Underestimation of treatment effects in sequentially monitored clinical trials that did not stop early for benefit

2018 ◽  
Vol 28 (10-11) ◽  
pp. 3027-3041 ◽  
Author(s):  
Ian C Marschner ◽  
I Manjula Schou
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Treatment Effect ◽  
Interim Analysis ◽  
Experimental Treatment ◽  
Final Analysis ◽  
Effect Estimate ◽  
Effectiveness Analysis ◽  
Simulation Results ◽  
Meta Analyses

In recent years, there has been a prominent discussion in the literature about the potential for overestimation of the treatment effect when a clinical trial stops at an interim analysis due to the experimental treatment showing a benefit over the control. However, there has been much less attention paid to the converse issue, namely, that sequentially monitored clinical trials which did not stop early for benefit tend to underestimate the treatment effect. In meta-analyses of many studies, these two sources of bias will tend to balance each other to produce an unbiased estimate of the treatment effect. However, for the interpretation of a single study in isolation, underestimation due to interim analysis may be an important consideration. In this paper, we discuss the nature of this underestimation, including theoretical and simulation results demonstrating that it can be substantial in some contexts. Furthermore, we show how a conditional approach to estimation, in which we condition on the study reaching its final analysis, may be used to validly inflate the observed treatment difference from a sequentially monitored clinical trial. Expressions for the conditional bias and information are derived, and these are used in supplied R code that computes the bias-adjusted estimate and an associated confidence interval. As well as simulation results demonstrating the validity of the methods, we present a data analysis example from a pivotal clinical trial in cardiovascular disease. The methods will be most useful when an unbiased treatment effect estimate is critical, such as in cost-effectiveness analysis or risk prediction.

scholarly journals Postpartum Haemorrhage in Anaemic Women: Assessing Outcome Measures for Clinical Trials

2021 ◽  
Author(s):  
Amy Charlotte Brenner ◽  
Ian Roberts ◽  
Eni Balogun ◽  
Folasade Adenike Bello ◽  
Rizwana Chaudhri ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Blood Loss ◽  
Clinical Diagnosis ◽  
Outcome Measures ◽  
Treatment Effect ◽  
Primary Outcome ◽  
Effect Estimate ◽  
Shock Index ◽  
Estimated Blood Loss

Abstract Background: Post-partum haemorrhage (PPH) is a leading cause of maternal mortality worldwide. Maternal anaemia greatly increases the risk of PPH and over a third of all pregnant women are anaemic. Because anaemia reduces the oxygen-carrying capacity of the blood, anaemic women cannot tolerate the same volume of blood loss as healthy women. Yet the same blood loss threshold is used to define PPH in all women. The lack of an established PPH definition in anaemic women means the most appropriate outcome measures for use in clinical trials are open to question. We used data from the WOMAN-2 trial to examine different definitions of PPH in anaemic women and consider their appropriateness as clinical trial outcome measures. Main body: The WOMAN-2 trial is assessing tranexamic acid (TXA) for PPH prevention in women with moderate or severe anaemia at baseline. To obtain an accurate, precise estimate of the treatment effect, outcome measures should be highly specific and reasonably sensitive. Some outcome misclassification is inevitable. Low sensitivity reduces precision, but low specificity biases the effect estimate towards the null. Outcomes should also be related to how patients feel, function, or survive. The primary outcome in the WOMAN-2 trial, a ‘clinical diagnosis of PPH’, is defined as estimated blood loss >500 ml or any blood loss within 24 hours sufficient to compromise haemodynamic stability. To explore the utility of several PPH outcome measures, we analysed blinded data from 4,521 participants. For each outcome, we assessed its: 1) frequency, 2) specificity for significant bleeding defined as shock index ≥1.0, and 3) association with fatigue (modified fatigue symptom inventory [MFSI]), physical endurance (six-minute walk test) and breathlessness. A clinical diagnosis of PPH was sufficiently frequent (7%), highly specific for clinical signs of early shock (95% specificity for shock index ≥1) and associated with worse maternal functioning after childbirth.Conclusion: Outcome measures in clinical trials of interventions for PPH prevention should facilitate valid and precise estimation of the treatment effect and be important to women. A clinical diagnosis of PPH appears to meet these criteria, making it an appropriate primary outcome for the WOMAN-2 trial.Clinical trial registration: ClinicalTrials.gov NCT03475342, registered on 23 March 2018; ISRCTN62396133, registered on 7 December 2017; Pan African Clinical Trial Registry PACTR201909735842379, registered on 18 September 2019.

scholarly journals Estimands: bringing clarity and focus to research questions in clinical trials

BMJ Open ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. e052953
Author(s):  
Timothy Peter Clark ◽  
Brennan C Kahan ◽  
Alan Phillips ◽  
Ian White ◽  
James R Carpenter
Keyword(s):  
Clinical Trial ◽  
Sensitivity Analysis ◽  
Clinical Trials ◽  
Clinical Research ◽  
Recent Work ◽  
Treatment Effect ◽  
Research Question ◽  
Probability Of Success ◽  
Research Questions

