著者
岩崎 学 吉田 清隆
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.26, no.2, pp.53-63, 2005-12-31 (Released:2011-09-30)
参考文献数
16

For the occurrence of a rare event A such as a severe adverse drug reaction, there exists the “Rule of Three” to remind practitioners that “absence of evidence is not evidence of absence.” The Rule of Three actually says that even if the event A was not observed among n patients it would be quite possible to observe three events among other n patients. The present paper examines this useful rule in detail and also extends it to a testing problem for occurrence probability of A.First, the Rule of Three is extended to the case that the number of the event observed among the first n patients is more than zero. We give rules that when k (> 0) events were observed among n patients, nk events would be possibly observed among other n patients. Next, a testing procedure is introduced to examine whether the occurrence probabilities of A for two populations are the same under the condition that k events were observed among n patients for one population. It will be shown that the relevant probability distribution is a negative binomial, and then critical regions for small k's are given. For a possible application of the procedure, we mention the signal detection for spontaneous reporting system of adverse drug reaction.
著者
武田 健太朗 大庭 真梨 柿爪 智行 坂巻 顕太郎 田栗 正隆 森田 智視
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.36, no.1, pp.25-50, 2015-07-20 (Released:2015-09-08)
参考文献数
47
被引用文献数
1 1

It is expected to develop new drug more efficiently by incorporating historical data into the current study data. Borrowing historical data which is sufficiently similar to the current data allows increasing power and improving the accuracy of the estimated treatment effect. On the other hand, if the historical data is not similar to the current data, there is a potential for bias and inflated type I error rate. Power prior and hierarchical model are widely known as the Bayesian approaches with borrowing strength from historical information. They have the advantage of deciding the amount of historical information continuously depending on the similarity between historical data and current data. Our goal is to introduce power prior and hierarchical model while showing some examples, and provide a review of points to keep in mind when these approaches are used in the clinical trials.
著者
佐藤 恵子 岩崎 学 菅波 秀規 佐藤 俊哉 椿 広計
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.35, no.1, pp.37-53, 2014-08-31 (Released:2014-10-15)
参考文献数
18
被引用文献数
1

All statisticians are expected to produce statistical outcomes of high quality and reliability. To ensure reliability in statistical performance and outcomes and to meet societal expectations, certain standards of conduct (SOC) must be established such that individual statisticians embrace their own principles and so that the community of statisticians as a whole functions with more self-control.In 2008, the Biometric Society of Japan began revision of the code of conduct, and the working group drafted an SOC. This particular draft re.ected the opinions of statisticians and the basic concepts which aligned well with ethical guidelines of the American Statistical Association and the International Statistical Institute. As forced guidelines rarely result in full compliance and increased ethical conduct, the SOC offers a framework to encourage individual biostatisticians to establish and hold their own principles and to act responsibly with integrity.The SOC comprises a preamble, mission statement, values, ten principles and background information. The draft SOC was approved by the Council of the Biometric Society of Japan in November 2013.The SOC will help statisticians improve their capacity to perform sound statistical practices, improve the working environment, cultivate the next generation of statisticians with professionalism, and acquire societal trust.
著者
柳川 堯
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.38, no.2, pp.153-161, 2018-03-01 (Released:2018-05-18)
参考文献数
5

Many clinical studies are conducted in Japan with sample sizes that are not deter-mined statistically. Application of Neyman-Pearson type statistical tests to data from such studies is not justifiable and should be stopped. Also 5% significance level that is commonly employed in a clinical study without taking into account disease, drug and other factors is not justifiable. Alternatively, the use of p-value is recommended in this paper as a measure of showing the magnitude of difference of two treatments; it is the role of principal investigator to summarize the study results by considering disease, drug and other factors, sample sizes and p-value.
著者
石原 幸司
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.32, no.Special_Issue, pp.S65-S75, 2010-05-31 (Released:2011-09-05)
参考文献数
8
著者
丹後 俊郎
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.27, no.Special_Issue, pp.S116-S119, 2006-09-30 (Released:2012-01-23)
参考文献数
1

