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Follicular lymphoma (FL) is morphologically and clinically diverse, with mutations in epigenetic regulators alongside t(14;18) identified as disease-initiating events. Identification of additional mutational entities confirms this cancer’s heterogeneity, but whether mutational data can be resolved into mechanistically distinct subsets remains an open question. Targeted sequencing was applied to an unselected population-based FL cohort (n = 548) with full clinical follow-up (n = 538), which included 96 diffuse large B-cell lymphoma (DLBCL) transformations. We investigated whether molecular subclusters of FL can be identified and whether mutational data provide predictive information relating to transformation. DNA extracted from FL samples was sequenced with a 293-gene panel representing genes frequently mutated in DLBCL and FL. Three clusters were resolved using mutational data alone, independent of translocation status: FL_aSHM, with high burden of aberrant somatic hypermutation (aSHM) targets; FL_STAT6, with high STAT6 & CREBBP mutation and low aSHM; and FL_Com, with the absence of features of other subtypes and enriched KMT2D mutation. Analysis of mutation signatures demonstrated differential enrichment of predicted mutation signatures between subgroups and a dominant preference in the FL_aSHM subgroup for G(C>T)T and G(C>T)C transitions consistent with previously defined aSHM-like patterns. Of transformed cases with paired samples, 17 of 26 had evidence of branching evolution. Poorer overall survival (OS) in the aSHM group (P = .04) was associated with older age; however, overall tumor genetics provided limited information to predict individual patient risk. Our approach identifies 3 molecular subclusters of FL linked to differences in underlying mechanistic pathways. These clusters, which may be further resolved by the inclusion of translocation status and wider mutation profiles, have implications for understanding pathogenesis as well as improving treatment strategies in the future.

Contains fulltext : 290857.pdf (Publisher’s version ) (Closed access) Information on causes of death (CoDs) and the impact of myelodysplastic syndromes (MDS) on survival in patients with lower-risk MDS (LR-MDS) is limited. A better understanding of the relationship between disease characteristics, clinical interventions and CoDs may improve outcomes of patients with LR-MDS. We prospectively collected data on patients with LR-MDS in the European MDS registry from 2008 to 2019. Clinical, laboratory and CoDs data were obtained. To examine MDS-specific survival, relative survival (RS) was estimated using national life tables. Of 2396 evaluated subjects, 900 died (median overall survival [OS]: 4.7 years; median follow-up: 3.5 years). The most common CoDs were acute myeloid leukaemia/MDS (20.1%), infection (17.8%) and cardiovascular disease (CVD; 9.8%). Patients with isolated del(5q) and with red cell transfusion needed during the disease course, had a higher risk of fatal CVD. The 5-year OS was 47.3% and the 5-year RS was 59.6%, indicating that most patients died due to their underlying MDS. Older patients (aged >80 years) and the lowest-risk patients were more likely to die from competing causes. This study shows that MDS and its related complications play crucial role in the outcome of patients with LR-MDS. 01 februari 2023

Diffuse large B-cell lymphoma (DLBCL) is characterised by pronounced genetic and biological heterogeneity. Several partially overlapping classification systems exist – developed from mutation, rearrangement or gene expression data from single studies. We apply a customised network analysis to nearly five thousand DLBCL cases to identify and quantify modules of tumour biology. Shared patterns of activity in these tumour biology modules identify biologically similar DLBCL, which resolve into communities of related cases. These lymphoma communities correlate with genetic mutation and rearrangement status, supporting and extending existing concepts of disease biology and delivering insight into relationships between differentiation state, genetic subtypes and rearrangement status. A notable example are communities linked to distinct germinal centre states that separate DLBCL respectively associated withMYC/BCL2andMYC/BCL6double hit rearrangement. By exploiting network analysis across a large number of well characterised cases, this study provides the first birds eye view of DLBCL tumour biology.

To describe characteristics of COVID-19 outbreaks in Australia to guide policy development for mitigation of future outbreaks, we conducted a retrospective analysis of COVID-19 outbreaks affecting two or more people reported to COVID-Net—an Australian national surveillance network—from 28 January until 27 December 2020. The COVID-Net surveillance network covered all Australian states and territories, with an estimated population of 25,649,985 persons as at 31 June 2020. We reported the epidemiology of COVID-19 outbreaks in Australia, including the setting in which they occurred, size, and duration.853 outbreaks of COVID-19 were reported; associated with 13,957 confirmed cases, of whom 2,047 were hospitalised, and 800 died. The pattern of outbreaks followed a similar trend to the epidemic in Australia, defined by two distinct peaks in mid-March and July. Victoria reported the greatest number of outbreaks across all settings aligned with the second wave of infections. Outbreaks most commonly occurred in the workplace/industry setting (22%, 190/853), followed by education (14%, 122/853), residential aged care (13%, 114/853) and hospitals (10%, 83/853). The majority (40%, 340/853) of outbreaks had 6 to 24 cases, and the median outbreak duration increased in proportion with the number of associated cases.This report summarising COVID-19 outbreaks in Australia identifies settings of highest risk. Surveillance of outbreaks informs our understanding of transmission dynamics in Australia relative to national and jurisdictional interventions. For settings that are high risk for COVID-19, it is important to prioritise planning, surveillance, and implementation of control measures.

We previously identified five single nucleotide polymorphisms (SNPs) at four susceptibility loci for diffuse large B-cell lymphoma (DLBCL) in individuals of European ancestry through a large genome-wide association study (GWAS). To further elucidate genetic susceptibility to DLBCL, we sought to validate two loci at 3q13.33 and 3p24.1 that were suggestive in the original GWAS with additional genotyping. In the meta-analysis (5662 cases and 9237 controls) of the four original GWAS discovery scans and three replication studies, the 3q13.33 locus (rs9831894; minor allele frequency [MAF] = 0.40) was associated with DLBCL risk [odds ratio (OR) = 0.83, P = 3.62 × 10−13]. rs9831894 is in linkage disequilibrium (LD) with additional variants that are part of a super-enhancer that physically interacts with promoters of CD86 and ILDR1. In the meta-analysis (5510 cases and 12 817 controls) of the four GWAS discovery scans and four replication studies, the 3p24.1 locus (rs6773363; MAF = 0.45) was also associated with DLBCL risk (OR = 1.20, P = 2.31 × 10−12). This SNP is 29 426-bp upstream of the nearest gene EOMES and in LD with additional SNPs that are part of a highly lineage-specific and tumor-acquired super-enhancer that shows long-range interaction with AZI2 promoter. These loci provide additional evidence for the role of immune function in the etiology of DLBCL, the most common lymphoma subtype.

