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  • 1
    Online Resource
    Online Resource
    SAGE Publications ; 2020
    In:  Health Informatics Journal Vol. 26, No. 4 ( 2020-12), p. 2362-2374
    In: Health Informatics Journal, SAGE Publications, Vol. 26, No. 4 ( 2020-12), p. 2362-2374
    Abstract: The accurate forecast of radiology emergency patient flow is of great importance to optimize appointment scheduling decisions. This study used a multi-model approach to forecast daily radiology emergency patient flow with consideration of different patient sources. We constructed six linear and nonlinear models by considering the lag effects and corresponding time factors. The autoregressive integrated moving average and least absolute shrinkage and selection operator (Lasso) were selected from the category of linear models, whereas linear-and-radial support vector regression models, random forests and adaptive boosting were chosen from the category of nonlinear models. The models were applied to 4-year daily emergency visits data in the radiology department of West China Hospital in Chengdu, China. The mean absolute percentage error of six models ranged from 8.56 to 9.36 percent for emergency department patients, whereas it varied from 10.90 to 14.39 percent for ward patients. The best-performing model for total radiology visits was Lasso, which yielded a mean absolute percentage error of 7.06 percent. The arrival patterns of emergency department and total radiology emergency patient flows could be modeled by linear processes. By contrast, the nonlinear model performed best for ward patient flow. These findings will benefit hospital managers in managing efficient patient flow, thus improving service quality and increasing patient satisfaction.
    Type of Medium: Online Resource
    ISSN: 1460-4582 , 1741-2811
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2020
    detail.hit.zdb_id: 2070802-6
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  • 2
    In: Therapeutic Advances in Medical Oncology, SAGE Publications, Vol. 11 ( 2019-01), p. 175883591988900-
    Abstract: The objectives of this phase II study were to determine the clinical activity of the MET tyrosine kinase inhibitor capmatinib (INC280) in patients with MET-dysregulated advanced hepatocellular carcinoma (HCC) and to assess the safety, pharmacokinetics, and correlation of biomarkers with the response. Methods: This phase II, open-label, single-arm study evaluated twice daily (BID) oral capmatinib in a dose-determining stage, utilizing a Bayesian Logistic Regression Model (BLRM) subject to Escalation with Overdose Control criteria, safety, pharmacokinetics, and pharmacodynamic information to determine a recommended dose for expansion (RDE) evaluating efficacy in patients with MET-dysregulated HCC. Results: A total of 38 patients received treatment. In the dose-determining stage, patients received capmatinib 300 mg BID capsules ( n = 8), and in the expansion, patients received 600 mg BID capsules ( n = 28) or 400 mg BID tablets ( n = 2) based on the BLRM and other relevant clinical data. No predefined qualifying adverse events (AEs) were observed during the first 28 days of treatment, and the RDE was 600 mg BID capsules (equivalent pharmacokinetics to 400 mg BID tablets). The most common any causality AEs were nausea (42%), vomiting (37%), and diarrhea (34%). In the expansion stage, in a subgroup of 10 patients with MET-high HCC, the overall response rate was 30%, including 1 durable complete response ( 〉 600 days) and 2 partial responses [1 durable ( 〉 600 days)]. Conclusions: Single agent capmatinib at the RDE is tolerable with a manageable safety profile. Antitumor activity was seen in a subset of patients with MET-dysregulated (MET-high) HCC. Trial registration: ClinicalTrials.gov: NCT01737827. https://clinicaltrials.gov/ct2/show/NCT01737827
    Type of Medium: Online Resource
    ISSN: 1758-8359 , 1758-8359
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2019
    detail.hit.zdb_id: 2503443-1
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