A case report of septic shock syndrome caused by S. pneumoniae in an immunocompromised patient despite of vaccination.

BACKGROUND AND CASE PRESENTATION: We report a case of septic shock syndrome caused by Streptococcus pneumoniae in a patient who had undergone splenectomy due to an autoimmune lymphoproliferative syndrome (ALPS), which is characterized as a dysfunction of immunoregulation. Although the patient was vaccinated with a conjugated polysaccharide vaccine after the splenectomy, he was still susceptible to S. pneumoniae infection, because the isolated serovar (24F), a serovar long thought to be apathogenic, is not covered by any vaccine currently approved, neither a conjugated nor an unconjugated polysaccharide one. CONCLUSIONS: This case demonstrates that, due to presence of different serovars, also infections with bacteria against which patients are vaccinated have to be considered as differential diagnosis. Although vaccine development has extended the coverage of S. pneumoniae from 7 to 23 serovars within recent years, there is still demand for novel vaccines which can provide broader protection also against so-thought "apathogenic" strains, especially for groups at high risk.

Association Between Decreased Serum Albumin With Risk of Venous Thromboembolism and Mortality in Cancer Patients.

BACKGROUND: In cancer patients, reduced serum albumin has been described as a marker for global declining health and poor prognosis. Our aim was to investigate the association of albumin concentrations with the occurrence of venous thromboembolism (VTE) and mortality in patients with cancer. METHODS: This investigation was performed in the framework of the Vienna Cancer and Thrombosis Study (CATS), a prospective observational cohort study. We included 1,070 patients with active cancer and assayed serum albumin from venous blood taken at study inclusion. Risk for occurrence of VTE was calculated in a proportional subdistribution hazard regression model with respect to competing risk of death and adjusted for cancer site, leukocyte count, estimated glomerular filtration rate, and cholinesterase. RESULTS: Patients (630 males [58.9%] and 440 females [41.1%]) were observed for a median of 723 days. During follow-up, 90 VTE events (8.4%) and 396 deaths (37.0%) occurred. The median albumin was 41.3 g/L (25th-75th percentile, 37.6-44.2). Patients with albumin levels below the 75th percentile had a 2.2-fold increased risk of VTE (95% confidence interval [CI] 1.09-4.32), as well as a 2.3-fold increased risk of death (95% CI 1.68-3.20) compared with patients with albumin above the 75th percentile. CONCLUSION: Decreased serum albumin levels in cancer patients were significantly associated with increased risk of VTE and mortality. Serum albumin, a marker of a cancer patient's overall prognosis, could be considered for risk assessment of important clinical outcomes such as VTE and mortality. IMPLICATIONS FOR PRACTICE: Cancer patients are at increased risk of venous thromboembolism (VTE). In this prospective cohort study of 1,070 cancer patients, decreased serum albumin was a marker for risk of VTE and mortality, independent of kidney or liver function and inflammation markers. The study identified a group of patients with high risk of cancer-associated VTE and a reduced prognosis who may benefit from supportive therapy such as primary VTE prophylaxis.

Dynamic assessment of venous thromboembolism risk in patients with cancer by longitudinal D-Dimer analysis: A prospective study.

BACKGROUND: Venous thromboembolism (VTE) is a frequent complication of cancer. Elevated D-dimer is associated with an increased risk of cancer-associated VTE. Whether changes in D-dimer over time harbor additional prognostic information that may be exploited clinically for dynamic prediction of VTE is unclear. OBJECTIVES: To explore the potential role of longitudinal D-dimer trajectories for personalized prediction of cancer-associated VTE. PATIENTS/METHODS: A total of 167 patients with active malignancy were prospectively enrolled (gastrointestinal: n = 59 [35%], lung: n = 56 [34%], brain: n = 50 [30%], others: n = 2 [1%]; metastatic disease: n = 74 [44%]). D-dimer (median = 0.8 µg/mL [25th-75th percentile: 0.4-2.0]) was measured at baseline and during 602 monthly follow-up visits. Joint models of longitudinal and time-to-event data were implemented to quantify the association between D-dimer trajectories and prospective risk of VTE. RESULTS: VTE occurred in 20 patients (250-day VTE risk = 12.1%, 95% confidence interval [CI], 7.8-18.5). D-dimer increased by 34%/month (0.47 µg/mL/month, 95% CI, 0.22-0.72, P < .0001) in patients who developed VTE, but remained constant in patients who did not develop VTE (change/month = -0.06 µg/mL, 95% CI, -0.15 to 0.02, P = .121). In joint modeling, a doubling of the D-dimer trajectory was associated with a 2.8-fold increase in the risk of VTE (hazard ratio = 2.78, 95% CI, 1.69-4.58, P < .0001). This finding was independent of established VTE risk factors. Highly personalized, dynamic predictions of VTE conditional on individual patients' D-dimer trajectories could be obtained. CONCLUSIONS: D-dimer increases before the onset of cancer-associated VTE, but remains constant over time in patients without VTE. This study represents proof-of-concept that longitudinal trajectories of D-Dimer may advance the personalized assessment of VTE risk in the oncologic setting.

