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Immunoglobulin heavy chain variable ( IGHV ) region mutations, TP53 mutation, fluorescence in situ hybridization (FISH), and cytogenetic analysis are the most important prognostic biomarkers used in chronic lymphocytic leukemia (CLL) patients in our daily practice. In real-life environment, there are scarce studies that analyze the correlation of these factors with outcome, mainly referred to time to first treatment (TTFT) and overall survival (OS). This study aimed to typify IGHV mutation status, family usage, FISH aberrations, and complex karyotype (CK) and to analyze the prognostic impact in TTFT and OS in retrospective study of 375 CLL patients from a Spanish cohort. We found unmutated CLL (U-CLL) was associated with more aggressive disease, shorter TTFT (48 vs. 133 months, p  < 0.0001), and shorter OS (112 vs. 246 months, p  < 0.0001) than the mutated CLL. IGHV3 was the most frequently used IGHV family (46%), followed by IGHV1 (30%) and IGHV4 (16%). IGHV5-51 and IGHV1-69 subfamilies were associated with poor prognosis, while IGHV4 and IGHV2 showed the best outcomes. The prevalence of CK was 15% and was significantly associated with U-CLL. In the multivariable analysis, IGHV2 gene usage and del13q were associated with longer TTFT, while VH1-02, +12, del11q, del17p, and U-CLL with shorter TTFT. Moreover, VH1-69 usage, del11q, del17p, and U-CLL were significantly associated with shorter OS. A comprehensive analysis of genetic prognostic factors provides a more precise information on the outcome of CLL patients. In addition to FISH cytogenetic aberrations, IGHV and TP53 mutations, IGHV gene families, and CK information could help clinicians in the decision-making process., Competing Interests: Conflict of Interest None declared., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. ( https://creativecommons.org/licenses/by/4.0/ ).)

