Drug Information Journal最新文献

{"title":"Relative Efficiency of Unequal Versus Equal Cluster Sizes for the Nonparametric Weighted Sign Test Estimators in Clustered Binary Data.","authors":"Chul Ahn,&nbsp;Fan Hu,&nbsp;Seung-Chun Lee","doi":"10.1177/0092861512449818","DOIUrl":"https://doi.org/10.1177/0092861512449818","url":null,"abstract":"<p><p>We consider analysis of clustered binary data from multiple observations for each subject in which any two observations from a subject are assumed to have a common correlation coefficient. In the weighted sign test on proportion in clustered binary data, three weighting schemes are considered: equal weights to observations, equal weights to clusters and the optimal weights that minimize the variance of the estimator. Since the distribution of cluster sizes may not be exactly specified before the trial starts, the sample size is usually determined using an average cluster size without taking into account any potential imbalance in cluster size even though cluster size usually varies among clusters. In this paper we investigate the relative efficiency (RE) of unequal versus equal cluster sizes for clustered binary data using the weighted sign test estimators. The REs are computed as a function of correlation among observations within each subject and the various cluster size distributions. The required sample size for unequal cluster sizes will not exceed the sample size for an equal cluster size multiplied by the maximum RE. It is concluded that the maximum RE for various cluster size distributions considered here does not exceed 1.50, 1.61 and 1.12 for equal weights to observations, equal weights to clusters and optimal weights, respectively. It suggests sampling 50%, 61% and 12% more clusters depending on the weighting schemes than the number of clusters computed using an average cluster size.</p>","PeriodicalId":51023,"journal":{"name":"Drug Information Journal","volume":"46 4","pages":"428-433"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0092861512449818","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31303742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Patient Focused Solution for Enrolling Clinical Trials in Rare and Selective Cancer Indications: A Landscape of Haystacks and Needles.","authors":"Eric B Lynam,&nbsp;Jiin Leaw,&nbsp;Matthew B Wiener","doi":"10.1177/0092861512443436","DOIUrl":"https://doi.org/10.1177/0092861512443436","url":null,"abstract":"<p><p>Participation of adult cancer patients in US based clinical trials has remained near 3% for decades. Traditional research methodology reaches a small fraction of the target population with a fixed number of predetermined sites. Solutions are needed to ethically increase patient participation and accelerate cancer trial completion. We compared enrollment outcomes of traditional and patient focused research methodologies. A patient prioritized method (Just-In-Time, JIT) was implemented in parallel with traditionally managed sites in three cancer trials. JIT research sites were initiated after candidate patients presented, while traditional sites were initiated in advance. JIT sites enrolled with mean rates no less than, and up to 2.75 fold greater than, traditional sites. Mean patients enrolled per site was comparable (JIT-1.82, traditional-1.78). There were fewer non-enrolling JIT sites (2/28, 7%) compared to traditional sites 19/52, 37%). This retrospective analysis supports JIT as a prospective solution to increase cancer clinical trial enrollment and the efficiency of clinical trial administrative activities.</p>","PeriodicalId":51023,"journal":{"name":"Drug Information Journal","volume":"46 4","pages":"472-478"},"PeriodicalIF":0.0,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0092861512443436","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31695179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Testing in a Prespecified Subgroup and the Intent-to-Treat Population.","authors":"Mark D Rothmann,&nbsp;Jenny J Zhang,&nbsp;Laura Lu,&nbsp;Thomas R Fleming","doi":"10.1177/0092861512436579","DOIUrl":"https://doi.org/10.1177/0092861512436579","url":null,"abstract":"<p><p>In many settings, testing has been proposed to assess the effect of an experimental regimen within a biomarker-positive subgroup where it is biologically plausible that benefit is stronger in such patients, and in the overall population that also includes biomarker-negative subjects less likely to benefit from that regimen. A statistically favorable result in the biomarker-positive subgroup would lead to a claim for that subgroup, whereas a statistically favorable result for the overall population would lead to a claim that includes both biomarker subgroups. The latter setting is problematic when biomarker-negative patients truly do not benefit from the experimental regimen. When it is prespecified that biomarker-negative patients should not be included in the primary analysis of treatment effect in biomarker-positive patients because of the likelihood that treatment effects would differ between the 2 subgroups, it is logically inconsistent to include biomarker-positive patients in the primary analysis of treatment effect in biomarker-negative patients.