scholarly journals DEBATE-statistical analysis plans for observational studies

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Bart Hiemstra ◽  
Frederik Keus ◽  
Jørn Wetterslev ◽  
Christian Gluud ◽  
Iwan C. C. van der Horst
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Statistical Analysis ◽  
Observational Study ◽  
Observational Studies ◽  
Data Driven ◽  
Study Power ◽  
Definition Of ◽  
Main Message ◽  
New Item

Abstract Background All clinical research benefits from transparency and validity. Transparency and validity of studies may increase by prospective registration of protocols and by publication of statistical analysis plans (SAPs) before data have been accessed to discern data-driven analyses from pre-planned analyses. Main message Like clinical trials, recommendations for SAPs for observational studies increase the transparency and validity of findings. We appraised the applicability of recently developed guidelines for the content of SAPs for clinical trials to SAPs for observational studies. Of the 32 items recommended for a SAP for a clinical trial, 30 items (94%) were identically applicable to a SAP for our observational study. Power estimations and adjustments for multiplicity are equally important in observational studies and clinical trials as both types of studies usually address multiple hypotheses. Only two clinical trial items (6%) regarding issues of randomisation and definition of adherence to the intervention did not seem applicable to observational studies. We suggest to include one new item specifically applicable to observational studies to be addressed in a SAP, describing how adjustment for possible confounders will be handled in the analyses. Conclusion With only few amendments, the guidelines for SAP of a clinical trial can be applied to a SAP for an observational study. We suggest SAPs should be equally required for observational studies and clinical trials to increase their transparency and validity.

scholarly journals Practical and conceptual issues of clinical trial registration for Brazilian researchers

2015 ◽  
Vol 134 (1) ◽  
pp. 28-33 ◽  
Author(s):  
Carolina Gomes Freitas ◽  
Thomas Fernando Coelho Pesavento ◽  
Maurício Reis Pedrosa ◽  
Rachel Riera ◽  
Maria Regina Torloni
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
International Committee ◽  
New Drugs ◽  
Trial Registration ◽  
Clinical Trial Registry ◽  
Clinical Trial Registration ◽  
Registration Process ◽  
Trial History ◽  
Definition Of

CONTEXT AND OBJECTIVE: Clinical trial registration is a prerequisite for publication in respected scientific journals. Recent Brazilian regulations also require registration of some clinical trials in the Brazilian Clinical Trials Registry (ReBEC) but there is little information available about practical issues involved in the registration process. This article discusses the importance of clinical trial registration and the practical issues involved in this process. DESIGN AND SETTING: Descriptive study conducted by researchers within a postgraduate program at a public university in São Paulo, Brazil. METHODS: Information was obtained from clinical trial registry platforms, article reference lists and websites (last search: September 2014) on the following topics: definition of a clinical trial, history, purpose and importance of registry platforms, the information that should be registered and the registration process. RESULTS: Clinical trial registration aims to avoid publication bias and is required by Brazilian journals indexed in LILACS and SciELO and by journals affiliated to the International Committee of Medical Journal Editors (ICMJE). Recent Brazilian regulations require that all clinical trials (phases I to IV) involving new drugs to be marketed in this country must be registered in ReBEC. The pros and cons of using different clinical trial registration platforms are discussed. CONCLUSIONS: Clinical trial registration is important and various mechanisms to enforce its implementation now exist. Researchers should take into account national regulations and publication requirements when choosing the platform on which they will register their trial.

scholarly journals Post-Exposure Effects of Vaccines on Infectious Diseases

2019 ◽  
Author(s):  
Tara Gallagher ◽  
Marc Lipsitch
Keyword(s):  
Clinical Trials ◽  
Observational Studies ◽  
Case Fatality ◽  
Hepatitis E ◽  
Vaccine Preventable Diseases ◽  
Post Exposure ◽  
Vaccine Trials ◽  
Tick Borne Encephalitis ◽  
Pubmed Database ◽  
Definition Of

