Ruxolitinib in refractory acute and chronic graft-versus-host disease: a multicenter survey study.

Graft-versus-host disease is the main cause of morbidity and mortality after allogeneic hematopoietic stem cell transplantation. First-line treatment is based on the use of high doses of corticosteroids. Unfortunately, second-line treatment for both acute and chronic graft-versus-host disease, remains a challenge. Ruxolitinib has been shown as an effective and safe treatment option for these patients. Seventy-nine patients received ruxolitinib and were evaluated in this retrospective and multicenter study. Twenty-three patients received ruxolitinib for refractory acute graft-versus-host disease after a median of 3 (range 1-5) previous lines of therapy. Overall response rate was 69.5% (16/23) which was obtained after a median of 2 weeks of treatment, and 21.7% (5/23) reached complete remission. Fifty-six patients were evaluated for refractory chronic graft-versus-host disease. The median number of previous lines of therapy was 3 (range 1-10). Overall response rate was 57.1% (32/56) with 3.5% (2/56) obtaining complete remission after a median of 4 weeks. Tapering of corticosteroids was possible in both acute (17/23, 73%) and chronic graft-versus-host disease (32/56, 57.1%) groups. Overall survival was 47% (CI: 23-67%) at 6 months for patients with aGVHD (62 vs 28% in responders vs non-responders) and 81% (CI: 63-89%) at 1 year for patients with cGVHD (83 vs 76% in responders vs non-responders). Ruxolitinib in the real life setting is an effective and safe treatment option for GVHD, with an ORR of 69.5% and 57.1% for refractory acute and chronic graft-versus-host disease, respectively, in heavily pretreated patients.

Pre-engraftment cytomegalovirus DNAemia in allogeneic hematopoietic stem cell transplant recipients: incidence, risk factors, and clinical outcomes.

To gauge the risk of delaying initiation of prophylaxis with letermovir from the time of donor infusion to prevent CMV infection in allo-HSCT recipients we investigated the clinical outcomes of CMV DNAemia episodes occurring before engraftment, and compared to that of episodes developing after engraftment (up to day +365). A total of 197 consecutive adult patients were included. Plasma CMV DNA load was monitored by real-time PCR assays [limit of detection: 31 IU/ml]. A total of 150 out of 197 patients had CMV DNAemia (cumulative incidence of 77%; 95% CI, 73-81%), and 38 out of the 197 patients developed it before engraftment (cumulative incidence, 19%; 95% CI, 10-30.3%). Nine episodes of CMV DNAemia were detected prior to the time of donor progenitor cell infusion. A greater number of post-engraftment episodes required preemptive antiviral therapy compared with pre-engraftment episodes (62.5% vs 44.7%; P = 0.05). The cellular content of the donor progenitor cell infusion and transplant characteristics of patients did not differ between patients with pre-engraftment or post-engraftment CMV DNAemia. The cumulative incidence of overall mortality by days 100 and 365, aGvHD by day 100 and relapse by day 365 were not significantly different between patients with pre-engraftment or post-engraftment CMV DNAemia.

A classification of user-generated content into consumer decision journey stages.

In the last decades, the availability of digital user-generated documents from social media has dramatically increased. This massive growth of user-generated content has also affected traditional shopping behaviour. Customers have embraced new communication channels such as microblogs and social networks that enable them not only just to talk with friends and acquaintances about their shopping experience, but also to search for opinions expressed by complete strangers as part of their decision making processes. Uncovering how customers feel about specific products or brands and detecting purchase habits and preferences has traditionally been a costly and highly time-consuming task which involved the use of methods such as focus groups and surveys. However, the new scenario calls for a deep assessment of current market research techniques in order to better interpret and profit from this ever-growing stream of attitudinal data. With this purpose, we present a novel analysis and classification of user-generated content in terms of it belonging to one of the four stages of the Consumer Decision Journey Court et al. (2009) (i.e. the purchase process from the moment when a customer is aware of the existence of the product to the moment when he or she buys, experiences and talks about it). Using a corpus of short texts written in English and Spanish and extracted from different social media, we identify a set of linguistic patterns for each purchase stage that will be then used in a rule-based classifier. Additionally, we use machine learning algorithms to automatically identify business indicators such as the Marketing Mix elements McCarthy and Brogowicz (1981). The classification of the purchase stages achieves an average precision of 74%. The proposed classification of texts depending on the Marketing Mix elements expressed achieved an average precision of 75% for all the elements analysed.