</p>","PeriodicalId":51023,"journal":{"name":"Drug Information Journal","volume":"46 2","pages":"175-179"},"PeriodicalIF":0.0,"publicationDate":"2012-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0092861512436579","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30710754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Correction of Product Information in Drug References and Medical Textbooks","authors":"Ching Lum PharmD, Soo Mi Ahn PharmD","doi":"10.1177/0092861511427875","DOIUrl":"https://doi.org/10.1177/0092861511427875","url":null,"abstract":"The purpose of this project was to correct inaccurate information about Novo Nordisk products in drug references and medical textbooks. Twenty-six commonly used drug references (print or electronic) and 11 medical textbooks were reviewed for accuracy of information for all Novo Nordisk products; errors or omissions were identified in 32 of the 37 references reviewed. Inaccurate drug information most commonly involved product omissions or outdated product information. Letters describing the identified errors and suggested corrections were sent via US mail or e-mail to the authors, editors, or publishers. Within 18 months of sending the letters, 21 of the 32 references reviewed had published updated editions, which were then reviewed again to assess the impact of the communication. A total of 190 of 448 identified errors (42%) had been corrected.","PeriodicalId":51023,"journal":{"name":"Drug Information Journal","volume":"46 1","pages":"94-98"},"PeriodicalIF":0.0,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0092861511427875","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64842924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of Data Entry Errors and Data Changes to an Electronic Data Capture Clinical Trial Database.","authors":"Jules T Mitchel,&nbsp;Yong Joong Kim,&nbsp;Joonhyuk Choi,&nbsp;Glen Park,&nbsp;Silvana Cappi,&nbsp;David Horn,&nbsp;Morgan Kist,&nbsp;Ralph B D Agostino","doi":"10.1177/009286151104500404","DOIUrl":"https://doi.org/10.1177/009286151104500404","url":null,"abstract":"<p><p>Monitoring of clinical trials includes several disciplines, stakeholders, and skill sets. The aim of the present study was to identify database changes and data entry errors to an electronic data capture (EDC) clinical trial database, and to access the impact of the changes. To accomblish the aim, Target e*CRF was used as the EDC tool for a multinational, dose-finding, multicenter, double-blind, randomized, parallel, placebo-controlled trial to investigate efficacy and safety of a new treatment in men with lower urinary tract symptoms associated with benign prostatic hyperplasia. The main errors observed were simple transcription errors from the paper source documents to the EDC database. This observation was to be expected, since every transaction has an inherant error rate. What and how to monitor must be assessed within the risk-based monitoring section of the comprehensive data monitoring plan. With the advent of direct data entry, and the elimination of the requirement to transcribe from a paper source record to an EDC system, error rates should go down dramatically. In addition, protocol violations and data outside the normal range can be identified at the time of data entry and not days, weeks, and months after the fact.</p>","PeriodicalId":51023,"journal":{"name":"Drug Information Journal","volume":"45 4","pages":"421-430"},"PeriodicalIF":0.0,"publicationDate":"2011-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/009286151104500404","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31750940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A New Mechanism for Tracking Publicly Available Study Volunteer Demographics.","authors":"Rachael Zuckerman,&nbsp;Kenneth Getz,&nbsp;Kenneth Kaitin","doi":"10.1177/009286151104500106","DOIUrl":"https://doi.org/10.1177/009286151104500106","url":null,"abstract":"<p><p>The importance of gathering and monitoring aggregate demographic data on the annual population of study volunteers in FDA-regulated clinical trials is widely acknowledged. To date, no formal mechanism exists to capture this information. The Tufts Center for the Study of Drug Development identified and tested a publicly available source of information on clinical trial participant data, NDA Reviews stored in the FDA's drugs@FDA database, to determine its accuracy, reliability, and feasibility. Thirty-seven new drug applications approved between 2006 and 2008 were evaluated and compared with published sources of demographic data. The authors conclude that the approach described here-NDA review extraction-provides reasonably reliable and conservative estimates of study volunteer demographics and can serve as a useful baseline until Clinicaltrials.gov or other, more complete, public sources become available.