pts) from separate ethnic groups we performed an analysis of 1048 pts from Dusseldorf, Germany (G), 242 pts from Seoul, Korea (K), and 143 pts from Saitama, Japan (J). Initially, we compared clinical characteristics. Then we evaluated the influence of important prognostic factors. For all pts included at least the parameters needed to determine the IPSS had to be available. For survival analyses pts who received induction chemotherapy or allogeneic transplantation were excluded. Median age was 66 yrs in Germany, 54 in Korea, and 68 in Japan. The distribution of gender, with a male preponderance, was comparable in all cohorts. Median blast count was <5% in all groups. Median cell counts were significantly lower in the Japanese and Korean, when compared to the German pts. However, although Asian pts tended to have more severe cytopenias regarding all 3 lineages, they also had a significantly higher percentage of refractory cytopenias with unilineage dysplasia (21% (K) and 36% (J) compared to 7% (G)). MDS with del5q was significantly more frequent in German pts (9 vs 0 vs 1%) as well as RCMD (40 vs 22 vs 18%), while the frequency of RAEB I/II was comparable. Due to the high incidence of pancytopenia Asian pts rarely had a low risk IPSS (2% (K), 12% (J) vs 27% (G)), while the int I risk group was larger and int II and high risk groups were of almost the same size. Regarding karyotype (KT) risk according to IPSS, the intermediate risk group was smaller, and the low risk group was larger in Asian pts. To evaluate the relevance of different prognostic factors we first compared the whole cohorts of not intensively treated pts. Since the result was all factors analyzed were important in German while many were not in Asian pts we decided to look at a smaller subgroup of German pts to compare similar sizes. Pts were chosen by chance to avoid any kind of bias by matching. The results are presented in table 1. Already survival was very different in the 3 groups: 31 months (ms) (G) vs 43 ms (K) vs 157 ms (J). In univariate analysis in German pts variables with significant influence on survival were Hb, sex, age, LDH, platelets, blast count, KT, and IPSS, while in the Korean and Japanese pts the 3 different cytopenias and LDH had no influence on survival (except a borderline influence of Hb in Japanese pts). Very striking was the importance of gender in the 2 Asian countries. In both men lived for a median of only about 2 years, comparable to German pts, while women had a very long survival with median not reached. Regarding KT risk, the intermediate risk group had in the Asian countries a significantly longer survival than in Germany (nr vs 24 ms), possibly due to a high frequency of +8. The IPSS divided, again in both Asian countries, 2 different risk groups, but not 4. Multivariate analysis identified Hb, platelets, blasts, LDH, age, and KT as independent risk factors for German pts, compared to ANC, blast count, and age in Korean, and blast count plus KT in Japanese pts. It is established that survival of Asian MDS pts is longer than that of European, but it remains unclear why there is such a strong difference between Korean and Japanese pts although the former are younger and most other features are very comparable between the two. The most striking features of Asian MDS are the strong influence of gender, as well as the lesser importance of cytopenias compared to European pts. This, together with a slight difference in the survival according to KT, leads to an inferior separation of risk groups by the IPSS. The most important factor with equal relevance in all MDS pts remains blast count. Disclosures: No relevant conflicts of interest to declare.

scholarly journals 55例血管免疫母细胞性T细胞淋巴瘤的临床特征和预后模型

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 37-38
Author(s):  
Xiaohong Tan ◽  
Jie Sun ◽  
Sha He ◽  
Chao Rong ◽  
Hong Cen
Keyword(s):  
High Risk ◽  
Prognostic Model ◽  
Risk Group ◽  
Prognostic Index ◽  
Risk Groups ◽  
High Risk Group ◽  
Low Risk ◽  
Intermediate Risk ◽  
Ecog Ps ◽  
Medical University