Summary: Background: A cornerstone of Australia's ability to control COVID-19 has been effective border control with an extensive supervised quarantine programme. However, a rapid recrudescence of COVID-19 was observed in the state of Victoria in June, 2020. We aim to describe the genomic findings that located the source of this second wave and show the role of genomic epidemiology in the successful elimination of COVID-19 for a second time in Australia. Methods: In this observational, genomic epidemiological study, we did genomic sequencing of all laboratory-confirmed cases of COVID-19 diagnosed in Victoria, Australia between Jan 25, 2020, and Jan 31, 2021. We did phylogenetic analyses, genomic cluster discovery, and integrated results with epidemiological data (detailed information on demographics, risk factors, and exposure) collected via interview by the Victorian Government Department of Health. Genomic transmission networks were used to group multiple genomic clusters when epidemiological and genomic data suggested they arose from a single importation event and diversified within Victoria. To identify transmission of emergent lineages between Victoria and other states or territories in Australia, all publicly available SARS-CoV-2 sequences uploaded before Feb 11, 2021, were obtained from the national sequence sharing programme AusTrakka, and epidemiological data were obtained from the submitting laboratories. We did phylodynamic analyses to estimate the growth rate, doubling time, and number of days from the first local infection to the collection of the first sequenced genome for the dominant local cluster, and compared our growth estimates to previously published estimates from a similar growth phase of lineage B.1.1.7 (also known as the Alpha variant) in the UK. Findings: Between Jan 25, 2020, and Jan 31, 2021, there were 20 451 laboratory-confirmed cases of COVID-19 in Victoria, Australia, of which 15 431 were submitted for sequencing, and 11 711 met all quality control metrics and were included in our analysis. We identified 595 genomic clusters, with a median of five cases per cluster (IQR 2–11). Overall, samples from 11 503 (98·2%) of 11 711 cases clustered with another sample in Victoria, either within a genomic cluster or transmission network. Genomic analysis revealed that 10 426 cases, including 10 416 (98·4%) of 10 584 locally acquired cases, diagnosed during the second wave (between June and October, 2020) were derived from a single incursion from hotel quarantine, with the outbreak lineage (transmission network G, lineage D.2) rapidly detected in other Australian states and territories. Phylodynamic analyses indicated that the epidemic growth rate of the outbreak lineage in Victoria during the initial growth phase (samples collected between June 4 and July 9, 2020; 47·4 putative transmission events, per branch, per year [1/years; 95% credible interval 26·0–85·0]), was similar to that of other reported variants, such as B.1.1.7 in the UK (mean approximately 71·5 1/years). Strict interventions were implemented, and the outbreak lineage has not been detected in Australia since Oct 29, 2020. Subsequent cases represented independent international or interstate introductions, with limited local spread. Interpretation: Our study highlights how rapid escalation of clonal outbreaks can occur from a single incursion. However, strict quarantine measures and decisive public health responses to emergent cases are effective, even with high epidemic growth rates. Real-time genomic surveillance can alter the way in which public health agencies view and respond to COVID-19 outbreaks. Funding: The Victorian Government, the National Health and Medical Research Council Australia, and the Medical Research Future Fund.

We present a case of late symptom onset of COVID-19 infection 72 days after initial diagnosis in an immunocompromised 53-year-old man. SARS-CoV-2 was cultured from his sputum sample at this time, and genomic sequencing suggested reinfection was unlikely. After receipt of convalescent plasma, SARS-CoV-2 became undetectable by PCR 111 days after diagnosis, although SARS-CoV-2 antibodies remained not detectable. This case posed difficult public health management issues in a low prevalence COVID-19 setting as the person required extended home isolation given his prolonged SARS-CoV-2 PCR detection.

Contains fulltext : 237720.pdf (Publisher’s version ) (Open Access) We present a noninvasive Web-based app to help exclude or diagnose myelodysplastic syndrome (MDS), a bone marrow (BM) disorder with cytopenias and leukemic risk, diagnosed by BM examination. A sample of 502 MDS patients from the European MDS (EUMDS) registry (n > 2600) was combined with 502 controls (all BM proven). Gradient-boosted models (GBMs) were used to predict/exclude MDS using demographic, clinical, and laboratory variables. Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were used to evaluate the models, and performance was validated using 100 times fivefold cross-validation. Model stability was assessed by repeating its fit using different randomly chosen groups of 502 EUMDS cases. AUC was 0.96 (95% confidence interval, 0.95-0.97). MDS is predicted/excluded accurately in 86% of patients with unexplained anemia. A GBM score (range, 0-1) of less than 0.68 (GBM < 0.68) resulted in a negative predictive value of 0.94, that is, MDS was excluded. GBM ≥ 0.82 provided a positive predictive value of 0.88, that is, MDS. The diagnosis of the remaining patients (0.68 ≤ GBM < 0.82) is indeterminate. The discriminating variables: age, sex, hemoglobin, white blood cells, platelets, mean corpuscular volume, neutrophils, monocytes, glucose, and creatinine. A Web-based app was developed; physicians could use it to exclude or predict MDS noninvasively in most patients without a BM examination. Future work will add peripheral blood cytogenetics/genetics, EUMDS-based prospective validation, and prognostication.