Background: Patients with chronic lymphocytic leukemia (CLL) have a higher risk of developing other malignancies (OMs) compared to the general population. However, the impact of CLL-related risk factors and CLL-directed treatment is still unclear and represents the focus of this work., Methods: We conducted a retrospective international multicenter study to assess the incidence of OMs and detect potential risk factors in 19,705 patients with CLL, small lymphocytic lymphoma, or high-count CLL-like monoclonal B-cell lymphocytosis, diagnosed between 2000 and 2016. Data collection took place between October 2020 and March 2022., Findings: In 129,254 years of follow-up after CLL diagnosis, 3513 OMs were diagnosed (27.2 OMs/1000 person-years). The most common hematological OMs were Richter transformation, myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). Non-melanoma skin (NMSC) and prostate cancers were the most common solid tumors (STs).The only predictor for MDS and AML development was treatment with fludarabine and cyclophosphamide with/without rituximab (FC ± R) (OR = 3.7; 95% CI = 2.79-4.91; p < 0.001). STs were more frequent in males and patients with unmutated immunoglobulin heavy variable genes (OR = 1.77; 95% CI = 1.49-2.11; p < 0.001/OR = 1.89; 95% CI = 1.6-2.24; p < 0.001).CLL-directed treatment was associated with non-melanoma skin and prostate cancers (OR = 1.8; 95% CI = 1.36-2.41; p < 0.001/OR = 2.11; 95% CI = 1.12-3.97; p = 0.021). In contrast, breast cancers were more frequent in untreated patients (OR = 0.17; 95% CI = 0.08-0.33; p < 0.001).Patients with CLL and an OM had inferior overall survival (OS) than those without. AML and MDS conferred the worst OS (p < 0.001)., Interpretation: OMs in CLL impact on OS. Treatment for CLL increased the risk for AML/MDS, prostate cancer, and NMSC. FCR was associated with increased risk for AML/MDS., Funding: AbbVie, and EU/EFPIAInnovative Medicines Initiative Joint Undertaking HARMONY grant n° 116026., Competing Interests: TC received honoraria from AbbVie. LS received consulting fees from AbbVie, BeiGene, AstraZeneca, Lilly, and Janssen, honoraria from Janssen and Octapharma, support for attending meetings from BeiGene and Janssen and advisory board fees from Merck. SMu received advisory board fees from AbbVie, AstraZeneca, Janssen, Roche and BeiGene. JAHR received honoraria as a consultant from Janssen, AbbVie, AstraZeneca, Lilly, and BeiGene and support for attending meetings from Janssen, AbbVie, AstraZeneca, and BeiGene. LI received honoraria from AbbVie, Roche, and Janssen-Cilag. APK received advisory board fees and research money from Janssen, AbbVie, BMS, AstraZeneca, Roche/Genentech, support for attending meetings from Janssen and AbbVie. M-DL received travel expenses from Janssen and AbbVie. GMR received honoraria for participation to speaker's bureau from AbbVie, Astra Zeneca, Beigene, and Janssen, and support for attending meetings from Janssen. JVT received consulting fees from AbbVie, AstraZeneca, BeiGene, and Janssen, honoraria for scientific talks from AbbVie, AstraZeneca, BeiGene, Janssen, Lilly, and Roche, travel support from AbbVie, AstraZeneca, BeiGene, Janssen, Roche, and Lilly, and advisory boards fees for AbbVie, Amgen, AstraZeneca, BeiGene. GI received honoraria from Novartis, BMS, Sandoz, AstraZeneca, Janssen, Kite/Gilead, and Miltenyi, support for attending meetings from Kite/Gilead, AstraZeneca, and AbbVie and advisory board fees from Kite/Gilead, Novartis, BMS, and Autolus. FBi received support for attending meetings from AbbVie. RCo received support for attending meetings from Janssen-Cilag and S.A. SG received honoraria support for attending meetings from AbbVie, AstraZeneca, Jazz, Novartis, and Incyte, honoraria from Roche, Celgene, Pfizer, and Janssen, and support for attending meetings from Jazz, AstraZeneca, and Roche. RGS received support for attending meetings from AbbVie and S.L.U. RG received honoraria, consulting fees, and support for attending meetings from AbbVie, Beigene, Roche, Janssen, AstraZeneca. YH received honoraria from Janssen, AbbVie, Roche, AstraZeneca, Medion, and Lilly. OJ received honoraria from Johnson and Johnson, AstraZeneca, and Lilly, honoraria from Johnson and Johnson, AbbVie, AstraZeneca, and Lilly, and support for attending meetings from Johnson and Johnson, and AbbVie. LK received consulting fees from AbbVie, AstraZeneca, Janssen, Beigene, Takeda, and