Pharmacology and Clinical Evaluation of Ensartinib Hydrochloride Capsule / 中国肺癌杂志

Lung cancer is one of the most common malignancies with the highest incidence rate and mortality rate worldwide, and non-small cell lung cancer (NSCLC) accounts for about 85%. Only 5% NSCLC patients are anaplastic lymphoma kinase (ALK) rearrangement positive NSCLC, but the prognosis of these patients is poor, and treatment is urgent. Ensartinib (X-396), a next-generation ALK tyrosine kinase inhibitor (ALK-TKI), has shown greater potency on inhibiting ALK activity and controlling brain metastases than crizotinib, which is indicated for the treatment of crizotinib-resistant, ALK-positive NSCLC patients. Several phase I to III clinical trials included both healthy volunteers and NSCLC patients have been conducted both in China and abroad. In this review, we briefly summarized the results of these trials, and preliminary efficacy, safety, pharmacology and pharmacokinetics/pharmacodynamics of ensartinib were discussed.

Establishment and research of Kawasaki disease diagnosis model / 国际儿科学杂志

Objective To establish a Kawasaki disease mathematical diagnosis model in order to sup-port clinical decision-making. Methods Children with fever admitted to Shanghai Children's Hospital from Jan-uary 2013 to July 2017 were recruited and were divided into Kawasaki disease group and other disease control groups according to the final clinical diagnosis. The general clinical information and laboratory indicators were compared,a mathematical model was established and evaluated through the logistic regression analysis. Results A total of 1916 children were enrolled in this study,with an average age of 3. 47 ± 2. 83 years. Of these,1085 (56. 6％) were male,831 (43. 4％) were female,479 (25. 0％) were diagnosed with Kawasaki disease and 1099 (75. 0％) were with other diagnosis. Logistic regression analysis included dependent variables and inde-pendent variables,and the results showed that the Hosmer and Lemeshow test of this model was P=0. 944,the difference was not significant,indicating that the fitting equation and the true equation without deviation; age , fever days,ESR,CRP,WBC,ALB and DD dimers were independent risk factors for Kawasaki disease. The pre-dictive equation of Logistic regression is:ln P1-p( )= -7. 337 +2. 163 × CRP+1. 56 × DD+1. 612 × ESR+1. 392+age+1. 724 × days of fever +2. 295 × WBC +0. 808 × ALB. The patient model score and the ROC curve was calculated. The area under the curve was 0. 927 (95％ CI:0. 905-0. 950). When the score was 9,the Youden index was the highest(72. 9％),the sensitivity and specificity were 89. 7％ and 83. 2％. Conclusion The Kawasaki disease diagnosis mathematical model established in this study has good diagnostic efficacy,which need to be confirmed by further large-scale,multicenter studies.

Primary Study on Predicting the Termination of Paroxysmal Atrial Fibrillation Based on a Novel RdR RR Intervals Scatter Plot / 生物医学工程学杂志

Predicting the termination of paroxysmal atrial fibrillation (AF) may provide a signal to decide whether there is a need to intervene the AF timely. We proposed a novel RdR RR intervals scatter plot in our study. The abscissa of the RdR scatter plot was set to RR intervals and the ordinate was set as the difference between successive RR intervals. The RdR scatter plot includes information of RR intervals and difference between successive RR intervals, which captures more heart rate variability (HRV) information. By RdR scatter plot analysis of one minute RR intervals for 50 segments with non-terminating AF and immediately terminating AF, it was found that the points in RdR scatter plot of non-terminating AF were more decentralized than the ones of immediately terminating AF. By dividing the RdR scatter plot into uniform grids and counting the number of non-empty grids, non-terminating AF and immediately terminating AF segments were differentiated. By utilizing 49 RR intervals, for 20 segments of learning set, 17 segments were correctly detected, and for 30 segments of test set, 20 segments were detected. While utilizing 66 RR intervals, for 18 segments of learning set, 16 segments were correctly detected, and for 28 segments of test set, 20 segments were detected. The results demonstrated that during the last one minute before the termination of paroxysmal AF, the variance of the RR intervals and the difference of the neighboring two RR intervals became smaller. The termination of paroxysmal AF could be successfully predicted by utilizing the RdR scatter plot, while the predicting accuracy should be further improved.