AbstractMany available vaccines have demonstrated post-exposure effectiveness, but no published systematic reviews have synthesized these findings. We searched the PubMed database for clinical trials and observational human studies concerning the post-exposure vaccination effects, targeting infections with an FDA-licensed vaccine plus dengue, hepatitis E, malaria, and tick borne encephalitis, which have licensed vaccines outside of the U.S. Studies concerning animal models, serologic testing, and pipeline vaccines were excluded. Eligible studies were evaluated by definition of exposure, and their attempt at distinguishing pre- and post-exposure effects was rated on a scale of 1-4. We screened 4518 articles and ultimately identified 14 clinical trials and 31 observational studies for this review, amounting to 45 eligible articles spanning 7 of the 28 vaccine-preventable diseases. For secondary attack rate, this body of evidence found the following medians for post-exposure vaccination effectiveness: hepatitis A: 85% (IQR: 28; 5 sources), hepatitis B: 85% (IQR: 22; 5 sources), measles: 83% (IQR: 21; 8 sources), varicella: 67% (IQR: 48; 9 sources), smallpox: 45% (IQR: 39; 4 sources), and mumps: 38% (IQR: 7; 2 sources). For case fatality proportions resulting from rabies and smallpox, the vaccine efficacies had medians of 100% (IQR: 0; 6 sources) and 63% (IQR: 50; 8 sources) post-exposure. Although mainly used for preventive measures, many available vaccines can modify or preclude disease if administered after exposure. This post-exposure effectiveness could be important to consider during vaccine trials and while developing new vaccines.

scholarly journals Guidelines on how to assess the validity of results presented in subgroup analysis of clinical trials

2002 ◽  
Vol 57 (2) ◽  
pp. 83-88 ◽  
Author(s):  
Edson Duarte Moreira ◽  
Ezra Susser
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Randomized Clinical Trial ◽  
Subgroup Analysis ◽  
Observational Studies ◽  
Randomized Clinical Trials ◽  
Usual Method ◽  
Validity Of Results ◽  
Results Of Treatment ◽  
Trial Participants

In observational studies, identification of associations within particular subgroups is the usual method of investigation. As an exploratory method, it is the bread and butter of epidemiological research. Nearly everything that has been learned in epidemiology has been derived from the analysis of subgroups. In a randomized clinical trial, the entire purpose is the comparison of the test subjects and the controls, and when there is particular interest in the results of treatment in a certain section of trial participants, a subgroup analysis is performed. These subgroups are examined to see if they are liable to a greater benefit or risk from treatment. Thus, analyzing patient subsets is a natural part of the process of improving therapeutic knowledge through clinical trials. Nevertheless, the reliability of subgroup analysis can often be poor because of problems of multiplicity and limitations in the numbers of patients studied. The naive interpretation of the results of such examinations is a cause of great confusion in the therapeutic literature. We emphasize the need for readers to be aware that inferences based on comparisons between subgroups in randomized clinical trials should be approached more cautiously than those based on the main comparison. That is, subgroup analysis results derived from a sound clinical trial are not necessarily valid; one must not jump to conclusions and accept the validity of subgroup analysis results without an appropriate judgment.

Statistical analysis plan for evaluating different intensities of blood pressure control in the ENhanced Control of Hypertension And Thrombolysis strokE stuDy

2018 ◽  
Vol 14 (5) ◽  
pp. 555-558 ◽  
Author(s):  
Craig S Anderson ◽  
Mark Woodward ◽  
Hisatomi Arima ◽  
Xiaoying Chen ◽  
Richard I Lindley ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Body Weight ◽  
Statistical Analysis ◽  
Lower Risk ◽  
Standard Dose ◽  
Statistical Analysis Plan ◽  
Symptomatic Intracerebral Hemorrhage ◽  
Stroke Study