BACKGROUND: A cornerstone of Australia’s ability to control COVID-19 has been effective border control, using an extensive supervised quarantine program. However, a rapid recrudescence in COVID-19 cases was observed in the state of Victoria in June 2020. Here, we describe the genomic findings that located the source of this second wave as a breach in supervised hotel quarantine and demonstrate the successful elimination of COVID-19 for a second time in Australia. METHODS: Genome sequencing was performed on all available SARS-CoV-2-positive samples in Victoria and integrated genomic and epidemiological investigation undertaken. RESULTS: At 31st January 2021, 20,451 COVID-19 cases were reported in Victoria; samples were sequenced from 75% of cases (15,431/20,451). Genomics revealed 98% (10,426/10,646) of locally-acquired cases during the second wave were derived from a single incursion from hotel quarantine, with the outbreak strain rapidly detected in other Australian states and territories. Phylodynamic analyses indicated an epidemic growth rate comparable to emerging variants, such as B.1.1.7 in the United Kingdom. Strict public health interventions resulted in the elimination of the outbreak strain by 29th October 2020. Subsequent cases represented independent international or interstate introductions, with limited local spread. CONCLUSIONS: Rapid escalation of clonal outbreaks can occur from even a single breach of control practices, as revealed through our genomic ‘enhanced outbreak-detection' system. The subsequent elimination and rapid control of new SARS-CoV-2 incursions reinforce that decisive public health responses to emergent cases are effective even with high epidemic growth rates, and “elimination” should be favored in settings where this is achievable. FUNDING STATEMENT: The Microbiological Diagnostic Unit Public Health Laboratory (MDU PHL) and the Victorian Infectious Diseases Reference Laboratory (VIDRL) at The Doherty Institute are funded by the Victorian Government. This work was supported by the National Health and Medical Research Council, Australia (NHMRC); Partnership Grant (APP1149991), Investigator Grant to BPH (APP1196103), Investigator Grant to DAW (APP1174555), Research Fellowship to TPS (APP1105525), MRFF COVID-19 Genomics Grant (MRF9200006). DECLARATION OF INTERESTS: None to declare. ETHICS APPROVAL STATEMENT: Data were collected in accordance with the Victorian Public Health and Wellbeing Act 2008. Ethical approval was received from the University of Melbourne Human Research Ethics Committee (study number 1954615.3).

Countries worldwide are experiencing a second wave of coronavirus disease 2019 (COVID-19), which is proving to be difficult to control. We describe the combination of physical distancing, mandatory mask wearing, movement restrictions, and enhanced test, trace, and isolation efforts that can be used to successfully suppress community transmission to zero.

We recently published results of targeted sequencing applied to 928 unselected cases of DLBCL registered in the Haematological Malignancy Research Network (HMRN) registry (1). Clustering allowed us to resolve five genomic subtypes. These subtypes shared considerable overlap with those proposed in two independent genomic studies(2, 3), suggesting the potential to use genetics to stratify patients by both risk and biology. In the original studies, clustering techniques were applied to sample cohorts to reveal molecular substructure, but left open the challenge of how to classify an individual patient. This was addressed by the LymphGen classification tool (4). LymphGen assigns an individual case to one of six molecular subtypes. The tool accommodates data from exome or targeted sequencing, either with or without copy number variant (CNV) data. Separate gene expression data allows classification of a seventh, MYC-driven subtype defined by a double hit (DHL) or molecular high-grade (MHG) gene expression signature(5-7).

Recognition of dying is a difficult task in end-stage heart failure, yet it remains an important clinical skill in providing good palliative care to these patients.To use routinely collected data to explore evidence for physiological change in the final two weeks of life in end-stage heart failure.This was a retrospective cohort study of routinely collected data from hospital inpatients dying as a result of heart failure during a one-year period in a U.K. hospital. Data were analyzed using descriptive techniques and multilevel modeling.Results were obtained on 81 patients. Respiratory function (evidenced by falling oxygen saturation and rising respiratory rate) deteriorated by a clinically significant amount in the final two weeks of life (P 0.001). Renal function (evidenced by rising serum urea and creatinine) also demonstrated a clinically significant deterioration over the same period (P 0.001 and P = 0.005, respectively). Serum albumin fell over a period of months (P 0.001). Heart rate and blood pressure did not demonstrate clinically significant change over the same period.Deteriorating respiratory and renal function may indicate imminent dying in heart failure. A fall in serum albumin may signify poor prognosis over a timescale of weeks to months. Conversely, hemodynamic parameters may remain relatively stable in the final days of life and should not be reassuring in end-stage heart failure patients.

Based on the profile of genetic alterations occurring in tumor samples from selected diffuse large B-cell lymphoma (DLBCL) patients, 2 recent whole-exome sequencing studies proposed partially overlapping classification systems. Using clustering techniques applied to targeted sequencing data derived from a large unselected population-based patient cohort with full clinical follow-up (n = 928), we investigated whether molecular subtypes can be robustly identified using methods potentially applicable in routine clinical practice. DNA extracted from DLBCL tumors diagnosed in patients residing in a catchment population of ∼4 million (14 centers) were sequenced with a targeted 293-gene hematological-malignancy panel. Bernoulli mixture-model clustering was applied and the resulting subtypes analyzed in relation to their clinical characteristics and outcomes. Five molecular subtypes were resolved, termed MYD88, BCL2, SOCS1/SGK1, TET2/SGK1, and NOTCH2, along with an unclassified group. The subtypes characterized by genetic alterations of BCL2, NOTCH2, and MYD88 recapitulated recent studies showing good, intermediate, and poor prognosis, respectively. The SOCS1/SGK1 subtype showed biological overlap with primary mediastinal B-cell lymphoma and conferred excellent prognosis. Although not identified as a distinct cluster, NOTCH1 mutation was associated with poor prognosis. The impact of TP53 mutation varied with genomic subtypes, conferring no effect in the NOTCH2 subtype and poor prognosis in the MYD88 subtype. Our findings confirm the existence of molecular subtypes of DLBCL, providing evidence that genomic tests have prognostic significance in non-selected DLBCL patients. The identification of both good and poor risk subtypes in patients treated with R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) clearly show the clinical value of the approach, confirming the need for a consensus classification.

