Efficacy of minimal residual disease driven immune-intervention after allogeneic hematopoietic stem cell transplantation for high-risk chronic lymphocytic leukemia: results of a prospective multicenter trial

Allogeneic hematopoietic stem cell transplantation (HSCT) remains a potentially curative and useful strategy in high-risk relapsing CLL. Minimal Residual Disease (MRD) assessment at 12 months post-HSCT is predictive of relapse. This phase 2 study aimed to achieve M12 MRD negativity (MRDneg) using MRD-driven immune-intervention (Md-PII) algorithm based on serial flow-cytometry blood MRD, involving cyclosporine tapering followed if failure by donor lymphocytes infusions. Patients had high-risk CLL according to 2006 EBMT consensus, in complete or partial response with lymphadenopathy &lt; 5 cm and comorbidity score ≤ 2. Donors were HLA-matched sibling or matched unrelated (10/10). Forty-two enrolled patients with either 17p deletion (front-line, n=11; relapse n=16) or other high-risk relapse (n=15) received reduced intensity-conditioning regimen before HSCT and were submitted to Md-PII. M12-MRDneg status was achieved in 64% versus 14.2% before HSCT. With a median follow-up of 36 months (range, 19-53), 3-year overall survival, non-relapse mortality and cumulative incidence of relapse are 86.9% (95%CI, 70.8-94.4), 9.5% (95%CI, 3.7-23.4) and 29.6% (95%CI, 17.3-47.7). Incidence of 2-year limited and extensive chronic graft versus host disease (cGVHD) is 38% (95%CI, 23-53) and 23% (95%CI, 10-36) including 2 cases post Md-PII. Fifteen patients converted to MRDneg either after CsA withdrawal (n=12) or after cGVHD (n=3). As a time-dependent variable, MRDneg achievement at any time-point correlates with reduced relapse (HR=0.14 [0.04-0.53], p=0.004) and improvement of both progression free (HR=0.18 [0.06-0.6], p&lt;0.005) and overall (HR: 0.18 [0.03-0.98], p=0.047) survival. These data highlight the value of MRD-driven immune-intervention to induce prompt MRD clearance in the therapy of CLL.</jats:p

Dissertatio historica de initiis monarchiae Babyloniorum, quam, cum cons. ampliss. Colleg. Philos. in Reg. Acad. Upsal. sub praesidio ... Jacobi Arrhenii ... publico examini modeste subjicit Petrus Hagberg Gestr. In audit. Gustav. maj. ad d. 25. Maji. Anni MDCCV.

International audienceBackground : The incidence of childhood type 1 diabetes (T1D) incidence is rising in many countries, supposedlybecause of changing environmental factors, which are yet largely unknown. The purpose of the study was tounravel environmental markers associated with T1D. Methods : Cases were children with T1D from the French Isis-Diab cohort. Controls were schoolmates or friends ofthe patients. Parents were asked to fill a 845-item questionnaire investigating the child’s environment before diagnosis.The analysis took into account the matching between cases and controls. A second analysis used propensity scoremethods. Results : We found a negative association of several lifestyle variables, gastroenteritis episodes, dental hygiene, hazelnutcocoa spread consumption, wasp and bee stings with T1D, consumption of vegetables from a farm and death of a petby old age. Conclusions : The found statistical association of new environmental markers with T1D calls for replication in othercohorts and investigation of new environmental areas

The association between macrovascular complications and intensive care admission, invasive mechanical ventilation, and mortality in people with diabetes hospitalized for coronavirus disease-2019 (COVID-19)

International audienceAbstract Background It is not clear whether pre-existing macrovascular complications (ischemic heart disease, stroke or peripheral artery disease) are associated with health outcomes in people with diabetes mellitus hospitalized for COVID-19. Methods We conducted cohort studies of adults with pre-existing diabetes hospitalized for COVID-19 infection in the UK, France, and Spain during the early phase of the pandemic (between March 2020—October 2020). Logistic regression models adjusted for demographic factors and other comorbidities were used to determine associations between previous macrovascular disease and relevant clinical outcomes: mortality, intensive care unit (ICU) admission and use of invasive mechanical ventilation (IMV) during the hospitalization. Output from individual logistic regression models for each cohort was combined in a meta-analysis. Results Complete data were available for 4,106 (60.4%) individuals. Of these, 1,652 (40.2%) had any prior macrovascular disease of whom 28.5% of patients died. Mortality was higher for people with compared to those without previous macrovascular disease (37.7% vs 22.4%). The combined crude odds ratio (OR) for previous macrovascular disease and mortality for all four cohorts was 2.12 (95% CI 1.83–2.45 with an I 2 of 60%, reduced after adjustments for age, sex, type of diabetes, hypertension, microvascular disease, ethnicity, and BMI to adjusted OR 1.53 [95% CI 1.29–1.81]) for the three cohorts. Further analysis revealed that ischemic heart disease and cerebrovascular disease were the main contributors of adverse outcomes. However, proportions of people admitted to ICU (adjOR 0.48 [95% CI 0.31–0.75], I 2 60%) and the use of IMV during hospitalization (adjOR 0.52 [95% CI 0.40–0.68], I 2 37%) were significantly lower for people with previous macrovascular disease. Conclusions This large multinational study of people with diabetes mellitus hospitalized for COVID-19 demonstrates that previous macrovascular disease is associated with higher mortality and lower proportions admitted to ICU and treated with IMV during hospitalization suggesting selective admission criteria. Our findings highlight the importance correctly assess the prognosis and intensive monitoring in this high-risk group of patients and emphasize the need to design specific public health programs aimed to prevent SARS-CoV-2 infection in this subgroup

