Introduction Several studies have suggested that an increased peripheral blood absolute lymphocyte count (ALC) at day 15 after ASCT is associated with improved survival and decreased relapse rate. Recently, the ratio of ALC to the absolute monocyte count (AMC) (Lymphocyte:Monocyte Ratio; LMR) has been described as a strong prognostic factor at time of diagnosis in patients with various lymphoid malignancies. In most reports, a LMR cut-off value of less than 1.1 indicates patients who have a worse outcome. Objective To evaluate the prognostic impact of the LMR at start of conditioning regimen and at day 15 post ASCT in patients with a diagnosis of lymphoma and myeloma Methods We retrospectively reviewed the medical records of 121 adult patients with a diagnosis of lymphoma or myeloma who underwent ASCT at Hospital Israelita Albert Einstein from January, 2005 to July, 2012. Lymphocyte count was registered at the 15th day after SCT and lymphopenia was defined as an ALC< 500 at this time point. The LMR was calculated considering the ALC and AMC at baseline (start of conditioning regimen) and at day 15 post-ASCT. Overall survival (OS) was estimated from the time of transplant until death, with surviving patients censored at last follow-up. Variables entered into the multivariate Cox analysis were those with a p-value <0.10 in the univariate analysis. Statistical analysis was performed with STATA (v11.0) and alfa error was defined as 5%. Results The majority of patients were male (69%) and the median age was 58 years old (range: 3–76). Peripheral stem cell harvest was the main source of cells (61%). Diagnosis included multiple myeloma (49%), non-Hodgkin’s lymphoma (45%) and Hodgkin’s lymphoma (6%). The median LMR at start of conditioning regimen was 0.60, while at day 15 it was 1.75. Seventy-three percent of patients at start of conditioning had a LMR <1.1, while the same percentage at day 15 was 25%. Considering LMR cut-off at 1.1, an increased LMR value at baseline was associated with improved survival (HR 0.44; p=0.03), while it was not predictive at day 15 (HR=0.99; p=0.99). At 2 years, the OS was 48% for patients with a LMR<1.1 at start of conditioning regimen versus 76% for those patients with a LMR ≥1.1 (p=0.03 by logrank). In a multivariate Cox analysis considering age, sex, diagnosis, day 15 lymphopenia and baseline LMR, baseline LMR remained an independent variable associated with survival (HR=0.40, p=0.044), while day15 lymphopenia had no prognostic value (HR=0.80. p=0.56). Conclusion In our cohort of patients, the presence of an increased LMR at baseline before start of conditioning regimen identified a subgroup of patients who had a very good outcome. These results should be validated in other cohorts. Strategies to improve outcome for patients who present with decreased LMR and a better understanding of the role of LMR should be the focus of future studies. Disclosures: No relevant conflicts of interest to declare.
Introduction: Hematopoietic stem cell transplantation (HSCT) is an effective treatment option for patients with hematological and neoplastic diseases. Despite recent improvements, HSCT is still associated with a significant risk of mortality. Determining risk factors for death within the first 100 days after HSCT could help to identify patients who would benefit from interventions in order to decrease that risk. We have previously reported that increased fluid accumulation during conditioning chemotherapy and in the early period after HSCT was associated with decreased survival (Costa EMM et al, ASH 2013Abstract #4512). Herein, we expand that series of patients and we further analyze the impact of weight gain on early (100-days) mortality in patients who underwent HSCT at our institution. Objective: To determine the impact of weight gain during the first 10 days post-HSCT on 100 days mortality. Methods:We retrospectively reviewed the medical charts of 331 patients who underwent HSCT at our institution from January, 2007 until December, 2013. Information on patients' body weight (BW) was measured daily, starting at admission. The highest BW recorded until until the first 10 days post-SCT (D+10) was used to calculate the BW increase in relation to the baseline BW. Based on our previous study, we used a cutoff of 6% gain in BW to identify a group of patients with increased risk of complications. The primary endpoint was mortality within 100 days post HSCT. Overall survival (OS) was estimated from the time of HSCT until death, and surviving patients were censored at last follow-up. A