Using a Burkitt lymphoma-like gene expression signature, we recently defined a high-risk molecular high-grade (MHG) group mainly within germinal centre B-cell like diffuse large B-cell lymphomas (GCB-DLBCL), which was enriched for MYC/BCL2 double-hit (MYC/BCL2-DH). The genetic basis underlying MHG-DLBCL and their aggressive clinical behaviour remain unknown. We investigated 697 cases of DLBCL, particularly those with MYC/BCL2-DH (n = 62) by targeted sequencing and gene expression profiling. We showed that DLBCL with MYC/BCL2-DH, and those with BCL2 translocation, harbour the characteristic mutation signatures that are associated with follicular lymphoma and its high-grade transformation. We identified frequent MYC hotspot mutations that affect the phosphorylation site (T58) and its adjacent amino acids, which are important for MYC protein degradation. These MYC mutations were seen in a subset of cases with MYC translocation, but predominantly in those of MHG. The mutations were more frequent in double-hit lymphomas with IG as the MYC translocation partner, and were associated with higher MYC protein expression and poor patient survival. DLBCL with MYC/BCL2-DH and those with BCL2 translocation alone are most likely derived from follicular lymphoma or its precursor lesion, and acquisition of MYC pathogenic mutations may augment MYC function, resulting in aggressive clinical behaviour.

Background. The severity of hematopoietic impairment and the kinetics of disease progression in lower risk myelodysplastic syndromes (LR-MDS) are extremely variable. Genomic profiling has the potential to inform the clinical management of these disorders, including improved classification, risk assessment and therapeutic choice. In the present study, based on a comprehensive mutation analysis in a large and clinically well-characterized cohort of LR-MDS patients, either recruited into the European MDS Registry or referred to European excellence centers involved in the MDS-RIGHT project, we adopted unsupervised hierarchical clustering analyses to identify relevant genetically defined disease subtypes within early stage MDS. Methods. The dataset comprised 856 cases identified as LR-MDS based on IPSS risk low or intermediate-1. Median age was 73 years (range 36-98); IPSS-R risk was very low in 30.1% of patients, low in 50.4%, intermediate in 19.5%. We investigated possible sub-structure amongst patients according to their mutational profiles, and correlated this sub-structure with relevant endpoints. For this analysis, unsupervised clustering was used, based on a mixture model of multivariate Bernoulli distributions. The optimal number of clusters was chosen using the Bayes Information Criterion (BIC), with secondary structure identified with the Akaike Information Criterion (AIC). Results. This analysis identified three distinct clusters within LR-MDS. Cluster 1 comprised exclusively patients with SF3B1 mutation, either isolated or associated with other mutations (SF3B1-mutant cluster) (37% of patients). Cluster 2 was characterized by excess mutations associated with higher risk disease (high-risk (HR) cluster) (27% of patients), including a significantly higher prevalence of ASXL1, IDH1/IDH2, SRSF2, RUNX1, CBL and EZH2 mutations (P The three recognized clusters showed distinct clinical features and outcome measures. Patients within HR cluster were significantly older (P=.008) and showed significant enrichment in WHO categories with multi-lineage dysplasia and excess blasts (P HR-cluster showed significantly lower overall survival (OS) compared to CHIP-like and SF3B1-mutant clusters (median 2.6 vs 6.8 or 6.4 years; P Conclusion. Mutation profiling identifies meaningful clusters of lower risk MDS with distinct molecular pathways, clinical features and endpoints. These results represent a robust basis to inform genetic ontogeny-based classification and individual risk assessment, as well as to inspire biology-driven clinical trials in lower risk MDS. Disclosures Symeonidis: Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck Sharp & Dohme: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi/Genzyme: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; WinMedica: Research Funding; Celgene: Honoraria, Research Funding; Astellas: Research Funding; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; GenesisPharma: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Stauder:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Teva: Research Funding. Fenaux:Novartis: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding; Jazz: Honoraria, Research Funding; BMS: Honoraria, Research Funding. Van Marrewijk:EUMDS and MDS-RIGHT (Providing the right care to the right patient with MyeloDysplastic Syndrome at the right time) project: Other: Project manager of the EUMDS Registry.

The diagnosis of chronic myelomonocytic leukemia (CMML) remains centered on morphology, meaning that the distinction from a reactive monocytosis is challenging. Mutational analysis and immunophenotyping have been proposed as potential tools for diagnosis; however, they have not been formally assessed in combination. We aimed to investigate the clinical utility of these technologies by performing targeted sequencing, in parallel with current gold standard techniques, on consecutive samples referred for investigation of monocytosis over a 2-year period (N = 283). Results were correlated with the morphological diagnosis and objective outcome measures, including overall survival (OS) and longitudinal blood counts. Somatic mutations were detected in 79% of patients, being invariably identified in those with a confirmed diagnosis (99%) but also in 57% of patients with nondiagnostic bone marrow features. The OS in nondiagnostic mutated patients was indistinguishable from those with CMML (P = .118) and significantly worse than in unmutated patients (P = .0002). On multivariate analysis, age, ASXL1, CBL, DNMT3A, NRAS, and RUNX1 mutations retained significance. Furthermore, the presence of a mutation was associated with a progressive decrease in hemoglobin/platelet levels and increasing monocyte counts compared with mutation-negative patients. Of note, the immunophenotypic features of nondiagnostic mutated patients were comparable to CMML patients, and the presence of aberrant CD56 was highly specific for detecting a mutation. Overall, somatic mutations are detected at high frequency in patients referred with a monocytosis, irrespective of diagnosis. In those without a World Health Organization–defined diagnosis, the mutation spectrum, immunophenotypic features, and OS are indistinguishable from CMML patients, and these patients should be managed as such.

