Ball, Somedeb

Introduction HMAs are the only approved therapy for CMML. In order to improve response rates and survival, the addition of VEN has been utilized in both CMML and after blast transformation (CMML-BT) with conflicting results in small single center studies. To clarify the role of upfront HMA+VEN in CMML and CMML-BT, we performed a large multicenter analysis. Methods We included patients with HMA-naïve CMML and CMML-BT treated with combination HMA and VEN from 4 academic centers. The primary outcome was overall survival (OS) with secondary outcomes including overall response rate (ORR) by 2015 MDS/MPN IWG criteria for CMML and 2022 ELN criteria for CMML-BT. To better appreciate the benefit of adding VEN to HMA treatment, we also performed 1:1 propensity score matched (PSM) analysis of patients treated with HMA alone as upfront therapy for CMML or CMML-BT. Matching was based on age, sex, ECOG performance status, CPSS-Mol, blood counts, peripheral and bone marrow blasts. Results Eighty-nine patients were treated with frontline HMA+VEN, 51 CMML and 38 CMML-BT (5 had received HMA alone for prior CMML). The median age was 71 years, 70% were male, and 83% had ECOG 0-1. Among CMML patients, 55% had MP-CMML subtype, 65% had CMML-2 and 12%, 30%, 58% were CPSS-mol intermediate-1, intermediate-2 and high risk, respectively. In the entire cohort, ASXL1 (63%), TET2 (47%), SRSF2 (39%) and RUNX1 (27%) were the most commonly mutated genes and 55% of patients harbored a RAS mutation ( KRAS [20%], NRAS [18%], CBL [13%], NF1 [11%], PTPN11 [9%]). For HMA combination partner, 46 (52%) were treated with azacitidine, 35 (39%) with decitabine, and 8 (9%) with both during their VEN course. During a median follow-up time of 15.8 months (mos) 52 patients (58%) died: 23 (45%) with CMML and 29 (76%) with CMML-BT. Among CMML patients, the ORR was 90%, including complete remission (CR) in 22%, complete cytogenic remission (CCR) in 4%, optimal marrow response (CMR) in 50%, and partial marrow response (PMR) in 6%. The OS of CMML patients was 25.1 mo (95% CI 15.7 - NR). A PSM population of HMA patients matched to HMA+VEN treated patients showing similar baseline characteristics. ORR was significantly higher with HMA+VEN (95%) as compared those treated with HMA alone (46%), p < 0.001. However, there was no significant OS difference between HMA+VEN vs HMA alone (19.1 mos vs 19.1 mos, p = 0.85, Figure 1). For CMML-BT patients, the ORR of HMA+VEN was 81% including CR in 17%, CR with partial hematologic recover (CRh) in 3%, CR with incomplete hematologic recovery (CRi) in 28%, morphologic leukemia-free state (MLFS) in 22% and partial response (PR) in 11%. The OS of CMML-BT patients was 8 mos (95% CI 4.6 - 26.2). A PSM population of CMML-BT patients treated with HMA alone showed a significantly increased ORR with HMA+VEN (82% vs 40%, p = 0.039). However, there was no difference in OS (7.49 mos vs 9.26 mos, p = 0.83, Figure 2). Among HMA-VEN treated patients, achievement of a CR was associated with an improved OS in the CMML (HR 0.31, 95% CI 0.13 - 0.75) and CMML-BT (HR 0.37, 95% CI 0.19 - 0.74). No predictors of response were identified, including the presence of a RAS mutation. In terms of safety, 7 patients (7.9%) had a grade 3/4 (G3/4) neutropenic infection and 2 patients (2.2%) had a G3/4 hemorrhagic event while being treated with HMA+VEN. A total of 29 patients went on to receive allogeneic transplant (alloSCT): 22 (43%) with CMML and 7 (18%) with CMML-BT. CMML patients who underwent alloSCT after HMA+VEN were younger as compared to non-transplanted patients (64 vs 74 years, p < 0.0001), but had otherwise similar baseline characteristics including stage, CPSS-mol category and prevalence of RAS mutations. Similarly, CMML-BT patients bridged to alloSCT were younger (66 vs 74 years, p < 0.002) and had a better ECOG performance status (p = 0.047). Of patients who received alloSCT, 10 patients (34%) died, 5 with CMML and 5 with CMML-BT. The median OS after alloSCT was 26.7 mo. Conclusions Although the use of VEN with HMA in the upfront treatment of CMML and AML secondary to CMML results in higher response rates compared to HMA alone, this combination does not improve survival based on this multi-center PSM analysis. The current sample size of CMML-BT may limit detection of OS differences between treatment groups. The role of VEN to reduce blasts and serve as a bridge to alloSCT, particularly after HMA failure, requires further investigation in larger studies in both the CMML and CMML-BT populations.

