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Cutaneous angiosarcoma (CAS) is a rare malignant tumor with a poor prognosis for which neither basic research on molecular pathomechanisms nor clinical prospective studies have progressed. A retrospective study of 28 CAS cases reported that chemoradiotherapy with taxanes was superior to conventional surgery. Since that time, chemoradiotherapy with paclitaxel (PTX + RT) has become a standard treatment. In this paper, we retrospectively investigate 21 cases of CAS that had been treated in the Department of Dermatology at Hokkaido University Hospital. Patients initially treated with PTX + RT followed by maintenance taxane chemotherapy showed better prognosis in overall survival (OS) and progression-free survival (PFS) (median OS, 28 months; median PFS, 12 months) compared to others (median OS, 10 months; median PFS, 5 months) (OS and PFS: p 0.05, log-rank test). Our results are consistent with those of a previous study that suggested that PTX + RT followed by maintenance taxane chemotherapy is a better therapeutic option than other interventions, including surgery.

In this paper, testing the equality of two mean vectors is considered when each dataset has a monotone pattern of missing observations. A simplified Hotelling’s T 2-type test statistic in a two-sam...

Objectives: The aim of this study was to investigate the relationship between quality of life (QOL) and residual urine volume in patients undergoing bacille Calmette-Guérin (BCG) therapy. Methods: Patients requiring BCG therapy, including those with carcinoma in situ, were enrolled prospectively. The urine volume collected through urethral catheterization was measured as post-voiding residual volume (PVR) during BCG therapy. Patients were divided into two groups: small PVR (SPVR), with PVR less than 30 ml, and large PVR (LPVR), with PVR greater than or equal to 30 ml. QOL status was assessed using the European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 system before and after BCG therapy. Moreover, some patients were assessed by International Prostate Symptom Score (IPSS) at the same time as assessment with the EORTC QLQ-C30 system. The primary end point was the evaluation of QOL during BCG therapy. Results: Among the 69 patients with non–muscle-invasive bladder cancer included in this study, 43 were in the SPVR group and 26 were in the LPVR group. The proportions of women and analgesic use in the SPVR group were higher than that in the LPVR group; however, medication use for dysuria in the SPVR group was less than that in the LPVR group. In the QOL analyses, cognitive function and emotional function in the functional scale and fatigue, nausea/vomiting, and dyspnoea in the symptomatic scale were worse in the SPVR group than in the LPVR group. In the multivariate analysis, fatigue was worse in the SPVR group than in the LPVR group. Conclusions: During BCG therapy, patients in the SPVR group had worse QOL, especially fatigue, than those in the LPVR group. Level of evidence: Not applicable for this multicentre audit.

This article focuses on the maximum likelihood estimators (MLEs) of the mean parameter vector and the covariance matrix in a one-sample version of the growth curve model when the dataset has a mono...

Multivariate skewness and kurtosis were defined by Mardia. However, the distribution of multivariate normality test statistics based on skewness and kurtosis is only obtainable for large sa...

This article deals with the problem of testing for two normal sub-mean vectors when the data set have two-step monotone missing observations. Under the assumptions that the population covariance matrices are equal, we obtain the likelihood ratio test (LRT) statistic. Furthermore, an asymptotic expansion for the null distribution of the LRT statistic is derived under the two-step monotone missing data by the perturbation method. Using the result, we propose two improved statistics with good chi-squared approximation. One is the modified LRT statistic by Bartlett correction,and the other is the modified LRT statistic using the modification coefficient by linear interpolation. The accuracy of the approximations are investigated by using a Monte Carlo simulation. The proposed methods are illustrated using an example.

This paper deals with a sample measure of multivariate kurtosis, which is used as a test statistic in multivariate normality testing problems. We define a new multivariate sample kurtosis measure to provide a multivariate normality test for data with a two-step monotone missing structure. Furthermore, we derive its expectation and variance using a perturbation method. To evaluate the accuracy of a normal approximation, we conducted a Monte Carlo simulation for certain parameters. Finally, we present a numerical example to illustrate the proposed procedure.