Highlights • Diffuse-large B-cell and marginal zone lymphoma: inflammatory conditions increase risk. • Myeloma, follicular lymphoma and chronic lymphocytic leukaemia: inflammatory conditions do not impact on risk. • Inflammatory conditions are far more common in women, but gender is not an effect modifier. • Inflammatory co-morbidities do not impact adversely on mature B-cell malignancy survival. • The increased risk for diffuse large B-cell lymphoma is not mediated by the activated B-cell subtype., Background Autoimmune inflammatory disease increases the risk of diffuse large B-cell lymphoma (DLBCL) and marginal zone lymphoma (MZL), but findings for other mature B-cell malignancies are equivocal. Furthermore, it has been suggested that the increase in DLBCL is due to the activated B-cell (ABC) subtype; but data on this, and the impact of inflammatory co-morbidities on survival, are sparse and contradictory. Methods Data are from an established UK population-based cohort. Patients (n = 6834) diagnosed between 01/2009 and 08/2015 are included; DLBCL (n = 1771), myeloma (n = 1760), chronic lymphocytic leukaemia (CLL, n = 1580), MZL (n = 936), and follicular lymphoma (FL, n = 787). Information on rheumatological disorders and deaths was obtained by record-linkage to nationally compiled Hospital Episode Statistics, with age-and sex-matched individuals (n = 68,340) from the same catchment population (˜4 million people) providing the comparator. Results Significantly increased risks for DLBCL (OR = 2.3, 95% CI 1.8–2.8) and MZL (OR = 2.0, 95% CI 1.5–2.7) were found for those with rheumatological disorders; the site distribution of those with/without rheumatological conditions differing for DLBCL (p = 0.007) and MZL (p = 0.002). No increases in risk were observed for the remaining mature B-cell malignancies, and no associations with survival were detected for DLBCL (age-adjusted HR = 1.2, 95% CI 0.9–1.6) or MZL (age-adjusted HR = 1.0, 95% CI 0.6–1.9). Furthermore, whilst our findings provide evidence for an association with rheumatological disease severity for DLBCL, they offer little support for the notion that the association is driven by an increase in the incidence of the ABC subtype. Conclusion Our findings support the hypothesis that the chronic activation and proliferation of specific B-cell populations which characterize autoimmune disease increase the potential for the lymphomagenic events that lead to DLBCL and MZL in both males and females; but have no impact on the development of CLL, FL or MM, or on survival.

Background Diffuse large B-cell lymphoma (DLBCL) is the commonest non-Hodgkin lymphoma. Previous studies examining the cost of treating DLBCL have generally focused on a specific first-line therapy alone; meaning that their findings can neither be extrapolated to the general patient population nor to other points along the treatment pathway. Based on empirical data from a representative population-based patient cohort, the objective of this study was to develop a simulation model that could predict costs and life expectancy of treating DLBCL. Methods All patients newly diagnosed with DLBCL in the UK’s population-based Haematological Malignancy Research Network (www.hmrn.org) in 2007 were followed until 2013 (n = 271). Mapped treatment pathways, alongside cost information derived from the National Tariff 2013/14, were incorporated into a patient-level simulation model in order to reflect the heterogeneities of patient characteristics and treatment options. The NHS and social services perspective was adopted, and all outcomes were discounted at 3.5 % per annum. Results Overall, the expected total medical costs were £22,122 for those treated with curative intent, and £2930 for those managed palliatively. For curative chemotherapy, the predicted medical costs were £14,966, £23,449 and £7376 for first-, second- and third-line treatments, respectively. The estimated annual cost for treating DLBCL across the UK was around £88–92 million. Conclusions This is the first cost modelling study using empirical data to provide ‘real world’ evidence throughout the DLBCL treatment pathway. Future application of the model could include evaluation of new technologies/treatments to support healthcare decision makers, especially in the era of personalised medicine. Electronic supplementary material The online version of this article (doi:10.1007/s10198-016-0775-4) contains supplementary material, which is available to authorized users.

In this study we aimed to test the associations between area-level ethnic density and health for Pakistani and White British residents of Bradford, England.The sample consisted of 8610 mothers and infant taking part in the Born in Bradford cohort. Ethnic density was measured as the percentage of Pakistani, White British or South Asian residents living in a Lower Super Output Area. Health outcomes included birth weight, preterm birth and smoking during pregnancy. Associations between ethnic density and health were tested in multilevel regression models, adjusted for individual covariates and area deprivation.In the Pakistani sample, higher own ethnic density was associated with lower birth weight (β = -0.82, 95% CI: -1.63, -0.02), and higher South Asian density was associated with a lower probability of smoking during pregnancy (OR = 0.99, 95% CI: 0.98, 1.00). Pakistani women in areas with 50-70% South Asian residents were less likely to smoke than those living in areas with less than 10% South Asian residents (OR = 0.39, 95% CI: 0.16, 0.97). In the White British sample, neither birth weight nor preterm birth was associated with own ethnic density. The probability of smoking during pregnancy was lower in areas with 10-29.99% compared to10% South Asian density (OR = 0.79, 95% CI: 0.64, 0.98).In this sample, ethnic density was associated with lower odds of smoking during pregnancy but not with higher birth weight or lower odds of preterm birth. Possibly, high levels of social disadvantage inhibit positive effects of ethnic density on health.

This study investigates the value of performing a staging bone marrow in patients with diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL) and classical hodgkin lymphoma (CHL). The results of 3112 staging bone marrow examinations were assessed for impact on prognostic assessment and critical treatment decisions. The detection of marrow involvement altered the disease-specific prognostic index for 4·3% of DLBCL, 6·2% of FL and 0·6% of CHL but marrow involvement in DLBCL was an independent prognostic factor. Knowing the marrow status potentially changed treatment in 92 patients, detection of these patients would have required 854 examinations to be performed.