Background The ENhanced Control of Hypertension And Thrombolysis strokE study (ENCHANTED) trial was initiated as a 2 × 2 partial-factorial active-comparison, prospective, randomized, open, blinded endpoint clinical trial to evaluate in thrombolysis-eligible acute ischemic stroke (AIS) patients whether: (1) Arm A – low-dose (0.6 mg/kg body weight) intravenous (iv) alteplase has noninferior efficacy and lower risk of symptomatic intracerebral hemorrhage (sICH) compared with standard-dose (0.9 mg/kg body weight) iv alteplase; and (2) Arm B – early intensive blood pressure (BP) lowering (systolic target 130–140 mmHg) has superior efficacy and lower risk of ICH compared with guideline-recommended BP control (systolic target <180 mmHg). Arm A was completed in 2016; Arm B is now concluding. Objective To outline in detail and make public the predetermined statistical analysis plan (SAP) for the ‘BP control’ arm of this study. Methods All data collected by participating researchers will be reviewed and formally assessed. Information pertaining to the baseline characteristics of patients, their process of care, and the delivery of treatments will be outlined, and for each item, statistically relevant descriptive elements will be described. For the trial outcomes, the most appropriate statistical comparisons to be made between groups are planned and described. Results A SAP was developed for the results of the BP control arm of this study that is transparent, available to the public, verifiable, and predetermined before completion of data collection. Conclusions We have developed a predetermined SAP for the ENCHANTED BP control arm to be followed to avoid analysis bias arising from prior knowledge of the study findings. Clinical trial registration ClinicalTrials.gov (NCT01422616); ISRCTN Register (ISRCTN82387104); Australian New Zealand Clinical Trial Registry (ACTRN12611000236998); EU Clinical Trials Register (2011-005545-12); and Clinical Trials Registry – India (REF/2017/05/014334).

Statistical basis of clinical trials

2014 ◽  
Author(s):  
Jeremy Prout ◽  
Tanya Jones ◽  
Daniel Martin
Keyword(s):  
Clinical Trials ◽  
Statistical Analysis ◽  
Observational Study ◽  
Odds Ratio ◽  
Binary Data ◽  
Statistical Significance ◽  
Sample Size Calculation ◽  
Number Needed To Treat ◽  
Drug Trials ◽  
Research Types

This chapter summarizes some aspects of study design and statistical analysis to allow the anaesthetist to appraise research. Types of observational study are described and aspects of interventional studies such as sample size calculation and power are explained. Research governance, phases of drug trials and levels of evidence are described. A section on statistical analysis includes expression of proportion for binary data (odds ratio, number needed to treat) and use of probability and confidence intervals to measure statistical significance.

Novel definition of BCG failure to enhance recruitment into clinical trials.

2013 ◽  
Vol 31 (6_suppl) ◽  
pp. 246-246
Author(s):  
Daniel Levi Willis ◽  
Eugene K. Lee ◽  
Rian J. Dickstein ◽  
Roosevelt Anderson ◽  
Shanna M. Pretzsch ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Trial Design ◽  
Clinical Trial Design ◽  
Prospective Clinical Trial ◽  
Fish Analysis ◽  
Free Survival ◽  
Bcg Therapy ◽  
Bcg Failure ◽  
Definition Of

246 Background: Designing clinical trials after BCG failure can be problematic without a reasonable control arm. Thus, there is a need for early identification of BCG failure relevant to clinical trial design which allows one arm to continue on BCG. Here we present a definition of BCG failure based on FISH profile at 6th week of induction BCG that would facilitate such trials. Methods: The definition presented is based on findings from our IRB-approved, prospective clinical trial where Urovysion FISH assays were performed serially during the normal course of BCG therapy (SWOG protocol) at various time points (pre-BCG, 6 weeks, 3 and 6 mo.). Herein we incorporated the FISH analysis at 6 weeks in patients with a negative 3 month cystoscopy and correlated the result with recurrence and progression rates at 24 months. A novel definition of BCG failure was proposed by focusing the analysis on 84 patients with high grade disease (cTa: 33, cT1: 44, cTis 7). The 6 week FISH was selected as this would allow the control arm to proceed with BCG maintenance in a timely fashion, taking into account the time required for obtaining FISH results, registration of patients, and randomization. Results: Of the 36 patients with a positive FISH at 6 weeks (and no tumor at 3 months), 17 recurred (PPV = 47%) and 11 progressed (PPV = 31%), while among those with a negative FISH, 5 recurred (NPV = 90%) and 4 progressed (NPV = 92%) (p<0.001). Kaplan Meier estimates of recurrence free survival with a positive 6 week FISH were 67% and 52%, and for progression free survival were 75% and 52%, at 1 and 2 years respectively. Therefore, if patients with a positive 6 week FISH (and negative 3 month cystoscopy) were considered as "molecular" BCG failures, a prospective clinical trial with 101 patients in the control (i.e. BCG maintenance) and experimental arms to detect a 20% difference in recurrence rates (α=0.05) with 80% power. Conclusions: Using the FISH status of patients at the 6 week interval on BCG therapy would allow a clinical trial design that incorporates one arm with continued BCG therapy, while enriching for events of interest, namely recurrence and progression. This would allow meaningful comparisons while negating any ethical concerns regarding a lack of “standard treatment” in BCG failure studies.