To test whether two populations have the same mean vector in a high-dimensional setting, Chen and Qin (2010, Ann. Statist.) derived an unbiased estimator of the squared Euclidean distance between the mean vectors and proved the asymptotic normality of this estimator under local assumptions about the mean vectors. In this study, their results are extended without assumptions about the mean vectors. In addition, asymptotic normality is established in the class of general statistics including Chen and Qin’s statistics and other important statistics under general moment conditions that cover both Chen and Qin’s moment condition and elliptical distributional assumption. These asymptotic results are applied to the construction of simultaneous intervals for all pair-wise differences between mean vectors of k ≥ 2 groups. The finite-sample and dimension performance of the proposed methods is also studied via Monte Carlo simulations. The methodology is illustrated using microarray data.

The increase in medical expenditure has been worsening and poses a serious social problem. Commonly, leftover drugs are retained by patients. We estimated the possible reduction in prescription rates by appropriately reusing leftover drugs, and investigated the medication efficacy classifications that render leftover drugs due to the medication non-adherence. A retrospective cross-sectional survey of prescription data was performed at community pharmacies engaged in the appropriate reuse of leftover drugs through the SETSUYAKU-BAG campaign. We evaluated the drug costs and number of drugs originally prescribed, the reduction in expenditure and numbers after the use of leftover drugs, and then calculated the prescription reduction ratio (PRR) based on the number of drugs. Factors contributing to non-adherence were analyzed by the PRR. After reviewing the prescription information of 1792 patients, the reduction rate in drug expenditure was found to be 20.1%. Purgatives, Chinese medicines, and agents for peptic ulcer had higher PRRs and belonged to the top ten medications according to the prescription efficacy classifications. Non-adherence associated with the medication efficacy classifications was assessed by analyzing 5466 formulations. Thirty percent of formulations were found to be non-adherent. According to the medication efficacy classifications, six medications including agents for hyperlipidemias, peptic ulcer, psychotropics agents, and others, were less adherent than antihypertensives. These results suggest that adjusting prescriptions by appropriately reusing leftover drugs in community pharmacies could reduce medical costs. Further considerations are necessary for improving medication adherence in Japan. Healthcare providers should monitor medication adherence more carefully, with the results identified in this study.

In this study, the distribution of the simplified Hotelling's statistic for testing the mean vector when a data matrix has a monotone missing pattern is considered. The test statistic is decomposed, and an asymptotic expansion of the null distribution of each term is derived. Using the result, approximations to the upper percentiles of this statistic are derived. Furthermore, transformed test statistics based on the Bartlett adjustment are proposed. Finally, using a Monte Carlo simulation it is shown that the transformed statistics usually perform better than the original statistic with respect to the speed of convergence to the chi-squared limiting distribution.

In this study, testing the equality of mean vectors in a one-way multivariate analysis of variance (MANOVA) is considered when each dataset has a monotone pattern of missing observations. The likel...

In the paper, tests for multivariate normality (MVN) of Jarque-Bera type, based on skewness and kurtosis, have been considered. Tests proposed by Mardia and Srivastava, and the combined tests based...

We estimate the misclassification probability of a Euclidean distance-based classifier in high-dimensional data. We discuss two types of estimator: a plug-in type estimator based on the normal approximation of misclassification probability (newly proposed), and an estimator based on the well-known leave-one-out cross-validation method. Both estimators perform consistently when the dimension exceeds the total sample size, and the underlying distribution need not be multivariate normality. We also numerically determine the mean squared errors (MSEs) of these estimators in finite sample applications of high-dimensional scenarios. The newly proposed plug-in type estimator gives smaller MSEs than the estimator based on leave-one-out cross-validation in simulation.