Summary Objectives We conducted a systematic review that aimed to document and describe how (1) expectation of benefit from treatment (response expectancies) were measured and reported in acupuncture trials, and (2) examine any effect on outcomes. Design We searched MEDLINE, EMBASE, AMED, CIHAHL, CENTRAL and Science and Technology Proceedings up to November 2007 for randomised (RCT) and quasi-randomised (CCT) controlled trials and prospective controlled cohorts of acupuncture as treatment for a medical or psychological condition in adults. An update citation search was conducted in April 2010. We included studies that mentioned soliciting response expectancies. Results We found 58 RCTs that fulfilled our inclusion criteria. Around half referenced one of five published instruments, most of which were designed to measure sham credibility and included one question on response expectancy. A wide range of question phrasing and response scales was used. There was some evidence that response scales may influence the measurement of expectations. Eight trials analysed the association between pre-randomisation expectations for assigned treatment and outcomes, and six the effect of pre-randomisation expectations across all patients independent of treatment allocation. Some showed associations but others did not. Conclusions There is some evidence that response expectancies interact with outcomes in acupuncture trials however the variety of question phrasing and analysis methods precludes drawing a firm conclusion about for whom and under which circumstance. To further our understanding of expectations, more methodological work is needed to standardise the questions and response scales that are used.

A proportion of MYC translocation positive diffuse large B-cell lymphomas (DLBCL) harbour a BCL2 and/or BCL6 translocation, known as double-hit DLBCL, and are clinically aggressive. It is unknown whether there are other genetic abnormalities that cooperate with MYC translocation and form double-hit DLBCL, and whether there is a difference in clinical outcome between the double-hit DLBCL and those with an isolated MYC translocation. We investigated TP53 gene mutations along with BCL2 and BCL6 translocations in a total of 234 cases of DLBCL, including 81 with MYC translocation. TP53 mutations were investigated by PCR and sequencing, while BCL2 and BCL6 translocation was studied by interphase fluorescence in situ hybridization. The majority of MYC translocation positive DLBCLs (60/81 = 74%) had at least one additional genetic hit. In MYC translocation positive DLBCL treated by R-CHOP (n = 67), TP53 mutation and BCL2, but not BCL6 translocation had an adverse effect on patient overall survival. In comparison with DLBCL with an isolated MYC translocation, cases with MYC/TP53 double-hits had the worst overall survival, followed by those with MYC/BCL2 double-hits. In MYC translocation negative DLBCL treated by R-CHOP (n = 101), TP53 mutation, BCL2 and BCL6 translocation had no impact on patient survival. The prognosis of MYC translocation positive DLBCL critically depends on the second hit, with TP53 mutations and BCL2 translocation contributing to an adverse prognosis. It is pivotal to investigate both TP53 mutations and BCL2 translocations in MYC translocation positive DLBCL, and to distinguish double-hit DLBCLs from those with an isolated MYC translocation.

Background: Population-based information about cancer occurrence and survival are required to inform clinical practice and research; but for most lymphomas data are lacking. Methods: Set within a socio-demographically representative UK population of nearly 4 million, lymphoma data (N ¼ 5796) are from an established patient cohort. Results: Incidence, survival (overall and relative) and prevalence estimates for 420 subtypes are presented. With few exceptions, males tended to be diagnosed at younger ages and have significantly (Po0.05) higher incidence rates. Differences were greatest at younger ages: the o15 year male/female rate ratio for all subtypes combined being 2.2 (95% CI 1.3–3.4). These gender differences impacted on prevalence; most subtype estimates being significantly (Po0.05) higher in males than females. Outcome varied widely by subtype; survival of patients with nodular lymphocyte predominant Hodgkin lymphoma approached that of the general population, whereas less than a third of those with other B-cell (e.g., mantle cell) or T-cell (e.g., peripheral-T) lymphomas survived for Z5 years. No males/female survival differences were detected. Conclusions: Major strengths of our study include completeness of ascertainment, world-class diagnostics and generalisability. The marked variations demonstrated confirm the requirement for ‘real-world’ data to inform aetiological hypotheses, health-care planning and the future monitoring of therapeutic changes.

Objective: Determinants of the increased risk of diffuse large B-cell lymphoma (DLBCL) in SLE are unclear. Using data from a recent lymphoma genomewide association study (GWAS), we assessed whether certain lupus-related single nucleotide polymorphisms (SNPs) were also associated with DLBCL. Methods: GWAS data on European Caucasians from the International Lymphoma Epidemiology Consortium (InterLymph) provided a total of 3857 DLBCL cases and 7666 general-population controls. Data were pooled in a random-effects meta-analysis. Results: Among the 28 SLE-related SNPs investigated, the two most convincingly associated with risk of DLBCL included the CD40 SLE risk allele rs4810485 on chromosome 20q13 (OR per risk allele=1.09, 95% CI 1.02 to 1.16, p=0.0134), and the HLA SLE risk allele rs1270942 on chromosome 6p21.33 (OR per risk allele=1.17, 95% CI 1.01 to 1.36, p=0.0362). Of additional possible interest were rs2205960 and rs12537284. The rs2205960 SNP, related to a cytokine of the tumour necrosis factor superfamily TNFSF4, was associated with an OR per risk allele of 1.07, 95% CI 1.00 to 1.16, p=0.0549. The OR for the rs12537284 (chromosome 7q32, IRF5 gene) risk allele was 1.08, 95% CI 0.99 to 1.18, p=0.0765. Conclusions: These data suggest several plausible genetic links between DLBCL and SLE. © 2017 BMJ Publishing Group. All rights reserved.