Novartis. MKM received honoraria from Novartis, Pfizer, and Gad Medical LTD and support for attending meetings from Novartis. IKo received honoraria and consulting fees from AbbVie and Janssen. IM received honoraria from AbbVie, Roche, Sandoz, AstraZeneca, and Janssen, and support for attending meetings from AbbVie, Roche, and Takeda. ANB received honoraria, advisory board fees and support for attending meetings from AbbVie, AstraZeneca, Takeda, Janssen, and Beigene. JO received honoraria from AbbVie, AstraZeneca, and Janssen. GR received consulting fees from AbbVie, AstraZeneca, Janssen, and Beigene, and is currently employed by AstraZeneca. TP received honoraria and advisory board fees from AbbVie, Janssen-Cilag, and AstraZeneca and support for attending meeting from AstraZeneca. MS received honoraria and support for attending meeting from AstraZeneca, AbbVie, and Janssen-Cilag and owns shares of stock in AbbVie, AstraZeneca, Merck, Eli Lilly, Sanofi, Johnson and Johnson, Pfizer, Gilead, and GSK. MSp received honoraria and consulting and advisory board fees, and support for attending meeting from AbbVie, AstraZeneca, and Janssen. ET received support for attending meetings from Takeda. TV received honoraria from Takeda, Roche, Genesis Pharma, Merck, Novartis, Gilead, Sandoz, AstraZeneca, Integris, and Servier and support for attending meetings from Takeda, Roche, Genesis Pharma, Merck, Pfizer, and Winmedica. CV received honoraria from AbbVie, consulting fees from AstraZeneca and support for attending meeting from AstraZeneca, Takeda, and Janssen. RW received honoraria from AbbVie, AstraZeneca, and Beigene, support for attending meetings from Janssen, AbbVie, and AstraZeneca and advisory board fees from AbbVie, AstraZeneca, Janssen, Beigene, and SecuraBio. EWS received honoraria from AbbVie, Roche, and Janssen-Cilag and support for attending meetings from AbbVie. LY received honoraria from AbbVie, AstraZeneca, Novartis, Gilead, Janssen, Jazz, MSD, and Pfizer, support for attending meetings from AbbVie, AstraZeneca, Gilead, Janssen, and Pfizer, and advisory board fees from AbbVie, AstraZeneca, Jazz, Janssen, Beigene, and Celgene. MAn received consulting fees from AbbVie, Takeda, Janssen, Roche, Genesis, Gilead, and Amgen and honoraria from AbbVie, Takeda, Roche, Genesis, Gilead, and Novartis. MC received honoraria, advisory board fees, and support for attending meetings from AbbVie, AstraZeneca, and Janssen. ACu received honoraria, advisory board fees, and support for attending meetings from AbbVie, AstraZeneca, Beigene, Janssen, and Lilly. FD support for attending meetings from Janssen and AbbVie. GG received honoraria, and advisory board fees from AbbVie, AstraZeneca, Beigene, Janssen and advisory board fees from Lilly. EN received honoraria from AbbVie. LSm received consulting fees, honoraria and support for attending meetings from AbbVie, AstraZeneca, and Janssen and advisory board fees from AbbVie and AstraZeneca. NS received honoraria from Janssen, AbbVie, AstraZeneca, and Lilly, and support for attending meetings from Janssen and AstraZeneca. CT received honoraria from AbbVie, Beigene, Janssen, and LOXO. FB received consulting fees, honoraria and payment for expert testimony from AbbVie, Genentech, Novartis, Takeda, Janssen, Roche, Mundipharma, Celgene/BMS, AstraZeneca, Lilly, Beigene, Gilead and TG Therapeutics, Advantage Allogene, Lava Therapeutics, and Enterome. MDo received honoraria and advisory board fees from AbbVie, AstraZeneca and Janssen, advisory board fees from Swixx, and support for attending meetings from Janssen. PG received honoraria and consulting fees from AbbVie, AstraZeneca, BMS, Janssen, Lilly/Loxo Oncology, MSD, and Roche; grant support from AbbVie, AstraZeneca, BMS, Janssen. KS received honoraria from Janssen, AbbVie, Lilly and AstraZeneca, consulting fees and support for attending meetings from Janssen and AstraZeneca. GK, EM, DC, JK, CD, MA, SA, TAS, FBa, MB, ACa, AM, AKM, RC, SC, ACh, ZD, MDi, DD, GDS, BD, ME, SEA, AE, AF, AG, EG, IGGM, AGo, AjG, RGu, SH, EH, SJ, EKa, VK, BK, MK, EK, RJK, JL, DL, IL, TL, ALG, JM, LMR, MMa, SM, CMB, BM, FM, RM, MMo, RMu, UKN, ACO, DO, IPS, MP, ZK, PP, CP, AP, LR, RR, MDDS, AS, YS, MSi, SS, DSAS, TT, KT, AV, GV, VV, ZX, MYa, MY, JZ, DA, BB, MCa, RCl, BE, OBK, LL, GP, PPa, VMP, SP, PS, LT, AC, have no conflict of interest to disclose., (© 2023 Published by Elsevier Ltd.)