Background. The inclusion of gene mutations and chromosomal abnormalities in the 2022 WHO and ICC Classifications of MDS has enhanced diagnostic precision and is expected to improve clinical decision-making process. Although these two systems share similarities, clinically relevant discrepancies still exist and potentially cause inconsistency in their adoption in a clinical setting. In this study on behalf of the International Consortium for MDS (icMDS), we adopted a data-driven approach to provide a harmonization roadmap between the 2022 WHO and ICC classification for MDS. A modified Delphi Process consensus approach is currently ongoing among icMDS experts to finalize a harmonized MDS classification scheme. Methods. We analyzed retrospective international cohorts of patients with a diagnosis of MDS (n=7017) and AML (n=1002) according to WHO 2016 criteria. Hierarchical Dirichlet Processes were applied to define clusters capturing broad dependencies among all gene mutations and cytogenetic abnormalities. To investigate the features of importance and their impact on the clustering process, we employed the SHapley Additive exPlanations approach (SHAP). This allowed to define harmonized labels for each clinical entity. The clinical relevance of the unsupervised clustering was assessed through the analysis of phenotypic features and outcomes among each group. ( Blood 2022;140: 9828-9830) Results. Patients' characteristics are summarized in Table 1. We identified 9 clusters, defined by specific genomic features. The cluster of highest hierarchical importance was characterized by biallelic inactivation of TP53 (biTP53). According to SHAP analysis, bi TP53 was defined as 2 or more TP53 mutations, or 1 mutation with copy number loss or cnLOH. Most patients assigned to bi TP53 cluster had TP53 VAF>10% (77.9%) and complex karyotype (70.1%). Assignment to bi TP53 cluster was irrespective of blast count. Patients with monoallelic TP53 mutation segregated into other clusters. Hierarchically, the second cluster included patients with del(5q). SHAP analysis highlighted 5q deletion alone, or with one other chromosomal abnormality other than -7, and absence of bi TP53, as the most relevant features. Most of these patients had blast counts <5% (88.1%). The third distinct cluster included patients with SF3B1 mutations (in the absence of concurrent del(7q), abn3q26.2, complex karyotype or RUNX1 mutation). Most patients with MDS and SF3B1 mutation had <5% blasts (94.2%). Common co-mutated variants in the SF3B1 cluster included mutant DNMT3A (25.2%) and TET2 (38.3%). Morphologically defined MDS cases (i.e., not meeting criteria for bi TP53, del(5q) or SF3B1) were preferentially assigned to the following additional clusters: SF3B1 and concurrent higher-risk mutations (e.g., RUNX1 and ASXL1); SRSF2 and concomitant TET2 mutations; U2AF1 mutations with del(20q), del(7q) or -7; SRSF2 with TET2 mutations and co-mutational patterns including RUNX1 and ASXL1; and AML-like genomic signatures. Our analyses suggest that morphologically defined MDS is characterized by a large heterogeneity in terms of mutation profiles, not entirely captured by the presence of unilineage versus multilineage dysplasia, percentage of bone marrow blasts, and presence of hypocellularity and fibrosis. To better investigate the continuum between high risk MDS (i.e., patients with ≥10% blasts) and AML, an exploratory comparison was made using a cohort of AML (defined according to WHO 2016) patients analyzed using the same statistical methods. Only a partial overlap in genetic signatures was observed between MDS with ≥10% blasts and AML. However, similarities were observed between the AML-like MDS clusters (characterized by mutant NPM1, bZIP CEBPA, and Core Binding Factor abnormalities) and AML clusters defined by the same genetic signature, thus supporting the classification of these entities as AML, irrespective of blast count. Conclusion. Our study demonstrated the utility of a data-driven approach based on advanced statistical methods to generate a harmonized classification for MDS. Table 2 shows a provisional, hierarchical classification algorithm. Further refinement of entity labels and classification criteria is the subject of the ongoing modified Delphi Process consensus approach among icMDS experts.