Background: Recognising dying remains a difficult clinical skill which has gained increasing importance in the United Kingdom since the Neuberger review. Clinical and research methods exist to aid recognition of dying but do not exhibit the level of accuracy required for such an important decision. Aim: To explore change in key clinical parameters as cancer patients near the end of life. Design: This is a retrospective cohort study of terminally ill patients. Data were collected from hospital case-notes. Case-note data were analysed using multilevel modelling to explore absolute values and rates of change of given variables. Setting/participants: Hospital in-patients who died from solid-tumour malignancies within a 3-month period in 2009 formed the cohort. The setting was an acute hospital trust in the North of England. Results: A total of 15,337 data points from the case-notes of 102 patients were analysed. There was a clinically and statistically significant deterioration in respiratory function and renal function over the last 2 weeks of life. Heart rate and serum sodium also changed but did not vary greatly from normal limits. White cell parameters, haemoglobin and albumin showed evidence for change over longer periods. Conclusion: Results demonstrate statistically and clinically significant change in routinely measured respiratory and renal function variables during the final 2 weeks of life in people dying with cancer. Although useful in acute early warning scores, in a terminally ill patient, relative haemodynamic stability should not be interpreted as reassuring. Further work is needed to understand how these findings apply to the individual or inform other prognostic work.

Guidelines recommend exercise-based cardiac rehabilitation (EBCR) for patients with heart failure (HF). However, established research has not investigated the longer-term outcomes including mortality and hospitalisation in light of the contemporary management of HF.This was a systematic review including a meta-analysis of EBCR on all-cause mortality, hospital admission, and standardised exercise capacity using four separate exercise tests in patients with heart failure over a minimum follow-up of six months from January 1999-January 2013. Electronic searches were performed in the databases: Medline, CENTRAL, EMBASE, CINAHL, and PsycINFO constrained to randomised controlled trials (RCTs).A total of 46 separate RCTs qualified for the meta-analysis, which employed conventional methods for binary and continuous data. The relative risk (RR) ratio for hospital admission (12 studies) was significantly reduced (RR ratio 0.65; 95% confidence interval (CI) 0.50-0.84; p = 0.001), but mortality (21 studies) was not (RR ratio 0.88; 95% CI 0.77-1.02; p = 0.08). The standardised exercise capacity (26 studies) showed a standardised mean difference (SMD) in favour of the exercise group as compared with the controls (SMD 0.98, 95% CI 0.59-1.37; p 0.001). Women and elderly people were less frequently enrolled in the RCTs independent of the outcomes. Heterogeneity was moderate to high in the analysis of hospital admission and the standardised exercise capacity demonstrated through skewedness in their funnel plots.EBCR in patients with HF is associated with significant improvements in exercise capacity and hospital admission over a minimum of six months follow-up, but not in all-cause mortality.

Objectives We present a new method for determining prevalence estimates together with estimates of their precision, from incidence and survival data using Monte-Carlo simulation techniques. The algorithm also provides for the incidence process to be marked with the values of subject level covariates, facilitating calculation of the distribution of these variables in prevalent cases. Methods Disease incidence is modelled as a marked stochastic process and simulations are made from this process. For each simulated incident case, the probability of remaining in the prevalent sub-population is calculated from bootstrapped survival curves. This algorithm is used to determine the distribution of prevalence estimates and of the ancillary data associated with the marks of the incidence process. This is then used to determine prevalence estimates and estimates of the precision of these estimates, together with estimates of the distribution of ancillary variables in the prevalent sub-population. This technique is illustrated by determining the prevalence of acute myeloid leukaemia from data held in the Haematological Malignancy Research Network (HMRN). In addition, the precision of these estimates is determined and the age distribution of prevalent cases diagnosed within twenty years of the prevalence index date is calculated. Conclusion Determining prevalence estimates by using Monte-Carlo simulation techniques provides a means of calculation more flexible that traditional techniques. In addition to automatically providing precision estimates for the prevalence estimates, the distribution of any measured subject level variables can be calculated for the prevalent sub-population. Temporal changes in incidence and in survival offer no difficulties for the method.

The high frequency of somatic mutations in myelodysplastic syndromes (MDS) provides an additional biomarker modality for MDS diagnosis. This has significant potential in the investigation of cytopenias particularly in cases with All patient samples referred for unexplained cytopenia or suspected MDS to the Haematological Malignancy Diagnostic Service in the UK over a 2-year period (July 2014-2016) were included. Samples were analysed using established diagnostic assays (morphology, flow cytometry, cytogenetics) and in parallel subjected to targeted sequencing of 27 genes commonly mutated in myeloid malignancies. Outcome data was captured including serial blood count data, subsequent diagnoses and overall survival. A subgroup of 37 mutation negative samples underwent extended genotyping of 126 genes. A total of 2089 samples passed QC for targeted sequencing. Of these, 538 had a confirmed diagnosis (26%), the majority of which were diagnosed with a myeloid malignancy (449/538; 83%). Mutations were commonly identified in the latter with ≥1 somatic mutation +/or karyotypic abnormality detected in 91% of patients. Importantly, mutations were also detected in 28% of non-diagnostic (ND) samples (412/1496). The spectrum of mutations was similar between ND and MDS samples, though varied in frequency. In ND samples TET2, SRSF2 and DNMT3A mutations predominated (47%, 22%, 19% respectively) while SF3B1, TET2 and ASXL1 were most frequently mutated in MDS (25%, 24%, 24% respectively). The number of mutations detected per sample and the variant allele fraction (VAF) was also significantly lower in ND samples (median no. of mutations 1 vs 2; median VAF 17.7% vs 35.1%; p To determine the clinical significance of mutations, correlation was made with subsequent diagnoses and clinical outcome. Follow-up bone marrow samples were received in 205 ND samples and 82 of these had a confirmed diagnosis of which 61 had a myeloid malignancy. The presence of a mutation at baseline was strongly associated with a subsequent myeloid diagnosis (NDmut vs NDunmut ;13% vs 0.5%; p1 mutation; p Importantly the presence of a mutation impacted significantly on survival in the ND group (odds ratio=1.59; p By analysing a large unselected cohort of cytopenic patients, this study has demonstrated the power of mutation analysis to predict both a subsequent myeloid diagnosis and clinical outcome in those without a confirmed diagnosis. While standard techniques will identify some of these patients over time, crucially, those at highest risk can remain undetected. Identifying these patients would ensure close clinical follow-up and provide an opportunity for early intervention. Ultimately this will facilitate the development of predictive models and refine diagnostic algorithms and this work is ongoing. Disclosures Cargo: Celgene: Research Funding. Evans:Diaceutics: Honoraria; Novartis: Honoraria. Papaemmanuil:Celgene: Research Funding.