Chronic lymphocytic leukemia (CLL) is a disease of the elderly, but chronological age does not accurately discriminate frailty status at the inter-individual level. Frailty describes a person's overall resilience. Since CLL is a stressful situation, it is relevant to assess the patient´s degree of frailty, especially before starting antineoplastic treatment. We are in the era of targeted therapies, which have helped to control the disease more effectively and avoid the toxicity of chemo (immuno) therapy. However, these drugs are not free of side effects and other aspects arise that should not be neglected, such as interactions, previous comorbidities, or adherence to treatment, since most of these medications are taken continuously. The challenge we face is to balance the risk of toxicity and efficacy in a personalized way and without forgetting that the most frequent cause of death in CLL is related to the disease. For this purpose, comprehensive geriatric assessment (GA) provides us with the opportunity to evaluate multiple domains that may affect tolerance to treatment and that could be improved with appropriate interventions. In this review, we will analyze the state of the art of GA in CLL through the five Ws.

Vaccine-associated hypermetabolic lymphadenopathy (VAHL) has been reported as a common post-vaccination side effect, especially with mRNA-based COVID-19 vaccines. Most VAHL cases present normal or enlarged regional lymph nodes close to the injection site, usually with mild-moderate FDG (18 F-Fluorodeoxyglucose) uptake on FDG positron emission tomography (PET)/CT. Here, we describe the case of a 33-year-old woman with past history of Classic Hodgkin Lymphoma (CHL) who underwent follow-up FDG PET/CT 3 days (d) after the first dose of the adenovirus-vectored Oxford-AstraZeneca COVID-19 vaccine. FDG PET/CT showed unexpected small hypermetabolic cervical and abdominal lymph nodes in the same location as at the onset of the disease, suggesting radiological relapse. Considering temporal relationship and other cases of VAHL, a new image was performed 2 months later, which revealed decreased lymph nodes and normalization of FDG uptake. This case illustrates that the possibility of a false-positive should always be considered by physicians in this new context, even when hypermetabolic lymph nodes appear far from the vaccination site.

BIRC3 is monoallelically deleted in up to 80% of chronic lymphocytic leukemia (CLL) cases harboring del(11q). In addition, truncating mutations in the remaining allele of this gene can lead to BIRC3 biallelic inactivation, which has been shown to be a marker for reduced survival in CLL. Nevertheless, the biological mechanisms by which these lesions could contribute to del(11q) CLL pathogenesis and progression are partially unexplored. We implemented the CRISPR/Cas9-editing system to generate isogenic CLL cell lines harboring del(11q) and/or BIRC3 mutations, modeling monoallelic and biallelic BIRC3 loss. Our results reveal that monoallelic BIRC3 deletion in del(11q) cells promotes non-canonical NF-κB signaling activation via RelB-p52 nuclear translocation, being these effects allelic dose-dependent and therefore further enhanced in del(11q) cells with biallelic BIRC3 loss. Moreover, we demonstrate ex vivo in primary cells that del(11q) cases including BIRC3 within their deleted region show evidence of non-canonical NF-κB activation which correlates with high BCL2 levels and enhanced sensitivity to venetoclax. Furthermore, our results show that BIRC3 mutations in del(11q) cells promote clonal advantage in vitro and accelerate leukemic progression in an in vivo xenograft model. Altogether, this work highlights the biological bases underlying disease progression of del(11q) CLL patients harboring BIRC3 deletion and mutation., (© 2021. The Author(s).)

The knowledge of chronic lymphocytic leukemia (CLL) has progressively deepened during the last forty years. Research activities and clinical studies have been remarkably fruitful in novel findings elucidating multiple aspects of the pathogenesis of the disease, improving CLL diagnosis, prognosis and treatment. Whereas the diagnostic criteria for CLL have not substantially changed over time, prognostication has experienced an expansion with the identification of new biological and genetic biomarkers. Thanks to next-generation sequencing (NGS), an unprecedented number of gene mutations were identified with potential prognostic and predictive value in the 2010s, although significant work on their validation is still required before they can be used in a routine clinical setting. In terms of treatment, there has been an impressive explosion of new approaches based on targeted therapies for CLL patients during the last decade. In this current chemotherapy-free era, BCR and BCL2 inhibitors have changed the management of CLL patients and clearly improved their prognosis and quality of life. In this review, we provide an overview of these novel advances, as well as point out questions that should be further addressed to continue improving the outcomes of patients.