Maintaining medication adherence is a critical issue in determining health outcomes in patients with chronic diseases. However, many patients do not adhere to their prescribed regimens. This study aimed to determine the effects of using adherence score sheets according to application timing in improving medication adherence among non-adherent outpatients. In community pharmacies, both patients and pharmacists evaluated medication adherence based on application timing (morning, noon, evening, and before going to bed) in 11 levels (0-10) for >4 months. A total of 58 outpatients were included in the study. The median scores among application timing at intermediate (patient 9.3, pharmacist 9.0) and final (patient 9.5, pharmacist 9.5) analyses were significantly higher than that at baseline (patient 7.6, pharmacist 7.0). At the end of the investigation, the ratio of non-adherent patients prescribed with hyperlipidemic medications was higher than those prescribed with medications for other lifestyle diseases. Approximately 80% of the patients reported improved medication adherence based on the questionnaires regarding their understanding on diseases and medications, medication awareness, and communication with pharmacists. Therefore, the utilization of an adherence score sheet according to application timing improved medication adherence of patients with chronic diseases.

SYNOPTIC ABSTRACTIn this article, we consider the distributions of the Hotelling’s T2-type test statistics for mean vectors when each dataset has a monotone missing data pattern. We give the approximate upper percentiles of the simplified Hotelling’s T2-type statistics in the case of data with k-step monotone missing data patterns. We also consider multivariate multiple comparisons for mean vectors with k-step monotone missing data. Approximate simultaneous confidence intervals for pairwise comparisons among mean vectors and comparisons with a control are obtained using Bonferroni’s approximation procedure. Finally, the accuracy and asymptotic behavior of the approximations are investigated by Monte Carlo simulation.

In this article, we consider the problem of testing the equality of multivariate normal populations when the data set has missing observations with a two-step monotone pattern. The likelihood ratio test (LRT) statistic for the simultaneous testing of the mean vectors and the covariance matrices is given under the condition of two-step monotone missing data. An approximate modified likelihood ratio test (MLRT) statistic is presented using linear interpolation based on the coefficients of the MLRT statistic in the case of complete data sets. As an alternative approach, we propose approximate MLRT statistics of two kinds with two-step monotone missing data using the decompositions of the likelihood ratio (LR). An approximate upper percentile of the LRT statistic with two-step monotone missing data is also derived based on an asymptotic expansion for the LRT statistic in the case of complete data sets. Finally, we investigate the accuracy of the approximations using Monte Carlo simulation.

We consider the tests for a single mean vector and two mean vectors with two-step monotone missing data. In this paper, we propose new test statistics for one sample and two sample designs based on the simplified T^2-type test statistic. Further, we present the approximation to the upper percentiles of these statistics and propose the transformed test statistics. Finally, we investigate the accuracy and asymptotic behavior of the approximation for X^2 distribution by a Monte Carlo simulation.

In this paper, we consider tests for sub-mean vectors and its simultaneous confidence intervals in two-sample problems. We give the T^2 type test statistic and the simultaneous confidence intervals by using two approximate upper percentiles of T^2 type test statistic. One of the approximate percentiles is obtained by normal approximation for a part of the T^2 type statistic, and the other is an approximation obtained by correcting the degrees of freedom of the F distribution. Finally, we investigate the asymptotic behavior of the approximate upper percentiles of T^2 type statistic by Monte Carlo simulation, and we give an example to illustrate the simultaneous confidence intervals.

Performance accuracy of the Euclidean Distance Discriminant rule (EDDR) is studied in the high-dimensional asymptotic framework which allows the dimensionality to exceed sample size. Under mild assumptions on the traces of the covariance matrix, our new results provide the asymptotic distribution of the conditional misclassification rate and the explicit expression for the consistent and asymptotically unbiased estimator of the expected misclassification rate. To get these properties, new results on the asymptotic normality of the quadratic forms and traces of the higher power of Wishart matrix, are established. Using our asymptotic results, we further develop two generic methods of determining a cut-off point for EDDR to adjust the misclassification rates. Finally, we numerically justify the high accuracy of our asymptotic findings along with the cut-off determination methods in finite sample applications, inclusive of the large sample and high-dimensional scenarios.