logistic regression model and a Cox model were fit to determine variables that predicted death within 100 days and OS, respectively. Statistical analysis was performed with STATA (v11.0) and alfa error was defined as 5%. Results: Median age was 43 years old (range <1 year-76 years) and 60% were male. HSC sources included autologous (46%), matched related donors (16%), matched unrelated donors (12%), cord blood units (16%) and mismatched related/unrelated donors (10%). Diagnosis included acute leukemia or chronic myeloid disorders (34%), lymphoma/multiple myeloma (42%) and non-malignant hematological disorders (24%). Twenty-one percent of patients had a ≥6% gain in BW until the first 10 days post-HSCT. These patients had developed an increased inflammatory state after the start of the conditioning regimen: there was no difference in baseline levels of C-reactive protein (4.8 mg/L vs. 7.4, p=0.37), but by D+10 patients who gained more BW had higher CRP (116.7 mg/L vs. 178.6 mg/L; p=0.01). Patients with increased gain in BW until D+10 had a decreased OS (HR 2.33, p<0.0001, 95% CI 1.45-3.73). The mortality within 100 days was 47% in the increased BW vs. 17% in the control group (p<0.0001). Among 18 patients who died within 100 days and had a ≥6% BW gain by D+10, causes of death included pneumonia (N=4), septic shock (N=9), fungal endocarditis (N=1), ischemic stroke (N=1) and disease progression (N=3). In a logistic regression analysis, after adjusting for age, sex, diagnosis and type of SCT, a ≥6% BW gain by D10 was associated with an increased risk of being dead within 100 days (coefficient 1.75; p<0.0001; 95% CI 0.90-2.61). Similarly, in a multivariate Cox analysis after adjusting for age, sex, diagnosis and type of SCT, a ≥6% BW gain by D10 was an independent risk factor for survival (HR 2.72, p<0.0001, 95% CI 1.65-4.48). A landmark analysis at D+100 revealed that the negative impact of weight gain by D+10 on survival was restricted to the first 100 days, as after this time point there was no survival difference between the two groups (HR 1.35; p=0.41; 95% CI 0.65-2.83). Conclusion: A ≥6% BW gain by D+10 is a risk factor for early mortality in both autologous and allogeneic HSCT. The most common cause of death in these patients is infectious-related complications. An increase in BW is related to the development of an inflammatory state, probably induced by the conditioning regimen. BW gain is a simple variable that can be easily used to determine prognosis of patients post-allogeneic HSCT, and further studies are needed to determine its etiology. Disclosures No relevant conflicts of interest to declare.
Introduction: The development of next-generation sequencing has made it feasible to interrogate the entire genome or exome (coding genome) in a single experiment. Accordingly, our knowledge of the somatic mutations that cause cancer has increased exponentially in the last years. MPNs and MDS/MPD are chronic myeloid neoplasms characterized by an increased proliferation of one or more hematopoietic cell lineages, and an increased risk of transformation to acute myeloid leukemia (AML). MPNs and MDS/MPDs are heterogenous disorders, both in clinical presentation and in prognosis. We sought to determine the genetic landscape of Ph-negative MPNs and MDS/MPD through next-generation sequencing. Methods: Paired DNA (sorted CD66b-granulocytes/skin biopsy) from 102 patients with MPNs or MDS/MPD was subjected to whole exome sequencing on a Illumina HiSeq 2000 platform using Agilent SureSelect kit. Diagnosis included primary myelofibrosis (MF; N=42), essential thrombocythemia (ET; N=28), polycythemia vera (PV; N=12), chronic myelomonocytic leukemia (CMML; N=10), systemic mastocytosis (MS; N=6), MDS/MPD-Unclassified (N=2) and post-MPN AML (N=2). Tumor coverage was 150x and germline coverage was 60x. Somatic variants calls were generated by combining the output of Somatic Sniper (Washington University), Mutect (Broad Institute) and Pindel (Washington University). The combined output of these 3 tools was further filtered by in-house criteria in order to reduce false-positive calls (minimum coverage at both tumor/germline ≥8 reads; fraction of reads supporting alternate allele ≥10% in tumor and ≤10% in germline; ratio of allele fraction tumor:germline >2; excluding mutations seen in SNP databases). All JAK2 and CALR mutations were validated through Sanger sequencing. Validation of other somatic mutations is currently underway. Analysis of driver mutations was made with the Intogen web-based software, using the