Background: The COVID-19 outbreak has affected almost all hospital departments, including transfusion services. However, the demand for transfusions in a general hospital designated to deal with COVID-19 patients has not been analysed before., Study Design and Methods: A retrospective study was conducted to evaluate blood transfusion practices from 15 March to 14 April 2020 at Hospital Universitario Infanta Leonor (Madrid, Spain). During this month, with few exceptions, the hospital became a 'COVID-19' centre. In addition, transfusion rates during this time frame and the same period over the last 4 years were compared., Results: From 15 March to 14 April 2020, only 254 blood components were transfused, resulting in a 49·3% reduction over the previous year. Interestingly, in critically ill patients, the red blood cell (RBC) transfusion/bed ratio significantly decreased during this period (0·92) compared to the same ratio over the past 4 years (2·70) (P = 0·02). Of note, 106 blood components (95 RBC; 11 platelet concentrates) were transfused to only 36 out of 1348 COVID-19 patients (2·7%). The main reason for RBC transfusion in COVID-19 patients was a previous underlying disease (44%) followed by bleeding (25%) and inflammatory anaemia (25%)., Conclusion: This is the first study to report a decrease in blood transfusions during the COVID-19 pandemic in a general hospital and especially in the intensive care unit. The results of this study suggest that COVID-19 does not generally induce transfusion requiring anaemia, being the main causes for transfusion in these patients underlying conditions or bleeding., (© 2020 International Society of Blood Transfusion.)

Chronic lymphocytic leukemia (CLL) is an extremely heterogeneous disease. With the advent of oral targeted agents (Tas) the treatment of CLL has undergone a revolution, which has been accompanied by an improvement in patient's survival and quality of life. This paradigm shift also affects the value of prognostic and predictive biomarkers and prognostic models, most of them inherited from the chemoimmunotherapy era but with a different behavior with Tas. This review discusses: (i) the role of the most relevant prognostic and predictive biomarkers in the setting of Tas; and (ii) the validity of classic and new scoring systems in the context of Tas. In addition, a critical point of view about predictive biomarkers with special emphasis on 11q deletion, novel resistance mutations, TP53 abnormalities, IGHV mutational status, complex karyotype and NOTCH1 mutations is stated. We also go over prognostic models in early stage CLL such as IPS-E. Finally, we provide an overview of the applicability of the CLL-IPI for patients treated with Tas, as well as the emergence of new models, generated with data from patients treated with Tas.

We report 2 cases of composite lymphoma comprising mantle cell lymphoma and peripheral T-cell lymphoma, not otherwise specified, a rare association that has only been reported twice in the literature. In case 1, a 64-year-old woman presented with massive splenomegaly and lymphadenopathy. Immunohistochemical studies of the lymph node biopsy suggested the presence of 2 lymphomas, a predominant component of a peripheral T-cell lymphoma, not otherwise specified and an in situ mantle cell neoplasia. These suspicions were confirmed with polymerase chain reaction and fluorescence in situ hybridization studies. In case 2, a 45-year-old man presented with an enlarged right tonsil. Contrary to case 1, the biopsy suggested a predominant infiltration of a classical mantle cell lymphoma and an atypical proliferation of T cells. Biclonality was also confirmed with fluorescence in situ hybridization and molecular techniques. Both cases were treated with an up-front autologous stem cell transplantation after achieving first complete remission, and they remained free of disease for a long period of time.