This short note discusses statistical issues in the appropriate design of randomized controlled trials with regards to the recent two documents, “Points to Consider on Switching between Superiority and Non-inferiority” and “Guideline on the Choice of the Non-inferiority Margin” from the European Agency for the Evaluation of Medicinal Products. This paper also points out the inappropriateness of the terminology of “superiority”defined in ICH E9 (Statistical Principles for Clinical Trials) and discusses its relationship with these matters.
著者
寒水 孝司 杉本 知之 濱崎 俊光
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.34, no.1, pp.35-52, 2013-08-31 (Released:2013-09-20)
参考文献数
61
被引用文献数
1

Clinical trials often employ two or more primary endpoints because a single endpoint may not provide a comprehensive picture of the intervention’s effects. In such clinical trials, a decision is generally made as to whether it is desirable to evaluate the joint effects on all endpoints (i.e., co.primary endpoints) or at least one of the endpoints. This decision defines the alternative hypothesis to be tested and provides a framework for approaching trial design. In this article, we discuss recent statistical issues in clinical trials with multiple primary endpoints. Especially, we introduce the methods for power and sample size determinations in clinical trials with co-primary endpoints, considering the correlations among the endpoints into the calculations. We also discuss the methods to alleviate conservativeness of testing co-primary endpoints.
著者
松山 裕
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.25, no.2, pp.89-116, 2004-12-31 (Released:2012-02-08)
参考文献数
55
被引用文献数
1

Missing data is a prevalent complication in the analysis of data from longitudinal studies, and remains an active area of research for biostatisticians and other quantitative methodologists. This paper reviews several statistical methods that are used to address outcome-related drop-out. We begin with a review of important concepts such as missing data patterns, missing data mechanisms, ignorability and likelihood-based inference, which were originally proposed by Rubin (1976, Biometrika 63, 581-592). Secondly, we review the simple analysis methods for handling drop-outs such as a complete-case analysis, an available data analysis and a last observation carried forward analysis, and their limitations are given. Thirdly, we review the more sophisticated approaches for handling drop-outs, which take account of the missing data mechanisms in the analysis. Inverse probability weighted methods and multiple imputation methods, which represent two distinct paradigms for handling missing data, are reviewed. The analysis methods for non-ignorable drop-outs are also reviewed. Three approaches, selection models, pattern mixture models and latent variable models are presented. We illustrate the analysis techniques using the longitudinal clinical trial of contracepting women reported by Machine et al (1988, Contraception 38, 165-179). We briefly review the analysis methods in the presence of missing covariates. Finally, we give some notice in the analysis of missing data.
著者
川口 淳
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.33, no.2, pp.145-174, 2013-02-28 (Released:2013-03-07)
参考文献数
116

Imaging techniques have been used for effectively studying the brain in a non-invasive manner in several fields, for example, psychiatry and psychology. In this review, we focus on two imaging techniques that provide different views of brain structure and function. Structural magnetic resonance imaging (sMRI) provides information about various tissue types in the brain, for example, gray matter, white matter, and cerebrospinal fluid. Functional MRI (fMRI) measures brain activity by detecting changes in cerebral blood flow. These techniques enable high-quality visualization of brain activity or the location of atrophies; moreover, these techniques facilitate the study of disease mechanisms in the healthy brain and might lead to the development of effective therapies or drugs against such diseases. However, raw MRI data must be statistically analyzed to obtain objective answers to clinical questions. Therefore, statistical methods play a very important role in brain research. Here, we briefly review the most commonly used statistical analyses, namely, data pre-processing, general linear model, random field theory, mixed effect model, independent component analysis, network analysis, and discriminant analysis. Further, we provide information about brain imaging data structure and introduce useful software to implement these methods.
著者
大門 貴志
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.33, no.1, pp.1-29, 2012-08-31 (Released:2012-10-02)
参考文献数
145
被引用文献数
2

A number of designs of phase I dose-finding trials have been developed. Algorithm-based designs such as standard 3 + 3 designs are easy to understand and implement since they do not require explicit model specification for a dose-toxicity relationship. On the other hand, model-based designs such as the continual reassessment method (CRM) (O’Quigley et al., 1990) have been proposed. The author will give a review of the CRM and its related topics. In particular, the author makes mention of some of the problems with 3 + 3 designs that have often been used in phase I dose-finding studies and gives a detailed description of ideas, concepts, theories, properties and issues in the CRM.
著者
渡橋 靖
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.29, no.Special_Issue_1, pp.S61-S68, 2008-07-01 (Released:2011-12-02)
参考文献数
20