Oncodrive-FM and Oncodrive-cluster algorithms (www.intogen.org). Significantly mutated genes were considered as those with a q-value of <0.10. Results: We identified a total of 309 somatic mutations in all patients, with each patient having an average of 3 somatic abnormalities, fewer than most solid tumors that have been sequenced so far. Mutations occurred in 166 genes, and 40 of these were recurrently somatically mutated in Ph-negative MPNs. By the Oncodrive-FM algorithm, the following genes were identified as the most significantly mutated driver genes in Ph-negative MPNs and MDS/MPDs (in order of significance): CALR, ASXL1, JAK2, CBL, DNMT3A, U2AF1, TET2, TP53, RUNX1, EZH2, SH2B3 and KIT. By the Oncodrive-cluster algorithm, which considers clustering of mutations at a hotspot, the following genes were significantly mutated: KIT, JAK2, SRSF2 and U2AF1. Somatic mutations were seen in genes that are mutated at a low frequency in Ph-negative MPNs, including ATRX, BCL11A, BCORL1, BIRC5, BRCC3, CSF2RB, CUX1, IRF1, KDM2B, ROS1 and SUZ12. Consistent with the clinical phenotype, 96 patients (94%) had mutations that lead to increased cellular proliferation, either through activation of the JAK-STAT pathway (e.g. JAK2, CALR) or mutations that activated directly or indirectly signaling by receptor tyrosine kinases (e.g. FLT3, KIT, CBL). Besides biological pathways regulating cell proliferation, the most commonly implicated pathways included regulation of DNA methylation (e.g. DNMT3A, TET2), mRNA splicing (e.g. U2AF1, SRSF2) and histone modifications (e.g. ASXL1, EZH2), seen in 27%, 25% and 22% of patients, respectively. Abnormalities in these 3 pathways were more often seen in MF, MDS/MPD and CMML, as compared to PV and ET (65% vs. 20%; p<0.0001). Conclusions: Our study represents one of the largest series of patients with these neoplasms evaluated by whole exome sequencing, and together with the published data helps to delineate the genomic landscape of Ph-negative MPNs and MDS/MPDs. The majority of the most frequent mutations seen in Ph-negative MPNs have already been reported. Nevertheless, there are several low frequency mutations that need to be further studied and functionally validated in vitro and in vivo for a deeper knowledge of the pathophysiology of MPNs. Besides activation of cellular proliferation, abnormalities of DNA methylation, histone modification and mRNA splicing emerge as the most important biological pathways in these disorders. Disclosures No relevant conflicts of interest to declare.
Introduction It has been previously reported that increased fluid accumulation during peripheral blood hematopoietic stem cell (HSC) mobilization is associated with poor outcome in patients with amyloidosis who undergo autologous HSCT. It is unknown whether increased fluid accumulation during the early phases of HSCT is associated with poor survival in patients undergoing HSCT for other diseases. Objective To determine the impact of fluid accumulation during conditioning and in the first 10 days post HSC infusion on survival and risk of complications of patients who underwent both autologous and allogeneic HSCT. Methods We retrospectively reviewed the medical charts of 257 consecutive patients who underwent HSCT at our institution from January, 2007 until December, 2012. Information on patients' body weight (BW) was measured daily, starting at admission. The highest BW recorded until HSC infusion (D0) and until the first 10 days post-SCT (D+10) was used to calculate the BW increase in relation to the baseline BW. A ROC curve was built to determine the best cut-off point in BW increase that predicted for mortality. Information on the incidence of post-transplant complications was extracted from the time period that patients were admitted for transplant until discharge from the hospital. Endpoints analyzed included the presence or absence of respiratory failure, acute renal failure, sinusoidal obstruction syndrome (SOS), septic shock and requirement of diuretic use, hemodialysis, mechanical ventilation and ICU admission. Overall survival (OS) was estimated from the time of HSCT until death, and surviving patients were censored at last follow-up. Variables entered into the multivariate Cox analysis were those with a p-value<0.10 in the univariate analysis. Statistical analysis was performed with STATA (v11.0) and alfa error was defined as 5%. Results Mean age was 39.4 years old (range <1 year-76 years) and 61% were male. HSC sources included autologous (47%), matched related donors (15%), matched