scholarly journals Recommendations for Supporting Prospective Study Registration in the Basic Experimental Studies in Humans And Alternative Procedures for Results Dissemination

2021 ◽  
Author(s):  
David Thomas Mellor ◽  
Nicole Pfeiffer
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Research Study ◽  
Human Subjects ◽  
Behavioral Outcomes ◽  
Experimental Studies ◽  
Basic Research ◽  
Health Related ◽  
Alternative Procedures ◽  
Definition Of

Recently, the NIH has modified the definition of clinical trial so that it applies to a much broader range of studies that previously were classified as clinical research but not specifically as trials. This definition, below, specifically includes research where behavioral outcomes are a focus of the study: “A research study in which one or more human subjects are prospectively assigned to one or more interventions (which may include placebo or other control) to evaluate the effects of those interventions on health-related biomedical or behavioral outcomes.”With the addition of behavioral outcomes, many studies that previously would not have been “clinical trials” are now so classified. Research studies that meet both criteria for “clinical trial” and “basic research” are now referred to as basic experimental studies in humans (BESH). The purpose of this whitepaper is to analyze and investigate ways that existing infrastructure could be improved to support these new requirements in ways that benefit all stakeholders.

scholarly journals Rate of patient’s Recruitment and Recruitment Derivatives from the Perspectives of Internal factors - Protocol Study Nosology, Experience of Investigators and Potential Patient’s Pool of Sites

2021 ◽  
Vol 2 (2) ◽  
pp. 1-6
Author(s):  
Svyatoslav Milovanov
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Statistical Analysis ◽  
Retrospective Analysis ◽  
Analysis Data ◽  
Recruitment Rate ◽  
Internal Factor ◽  
Internal Factors ◽  
Study Recruitment ◽  
Protocol Study

The recruitment as a process found by many authors to be undergoing of many factors. There is a factors which are decreasing the recruitment and last data is reporting up to 80% trials failed due to law or even absence of recruitment on level of sites. But the factors are differently changing the recruitment. The final number of recruitment is static figure very well known, there is also known speed of recruitment which is calculating in the start of the study and these parameters along with others is quantitative evaluation of recruitment. We investigated the rate of recruitment in the light of some factors using parameters reflecting the recruitment progress of recruitment. Materials and Methods: Retrospective analysis of data of four clinical trials II-III phases in oncology and hematology, conducted since 2007 to 2017 years. Study objectives: to investigate the study recruitment rate using different parameters and its changes along with acting of internal factors; to develop new parameters which could be sensitive for evaluation of factor’s action. Statistical analysis: data had been collected from feasibility questionnaires, open statistical sources. Results: It was determined rate of recruitment and its derivatives where was acting an internal factor. Discussion: Recruitment been undergone the internal factors. The way of action is multidirectional and could boost the recruitment and in opposite to decrease one and knowing it is important in success of recruitment and clinical trial itself eventually

Application of Metadata Repository and Master Data Management in Clinical Trial and Drug Safety

2015 ◽  
pp. 33-46
Author(s):  
Chandrakant Ekkirala
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Data Management ◽  
Drug Safety ◽  
Detailed Explanation ◽  
Master Data ◽  
Master Data Management ◽  
Metadata Repository ◽  
Definition Of

This chapter talks about metadata repository, and master data management in clinical trial and drug safety. The chapter begins with the definition of metadata repository and gives an explanation around the same, It talks about a well designed metadata repository and the characteristics associated with the same. A brief around why we need metadata and the reasons for the using the same has also been mentioned. The benefits of a well structured metadata repository was also mentioned in detail. The chapter then gives a detailed explanation on master data management and the usage of MDM in clinical trials. MDM solutions for clinical trials management is also explained in detail.

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