Autoimmune hemolytic anemia (AIHA) is an acquired, heterogeneous group of diseases which includes warm AIHA, cold agglutinin disease (CAD), mixed AIHA, paroxysmal cold hemoglobinuria and atypical AIHA. Currently CAD is defined as a chronic, clonal lymphoproliferative disorder, while the presence of cold agglutinins underlying other diseases is known as cold agglutinin syndrome. AIHA is mediated by autoantibodies directed against red blood cells (RBCs) causing premature erythrocyte destruction. The pathogenesis of AIHA is complex and still not fully understood. Recent studies indicate the involvement of T and B cell dysregulation, reduced CD4+ and CD25+ Tregs, increased clonal expansions of CD8 + T cells, imbalance of Th17/Tregs and Tfh/Tfr, and impaired lymphocyte apoptosis. Changes in some RBC membrane structures, under the influence of mechanical stimuli or oxidative stress, may promote autohemolysis. The clinical presentation and treatment of AIHA are influenced by many factors, including the type of AIHA, degree of hemolysis, underlying diseases, presence of concomitant comorbidities, bone marrow compensatory abilities and the presence of fibrosis and dyserthropoiesis. The main treatment for AIHA is based on the inhibition of autoantibody production by mono- or combination therapy using GKS and/or rituximab and, rarely, immunosuppressive drugs or immunomodulators. Reduction of erythrocyte destruction via splenectomy is currently the third line of treatment for warm AIHA. Supportive treatment including vitamin supplementation, recombinant erythropoietin, thrombosis prophylaxis and the prevention and treatment of infections is essential. New groups of drugs that inhibit immune responses at various levels are being developed intensively, including inhibition of antibody-mediated RBCs phagocytosis, inhibition of B cell and plasma cell frequency and activity, inhibition of IgG recycling, immunomodulation of T lymphocytes function, and complement cascade inhibition. Recent studies have brought about changes in classification and progress in understanding the pathogenesis and treatment of AIHA, although there are still many issues to be resolved, particularly concerning the impact of age-associated changes to immunity.

The aim of the study was to investigate the prognostic significance of selected risk assessment models (RAMs) for predicting venous thromboembolism (VTE) events in patients undergoing outpatient chemotherapy for lung cancer. We evaluated the following VTE-risk assessment tools: Khorana risk score (KRS), PROTECHT score, CONKO score and COMPASS-cancer-associated thrombosis score (COMPASS-CAT). Retrospective analyses were performed on 118 patients with lung cancer, 20 of whom developed VTE with a median of 2.5 months from diagnosis. Patients receiving gemcitabine-based regimen (25%), patients with a history of atrial fibrillation (AF) and patients with chronic kidney disease developed VTE more often than other patients. In the multivariate analysis, high COMPASS-CAT score (OR 8.73; 95% CI 1.01–75.22, P = 0.049), gemcitabine chemotherapy (OR 3.37; 95% CI 1.09–10.39, P = 0.035) and AF (OR 7.19; 95% CI 1.89–27.33, P = 0.004) were all significantly associated with VTE development. VTE occurred in; 13% (n = 2) of the KRS high-risk group, 17.7% (n = 11) of the PROTECHT high-risk group, 15% (n = 4) of the CONKO high-risk group and 23.8% (n = 20) of the COMPASS-CAT high-risk group (n = 84). Only the COMPASS-CAT score was able to identify 100% of patients who developed VTE, and best discriminated between patients with high and low risk of VTE development (C statistic 0.89). The ROC analysis indicated a cutoff value of 11 points (95% CI 0.821–0.962) for COMPASS-CAT for VTE development in patients with lung cancer. In conclusion, in our study of all the VTE–RAMs analyzed, the COMPASS-CAT model was the most accurate predictor of VTE development in patients with lung cancer.