Precise specification of the research question and associated treatment effect of interest is essential in clinical research, yet recent work shows that they are often incompletely specified. The ICH E9 (R1) Addendum on Estimands and Sensitivity Analysis in Clinical Trials introduces a framework that supports researchers in precisely and transparently specifying the treatment effect they aim to estimate in their clinical trial. In this paper, we present practical examples to demonstrate to all researchers involved in clinical trials how estimands can help them to specify the research question, lead to a better understanding of the treatment effect to be estimated and hence increase the probability of success of the trial.

scholarly journals Impact of informative censoring on the treatment effect estimate of disability worsening in multiple sclerosis clinical trials

2020 ◽  
Vol 39 ◽  
pp. 101865
Author(s):  
Katherine Riester ◽  
Ludwig Kappos ◽  
Krzysztof Selmaj ◽  
Stacy Lindborg ◽  
Ilya Lipkovich ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Clinical Trials ◽  
Treatment Effect ◽  
Informative Censoring ◽  
Effect Estimate ◽  
Treatment Effect Estimate

scholarly journals Transparency in clinical trials

2021 ◽  
Author(s):  
ChS Pavlov ◽  
DL Varganova ◽  
AA Svistunov ◽  
C Gluud
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Technology Development ◽  
Personal Data ◽  
Clinical Trial Data ◽  
Trial Data ◽  
Positive Effects ◽  
The World ◽  
Information Technology Development ◽  
Meta Analyses

In the age of information technology development, healthcare professionals around the world have the opportunity to simultaneously access advanced scientific developments, modern achievements, and the results of new clinical trials. The clinical guidelines of the international medical communities are based on the results of meta-analyses of clinical trial data. As new medical challenges emerge, clinical trial data are reviewed and re-analyzed. Unfortunately, to date, the results of not all studies are made public, or are presented selectively, indicating the positive effects of a particular technology (intervention), which makes it difficult to critically evaluate the results of work and makes the task of assessing the true effectiveness of the intervention more difficult. The problem of transparency of research data with the preservation of personal data of participants remains relevant for decades. This article is focused on possible ways of solving this problem and the analysis of the current situation in the world.

scholarly journals An investigation into the impact and implications of published papers from retracted research: systematic search of affected literature

BMJ Open ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. e031909 ◽  
Author(s):  
Alison Avenell ◽  
Fiona Stewart ◽  
Andrew Grey ◽  
Greg Gamble ◽  
Mark Bolland
Keyword(s):  
Systematic Review ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Research Misconduct ◽  
Evidence Base ◽  
Bibliographic Databases ◽  
Potential Influence ◽  
Relevant Research ◽  
Meta Analyses ◽  
The Impact

ObjectiveAnalyses of the impact of a body of clinical trial reports subject to research misconduct have been few. Our objective was to examine the impact on clinically relevant research of a group of researchers’ trial reports (‘affected trial reports’) affected by research misconduct, and whether identification of misconduct invoked a reappraisal.DesignIn 2016, we used five databases and search engines to identify ‘citing publications’, that is, guidelines, systematic and other reviews, and clinical trials citing any of 12 affected trial reports, published 1998–2011, eventually retracted for research misconduct. The affected trial reports were assessed more likely to have had impact because they had hip fracture outcomes and were in journals with impact factor >4. Two authors assessed whether findings of the citing publications would change if the affected trial reports were removed. In 2018, we searched for evidence that the citing publications had undertaken a reassessment as a result of the potential influence of the affected trial reports.ResultsBy 2016 the affected trial reports were cited in 1158 publications, including 68 systematic reviews, meta-analyses, narrative reviews, guidelines and clinical trials. We judged that 13 guidelines, systematic or other reviews would likely change their findings if the affected trial reports were removed, and in another eight it was unclear if findings would change. By 2018, only one of the 68 citing publications, a systematic review, appeared to have undertaken a reassessment, which led to a correction.ConclusionsWe found evidence that this group of affected trial reports distorted the evidence base. Correction of these distortions is slow, uncoordinated and inconsistent. Unless there is a rapid, systematic, coordinated approach by bibliographic databases, authors, journals and publishers to mitigate the impact of known cases of research misconduct, patients, other researchers and their funders may continue to be adversely affected.

scholarly journals How should systematic reviewers handle conference abstracts? A view from the trenches

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Roberta W. Scherer ◽  
Ian J. Saldanha
Keyword(s):  
Systematic Reviews ◽  
Treatment Effect ◽  
Meta Analysis ◽  
Good Practice ◽  
Effect Estimate ◽  
Main Body ◽  
Unpublished Studies ◽  
Study Results ◽  
Meta Analyses ◽  
Positive Results