A clinical prediction model for cancer-associated venous thromboembolism: a development and validation study in two independent prospective cohorts.

BACKGROUND: Venous thromboembolism is a common complication of cancer, but the risk of developing venous thromboembolism varies greatly among individuals and depends on numerous factors, including type of cancer. We aimed to develop and externally validate a clinical prediction model for cancer-associated venous thromboembolism. METHODS: We used data from the prospective Vienna Cancer and Thrombosis Study (CATS) cohort (n=1423) to select prognostic variables for inclusion in the model. We then validated the model in the prospective Multinational Cohort Study to Identify Cancer Patients at High Risk of Venous Thromboembolism (MICA) cohort (n=832). We calculated c-indices to show how the predicted incidence of objectively confirmed venous thromboembolism at 6 months compared with the cumulative 6-month incidences observed in both cohorts. FINDINGS: Two variables were selected for inclusion in the final clinical prediction model: tumour-site risk category (low or intermediate vs high vs very high) and continuous D-dimer concentrations. The multivariable subdistribution hazard ratios were 1·96 (95% CI 1·41-2·72; p=0·0001) for high or very high versus low or intermediate and 1·32 (95% CI 1·12-1·56; p=0·001) per doubling of D-dimer concentration. The cross-validated c-indices of the final model were 0·66 (95% CI 0·63-0·67) in CATS and 0·68 (0·62-0·74) in MICA. The clinical prediction model was adequately calibrated in both cohorts. INTERPRETATION: An externally validated clinical prediction model incorporating only one clinical factor (tumour-site category) and one biomarker (D-dimer) predicted the risk of venous thromboembolism in ambulatory patients with solid cancers. This simple model is a considerable improvement on previous models for predicting cancer-associated venous thromboembolism, and could aid physicians in selection of patients who will likely benefit from thromboprophylaxis. FUNDING: Austrian Science Fund, Austrian National Bank Memorial Fund, and participating hospitals.

Hypercoagulabilty, venous thromboembolism, and death in patients with cancer. A Multi-State Model.

Venous thromboembolism (VTE) is a frequent complication of malignancy. The aim of this study was to investigate whether multi-state modelling may be a useful quantitative approach to dissect the complex epidemiological relationship between hypercoagulability, VTE, and death in cancer patients. We implemented a three-state/three-transition unidirectional illness-death model of cancer-associated VTE in data of 1,685 cancer patients included in a prospective cohort study, the Vienna Cancer and Thrombosis Study (CATS). During the two-year follow-up period, 145 (8.6 %) patients developed VTE, 79 (54.5 %) died after developing VTE, and 647 (38.4 %) died without developing VTE, respectively. VTE events during follow-up were associated with a three-fold increase in the risk of death (Transition Hazard ratio (HR)=2.98, 95 % confidence interval [CI]: 2.36-3.77, p< 0.001). This observation was independent of cancer stage. VTE events that occurred later during follow-up exerted a stronger impact on the risk of death than VTE events that occurred at earlier time points (HR for VTE occurrence one year after baseline vs at baseline=2.30, 95 % CI: 1.28-4.15, p=0.005). Elevated baseline D-dimer levels emerged as a VTE-independent risk factor for mortality (HR=1.07, 95 % CI: 1.05-1.08, p< 0.001), and also predicted mortality risk in patients who developed VTE. A higher Khorana Score predicted both the risk for VTE and death, but did not predict mortality after cancer-associated VTE. In conclusion, multi-state modeling represents a very potent approach to time-to-VTE cohort data in the cancer population, and should be used for both observational and interventional studies on cancer-associated VTE.

Association of mean platelet volume with risk of venous thromboembolism and mortality in patients with cancer. Results from the Vienna Cancer and Thrombosis Study (CATS).