</p>","PeriodicalId":51023,"journal":{"name":"Drug Information Journal","volume":"45 1","pages":"55-64"},"PeriodicalIF":0.0,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/009286151104500106","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29901168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SCORE Study Report 8: Closed Tests for All Pair-Wise Comparisons of Means.","authors":"Neal Oden,&nbsp;Paul C Vanveldhuisen,&nbsp;Ingrid U Scott,&nbsp;Michael S Ip","doi":"10.1177/009286151004400405","DOIUrl":"https://doi.org/10.1177/009286151004400405","url":null,"abstract":"<p><p>We compare five closed tests for strong control of family-wide type I error (FWE) while making all pair-wise comparisons of means in clinical trials with multiple arms such as the SCORE Study. We simulated outcomes of the SCORE Study under its design hypotheses, and used p-values from chi-squared tests to compare performance of a \"pairwise\" closed test described below to Bonferroni and Hochberg adjusted p-values. \"Pairwise\" closed testing was more powerful than Hochberg's method by several definitions of multiple-test power. Simulations over a wider parameter space, and considering other closed methods, confirmed this superiority for p-values based on normal, logistic, and Poisson distributions. The power benefit of \"pair-wise\" closed testing begins to disappear with 5 or more arms, and with unbalanced designs. For trials with 4 or fewer arms and balanced designs, investigators should consider using \"pair-wise\" closed testing in preference to Shaffer's, Hommel's, and Hochberg's approaches when making all pairwise comparisons of means. If not all p-values from the closed family are available, Shaffer's method is a good choice.</p>","PeriodicalId":51023,"journal":{"name":"Drug Information Journal","volume":"44 4","pages":"405-420"},"PeriodicalIF":0.0,"publicationDate":"2010-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/009286151004400405","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29926210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nonparametric Sample Size Estimation for Sensitivity and Specificity with Multiple Observations per Subject.","authors":"Fan Hu,&nbsp;William R Schucany,&nbsp;Chul Ahn","doi":"10.1177/009286151004400508","DOIUrl":"https://doi.org/10.1177/009286151004400508","url":null,"abstract":"<p><p>We propose a sample size calculation approach for the estimation of sensitivity and specificity of diagnostic tests with multiple observations per subjects. Many diagnostic tests such as diagnostic imaging or periodontal tests are characterized by the presence of multiple observations for each subject. The number of observations frequently varies among subjects in diagnostic imaging experiments or periodontal studies. Nonparametric statistical methods for the analysis of clustered binary data have been recently developed by various authors. In this paper, we derive a sample size formula for sensitivity and specificity of diagnostic tests using the sign test while accounting for multiple observations per subjects. Application of the sample size formula for the design of a diagnostic test is discussed. Since the sample size formula is based on large sample theory, simulation studies are conducted to evaluate the finite sample performance of the proposed method. We compare the performance of the proposed sample size formula with that of the parametric sample size formula that assigns equal weight to each observation. Simulation studies show that the proposed sample size formula generally yields empirical powers closer to the nominal level than the parametric method. Simulation studies also show that the number of subjects required increases as the variability in the number of observations per subject increases and the intracluster correlation increases.