It has been suggested that mean platelet volume (MPV) is associated with the risk of venous thromboembolism (VTE) and increased mortality in patients with cancer. We evaluated the association of MPV with VTE and mortality in patients treated for diffuse large B-cell lymphoma (DLBCL). Retrospective analyses were performed on 184 adult patients (median age 59, 55% men), of whom 141 were newly diagnosed, and 43 had relapse/refractory DLBCL. During the observation period (median 499 days), 39 (21.2%) patients developed VTE. Thirty-nine patients died of various causes. In univariate analysis, only the MPV and the treatment line were associated with the occurrence of VTE. In multivariate analysis, MPV ≤10th percentile (odd ratio 1.81; 95% confidence interval 1.06-3.11, p = 0.03) and salvage therapy (odd ratio 2.46; 95% confidence interval 1.66-3.65, p < 0.001) remained significant factors for developing VTE. Other patient-related factors-age, gender, disease-related factors-stage, the International Prognostic Index score, DLBCL subclassification (the germinal centre type and the activated B-cell type), Ki-67 index and VTE risk assessment model failed to be prognostic for VTE. In a Kaplan-Meier analysis, patients with MPV >10th percentile had statistically significantly longer VTE-free survival than patients with lower MPV. In multivariable Cox regression analysis, MPV ≤10th percentile (hazard ratio 5.56, p < 0.001), male gender, age, Ki-67 index, high or high-intermediate International Prognostic Index and VTE development (hazard ratio 7.81, p = 0.029) all significantly correlated with the risk of mortality. The probability of survival was higher in patients with MPV >10th percentile. In conclusion, our results suggest that the pre-chemotherapy MPV value is a cheap and available parameter that may be a useful prognostic marker for a significant risk of VTE and inferior survival rates in patients with DLBCL.

The utility of the venous thromboembolism (VTE) risk assessment model known as the Khorana Risk Score (KRS) in patients with lymphoid malignancies receiving outpatient chemotherapy is not defined. We evaluated the association of the KRS with VTE in patients treated for diffuse large B cell lymphoma (DLBCL) or Hodgkin lymphoma (HL). Retrospective analyses were performed in 428 patients, 241 of whom were newly diagnosed with DLBCL and 187 of whom had HL. During the initial therapy, 64 (15%) patients developed VTE and 56 died during follow-up. More VTE events occurred in patients with DLBCL than in patients with HL. According to the KRS, 364 (85%) and 64 (15%) patients were considered to be at intermediate risk and high risk of VTE development, respectively. The high-risk KRS patients were more often diagnosed with HL than DLBCL (19 vs. 10%, P = 0.0143). The KRS did not discriminate between high- and intermediate-risk patients with respect to VTE occurrence (17 vs. 15%, P = 0.5868). In our patients, the KRS did not adequately predict VTE (positive predictive value 15%, negative predictive value 82% and C statistic 0.51). In the multivariate analysis, bulky disease (OR 2.34; 95% CI 1.62–3.36, P < 0.0001), poor prognostic disease (OR 1.32; 95% CI 1.01–1.74, P = 0.049) and DLBCL histological subtype (OR 1.61; 95% CI 1.17–2.19, P = 0.003) were all significantly associated with the VTE development. In this cohort of patients with lymphoid malignancies, the KRS did not adequately stratify or predict VTE events in patients at a higher risk of VTE. This finding suggests the need for the development of a disease-specific VTE assessment model.

Anemia represents a common condition among the elderly; however, its prevalence and causes are not well known. This retrospective analysis was performed on 981 patients aged ≥ 60 in Poland over 2013–2014. The prevalence of anemia was 17.2% and increased with age. The predominant causes of anemia were the following: anemia of chronic disease (33.1%), unexplained anemia (28.4%), deficiency anemia (22.5%, including iron deficiency 13%), and chemo-/radiotherapy-induced anemia (8.9%). In the multivariate logistic regression model, factors increasing the risk of anemia were the following: age ≥ 80 years (OR 2.29; 95%CI 1.19–4.42; P = 0.013), the number of comorbidities (two diseases OR 2.85; 95%CI 1.12–7.30; P = 0.029, three diseases OR 6.28; 95%CI 2.22–17.76; P = 0.001, four diseases OR 4.64; 95%CI 1.27–17.01; P = 0.021), and hospitalizations (OR 1.34; 95%CI 1.13–1.58; P = 0.001). After a 2-year follow-up, the cumulative survival among patients without anemia in relation to the group with anemia was 90.76 vs. 78.08% (P < 0.001). In the multivariate model, anemia (HR 3.33, 95%CI 1.43–7.74, P = 0.005), heart failure (HR 2.94, 95%CI 1.33–6.50, P = 0.008), and cancer (HR 3.31, 95%CI 1.47–7.49, P < 0.004) were all significantly correlated with mortality. In patients ≥ 60 years, the incidence of anemia increases with age, number of comorbidities, and frequency of hospitalizations and has an adverse impact on survival.