Angioimmunoblastic T-cell lymphoma (AITL) is a distinct subtype of peripheral T-cell lymphoma with unique clinical and pathological features. This study aim to analyze the characteristics of AITL and to design a prognostic model specifically for AITL, providing risk stratification in affected patients. We retrospectively analyzed 55 newly diagnosed AITL patients at the Affiliated Tumor Hospital of Guangxi Medical University from January 2007 to June 2016 and was permitted by the Ethics Committee of the Affiliated Tumor Hospital of Guangxi Medical University. Among these patients, the median age at diagnosis was 61 (27-85) and 54.55% (30/55) of the patients were older than 60 years. 43 patients were male, accounting for 78.18% of the whole. Among these, 92.73% (51/55) of the diagnoses were estimated at advanced stage. A total of 20 (36.36%) patients were scored &gt;1 by the ECOG performance status. Systemic B symptoms were described in 16 (29.09%) patients. In nearly half of the patients (27/55; 49.09%) had extranodal involved sites. The most common extranodal site involved was BM (11/55; 20.00%). 38.18% (21/55) and 27.27% (15/55) patients had fever with body temperature ≥37.4℃ and pneumonia, respectively. 40% (22/55) patients had cavity effusion or edema. Laboratory investigations showed the presence of anemia (hemoglobin &lt;120 g/L) in 60% (33/55), thrombocytopenia (platelet counts &lt;150×109/L) in 29.09% (16/55), and elevated serum LDH level in 85.45% (47/55) of patients. Serum C-reactive protein and β2-microglobulin levels were found to be elevated in 60.98% (25/41) and 75.00% (36/48)of the patients, respectively. All patients had complete information for stratification into 4 risk subgroups by IPI score, in which scores of 0-1 point were low risk (9/55;16.36%), two points were low-intermediate risk (17/55; 30.92%), three points were high-intermediate risk (20/55; 36.36%), and four to five points were high risk (9/55; 16.36%). 55 patients were stratified by PIT score with 7.27% (4/55) of patients classified as low risk, 32.73% (18/55) as low-intermediate risk, 34.55% (19/55) as high-intermediate risk, and 25.45% (14/55) as high risk depending on the numbers of adverse prognostic factors.The estimated two-year and five-year overall survival (OS) rate for all patients were 50.50% and 21.70%. Univariate analysis suggested that ECOG PS (p= 0.000), Systemic B symptoms (p= 0.006), fever with body temperature ≥ 37.4℃ (p= 0.000), pneumonia (p= 0.001), cavity effusion or edema (p= 0.000), anemia (p= 0.013), and serum LDH (p= 0.007) might be prognostic factors (p&lt; 0.05) for OS. Multivariate analysis found prognostic factors for OS were ECOG PS (p= 0.026), pneumonia (p= 0.045), and cavity effusion or edema(p= 0.003). We categorized three risk groups: low-risk group, no adverse factor; intermediate-risk group, one factor; and high-risk group, two or three factors. Five-year OS was 41.8% for low-risk group, 15.2% for intermediate-risk group, and 0.0% for high-risk group (p&lt; 0.000). Patients with AITL had a poor outcome. This novel prognostic model balanced the distribution of patients into different risk groups with better predictive discrimination as compared to the International Prognostic Index and Prognostic Index for PTCL. Disclosures No relevant conflicts of interest to declare.

Induction Therapy with “3+7” Chemotherapy Plus ATRA Followed by Consolidations with Three Courses of Idarubicin Alone and Maintenance Therapy with ATRA in Newly Diagnosed Acute Promyelocytic Leukemia (APL) Has An Excellent Leukemia-Free Survival but Minimal Toxicity in Low and Intermediate Risk Groups.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 2072-2072
Author(s):  
Moon-Young Choi ◽  
Yeung-Chul Mun ◽  
Se Hoon Park ◽  
Eun Kyung Cho ◽  
Jae Hoon Lee ◽  
...  
Keyword(s):  
High Risk ◽  
Maintenance Therapy ◽  
Relapse Rate ◽  
Induction Therapy ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Low Risk ◽  
Intermediate Risk ◽  
Newly Diagnosed