unrelated donors (13%), cord blood units (19%) and mismatched related/unrelated donors (6%). Diagnosis included acute leukemia or chronic myeloid disorders (37%), lymphoma/multiple myeloma (42%) and non-malignant hematological disorders (21%).The results of the ROC curve defined the cut-point of 6% BW gain by D+10 as the best predictor for OS. A total of 69 patients (27%) had a BW increase ≥6% by D+10. This was associated with an increased risk of mortality, with a 100-days OS of 67% vs. 92% (HR 3.25, p<0.0001, 95% CI 2.04-5.18; Figure). A greater than 6% gain in BW by D+10 was also associated with an increased risk of developing SOS (31% vs. 6%; p<0.0001), septic shock (29% vs. 7%; p<0.0001), respiratory failure (35% vs. 9%; p<0.0001) and requiring diuretic use (91% vs. 71%; p<0.001), hemodialysis (13% vs. 4%, p=0.007), mechanical ventilation (33% vs. 9%; p<0.0001) and ICU admission (42% vs. 24%; p<0.0001). In a multivariate analysis considering age, diagnosis, type of SCT and sex, a ≥6% BW gain by D+10 was an independent variable associated with an increased risk of mortality (HR 3.28; p<0.0001; 95% CI 2.02-5.32). We next evaluated the prognostic impact of a ≥6% BW increase in the time period from admission until D0. Our results showed that it was similarly associated with an increased risk of mortality (HR 2.26; p=0.003; 95% CI 1.32-3.86), of developing SOS (32% vs. 9%; p<0.0001), respiratory failure (27%vs. 14%; p=0.04) and requiring hemodialysis (15% vs. 5%; p=0.01) and ICU admission (37% vs. 18%; p=0.008). After adjusting for age, sex, diagnosis and type of SCT, ≥6% BW gain by D0 was associated with an increased mortality (HR 1.94; p=0.026; 95% CI 1.08-3.48). Conclusion In our cohort of patients, fluid accumulation during the early stages of conditioning regimen and HSCT, reflected by a ≥6% increase in BW, was associated with an increased mortality and risk of developing severe complications. This may reflect the presence of increased endothelial damage, and further studies are needed to better clarify the mechanism behind weight gain during HSCT. Our results demonstrate that patients who have a ≥ 6% gain in BW by D0 and D+10 have an increased risk of complications, and more intensive monitoring of these patients is needed. Disclosures: No relevant conflicts of interest to declare.
Cell dose is a major criterion for cord blood unit (CBU) selection for allogeneic stem cell transplantation (allo-SCT). The aim of this study was the characterization of CBU cellular composition after thaw, and comparison with corresponding values at cryopreservation as reported by cord blood (CB) banks. The study included 87 CBUs, that were thawed for infusion in the context of single (n¼3) or dual-unit (n¼42) allo-SCT in adults with hematologic malignancies, from 8/2006 to 6/2013. Upon thawing, the cryoprotective solution (DMSO 10%) was either removed by centrifugation/washing (38 CBUs) or diluted in a less hypertonic solution of Dextran 40/Human Albumin 2.5% (49 CBUs). Total nucleated cells (TNC) were measured with a hematology analyzer, while enumeration of CD34+ stem cells was performed by singleplatform flow cytometry, according to ISHAGE guidelines. In 49 units, TNC and CD34+ cell viability was evaluated by addition of 7-AAD dye and sequential Boolean gating strategy. TNC counts after thawing were lower compared to their values at freezing (Wilcoxon test, p <10-4), and the difference was more pronounced in the units that were washed prior to infusion (Tables 1 and 2). Total cell viability was low (mean value, 42.6%), but this was mainly due to neutrophils. Regarding CD34+ cells, there was a significant difference between absolute counts at cryopreservation and at thaw (p<10-4). Despite reduction postthaw, the counts of both TNC and CD34+ cells did correlate with the corresponding values at cryopreservation by Spearman's analysis. Of note, washing seemed slightly advantageous in terms of CD34+ recovery (Tables 1 and 2). CD34+ cells retained high viability after thaw, with 90% of CBUs (44 out of 49 tested) demonstrating CD34+ viability !80%. Viability of <50% was noticed in only one CBU that failed to engraft. In conclusion, CB cellular content and especially the CD34+ cell count is frequently shown to be inferior at thaw compared to cryopreservation. This probably reflects both the lack of standardization of CD34+ cell measurement and the effect of thawing procedure. Therefore, CD34+ cell viability may be a more meaningful marker for determining CBU quality.
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