Impact of comorbidity on disease characteristics, treatment intent and outcome in diffuse large B-cell lymphoma: a Swedish lymphoma register study.

BACKGROUND: Comorbidity impacts overall survival amongst patients with diffuse large B-cell lymphoma (DLBCL). However, associations of comorbidity with lymphoma characteristics, treatment selection and lymphoma-specific mortality are less well known. OBJECTIVE: To examine the impact of comorbidity on DLBCL characteristics, treatment intent and cause of death. METHODS: We identified 3905 adult patients diagnosed with DLBCL 2007-2013 through the Swedish Lymphoma Register. We assessed comorbid disease history according to the Charlson comorbidity index (CCI). Comorbidity data and causes of death were collected through register linkage. Associations were estimated using multinomial regression and flexible parametric survival models. RESULTS: Overall, 45% of the patients (n = 1737) had a history of at least one comorbidity at DLBCL diagnosis (cardiovascular disease, diabetes and solid cancer were most frequent), and 997 (26%) had a CCI score of ≥2. The relative probability of presenting with poor performance status (PS > 2) was higher amongst comorbid patients [Relative Risk Ratio (RRR)PS>2 : 2.02, 95% CI: 1.63-2.51]. Comorbid patients had a substantially lower relative probability of receiving curative treatment (RRR: 0.48, 95% CI: 0.38-0.61). Amongst all patients, CCI ≥ 1 was associated with a significantly increased risk of all-cause and lymphoma-specific death after adjustments. Amongst patients selected for curative treatment, comorbidity was associated with an increased risk of all-cause death (HRCCI>1 : 1.54, 95% CI: 1.32-1.80), but not with lymphoma-specific death (HRCCI>1 : 1.05, 95% CI: 0.86-1.28). CONCLUSION: Comorbidity is associated with inferior DLBCL outcome, mainly due to a lower likelihood of receiving treatment with curative intent. Possibly, more comorbid DLBCL patients could be treated with curative intent if comorbid conditions were optimized in parallel.

Impact of chemotherapy regimen and rituximab in adult Burkitt lymphoma: a retrospective population-based study from the Nordic Lymphoma Group.

BACKGROUND: Standard treatment of adult Burkitt lymphoma is not defined due to the lack of randomised trials. In this situation, population-based data may represent a useful contribution in order to identify an optimal treatment strategy. PATIENTS AND METHODS: The aims of this study were to investigate the outcome for adult HIV-negative BL with different chemotherapy regimens, and to assess possible improvement within the time frame of the study. The study population was identified through the Swedish and Danish lymphoma registries 2000-2009. RESULTS: A total of 258 patients were identified. Since 2000, overall survival (OS) improved significantly only for younger patients (<65 years). Intensive regimens such as the Berlin-Frankfurt-Münster, hyper-fractionated cyclophosphamide, vincristine, doxorubicin, and dexamethasone (hyper-CVAD) and cyclophosphamide, vincristine, doxorubicin, methotrexate, ifosfamide, etoposide, and cytarabine (CODOX-M/IVAC) were associated with a favourable 2-year OS of 82%, 83%, and 69%, respectively. The low-intensive CHOP/CHOEP regimens achieved a 2-year OS of 38.8%, confirming their inadequacy for the treatment of BL. In a multivariate analysis, rituximab was not significantly associated with improved OS. CONCLUSIONS: In this population-based retrospective series of adult BL, intensive chemotherapy regimens were associated with favourable outcome. The impact of the addition of rituximab remains uncertain and warrants further investigation.

Three-dimensional vessel segmentation using a novel combinatory filter framework.

Blood vessel segmentation is of great importance in medical diagnostic applications. Filter based methods that make use of Hessian matrices have been found to be very useful for blood vessel segmentation in both 2D and 3D medical images. However, these methods often fail on images that contain high density microvessels and background noise. The errors in the form of missing, undesired broken or incorrectly merged vessels eventually lead to poor segmentation results. In this paper, we present a novel method for 3D vessel segmentation that is also suitable for segmenting microvessels, incorporating the advantages of a line filter and a Hessian-based vessel filter to overcome the problems. The proposed method is shown to be reliable for noisy and inhomogeneous images. Vessels can also be separated based on their scale/thickness so that the method can be used for different medical applications. Furthermore, a quantitative vessel analysis method based on the multifractal analysis is performed on the segmented vasculature and fractal properties are found in all images.