Abstract Abstract 2072 Poster Board II-49 Backgrounds Currently, there are many efforts to design risk-adapted strategies in newly diagnosed acute promyelocytic leukemia (APL) by modulating treatment intensity and those seem to be an efficient approach to minimize treatment-related morbidity and mortality (TRM) while maintain the potential in cure for each relapse-risk group. We had postulated that maintaining of Ara-C during induction therapy might have acceptable toxicities yet obtaining good CR in newly diagnosed APL, and idarubicin alone during consolidation periods might have excellent LFS and OS with low relapse rate. Patients and Methods Eighty six patients with newly diagnosed APL were enrolled in the “multicenter AML-2000 trial” after informed consents were obtained during the period of January 2000 to July 2007. For remission induction therapy, patients received oral ATRA (45mg/m2/d, maintained until CR) combined with idarubicin (12mg/m2/d, D1-D3) plus Ara-C (100mg/m2/d, D1-D7). After CR achievement, patients received 3 monthly consolidation courses consisting of idarubicin (12mg/m2/d, D1-D3) alone and maintenance therapy with ATRA (45mg/m2/d, D1-D15, every 2 month) alone had continued for 2 years. Total patients were divided into low-risk, intermediate-risk and high-risk groups according to a predictive model for relapse risk (Sanz score) based on pretreatment WBC and platelet count and the treatment outcomes were compared in the different risk groups. Results The median age of our cohort was 40 years old (range; 6-80) and median follow-up was 27 months (range; 1-90). The distribution of patients in the 3 risk groups was as follows ; 28 (32.6%) patients in low-risk, 40 (46.5%) in intermediate-risk and 18 (20.9%) in high-risk. Overall, CR was achieved in 78 (90.7%) of 86 patients. The CR rate according risk groups was 96.4% in low-risk, 87.5% in intermediate-risk, and 88.9% in high-risk group and there was no significant statistical difference among the different risk groups. During induction therapy, 48 (55.8%) patients experienced grade 3-4 treatment-related toxicity (TRT), mostly fever and infection (38.8% of all patients) and 6 (7.0%) patients died of treatment-related complications. During 3 consolidation courses, 25 (29.1%) of 78 patients experienced grade 3-4 TRT in 1st course, 27 (36.0%) of 75 patients in 2nd course, and 14 (28.0%) of 50 patients in 3rd course. Overall, 3 (3.5%) patients died of treatment-related complications in CR. The incidence of TRT and treatment-related mortality (TRM) during induction or consolidation therapy showed no significant statistical difference among the different risk groups. The relapse occurred in 6 (7.0%) patients; 2 cases in intermediate-risk and 4 cases in high-risk. However, none had relapsed in low risk group, 5 patients of relapsed patients relapsed during consolidation courses and only one patient, however, relapsed during maintenance therapy. The overall survival (OS) and leukemia-free survival (LFS) rate at 7 years in all of patients was 76.7% and 83.5%, respectively. The OS rate at 7 years was 92.9% in low-risk, 78.6% in intermediate-risk and 53.6% in high-risk group (P:0.04) and the LFS rate at 7 years was 96.4%, 83.4% and 62.2% respectively, showing the significant difference between 3 different risk groups (P:0.046). Conclusions This study indicates that our protocol composed of induction therapy with “3+7” chemotherapy plus ATRA followed by consolidations with three courses of idarubicin alone and maintenance therapy with ATRA alone yields a high CR rate and low relapse rate but minimal acceptable toxicities. Despite of adding Ara-C during induction therapy, we did not find much significant toxicities but having good CR rates, and despite of not adding any additional low/intermediate dose chemotherapies(ie, 6MP), we were able to observe significantly high relapse rate in low and intermediate risk group with excellent LFS and OS. Meanwhile, in high-risk group, the relapse rate was significantly higher than other risk groups and most of the relapses occurred in the middle of consolidation courses. This data suggests that our consolidation therapy composed of anthracycline alone may be not enough to minimize risk of relapse in high-risk group in contrast with the low and intermediate-risk groups. More intensive consolidation therapy combined with other effective, but get tolerable chemotherapies or hematopoietic stem cell transplantation in first CR or the combination of arsenic trioxide or others in front-line therapy should be considered in the patients with high-risk of relapse. Disclosures: No relevant conflicts of interest to declare.

