917 research outputs found
First-line treatment for chronic myeloid leukemia: dasatinib, nilotinib, or imatinib
Imatinib, a tyrosine kinase inhibitor (TKI) of BCR-ABL, was the standard first-line therapy for chronic myeloid leukemia (CML) for almost 10 years. Dasatinib and nilotinib, two newer drugs with higher potency than imatinib against BCR-ABL and activity against most imatinib-resistant BCR-ABL mutations, have each shown superior efficacy compared with imatinib for first-line treatment of chronic-phase CML in randomized phase 3 trials. With 14 months follow-up time, available data suggest no obvious differences in efficacy between dasatinib and nilotinib. Compared with imatinib, dasatinib is associated with higher rates of pleural effusion and thrombocytopenia, but lower rates of edema, gastrointestinal AEs, musculoskeletal AEs, and rash. Nilotinib is associated with higher rates of dermatologic toxicity, headache, and biochemical abnormalities associated with hepatic and pancreatic toxicity compared with imatinib, but lower rates of edema, gastrointestinal AEs, muscle spasm, and neutropenia. Several studies have shown that poor adherence to imatinib detrimentally affects responses and should be considered in patients with a suboptimal response. The different dosing requirements of dasatinib (once daily with or without food) and nilotinib (twice daily with fasting) may be an additional factor in selecting frontline agents. This review compares and contrasts the three FDA approved first line TKI agents
Substituting or Collaborating? A Diversion-Aware Bass Model for Evaluating Impacts from Online Content Copycats
The proliferation of social media not only enables users to produce original contents, but also brings plenty of copycatting opportunities. The copying behavior over online user-generated content (UGC) can impact content originators by diverting the potential content returns (e.g., likes and retweets). To maintain the originators’ incentive of producing original contents, it is necessary for social platforms to develop targeted punishment and compensation regulations based on the diverted returns. Thus, this study proposes to explore and measure the diversion process of content consumer returns. To formulate the returns diversion caused by copycats, a Diversion-Aware Bass model (DA-Bass) is developed by introducing the substitute effect and collaborative effect. The role of content originality in the diffusion process is further estimated. Experiments have been conducted to demonstrate the proposed model’s effectiveness in supporting social platforms to trace and measure the diverted returns
Enhancing Customer Satisfaction Analysis with a Machine Learning Approach: From a Perspective of Matching Customer Comment and Agent Note
With the booming of UGCs, customer comments are widely utilized in analyzing customer satisfaction. However, due to the characteristics of emotional expression, ambiguous semantics and short text, sentiment analysis with customer comments is easily biased and risky. This paper introduces another important UGC, i.e., agent notes, which not only effectively complements customer comment, but delivers professional details, which may enhance customer satisfaction analysis. Moreover, detecting the mismatch on aspects between these two UGCs may further help gain in-depth customer insights. This paper proposes a machine learning based matching analysis approach, namely CAMP, by which not only the semantics and sentiment in customer comments and agent notes can be sufficiently and comprehensively investigated, but the granular and fine-grained aspects could be detected. The CAMP approach can provide practical guidance for following-up service, and the automation can help speed-up service response, which essentially improves customer satisfaction and retains customer loyalty
“GROWTH OF THE FITTER”: EVOLUTIONARY GROWTH PATHS AND FIRM SIZE OF START-UPS IN E-MARKETS
Existing research related to firm growth has not paid sufficient attention to the growth paths of online stores in e-markets. The linkage between growth path and firm size has not been built up. This paper aims to investigate evolutionary trajectories and their effects on firm size. Theoretically, conceptually define three types of distinguishable paths, namely the convergent, tepid, and sustained paths. We then propose related theoretical hypotheses that reflect the impacts of different types of growth paths on the resulting firm size. To empirically validate the proposed hypotheses, we applied the trajectory analysis method with a novel indicator, the relative expansion rate, based on a data set that consists of 5,582 online stores on Taobao.com, the largest e-commerce platform in the world. Testing results largely support our hypotheses and suggest that the sustained growth path is the ideal mode nascent online sellers should struggle for, since it is significantly positively related to the firm size that the sellers can achieve. To achieve their goal of firm expansion, new online sellers should aggressively pursue opportunities in the short term, which is a reflection of the “the growth of the fitter” principle. Our findings also suggest that E-commerce platforms may attempt to facilitate the sustained growth path of sellers through including growth path analysis in the evaluation system of online stores
The Dark Side of Images: Effect of Customer Generated Images on Product Assessment
Customer Generated Image (CGI) on e-commerce platforms has been widely recognized as a marketing tool to persuade customers into purchases. Despite its persuasive power, the effect of CGI on post purchase satisfaction has seldom been examined. This study draws upon Elaboration Likelihood Model and proposes that the affective cues in CGI could distract consumer’s cognitive information processing and lead to unsatisfactory purchases with a larger probability. To empirically test our hypothesis, we employed a difference-in-differences model with propensity score weighting method and deep learning based face detection algorithm and found that CGI could cause subsequent review ratings 0.12 stars lower compared with those not exposed to CGI. Additional analysis indicated that this negative effect could be attenuated if the CGI contains human faces or the image review has a low rating. These findings have important implications for online platforms to better leverage user generated rich media content
Providing a Service for Interactive Online Decision Aids through Estimating Consumers\u27 Incremental Search Benefits
Consumer information search has been a focus of research nowadays, especially in the context of online business environments. One of the research questions is to determine how much information to search (i.e., when to stop searching), since extensive literature on behavior science has revealed that consumers often search either “too little” or “too much”, even with the help of existing interactive online decision aids (IODAs). In order to address this issue, this paper introduces a new approach to IODAs with effective estimation of the incremental search benefits. In doing so, the approach incorporates two important aspects into consideration, namely point estimation and distribution estimation, so as to make use of the relevant information by combining both current and historical facts in reflecting the behavioral patterns of the consumers in search. Moreover, experiments based on data provided by Netflix illustrate that the proposed approach is effective and advantageous over existing ones
PREDICTING CONSUMER INFORMATION SEARCH BENEFITS FOR PERSONALIZED ONLINE PRODUCT RANKING: A CONFIDENCE-BASED APPROACH
Product ranking mechanism is an important service for e-commerce that facilitates consumers’ decision-making process. This paper studies online product ranking under uncertainty. Different from previous studies that generally rank products merely based on predicted ratings, a new personalized product ranking method is proposed based on estimating consumer information search benefits and taking prediction uncertainty and confidence into consideration. Experiments using real data of movie ratings illustrate that the proposed method is advantageous over traditional point estimation methods, thus may help enhance customers’ satisfaction with the decision-making process and choices through saving their time and efforts
Emergency Percutaneous Coronary Intervention Through the Left Radial Artery is Associated with Less Vascular Complications than Emergency Percutaneous Coronary Intervention Through the Femoral Artery
OBJECTIVE: To compare the advantages and disadvantages of emergency percutaneous coronary intervention through the left radial artery with those of emergency percutaneous coronary intervention through the femoral artery. METHODS: A total of 206 patients with acute myocardial infarction who required emergency percutaneous coronary intervention and were admitted to our hospital between January 2011 and August 2013 were divided into the following two groups: a group that underwent percutaneous coronary intervention through the left radial artery and a group that underwent percutaneous coronary intervention through the femoral artery. The times required for angiographic catheter and guiding catheter placement, the success rate of the procedure and the incidence of vascular complications in the two groups were observed. RESULTS: There was no significant difference in catheter placement time or the ultimate success rate of the procedure between the two groups. However, the left radial artery group showed a significantly lower incidence of vascular complications than the femoral artery group (
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