Dan Painter

Genetic variation in the folate metabolic pathway and risk of childhood leukemia

Studies of childhood leukemia and the potential etiologic role of genetic variation in folate metabolism have produced conflicting findings and have often been based on small numbers. We investigated the association between polymorphisms in key folate metabolism enzymes (MTHFR 677 C>T, MTHFR 1298 A>C, SHMT1 1420 C>T, MTR 2756 A>G, TS 1494del6, and TS 28bp repeat) in 939 cases of childhood acute lymphoblastic leukemia (ALL) and 89 cases of acute myeloid leukemia (AML) recruited into the United Kingdom Childhood Cancer Study. We also examined the maternal genotypes of 752 of these cases. Data from 824 noncancer controls recruited were used for comparison. No evidence of an association with MTHFR 677 was observed for ALL or AML, either in children or their mothers. However, in children an increased risk of ALL (odds ratio [OR] = 1.88; 95% confidence interval [CI], 1.16-3.07; P = .010) and AML (OR = 2.74; 95% CI, 1.07-7.01; P = .036) was observed with the MTR 2756 GG genotype; the association was most pronounced for cases with the MLL translocation (OR = 4.90; 95% CI, 1.30-18.45; P = .019). These data suggest that genetic variation in methionine synthase could mediate risk of childhood leukemia, either via effects on DNA methylation or via effects on fetal growth and development.

Lymphoma incidence, survival and prevalence 2004–2014: sub-type analyses from the UK’s Haematological Malignancy Research Network

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=5796) are from an established patient cohort.Results:Incidence, survival (overall and relative) and prevalence estimates for >20 subtypes are presented. With few exceptions, males tended to be diagnosed at younger ages and have significantly (P<0.05) higher incidence rates. Differences were greatest at younger ages: the <15 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 (P<0.05) 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 ≥5 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.

Determinants of survival in patients with chronic myeloid leukaemia treated in the new era of oral therapy: findings from a UK population-based patient cohort

Objectives To examine contemporary survival patterns in the general population of patients diagnosed with chronic myeloid leukaemia (CML), and to identify patient groups with less than optimal outcomes. Design Prospective population-based cohort. Setting The UKs Haematological Malignancy Research Network (catchment population 3.6 million, with >2000 new haematological malignancies diagnosed annually). Participants All patients newly diagnosed with CML, from September 2004 to August 2011 and followed up to 31 March 2013. Main outcome measure Incidence and survival. Results With a median diagnostic age of 59 years, the CML age standardised (European) incidence was 0.9/100 000 (95% CIs 0.8 to 0.9), 5-year overall survival was 78.9% (72.3 to 84.0) and 5-year relative survival 88.6% (81.0 to 93.3). The efficacy of treatment across all ages was clearly demonstrated; the relative survival curves for those under 60 and over 60 years being closely aligned. Survival findings were similar for men and women, but varied with deprivation; the age and sex adjusted HR being 3.43 (1.89 to 6.22) for deprivation categories 4–5 (less affluent) versus 1–3 (more affluent). None of these differences were attributable to the biological features of the disease. Conclusions When therapy is freely provided, population-based survival for CML is similar to that reported in clinical trials, and age loses its prognostic significance. However, although most of the patients with CML now experience close to normal lifespans, those living in more deprived areas tend to have poorer outcomes, despite receiving the same clinical care. A significant improvement in overall population outcomes could be achieved if these socioeconomic differences, which may reflect the treatment compliance, could be eliminated.

Determining disease prevalence from incidence and survival using simulation techniques

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.

Melanocortin 1 receptor (MC1R), pigmentary characteristics and sun exposure: Findings from a case-control study of diffuse large B-cell and follicular lymphoma

The relationship between skin cancer and non-Hodgkin lymphoma (NHL) suggests common genetic, host or environmental causes. Ultraviolet radiation (UVR), pigmentary characteristics have been linked with both malignancies, and for skin cancer, the melanocortin 1 receptor (MC1R) which influences pigmentation has also been implicated. This paper reports on the relationship between MC1R, skin, hair and eye colour, time spent outdoors, and diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). Persons carrying MC1R homozygote variant alleles at R151C, R160W, D294H and D84E were more likely to have fair skin, red hair and to spend less time outdoors than those who did not. The variant allele at V92M was associated with FL (odds ratio (OR)=1.61, 95% confidence interval (CI) 1.08-2.39) and the r:wild type genotype with DLBCL (OR=0.58, 95% CI 0.38-0.89). Interactions between MC1R genotypes and skin colour influenced DLBCL risk; the RR genotype increased risk in individuals with medium or dark skin, based on 5 cases and no controls, but decreased risk among those of fair skin. On the whole, DLBCL and FL risk were not related to genetic variation in MC1R, pigmentation or time spent outdoors.

The clinical impact of staging bone marrow examination on treatment decisions and prognostic assessment of lymphoma patients

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.

Cohort Profile: The Haematological Malignancy Research Network (HMRN): a UK population-based patient cohort

Cohort Profile: The Haematological Malignancy Research Network (HMRN): a UK populationbased patient cohort Alexandra Smith, Debra Howell, Simon Crouch, Dan Painter, John Blase, Han-I Wang, Ann Hewison, Timothy Bagguley, Simon Appleton, Sally Kinsey, Cathy Burton, Russell Patmore and Eve Roman* Department of Health Sciences, University of York, York, UK, Paediatric Haematology and Oncology Unit, Leeds General Infirmary, St James’s Institute of Oncology, Leeds Teaching Hospitals NHS Trust, Leeds, UK and Queens Centre for Oncology, Castle Hill Hospital, Cottingham, UK

A category-free approach to prognostic modelling in aggressive non-Hodgkin B cell lymphomas based on large patient databases

teristics and outcomes. Results: The low NLR group showed significantly better response rates to induction chemotherapy vs the other one (P = .041). With a median follow‐up of 41.5 months, the high NLR group revealed significantly worse 3‐year overall survival (OS) (42.5 vs 71.2%; P = .031), and 3‐year progression‐free survival (PFS) (37.3 vs 60.1%; P = .028). In univariable Cox analysis, high NLR at diagnosis was a poor prognostic factor for both 3‐year OS (HR, 2.64; 95% CI, 1.06‐6.58; P = .038) and 3‐year PFS (HR, 2.41; 95% CI, 1.07‐5.42; P = .034). However, multivariable analyses adjusting for IELSG score and induction chemotherapy regimen showed no statistical significance albeit high NLRs tendency towards worse 3‐year OS (HR, 2.36; 95% CI, 0.84‐6.62; P = .102) and worse 3‐year PFS (HR, 2.28; 95% CI, 0.93‐5.63; P = .073). Conclusions: In conclusion, given the fact that it is simple and easy to obtain, NLR might play a potential role in prognostication of PCNSL from the very beginning of patient journey.