Background: The discovery of new biologic variables with high prognostic effect has been accompanied by the emergence of different prognostic indexes (PIs) to assess the time to first treatment in patients with early-stage (Binet A) chronic lymphocytic leukemia (CLL). The present study compared the prognostic value of 5 PIs: CLL international prognostic index (CLL-IPI), Barcelona-Brno, international prognostic score-A (IPS-A), CLL-01, and a tailored approach., Patients and Methods: We applied the 5 PIs to a cohort of 428 unselected patients with Binet A CLL from a multicenter Spanish database with clinical and biologic information available. The predictive value of the scores was assessed using Harrell's concordance index (C index) and area under the receiver operating characteristic curve (AUC)., Results: We found a significant association between time to first treatment and risk subgroups for all 5 PIs used. The most accurate PI was the IPS-A (C-index, 0.72; AUC, 0.76), closely followed by CLL-01 (C-index, 0.69; AUC, 0.70), CLL-IPI (C-index, 0.69; AUC, 0.69), Barcelona-Brno (C-index, 0.67; AUC, 0.69), and the tailored approach (C-index, 0.61 and 0.58; AUC, 0.58 and 0.54)., Conclusions: The concordance between the PIs was low (44%), suggesting that although all these PIs improve clinical staging and help physicians in routine clinical practice, it will be necessary to harmonize larger cohorts of patients to define the best PI for treatment decision-making in the real world., (Copyright © 2020 Elsevier Inc. All rights reserved.)

The presence of chromosomal gains other than trisomy 12 suggesting a hyperdiploid karyotype is extremely rare in chronic lymphocytic leukemia (CLL) and is associated with a dismal prognosis. However, the genetic mechanisms and mutational background of these patients have not been fully explored. To improve our understanding of the genetic underpinnings of this subgroup of CLL, seven CLL patients with several chromosomal gains were sequenced using a next-generation sequencing (NGS)-targeted approach. The mutational status of 54 genes was evaluated using a custom-designed gene panel including recurrent mutated genes observed in CLL and widely associated with CLL pathogenesis. A total of 21 mutations were detected; TP53 (42.8%), ATM (28.5%), SF3B1 (28.5%), and BRAF (28.5%) were the most recurrently mutated genes. Of these mutations, 61.9% were detected in genes previously associated with a poor prognosis in CLL. Interestingly, five of the seven patients exhibited alterations in TP53 or ATM (deletion and/or mutation), genes involved in the DNA damage response (DDR), which could be related to a high genetic instability in this subgroup of patients. In conclusion, CLL patients with several chromosomal gains exhibit high genetic instability, with mutations in CLL driver genes and high-risk genetic alterations involving ATM and/or TP53 genes., (Copyright © 2019. Published by Elsevier Inc.)

In recent years, new prognostic indexes (PIs) for chronic lymphocytic leukemia (CLL), which include clinical, biological, and genetic variables, have been validated, highlighting the MD Anderson Cancer Center prognostic index (MDACC PI), the CLL-international prognostic index (CLL-IPI), and the Barcelona-Brno biomarkers only prognostic model. The aim of this study is to compare the utility of these PIs in a cohort of Spanish patients. A retrospective analysis of 696 unselected CLL patients newly diagnosed and previously untreated from different Spanish institutions was performed. The MDACC PI, the CLL-IPI, and the biomarkers only PI were applied to these patients, and a comparison of the three PIs was performed. With a median follow-up time of 46 months, 394 patients were alive and 187 had received treatment. The median overall survival (OS) was 173 months and the median time to first therapy (TTFT) was 32 months. Significant differences were obtained in OS and TTFT for all subgroups when applying these PIs, with the CLL-IPI being the one with the higher c -index (0.676 for OS and 0.757 for TTFT). The three PIs were able to discriminate patients in different prognostic subgroups. In our cohort, the CLL-IPI showed higher power in predicting TTFT and OS.

We analyzed the features of chronic lymphocytic leukemia (CLL) with multiple abnormalities (MA) detected by FISH. A local database including 2095 CLL cases was used and 323 with MA (15.4%) were selected. MA was defined by the presence of two or more alterations (deletions of 13q14 (13q-), 11q22 (11q-), 17p13 (17p-) or trisomy 12 (+12)). The combination of 13q- with 11q- and 13q- with 17p-, accounted for 58.2% of the series, in contrast to 11q- with 17p- (3.7%). Patients carrying MA since diagnosis presented a short time to first therapy(TTFT) (27 months) and overall survival (OS) (76 months). The combinations including 17p- had a shorter OS (58 months) than the ones without 17p- (not reached, p = .002). Patients with a complex-FISH were the ones with worse OS (34 months). MA imply poor prognosis when they emerge at diagnosis, probably due to the high incidence of bad prognosis markers, which may be a reflection of a more complex karyotype.