The Utility Of Newer Risk Models In Predicting Outcomes Of Patients (pts) With Higher-Risk (HR) Myelodysplastic Syndromes (MDS) Treated With Azactidine (aza)

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2771-2771
Author(s):  
Amer M. Zeidan ◽  
Najla H Al Ali ◽  
Mohamed A. Kharfan-Dabaja ◽  
Eric Padron ◽  
Ling Zhang ◽  
...  
Keyword(s):  
High Risk ◽  
Scoring System ◽  
Research Funding ◽  
Goodness Of Fit ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Information Criteria ◽  
Prognostic Groups ◽  
Very High

Abstract Background While aza is the only drug shown to prolong survival in MDS, only half of aza-treated pts achieve objective responses (10-20% complete remission), and 4-6 months might be needed before a response is seen. Therefore the ability to select pts with high and low likelihoods of benefit from aza therapy is a clinical and a research priority. No clinical or laboratory parameter consistently predicts response or survival with aza therapy. A French prognostic scoring system (FPSS) was proposed to predict survival among aza-treated pts with HR-MDS. We sought to compare the relative prognostic discriminatory power of the FPSS with that of the revised IPSS (IPSS-R) and the global MD Anderson prognostic scoring system (MDAPSS) in a large cohort of aza-treated pts with IPSS HR-MDS. Methods The MDS database at Moffitt Cancer Center (MCC) was used to identify patients with HR-MDS (International Prognostic Scoring System [IPSS] intermediate-2 [INT-2] and high-risk) who received aza therapy. Kaplan-Meier curves were used to depict survivals, and the log-rank test was used to compare median overall survival (OS). Akaike information criteria (AIC) were used to assess the relative goodness of fit of the models. Results We identified 259 patients HR-MDS (74.1% with INT-2 and 25.9% with high IPSS) treated with aza at the MCC. The median duration of follow up since diagnosis was 53 months (M) (95% confidence interval [CI], 49-59 M). The median number of aza cycles was 5 (range 1-72), with 75% of pts receiving 4 cycles of therapy or more. The median time from diagnosis to aza initiation was 1.5 M. The median OS for the entire cohort was 19 M (95%CI, 16-22 M), 64% of pts were males, 91% were white, 80% were older than 60 years, and 25% had therapy-related MDS. For the IPSS, the median OS was 23.5 M (CI, 18.4-28.6 M) for INT-2 and 15.9 M (CI, 13.6-18.2 M) for high-risk group (P=0.004). For the FPSS, the median OS was 29.5 M (CI, 14.1-44.9 M) for low risk (LR), 21.1 M (CI, 16.4-26.0 M) for intermediate risk (IR), and 14.1 M (CI, 8.7-19.5 M) for HR (P=0.001). For the MDAPSS the median OS was not reached (NR) for low, 53.5 M (CI, 37.5-69.4 M) for INT-1, 29.5 M (CI, 18.3-40.6 M) for INT-2, and 16.1 M (CI, 14.5-17.7 M) for high risk groups (P<0.0001). For the IPSS-R, the median OS 40.6 M (CI, 22.8-58.4 M) for low, 44.7 M (CI, 25.0-64.4 M) for INT, 23.5 M (CI, 20.3-26.8 M) for high, and 15.2 M (CI, 13.7-16.8 M) for very-high risk groups (P<0.0001). Scores generated using AIC to assess the relative goodness of fit (lower is better) were 1453 (IPSS-R), 1480 (MDAPSS), 1512 (FPSS), and 1522 (IPSS). The IPSS could not refine any of the other models. All three newer models refined IPSS INT-2 but not IPSS high-risk. The IPSS did not refine any of the newer models. The MDAPSS refined the FPSS LR and IR and the IPSS-R high and very-high groups. The FPSS refined IPSS-R very high risk group but not the not the MDAPSS. The R-IPSS did not refine the MDAPSS or the FPSS. Response rates were not statically significantly different within the prognostic groups in any of the scoring systems. Conclusions The IPSS-R, MDAPSS, and the FPSS all functioned well to separate aza-treated pts with IPSS HR-MDS into prognostic groups with different survivals, but the IPSS-R and MDAPSS appear superior to the FPSS. None of the prognostic systems predicted response to aza therapy. HR-MDS patients with poor projected survival with aza therapy might be considered for experimental approaches. Disclosures: Off Label Use: entinostat for MDS. Lancet:Celgene: Research Funding. List:Celgene: Research Funding. Komrokji:Celgene: Research Funding, Speakers Bureau.

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