The utility in clinical practice of a recently developed and validated predictive model for venous thromboembolism (VTE) events in lymphoma patients, known as the thrombosis lymphoma (ThroLy) score, is unknown. We evaluated the association of ThroLy with VTE in patients treated for diffuse large B‐cell lymphoma (DLBCL) or Hodgkin lymphoma (HL) undergoing ambulatory first‐line chemotherapy. Retrospective analyses were performed on 428 patients (median age 50), 241 were newly diagnosed DLBCL, and 187 had HL. During initial chemotherapy, 64 (15%) patients developed VTE. According to the ThroLy, 322 (75.2%) patients were considered low risk, 88 (20.6%) patients had intermediate risk and 18 (4.2%) patients high risk for VTE development. Patients with DLBCL were more often in the high‐risk ThroLy group and had more VTE events than HL. VTE occurred in; 38.9% (n = 7) high‐risk patients, 29.5% (n = 26) intermediate risk, and 9.6% (n = 31) low risk according to the ThroLy score. However, in multivariate analysis, high ThroLy (OR 5.13; 95% CI: 1.83‐14.36, P = .002), intermediate ThroLy (OR 3.96; 95% CI: 2.19‐7.17, P < .001), and aggressive lymphoma‐DLBCL (OR 1.91; 95% CI: 1.05‐3.47, P = .034) were all significantly associated with development of VTE, 48% of the VTE events occurred in the low‐risk ThroLy score group (the ROC AUC (95% CI) 0.40‐0.70 and C statistic‐0.55). In our study, the ThroLy score was not a suitably accurate model for predicting VTE events in patients at higher risk of VTE. Further research should be conducted to identify new biomarkers that will predict these events and to establish a new VTE risk assessment model.

Introduction: We aimed to analyze the prevalence of unexplained anemia (UA) and assess its characteristics, potential causes and impact on survival in an elderly population. Material and methods: Medical files of 981 patients aged ≥ 60 years consulted in one primary medical clinic in Poland in 2013-2014 were retrospectively analyzed. Anemia, defined according to WHO criteria, diagnosed during either hospitalization or outpatient treatment, from the age of 60, was included. Unexplained anemia was diagnosed if, based on available clinical data and laboratory tests and other assessments in medical records, none of the well-known types of anemia were identified. Results: Of 981 patients with anemia, UA was found in 48 (28.4%) patients (4.9% of those studied) and incidence increased with age (≥ 80 years, 12.3%). In 81.3% no full hematological diagnostics were performed. Patients with UA, as with those with defined anemia, when compared to the group without anemia were older, had more co-morbidities, were more frequently hospitalized, more frequently had dementia syndrome and obtained lower Barthel scores (p < 0.0001). In the groups of patients with UA and defined anemia, there were more deaths than in those without anemia (10% vs. 13% vs. 2%, p < 0.0001) with significant differences in survival rates observed during 3-year follow-up. Conclusions: The increasing incidence with age of UA in the elderly population, insufficient diagnosis and the higher mortality of patients with UA in comparison to the group without anemia indicate the need to develop recommendations for its management by primary care physicians.

Mean platelet volume (MPV) is reported to be associated with the risk of venous thromboembolism (VTE) and mortality in patients with cancer.We sought to determine the association of MPV with symptomatic VTE occurrence in patients treated for newly diagnosed Hodgkin lymphoma (HL) and their outcomes. We retrospectively studied 167 consecutive adult patients treated with HL. During first-line treatment 12 (7.2%) patients developed VTE and 14 (8%) died within the observation period. The pre-chemotherapy values of MPV were significantly lower in VTE patients than those without (p=0.0343). Patients with MPV≤25th percentile (6.8 fl) had an increased risk of VTE occurrence (p=0.0244). In multivariate analysis, MPV≤25th percentile (OR 2.21; 95%CI 1.07-4.57, p=0.033), advanced stage (OR 2.08; 95%CI 1.06-4.07, p=0.033) and bulky disease (OR 2.23; 95%CI 1.16-4.31, p=0.016) were significant factors for developing VTE. Only the impact of MPV≤25th percentile on VTE-free survival rates was found. VTE occurred in 43% (n=3) of the high-risk patients of the Thrombosis Lymphoma (ThroLy) score and in 17% (n=2) of the high-risk of the Khorana Risk Score (KRS). Neither the KRS nor the ThroLy score could identify patients at a high risk of VTE with a high degree of accuracy. We expanded the ThroLy score with the addition of the MPV≤25th percentile to more accurately identify HL patients with a higher risk of VTE.Our study indicates that the pre-chemotherapy MPV value, while of no use as an overall prognosis predictor, may still represent a useful prognostic marker for a significant VTE risk especially when incorporated into VTE-risk assessment models.