The ICH E14 guideline provides recommendation to assess QT interval prolongation and proarrhythmic potential of non-antiarrhythmic drugs in clinical studies. As there exist many statistical issues in the clinical evaluation of QT prolongation, electrocardiograms, background information of the guideline and QT interval correction methods are described for introduction. Because of the inverse relationship to heart rates, QT intervals are corrected for heart rates in order to obtain a variable which is independent of heart rate. Population-derived correction, subject-specific correction, and other correction methods are introduced. Assumptions of each correction method and its properties are discussed. Study design should be considered to collect appropriate data and estimate accurate heart rate correction formulae.
著者
関山 英孝 寒水 孝司
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.37, no.2, pp.89-100, 2016-12-31 (Released:2017-05-16)
参考文献数
11

The Japanese Adverse Drug Event Report (JADER) database of the Pharmaceutical and Medical Devices Agency (PMDA) has been available to the public since 2012. The database includes reports on drug-related adverse events from pharmaceutical companies or medical institutions. It is expected to improve the proper use of pharmaceutical products through pharmacoepidemiological studies using the JADER. However, wrong results and interpretations would be derived unless the features of JADER are carefully considered before the study. However, no study has investigated JADER from the viewpoint of data cleaning.Herein, we summarized the features and precautions for use of JADER (downloaded on June 2015). For example, we found many misspellings and drug names input in various forms because of incorrect Japanese Kanji, voiced and semi-voiced dots, and half-width and full-width forms. We also found that the number of adverse events tends to increase throughout the year, with the highest number reported in the third quarter (October-December). Finally, emergency or rapid safety information (i.e., yellow letter and blue letter) and results of drug use surveys generally increase the number of adverse events reported in JADER.
著者
猪川 和朗 田中 潤
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.36, no.Special_Issue, pp.S3-S18, 2015-06-30 (Released:2015-09-08)
参考文献数
10

We describe fundamental knowledge of pharmacokinetics analysis for phase I trials, particularly focusing on basic parameters (such as bioavailability, volume of distribution, fraction unbound, clearance), estimation and analysis methods (such as compartmental and non-compartmental), points to consider (such as steady state and dose proportionality). The NCA is an abbreviation for Non Compartmental Analysis, and the meaning is pharmacokinetic analysis without pharmacokinetic model. There is something that we should consider in NCA such as AUC calculation method, handling method of not detectable concentrations, point selection for λz calculation, and selection of sampling time. Steady state occurs when the overall intake of a drug is equilibrium with its elimination. At steady state the mean plasma concentrations of the drug are similar by any dosing interval. In practice, it is generally considered that steady state is reached when a time of 5 times the half-life for a drug. For the dose proportionality, the measures of exposure, such as maximal blood concentration (Cmax), area under the curve from 0 to infinity (AUC), are proportional to the dose. The three methods, Analysis of variance of the PK response, normalized by dose, linear regression and power model, are used to assess dose proportionality.
著者
橋本 敏夫 山田 雅之 笠井 英史
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.36, no.Special_Issue, pp.S19-S31, 2015-06-30 (Released:2015-09-08)
参考文献数
14

This paper reviews the statistical aspects in pharmacokinetic analysis of clinical Phase 1 trials. Based on the understanding that most pharmacokinetic parameters follow a lognormal distribution, it is considered to be appropriate to summarize them by the geometric mean, geometric CV or geometric SD. Then we conducted simulation studies of a pharmacokinetic model to investigate whether pharmacokinetic parameters follow a lognormal distribution. Using numerical examples obtained by the simulation, we described in detail how to display the summary statistics of pharmacokinetic parameters. We also indicated that geometric mean is also useful to summarize the plasma concentration, and that the concetration below the lower limit of quantification shoud be carefully handled.
著者
西 次男
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.27, no.1, pp.69-79, 2006-06-30 (Released:2011-09-25)
参考文献数
9

