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.

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.

Increased mean platelet volume (MPV) is associated with platelet reactivity and is a predictor of cardiovascular risk and unprovoked venous thromboembolism. The aim of our study was to evaluate MPV in patients with confirmed antiphospholipid antibody syndrome (APS) and to identify the correlation between the value of MPV and the recurrence of thrombosis. The studied group consists of 247 patients with a history of thrombosis and/or pregnancy loss (median age 38, range 18–66 years) classified as APS group (n = 70) or APS negative patients (n = 177) according to the updated Sapporo criteria. The control group consisted of 98 healthy subjects. MPV was significantly higher in the group of patients with clinically and laboratory confirmed APS (median 7.85, range 4.73–12.2 fl) in comparison with the controls. It was also higher than in APS negative patients (7.61, range 5.21–12.3 fl). APS patients with triple positivity for antiphospholipid antibodies with respect to Miyakis classification categories had higher MPV values than other APS patients (9.69 ± 1.85 vs. 7.29 ± 1.3 fl, p = 0.001). Recurrent thrombotic episodes were observed in 83 patients, but among the triple positive high-risk patients with APS in 80 % cases (p = 0.0046). In receiver operating characteristic curve analysis, the value of MPV level for thrombosis recurrence prediction in the APS group with sensitivity of 86 % and specificity of 82 % was 7.4 fl. In the multivariate logistic regression model, MPV above 7.4 fl (OR 3.65; 95 % CI 1.38–9.64, p = 0.009) significantly predicts thrombosis recurrence. Our results identify the value of MPV as a prognostic factor of thrombosis recurrence in patients with APS.