Correct definition of the level of risk of invasive fungal infections is the first step in improving the targeting of preventive strategies. We investigated the potential relationship between pre-hospitalization exposure to sources of fungi and the development of invasive fungal infections in adult patients with newly diagnosed acute myeloid leukemia after their first course of chemotherapy. From January 2010 to April 2012, all consecutive acute myeloid leukemia patients in 33 Italian centers were prospectively registered. Upon first admission, information about possible pre-chemotherapy risk factors and environmental exposure was collected. We recorded data regarding comorbid conditions, employment, hygienic habits, working and living environment, personal habits, hobbies, and pets. All invasive fungal infections occurring within 30 days after the first course of chemotherapy were recorded. Of the 1,192 patients enrolled in this study, 881 received intensive chemotherapy and were included in the present analysis. Of these, 214 developed an invasive fungal infection, including 77 proven/probable cases (8.7%). Of these 77 cases, 54 were proven/probable invasive mold infections (6.1%) and 23 were proven yeast infections (2.6%). Upon univariate analysis, a significant association was found between invasive mold infections and age, performance status, diabetes, chronic obstructive pulmonary disease, smoking, cocaine use, job, hobbies, and a recent house renovation. Higher body weight resulted in a reduced risk of invasive mold infections. Multivariate analysis confirmed the role of performance status, job, body weight, chronic obstructive pulmonary disease, and house renovation. In conclusion, several hospital-independent variables could potentially influence the onset of invasive mold infections in patients with acute myeloid leukemia. Investigation of these factors upon first admission may help to define a patient's risk category and improve targeted prophylactic strategies. (Clinicaltrial.gov: NCT01315925) Pre-chemotherapy risk factors for invasive fungal diseases: prospective analysis of 1,192 patients with newly diagnosed acute myeloid leukemia (SEIFEM

PURPOSE High levels of circulating tumor plasma cells (CTC-high) in patients with multiple myeloma are a marker of aggressive disease. We aimed to confirm the prognostic impact and identify a possible cutoff value of CTC-high for the prediction of progression-free survival (PFS) and overall survival (OS), in the context of concomitant risk features and minimal residual disease (MRD) achievement. METHODS CTC were analyzed at diagnosis with two-tube single-platform flow cytometry (sensitivity 4 × 10–5) in patients enrolled in the multicenter randomized FORTE clinical trial (ClinicalTrials.gov identifier: NCT02203643 ). MRD was assessed by second-generation multiparameter flow cytometry (sensitivity 10–5). We tested different cutoff values in series of multivariate (MV) Cox proportional hazards regression analyses on PFS outcome and selected the value that maximized the Harrell's C-statistic. We analyzed the impact of CTC on PFS and OS in a MV analysis including baseline features and MRD negativity. RESULTS CTC analysis was performed in 401 patients; the median follow-up was 50 months (interquartile range, 45-54 months). There was a modest correlation between the percentage of CTC and bone marrow plasma cells ( r = 0.38). We identified an optimal CTC cutoff of 0.07% (approximately 5 cells/µL, C-index 0.64). In MV analysis, CTC-high versus CTC-low patients had significantly shorter PFS (hazard ratio, 2.61; 95% CI, 1.49 to 2.97, P < .001; 4-year PFS 38% v 69%) and OS (hazard ratio, 2.61; 95% CI, 1.49 to 4.56; P < .001; 4-year OS 68% v 92%). The CTC levels, but not the bone marrow plasma cell levels, affected the outcome. The only factor that reduced the negative impact of CTC-high was the achievement of MRD negativity (interaction P = .039). CONCLUSION In multiple myeloma, increasing levels of CTC above an optimal cutoff represent an easy-to-assess, robust, and independent high-risk factor. The achievement of MRD negativity is the most important factor that modulates their negative prognostic impact.

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Background Gender-related factors might affect vulnerability to Covid-19. The aim of this study was to describe the role of gender on clinical features and 28-day mortality in Covid-19 patients. Methods Observational study of Covid-19 patients hospitalized in Bergamo, Italy, during the first three weeks of the outbreak. Medical records, clinical, radiological and laboratory findings upon admission and treatment have been collected. Primary outcome was 28-day mortality since hospitalization. Results 431 consecutive adult patients were admitted. Female patients were 119 (27.6%) with a mean age of 67.0 ± 14.5 years (vs 67.8 ± 12.5 for males, p = 0.54). Previous history of myocardial infarction, vasculopathy and former smoking habits were more common for males. At the time of admission PaO2/FiO2 was similar between men and women (228 [IQR, 134–273] vs 238 mmHg [150–281], p = 0.28). Continuous Positive Airway Pressure (CPAP) assistance was needed in the first 24 h more frequently in male patients (25.7% vs 13.0%; p = 0.006). Overall 28-day mortality was 26.1% in women and 38.1% in men (p = 0.018). Gender did not result an independent predictor of death once the parameters related to disease severity at presentation were included in the multivariable analysis (p = 0.898). Accordingly, the Kaplan–Meier survival analysis in female and male patients requiring CPAP or non-invasive ventilation in the first 24 h did not find a significant difference (p = 0.687). Conclusion Hospitalized women are less likely to die from Covid-19; however, once severe disease occurs, the risk of dying is similar to men. Further studies are needed to better investigate the role of gender in clinical course and outcome of Covid-19.

Backgrounds Validated tools for predicting individual in-hospital mortality of COVID-19 are lacking. We aimed to develop and to validate a simple clinical prediction rule for early identification of in-hospital mortality of patients with COVID-19. Methods and findings We enrolled 2191 consecutive hospitalized patients with COVID-19 from three Italian dedicated units (derivation cohort: 1810 consecutive patients from Bergamo and Pavia units; validation cohort: 381 consecutive patients from Rome unit). The outcome was in-hospital mortality. Fine and Gray competing risks multivariate model (with discharge as a competing event) was used to develop a prediction rule for in-hospital mortality. Discrimination and calibration were assessed by the area under the receiver operating characteristic curve (AUC) and by Brier score in both the derivation and validation cohorts. Seven variables were independent risk factors for in-hospital mortality: age (Hazard Ratio [HR] 1.08, 95% Confidence Interval [CI] 1.07–1.09), male sex (HR 1.62, 95%CI 1.30–2.00), duration of symptoms before hospital admission <10 days (HR 1.72, 95%CI 1.39–2.12), diabetes (HR 1.21, 95%CI 1.02–1.45), coronary heart disease (HR 1.40 95% CI 1.09–1.80), chronic liver disease (HR 1.78, 95%CI 1.16–2.72), and lactate dehydrogenase levels at admission (HR 1.0003, 95%CI 1.0002–1.0005). The AUC was 0.822 (95%CI 0.722–0.922) in the derivation cohort and 0.820 (95%CI 0.724–0.920) in the validation cohort with good calibration. The prediction rule is freely available as a web-app (COVID-CALC: https://sites.google.com/community.unipa.it/covid-19riskpredictions/c19-rp). Conclusions A validated simple clinical prediction rule can promptly and accurately assess the risk for in-hospital mortality, improving triage and the management of patients with COVID-19.