In this paper, we consider the problem of testing for the mean vector when the data have a two-step monotone missing pattern. We derive the stochastic expansion of Hotelling's T2 type statistic for the case where the sample size is large. The asymptotic first two moments are obtained using stochastic expansion. We also propose the Bartlett and modified Bartlett corrected statistics for two-step monotone missing data. Finally, we present a numerical comparison based on Monte Carlo simulation for some selected parameters.

SYNOPTIC ABSTRACTIn this article, we consider the problem of testing the equality of two mean vectors when the data have a three-step monotone pattern of missing observations. We propose an approximate upper percentile of the Hotelling’s T2-type statistic in which each dataset has a three-step monotone missing data pattern and the population covariance matrices are equal. Further, we obtain the Hotelling’s T2-type statistics and their approximate upper percentiles in the case of data with unequal two-step monotone missing data patterns. We also consider multivariate multiple comparisons for mean vectors with three-step monotone missing data. Approximate simultaneous confidence intervals for pairwise comparisons among mean vectors and comparisons with a control are obtained using Bonferroni’s approximate upper percentiles of the T2max · p and T2max · c statistics, respectively. Finally, the accuracy of the approximations is investigated via Monte Carlo simulation.

Much of the damage to health caused by drugs could be prevented by appropriate care. A well-defined duty of care and further information are required for healthcare professionals. Although there are many litigation cases to use as references, neither the extent of the duty of care nor the obligation to explain medication according to the type of drug prescribed has yet been fully established. Thus, we systematically collected decided cases of adverse drug events, and assessed the degree of the duties of care and information. Specifically, we collected decided cases in which physicians, dentists, pharmacists, nurses, or hospitals had been sued. Data were derived from Bessatsu Jurist Iryo-kago Hanrei Hyakusen, Hanrei Jihou, and Hanrei Times from 1989 to November 2013, and information on precedents in the records of the Supreme Court of Japan from 2001 to November 2013. We analyzed the cases, and assessed the following according to the type of drug: (1) standards and explanations when dealing with drugs that were critical issues in litigation, and (2) the degree of the physician's or pharmacist's duties of care and information. In total, 126 cases were collected. The number of drug categories classified was 27, and 9 were considered of practical importance. After this systematic review, we found a trend in the degree of the required level of care and information on several drugs. With respect to duties of care and information, the gap between the required level and actual practice suggests that healthcare professionals must improve their care and explanations.

We consider profile analysis with unequal covariance matrices under multivariate normality. In particular, we discuss this problem for high-dimensional data where the dimension is larger than the sample size. We propose three test statistics based on Bennett’s (1951) transformation and the Dempster trace criterion proposed by Dempster (1958). We derive the null distributions as well as the nonnull distributions of the test statistics. Finally, in order to investigate the accuracy of the proposed statistics, we perform Monte Carlo simulations for some selected values of parameters.

SYNOPTIC ABSTRACTIn this article, we consider the problem of testing for mean vector and simultaneous confidence intervals when the data have a three-step monotone pattern that is missing observati...

The biosynthetic gene cluster of antifungal agent jawsamycin (FR-900848) has been identified by heterologous expression. A series of gene inactivations and in vitro and in vivo analysis of key enzymes in the biosynthetic pathway established their functions. A novel mechanism involving a radical S-adenosyl methionine (SAM) cyclopropanase collaborating with an iterative polyketide synthase is proposed for the construction of the unique polycyclopropanated backbone. Our reconstitution system sets the stage for studying the catalytic mechanism of this intriguing contiguous cyclopropanation.

In this paper, we consider testing the equality of two mean vectors with unequal covariance matrices. In the case of equal covariance matrices, we can use Hotelling’s T2 statistic, which follows the F distribution under the null hypothesis. Meanwhile, in the case of unequal covariance matrices, the T2 type test statistic does not follow the F distribution, and it is also difficult to derive the exact distribution. In this paper, we propose an approximate solution to the problem by adjusting the degrees of freedom of the F distribution. Asymptotic expansions up to the term of order N− 2 for the first and second moments of the U statistic are given, where N is the total sample size minus two. A new approximate degrees of freedom and its bias correction are obtained. Finally, numerical comparison is presented by a Monte Carlo simulation.