</p>","PeriodicalId":51023,"journal":{"name":"Drug Information Journal","volume":"44 5","pages":"609-616"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/009286151004400508","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30279143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effective Strategies for Maintaining Research Participation in Clinical Trials.","authors":"Allen Zweben, Lisa M Fucito, Stephanie S O'Malley","doi":"10.1177/009286150904300411","DOIUrl":"10.1177/009286150904300411","url":null,"abstract":"<p><p>Achieving high protocol adherence is essential for ensuring the overall success and scientific merit of clinical trials. Strategies for maximizing recruitment and treatment adherence have been previously explored in the literature. There has been less focus, however, on effective methods for maintaining participants in research follow-up. This article examines factors associated with poor follow-up rates as well as strategies for facilitating research commitment and addressing sources of nonadherence. Special attention is devoted to alcohol- and substance-dependent populations, groups known to have poor adherence rates. Examples are drawn from the COMBINE Study, an NIAAA-funded, nationwide, multisite, combined behavioral and pharmacotherapy trial for alcohol problems that achieved high one-year follow-up rates. The important role of coordinating centers in facilitating research retention is also discussed.</p>","PeriodicalId":51023,"journal":{"name":"Drug Information Journal","volume":"43 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2009-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3848036/pdf/nihms527870.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31931742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical Thinking for Non-Statisticians in Drug Regulation","authors":"M. DeWyngaert","doi":"10.1177/009286150804200513","DOIUrl":"https://doi.org/10.1177/009286150804200513","url":null,"abstract":"One of the major fascinations of Space Technology is the interdependence of the systems involved in spacecraft design. A significant modification to the power consumption of one unit can lead to changes in radiator size, collecting area of the array, structural design and mass increments, which then affect attitude control and so on. Since the scope of such a variety of systems and fields is wide and beyond the grasp of single individuals, it is helpful to have at hand a volume such as this containing definitions, explanations and links to further investigation. Although the author has in general steered clear of any temptation to create an encyclopaedia, there is the inclusion of descriptions of some relevant historical or significant missions which help to recall the configurations used and the diversity of earlier designs. A typical example is the Giotto mission to Halley’s comet, the entry for which contains reference to the Whipple shield concept for hypersonic impact defence—a thread which leads through to the selective protection design strategy for the International Space Station. It is difficult to review a dictionary since there is no real theme or plot to comment upon; one can only select subjects of particular personal experience and examine them for accuracy. I was able to draw upon my own background to assess a number of programme entries and found them to be of high quality and accuracy. There is an interesting mix of scientific background and technology where the subjects become complementary. I was particularly struck by the impressive, but succinct, explanation of the libration or LaGrange points of gravitational balance. This was used as a solar orbit location for the SOHO research spacecraft, which needed to observe the sun for long periods uninterrupted by eclipsing the Earth. In reading the entry I was surprised to be led further to discover that the Trojan asteroids occupy the libration points for Jupiter, orbiting the sun in tandem ahead and trailing the giant planet. In fact, although the title implies technology there are a considerable number of entries concerning space science, including magnetospheric physics, astronomy, solar physics, planetary exploration and earth observation. All of these are dealt with in easily understood terms and for the most part are related to actual missions, giving an insight into objectives and results. Other terms caught the attention; adaptations of physical principles lead to synthetic aperture radar—a means of scanning a subject with a single pass but building up a much larger picture. Another is very long baseline interferometry (VLBI) using widely separated locations to view the same stellar object. This has the effect of simulating the use of a very large telescope (in radio astronomy this can be the diameter of the Earth!). Coverage with more general topics includes a balanced coverage of US and other launcher programmes. This extends to rocket engine types and principles includin","PeriodicalId":51023,"journal":{"name":"Drug Information Journal","volume":"42 1","pages":"525-526"},"PeriodicalIF":0.0,"publicationDate":"2008-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/009286150804200513","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64842916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}