Aims Aspirin and statins are established therapies for acute myocardial infarction (MI), but their benefits in patients with chronic heart failure (HF) remain elusive. We investigated the impact of aspirin and statins on long-term survival in patients hospitalized with acute MI complicated by HF. Methods and results Of 4251 patients in the Evaluation of Methods and Management of Acute Coronary Events (EMMACE)-1 and -2 observational studies, 1706 patients had HF. A propensity score-matching method estimated the average treatment effects (ATEs) of aspirin and statins on survival over 90 months. ATEs were calculated as relative risk differences in all-cause mortality comparing patients receiving aspirin and statins with controls, respectively. Moreover, combined aspirin and statins vs. none (ATE I), aspirin or statins vs. none (ATE II), and aspirin and statins vs. aspirin or statins (ATE III) were assessed. The median survival times of the ATE I, ATE II and ATE III were 25, 50, and 85 months, respectively. Regarding aspirin, the ATE was significantly improved at 6, 12, and 90 months [ATE 6 months: 10%, 95% confidence interval (CI) 3–18%], where the ATE of statins favoured survival at 1–24 months (ATE 1 month: 5%, 95% CI 0.3–10%). Mortality was lower at 1, 6, and 24 months in those who received aspirin and statins (ATE I). When the combination was compared with either treatment alone, an effect persisted between 6 and 90 months (ATE III). Conclusion In patients with acute MI complicated by HF, prescription of aspirin and statins either alone or together was associated with better long-term survival.

Objective To review reporting of preferences in acupuncture studies and their effect on clinical outcomes. Study Design and Setting Systematic review of published randomized and quasi-randomized controlled trials of acupuncture reporting participant preferences for randomization or treatment or using a preference design. Results Of the 31 included trials, 5 reported on randomization preference, 18 on treatment preference, and 1 reported on both. Seven used a preference design. Four out of seven trials noted that the group with preferences had different baseline characteristics (less education, worse baseline measure score, and greater or fewer years with pain). There was a tendency for greater attrition in nonpreference arms at 6 months but not earlier. Around three-quarters of participants turned down randomization in favor of nontrial treatment, and preference for acupuncture was around 20% when offered multiple treatments. Questions used to elicit preferences varied across trials and were poorly reported. Ten trials reported the effects of preferences on outcomes; only one detected a statistically (but not clinically) significant difference. Conclusion There is little evidence that preferences cause detectable effects on outcomes in acupuncture trials; however, trials use inconsistent methods and poorly report these data. Monitoring the level and effect of preferences in trials is recommended.

Objective: Well-established cancer registries that routinely link to death registrations can estimate prevalence directly by counting patients alive at a particular point in time (observed prevalence). Such direct methods can only provide prevalence for the years over which the registry has been operational. Time-defined estimates, including 5- and 10-year prevalence, may however underestimate the total cancer burden, and compared with other cancers, there is a lack of accurate information on the total prevalence of hematological malignancy subtypes. Accordingly, we aimed to estimate prevalence (observed and total prevalence) of hematological malignancies and precursor conditions by clinically meaningful subtypes using data from the UK’s specialist population-based register, the Haematological Malignancy Research Network (www.hmrn.org). Methods: Observed and total prevalences were estimated from 15,810 new diagnoses of hematological malignancies from 2004 to 2011 and followed up to the 31 August 2011 (index data). Observed prevalence was calculated by the counting method, and a method based on modelling incidence and survival was used to estimate total prevalence. Estimates were made according to current disease classification for the HMRN region and for the UK. Results: The overall observed and total prevalence rates were 281.9 and 548.8 per 100,000, respectively; the total number of observed and total prevalent cases in the UK was estimated as 165,841 and 327,818 cases, as expected variation existed by disease subtype reflecting the heterogeneity in underlying disease incidence, survival and age distribution of hematological cancers. Conclusions: This study demonstrates the importance of estimating ‘total’ prevalence rather than ‘observed’ prevalence by current disease classification (ICD-O-3), particularly for subtypes that have a more indolent nature and for those that are curable. Importantly, these analyses demonstrate that relying on observed prevalence alone would result in a significant underestimation of the relative burden of some subtypes. While many of these cases may be considered cured and no longer being actively treated, people in this survivorship phase may have long-term medical needs and accordingly, it is important to provide accurate counts to allow for healthcare planning.

International audience; Evidence from a small number of studies suggests that longer telomere length measured in peripheral leukocytes is associated with an increased risk of non-Hodgkin lymphoma (NHL). However, these studies may be biased by reverse causation, confounded by unmeasured environmental exposures and might miss time points for which prospective telomere measurement would best reveal a relationship between telomere length and NHL risk. We performed an analysis of genetically inferred telomere length and NHL risk in a study of 10 102 NHL cases of the four most common B-cell histologic types and 9562 controls using a genetic risk score (GRS) comprising nine telomere length-associated single-nucleotide polymorphisms. This approach uses existing genotype data and estimates telomere length by weighing the number of telomere length-associated variant alleles an individual carries with the published change in kb of telomere length. The analysis of the telomere length GRS resulted in an association between longer telomere length and increased NHL risk [four B-cell histologic types combined; odds ratio (OR) = 1.49, 95% CI 1.22-1.82,P-value = 8.5 x 10(-5)]. Subtype-specific analyses indicated that chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL/SLL) was the principal NHL subtype contributing to this association (OR = 2.60, 95% CI 1.93-3.51,P-value = 4.0 x 10(-10)). Significant interactions were observed across strata of sex for CLL/SLL and marginal zone lymphoma subtypes as well as age for the follicular lymphoma subtype. Our results indicate that a genetic background that favors longer telomere length may increase NHL risk, particularly risk of CLL/SLL, and are consistent with earlier studies relating longer telomere length with increased NHL risk