Abstract Background While identifying and cataloging unpublished studies from conference proceedings is generally recognized as a good practice during systematic reviews, controversy remains whether to include study results that are reported in conference abstracts. Existing guidelines provide conflicting recommendations. Main body The main argument for including conference abstracts in systematic reviews is that abstracts with positive results are preferentially published, and published sooner, as full-length articles compared with other abstracts. Arguments against including conference abstracts are that (1) searching for abstracts is resource-intensive, (2) abstracts may not contain adequate information, and (3) the information in abstracts may not be dependable. However, studies comparing conference abstracts and fully published articles of the same study find only minor differences, usually with conference abstracts presenting preliminary results. Other studies that have examined differences in treatment estimates of meta-analyses with and without conference abstracts report changes in precision, but usually not in the treatment effect estimate. However, in some cases, including conference abstracts has made a difference in the estimate of the treatment effect, not just its precision. Instead of arbitrarily deciding to include or exclude conference abstracts in systematic reviews, we suggest that systematic reviewers should consider the availability of evidence informing the review. If available evidence is sparse or conflicting, it may be worthwhile to search for conference abstracts. Further, attempts to contact authors of abstracts or search for protocols or trial registers to supplement the information presented in conference abstracts is prudent. If unique information from conference abstracts is included in a meta-analysis, a sensitivity analysis with and without the unique results should be conducted. Conclusions Under given circumstances, it is worthwhile to search for and include results from conference abstracts in systematic reviews.

scholarly journals Number of Patients per Cohort and Sample Size Considerations Using Dose Escalation with Overdose Control

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Mourad Tighiouart ◽  
André Rogatko
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Phase I ◽  
Sample Size ◽  
Dose Escalation ◽  
Experimental Treatment ◽  
Maximum Tolerated Dose ◽  
Phase I Clinical Trials ◽  
Number Of Patients ◽  
Therapeutic Doses

The main objective of cancer phase I clinical trials is to determine a maximum tolerated dose (MTD) of a new experimental treatment. In practice, most of these trials are designed so that three patients per cohort are treated at the same dose level. In this paper, we compare the safety and efficiency of trials using the escalation with overdose control (EWOC) scheme designed with three or only one patient per cohort. We show through simulations that the number of patients per cohort does not impact the proportion of patients given therapeutic doses, safety of the trial, and efficiency of the estimate of the MTD. Additionally, we present guidelines and tabulated values on the number of patients needed to design a phase I cancer clinical trial using EWOC to achieve a given accuracy of the estimate of the MTD.

scholarly journals ANALYZING DIFFERENCES IN THE COSTS OF TREATMENT ACROSS CENTERS WITHIN ECONOMIC EVALUATIONS

2001 ◽  
Vol 17 (2) ◽  
pp. 155-163 ◽  
Author(s):  
Douglas Coyle ◽  
Michael F. Drummond
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
New Technology ◽  
Clinical Trial Design ◽  
Experimental Treatment ◽  
Economic Evaluations ◽  
Hospital Practice ◽  
Health Technologies ◽  
The United Kingdom ◽  
Study Results

Objectives: Assessments of health technologies increasingly include economic evaluations conducted alongside clinical trials. One particular concern with economic evaluations conducted alongside clinical trials is the generalizability of results from one setting to another. Much of the focus relating to this topic has been on the generalizability of results between countries. However, the characteristics of clinical trial design require further consideration of the generalizability of cost data between centers within a single country, which could be important in decisions about adoption of the new technology.Methods: We used data from a multicenter clinical trial conducted in the United Kingdom to assess the degree of variation in costs between patients and between treatment centers and the determinants of the degree of such variation.Results: The variation between patients was statistically significant for both the experimental and conventional treatments. However, the degree of variation between centers was only statistically significant for the experimental treatment. Such variation appeared to be a result of hospital practice, such as payment mechanisms for staff and provision of hostel accommodation, rather than variations in physical resource use or substantive differences in cost structure.Conclusions: Multicenter economic evaluations are necessary for determining the variations in hospital practice and characteristics that can in turn determine the generalizability of study results to other settings. Such analyses can identify issues that may be important in adopting a new health technology. Analysis is required of similar large multicenter trials to confirm these conclusions.

scholarly journals Key components and IT assistance of participant management in clinical research: a scoping review

JAMIA Open ◽  
2020 ◽  
Vol 3 (3) ◽  
pp. 449-458
Author(s):  
Johannes Pung ◽  
Otto Rienhoff
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Clinical Research ◽  
Computer Assisted ◽  
Trial Participant ◽  
Comprehensive Overview ◽  
Definition Of ◽  
Meta Analyses ◽  
Assisted Management ◽  
Trial Participants

Abstract Objectives Managing participants and their data are fundamental for the success of a clinical trial. Our review identifies and describes processes that deal with management of trial participants and highlights information technology (IT) assistance for clinical research in the context of participant management. Methods A scoping literature review design, based on the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement, was used to identify literature on trial participant-related proceedings, work procedures, or workflows, and assisting electronic systems. Results The literature search identified 1329 articles of which 111 were included for analysis. Participant-related procedures were categorized into 4 major trial processes: recruitment, obtaining informed consent, managing identities, and managing administrative data. Our results demonstrated that management of trial participants is considered in nearly every step of clinical trials, and that IT was successfully introduced to all participant-related areas of a clinical trial to facilitate processes. Discussion There is no precise definition of participant management, so a broad search strategy was necessary, resulting in a high number of articles that had to be excluded. Nevertheless, this review provides a comprehensive overview of participant management-related components, which was lacking so far. The review contributes to a better understanding of how computer-assisted management of participants in clinical trials is possible.

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