Introduction: Management of newly diagnosed multiple myeloma (NDMM), which accounts for 1% of all cancers, is an area in dire need of therapeutic innovation. In recent years, the introduction of novel agents is one of the major advances in the management of patients with NDMM, in both transplant- eligible and transplant- ineligible candidates. Studies have combined daratumumab, a human IgGκ monoclonal antibody that targets CD38 which is highly expressed on myeloma cells, with proteasome inhibitors and immunomodulatory agents-based regimens in the first-line treatment of NDMM. The purpose of our study is to explore and consolidate the efficacy of upfront daratumumab combination regimen in patients with NDMM. Methods: We systematically conducted a comprehensive literature search using MEDLINE, EMBASE databases and meeting abstracts from inception through June 2019. Phase III RCTs utilizing daratumumab in patients with newly diagnosed/ untreated multiple myeloma were incorporated in the analysis. A generic inverse variance method was used to calculate the estimated pooled hazard ratio (HR) for progression-free survival (PFS) with 95% confidence interval (CI). Mantel-Haenszel (MH) method was used to calculate the estimated pooled risk ratio (RR) for overall response rate (ORR), including stringent complete response (sCR), CR and very good partial response (VGPR). Heterogeneity was assessed with Cochran's Q -statistic. Random effects model was applied. Results: Three phase III RCTs with a total of 2,528 patients with NDMMwere included.Studies compared daratumumab (D) + bortezomib (V) + melphan (M) + prednisone (P) vs VMP, D + lenalidomide (R) + dexamethasone (d) vs Rd, and DVd + thalidomide (T) vs VTd. The randomization ratio was 1:1 in all studies. The I2statistic for heterogeneity was 0, suggesting homogeneity among RCT. The pooled HR for PFS was statistically significant at 0.52 (95% CI: 0.44-0.61; P < 0.0001). The PFS benefit was observed in all ISS categories, types of immunoglobulin (Ig) and standard risk cytogenetic; ISS I cohort (HR, 0.55; 95% CI: 0.37- 0.82; P = 0.003), ISS II cohort (HR, 0.43; 95% CI: 0.33- 0.55; P < 0.0001), ISS III cohort (HR, 0.63; 95% CI: 0.48- 0.82; P = 0.0006), IgG cohort (HR, 0.56; 95% CI: 0.40- 0.77; P = 0.0003), non-IgG cohort (HR, 0.52; 95% CI: 0.28- 0.97; P = 0.04), and standard risk cytogenetic cohort (HR, 0.43; 95% CI: 0.35- 0.53; P < 0.0001). The pooled HR for PFS in high risk cytogenetic cohort was not statistically significant at 0.76 (95% CI: 0.53- 1.10; P = 0.15). The pooled RR for ORR was 1.13 (95% CI: 1.01-1.26; P = 0.03), sCR was 2.02 (95% CI: 1.33-3.08; P = 0.001), CR was 1.46 (95% CI: 1.20-1.79; P = 0.0002),and VGPR was 1.01 (95% CI: 0.82-1.25; P = 0.93). The pooled RR for negative minimal residual disease (MRD) was 2.54 (95% CI: 1.24-5.20; P = 0.01). Conclusions: Upfront combination regimen with daratumumab significantly improved PFS, ORR, sCR and CR along with negative MRD, compared to control arm in patients with NDMM. The improvement in PFS was noted across all subgroups except in high-risk cytogenetic group. More randomized studies are required to explore further novel agents and to formulate optimal combination regimen to improve survival in this high-risk cytogenetic subset. Disclosures No relevant conflicts of interest to declare.

Introduction: Neutropenic diets are commonly prescribed to cancer patients with neutropenia with the intention of reducing rates of infection. These diets are restrictive and are associated with lower patient satisfaction and possibly malnutrition. Further, it is unclear if these restrictive diets are effective in reducing infection. We performed a meta-analysis on the rates of infection reported in trials comparing the neutropenic diet to unrestricted diets in cancer patients with neutropenia. Methods and Materials: A comprehensive database search for all published randomized controlled trials comparing infection rates in cancer patients receiving a neutropenic diet versus an unrestricted diet was performed for all publications in English language from database’s inception until September 12, 2017. The search strategy, study selection, and subsequent analysis adhered to PRISMA guidelines. Random effects modeling was used to obtain pooled relative risks. The primary outcome measure was the rate of infection. Results: Five randomized controlled trials with a total of 388 patients were included in the final analysis. Patients mostly had acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), or sarcoma. Infection was noted in 53.7% patients in the neutropenic diet group, as compared with 50% in the unrestricted diet group. No significant difference in infection rate was observed between the neutropenic diet versus unrestricted diet groups, pooled risk ratio (RR) 1.13 (95% CI, 0.98-1.30; P=0.10). Conclusions: This meta-analysis of randomized controlled trials suggests that the use of neutropenic diet was not associated with decreased risk of infection in neutropenic cancer patients. The continued use of neutropenic diets should be questioned.