Benefits and risks of noninvasive oxygenation strategy in COVID-19: a multicenter, prospective cohort study (COVID-ICU) in 137 hospitals

Abstract Rational To evaluate the respective impact of standard oxygen, high-flow nasal cannula (HFNC) and noninvasive ventilation (NIV) on oxygenation failure rate and mortality in COVID-19 patients admitted to intensive care units (ICUs). Methods Multicenter, prospective cohort study (COVID-ICU) in 137 hospitals in France, Belgium, and Switzerland. Demographic, clinical, respiratory support, oxygenation failure, and survival data were collected. Oxygenation failure was defined as either intubation or death in the ICU without intubation. Variables independently associated with oxygenation failure and Day-90 mortality were assessed using multivariate logistic regression. Results From February 25 to May 4, 2020, 4754 patients were admitted in ICU. Of these, 1491 patients were not intubated on the day of ICU admission and received standard oxygen therapy (51%), HFNC (38%), or NIV (11%) (P &lt; 0.001). Oxygenation failure occurred in 739 (50%) patients (678 intubation and 61 death). For standard oxygen, HFNC, and NIV, oxygenation failure rate was 49%, 48%, and 60% (P &lt; 0.001). By multivariate analysis, HFNC (odds ratio [OR] 0.60, 95% confidence interval [CI] 0.36–0.99, P = 0.013) but not NIV (OR 1.57, 95% CI 0.78–3.21) was associated with a reduction in oxygenation failure). Overall 90-day mortality was 21%. By multivariable analysis, HFNC was not associated with a change in mortality (OR 0.90, 95% CI 0.61–1.33), while NIV was associated with increased mortality (OR 2.75, 95% CI 1.79–4.21, P &lt; 0.001). Conclusion In patients with COVID-19, HFNC was associated with a reduction in oxygenation failure without improvement in 90-day mortality, whereas NIV was associated with a higher mortality in these patients. Randomized controlled trials are needed. </jats:sec

Predicting 90-day survival of patients with COVID-19: Survival of Severely Ill COVID (SOSIC) scores

Abstract Background Predicting outcomes of critically ill intensive care unit (ICU) patients with coronavirus-19 disease (COVID-19) is a major challenge to avoid futile, and prolonged ICU stays. Methods The objective was to develop predictive survival models for patients with COVID-19 after 1-to-2 weeks in ICU. Based on the COVID–ICU cohort, which prospectively collected characteristics, management, and outcomes of critically ill patients with COVID-19. Machine learning was used to develop dynamic, clinically useful models able to predict 90-day mortality using ICU data collected on day (D) 1, D7 or D14. Results Survival of Severely Ill COVID (SOSIC)-1, SOSIC-7, and SOSIC-14 scores were constructed with 4244, 2877, and 1349 patients, respectively, randomly assigned to development or test datasets. The three models selected 15 ICU-entry variables recorded on D1, D7, or D14. Cardiovascular, renal, and pulmonary functions on prediction D7 or D14 were among the most heavily weighted inputs for both models. For the test dataset, SOSIC-7’s area under the ROC curve was slightly higher (0.80 [0.74–0.86]) than those for SOSIC-1 (0.76 [0.71–0.81]) and SOSIC-14 (0.76 [0.68–0.83]). Similarly, SOSIC-1 and SOSIC-7 had excellent calibration curves, with similar Brier scores for the three models. Conclusion The SOSIC scores showed that entering 15 to 27 baseline and dynamic clinical parameters into an automatable XGBoost algorithm can potentially accurately predict the likely 90-day mortality post-ICU admission (sosic.shinyapps.io/shiny). Although external SOSIC-score validation is still needed, it is an additional tool to strengthen decisions about life-sustaining treatments and informing family members of likely prognosis. </jats:sec