The presence of chromosomal gains other than trisomy 12 in chronic lymphocytic leukaemia (CLL) is unusual. However, some patients may show gains on several chromosomes simultaneously suggesting a hyperdiploid karyotype., Objective: The objective of this study was to analyse by FISH the frequency and prognostic impact of hyperdiploidy in CLL., Method: A review of 1359 consecutive cases diagnosed with CLL referred for FISH analysis to a unique institution was carried out. Hyperdiploidy was considered when a gain of at least three of the five FISH probes used was observed., Results: Seven cases (0.51%) with hyperdiploidy were found, confirming that it is a rare event in this disease. Although most patients presented with early Binet stages at diagnosis, six of seven (86%) shortly progressed. The median of time to the first therapy (TTFT) and overall survival (OS) for the patients with hyperdiploidy were short (1.4 months and 20 months, respectively). Moreover, comparing them with a control group of patients (non-hyperdiploid) with completed follow-up data, TTFT and OS of the patients with hyperdiploidy were significantly shorter than the control group., Conclusion: The presence of hyperdiploidy is uncommon and probably associated with poor prognostic markers in CLL., (© 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

The prognosis of chronic lymphocytic leukemia (CLL) patients displaying trisomy 12 (+12) remains unclear. In this study, we analyzed the influence of the proportion of cells with +12, and other clinical and biologic factors, in time to first therapy (TTFT) and overall survival (OS), in 289 patients diagnosed with CLL carrying +12. Median OS was 129 months. One hundred seventy-four patients (60.2%) presented +12 in <60% of cells. TTFT and OS for this subgroup were longer than for the subgroup with +12 in ≥60% of cells, with a median TTFT of 49 months (CI95%, 39-58) vs 30 months (CI95%, 22-38) (P = 0.001); and a median OS of 159 months (CI95%, 119-182), vs 96 months (CI95%, 58-134) (P = 0.015). Other factors associated with a shorter TTFT were: Binet stage, B symptoms, lymphadenopathy, splenomegaly, high lymphocyte count, 11q-, high β2 microglobulin, and high LDH. In the multivariate analysis, clinical stage, +12 in ≥60% of cells, high lymphocyte count, B symptoms, and 11q- in addition, resulted of significance in predicting shorter TTFT. Significant variables for OS were: Binet stage, lymphadenopathy, splenomegaly, high LDH, high β2 microglobulin, 11q-, and CD38. In the multivariate analysis, only Binet stage, 11q-, and high β2microglobulin significantly predicted shorter OS. CLL with +12 entails a heterogeneous group with intermediate prognosis. However, a high proportion of cells carrying +12 separates a subgroup of patients with poor outcome. Copyright © 2015 John Wiley & Sons, Ltd., (Copyright © 2015 John Wiley & Sons, Ltd.)

The aim of this study was to investigate the frequency and mutation status of the immunoglobulin heavy variable chain (IGHV) in a cohort of 224 patients from northwest and central region of Spain diagnosed with chronic lymphocytic leukemia (CLL), and to correlate it with cytogenetic abnormalities, overall survival (OS) and time to first treatment (TTFT). 125 patients had mutated IGHV, while 99 had unmutated IGHV. The most frequently used IGHV family was IGHV3, followed by IGHV1 and IGHV4. The regions IGHV3-30, IGHV1-69, IGHV3-23, and IGHV4-34 were the most commonly used. Only 3.1% of the patients belonged to the subfamily IGHV3-21 and we failed to demonstrate a worse clinical outcome in this subgroup. The IGHV4 family appeared more frequently with mutated pattern, similar to IGHV3-23 and IGHV3-74. By contrast, IGHV1-69 was expressed at a higher frequency in unmutated CLL patients. All the cases from IGHV3-11 and almost all from IGHV5-51 subfamily belonged to the group of unmutated CLL.