Venous thromboembolism (VTE) is a frequent complication in cancer patients. Mean platelet volume (MPV) has been associated with arterial and venous thrombosis in patients without cancer. We analysed MPV in cancer patients and investigated the association of MPV with risk of VTE and mortality. MPV was routinely determined in the Vienna Cancer and Thrombosis Study, a prospective, observational cohort study of patients with newly diagnosed or progressive cancer after remission. Study endpoints were occurrence of symptomatic VTE or death during a maximum follow-up of two years. Out of 1,544 included patients, 114 (7.4%) developed VTE and 573 (37.1%) died during a median observation time of 576 days. High MPV ≥75th percentile of the study population; ≥10.8 fL) was associated with decreased risk of VTE compared to MPV below the 75th percentile (HR [95% CI]: 0.59 [0.37-0.95], p=0.031). In multivariable analysis, including age, sex, cancer groups, newly diagnosed vs recurrent disease, platelet count and soluble P-selectin, this association remained statistically significant (0.65 [0.37-0.98], p=0.041). Mortality of patients with MPV (≥75th percentile was significantly decreased compared to those with lower MPV (0.72 [0.59-0.88], p=0.001). Two-year probability of VTE and overall survival was 5.5% and 64.7% in patients with high MPV compared to 9% and 55.7% in those with lower MPV. In conclusion, high MPV is associated with decreased VTE risk and improved survival in cancer patients. This finding is contrary to results observed in patients without cancer. Further studies are needed to confirm our results and elucidate underlying mechanisms.

Biomarkers predictive of venous thromboembolism in patients with newly diagnosed high-grade gliomas.

BACKGROUND: High-grade gliomas (HGGs) are among the most prothrombotic of malignancies. METHODS: We performed a prospective study to investigate 11 potential biomarkers for prediction of venous thromboembolism (VTE) in newly diagnosed HGG patients who had undergone a neurosurgical intervention. In addition, we tested 2 VTE risk assessment models (RAMs). The strongest predictors of VTE, which were identified by statistical forward selection, were used for the first RAM. The parameters used for the second RAM were both predictive of VTE and available in routine clinical practice. RESULTS: One hundred forty-one HGG patients were included in this study, and 24 (17%) of them developed VTE during follow-up. An association with the risk of future VTE was found for the following parameters: leukocyte count, platelet count, sP-selectin, prothrombin-fragment 1 + 2, FVIII activity, and D-dimer. The first RAM included low platelet count (<25th percentile of the study population) and elevated sP-selectin (≥75th percentile). The cumulative VTE probability after 12 months was 9.7% for score 0 (n = 76), 18.9% for score 1 (n = 59), and 83.3% for score 2 (n = 6). The second RAM included low platelet count (<25th percentile), elevated leukocyte count, and elevated D-dimer (≥75th percentile). The probability of VTE was 3.3% for score 0 (n = 63), 23.0% for score 1 (n = 53), and 37.7% for score 2 (n = 22) or score 3 (n = 3). CONCLUSIONS: We identified biomarkers suitable for assessing the VTE risk in newly diagnosed HGG patients. The application of 2 RAMs allowed identification of patients at high risk of developing VTE. We could also define patients at low risk of VTE, who would most probably not benefit from extended primary thromboprophylaxis.

Red cell distribution width and other red blood cell parameters in patients with cancer: association with risk of venous thromboembolism and mortality.

BACKGROUND: Cancer patients are at high risk of developing venous thromboembolism (VTE). Red cell distribution width (RDW) has been reported to be associated with arterial and venous thrombosis and mortality in several diseases. Here, we analyzed the association between RDW and other red blood cell (RBC) parameters with risk of VTE and mortality in patients with cancer. METHODS: RBC parameters were measured in 1840 patients with cancers of the brain, breast, lung, stomach, colon, pancreas, prostate, kidney; lymphoma, multiple myeloma and other tumor sites, that were included in the Vienna Cancer and Thrombosis Study (CATS), which is an ongoing prospective, observational cohort study of patients with newly diagnosed or progressive cancer after remission. Primary study outcome is occurrence of symptomatic VTE and secondary outcome is death during a maximum follow-up of 2 years. RESULTS: During a median follow-up of 706 days, 131 (7.1%) patients developed VTE and 702 (38.2%) died. High RDW (>16%) was not associated with a higher risk of VTE in the total study cohort; in competing risk analysis accounting for death as competing variable the univariable subhazard ratio (SHR) was 1.34 (95% confidence interval [CI]: 0.80-2.23, p = 0.269). There was also no significant association between other RBC parameters and risk of VTE. High RDW was associated with an increased risk of mortality in the total study population (hazard ratio [HR, 95% CI]: 1.72 [1.39-2.12], p<0.001), and this association prevailed after adjustment for age, sex, hemoglobin, leukocyte and platelet count (HR [95% CI]: 1.34 [1.06-1.70], p = 0.016). CONCLUSIONS: RDW and other RBC parameters were not independently associated with risk of VTE in patients with cancer and might therefore not be of added value for estimating risk of VTE in patients with cancer. We could confirm that high RDW is an independent predictor of poor overall survival in cancer.