We showed a dynamic allocation procedure to achieve a specified proportion of sample sizes among treatment groups not only within all patients, but also within patients with strata composed of centers and/or prognostic factors in randomized controlled clinical trials. This procedure allocates a patient to one of treatment groups that are within a pre-specified range from the best balance, as well as the treatment groups with the best balance. When target sample sizes of two treatment groups are the same, Zelen (1974) showed a restriction for a range of obtained sample sizes. Proposed method is an extension of Zelen's restriction to the case of different target sample sizes of more than two treatment groups. This method can introduce randomness into a dynamic allocation procedure keeping comparability among treatment groups.
著者
山口 拓洋
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.26, no.2, pp.81-117, 2005-12-31 (Released:2011-09-30)
参考文献数
102
被引用文献数
2 2

Recurrent events data such as epileptic seizures and recurrence of superficial bladder cancer are frequently encountered in medical researches when individuals may experience multiple events of the same type. The analysis of recurrent events is complicated because related recurrent events within a subject are correlated and we need to take into account the dependence of responses from the same subject to draw valid statistical inferences. In principle, statistical strategies are classified into two approaches. The one is we focus on the number of events occurring within defined time intervals and compare / model the event rate (number of events per unit of time). The other is the recurrence times are viewed as multivariate failure times and survival analysis methods are applied. According to this perspective, we review several statistical methods to analyze recurrent events data and illustrate the techniques with real medical applications. We recommend that the choice of the endpoint (effect measure) and the corresponding statistical analysis method should be determined by the study purpose. Robust methods for the assumption of event occurring process should be used especially for analyzing confirmatory studies.
著者
手良向 聡
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.29, no.2, pp.111-124, 2008-12-01 (Released:2011-09-15)
参考文献数
32

The aim of single-arm clinical trials of a new drug is to determine whether it has sufficient promising activity to warrant its further development. For the last several years Bayesian statistical methods have been proposed and used. Bayesian approaches are ideal for earlier phase exploratory trials or proof-of-concept studies as they take into account information that accrues during a trial. Posterior and predictive probabilities are then updated and so become more accurate as the trial progresses. If the relevant external information is available, the decision will be made with a smaller sample size. The goal of this paper is to provide a review for statisticians who use Bayesian methods for the first time or investigators who have some statistical background. In addition, a clinical trial is presented as a real example to illustrate how to conduct a Bayesian approach for single-arm clinical trials with binary endpoints.
著者
浜田 知久馬 中西 豊支 松岡 伸篤
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.27, no.2, pp.139-157, 2006-12-01 (Released:2011-09-25)
参考文献数
50
被引用文献数
3 3

Meta-analysis is defined to be ‘the statistical analysis of a large collection of analysis results from individual studies for the purpose of integrating the findings'. Since the 1980s there has been an upsurge in the application of meta-analysis to medical research. The rapid increase in the number of meta-analysis being conducted during the last decade is mainly due to a greater emphasis on evidence based medicine and the need for reliable summaries of the vast and expanding volume of clinical studies. Over the same period there have been great developments and refinements of the associated methodology of meta-analysis. When judging the reliability of the results of a meta-analysis, attention should be focused on ‘publication bias’. Publication bias is the term for what occurs whenever the research that appears in the published literature is systematically unrepresentative of the population of completed studies. This bias can provide a flaw of the result of meta-analysis. In this article, the causes and origins of publication bias are reviewed, and then the history and some findings of publication bias in medical research are presented. Several statistical methods that have been developed to detect, quantify and assess the impact of publication bias in meta-analysis are demonstrated.
著者
西川 正子
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.29, no.2, pp.141-170, 2008-12-01 (Released:2011-09-15)
参考文献数
73
被引用文献数
1

The statistical analysis of survival time or failure time data is an important topic in many areas of research. In ordinary survival data, there is a single, possibly right-censored failure time for each individual. However, in a number of medical applications whereby data is collected an individual may experience one or more events but the first event will preclude the occurrence of another event under investigation. As a result, he/she can experience only one of several types of events. Such data are commonly referred to as competing risks data. Censoring due to such an event is generally not independent of the time to the event of interest.This paper reviews statistical methods for analyzing a competing risks model. Both conceptual considerations and common approaches to one-sample inference; two sample comparison; and covariate effect modeling are discussed. The theory for the analysis of ordinary right-censored survival data can be applied under certain circumstances. Standard statistical software package can perform the necessary analysis, although interpretation of results will vary.