Leveraging historical data to optimize the number of covariates and their explained variance in the analysis of randomized clinical trials.

2021 ◽  
pp. 096228022110652
Author(s):  
Samuel Branders ◽  
Alvaro Pereira ◽  
Guillaume Bernard ◽  
Marie Ernst ◽  
Jamie Dananberg ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Degrees Of Freedom ◽  
Randomized Clinical Trials ◽  
Historical Data ◽  
Cost Benefit ◽  
Patient Characteristics ◽  
Cost Ratio ◽  
Optimum Number ◽  
Number Of Patients

The amount of data collected from patients involved in clinical trials is continuously growing. All baseline patient characteristics are potential covariates that could be used to improve clinical trial analysis and power. However, the limited number of patients in phases I and II studies restricts the possible number of covariates included in the analyses. In this paper, we investigate the cost/benefit ratio of including covariates in the analysis of clinical trials with a continuous outcome. Within this context, we address the long-running question “What is the optimum number of covariates to include in a clinical trial?” To further improve the benefit/cost ratio of covariates, historical data can be leveraged to pre-specify the covariate weights, which can be viewed as the definition of a new composite covariate. Here we analyze the use of a composite covariate to improve the estimated treatment effect in small clinical trials. A composite covariate limits the loss of degrees of freedom and the risk of overfitting.

scholarly journals Are clinical trial results transferable in the real life?

2016 ◽  
Vol 84 (1-2) ◽  
Author(s):  
Enrico Natale ◽  
Alfiera Marsocci
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Clinical Practice ◽  
Recurrent Events ◽  
Randomized Clinical Trials ◽  
Real Life ◽  
Recurrent Event ◽  
The Real ◽  
Number Of Patients ◽  
Clinical Trial Results

<p>Generally in the clinical practice patients are more complex in comparison with those included in the clinical trials. In this article, we discuss three relevant items, which may implement the transferability of the clinical trial results in the real world. The observational studies have fewer restrictions on the number of patients included, due to more relaxed inclusion and exlusion criteria than in randomized clinical trials. The absence of randomization however may lead to potential for bias. The recurrent event analysis may extend the positive results of clinical trials regarding the reductions of the first primary endpoint event to total events, including those beyond the first event. This analysis is of great interest in the clinical practice, where recurrent events are common. Finally the reliability of subgroup analysis is discussed. Pre-specified subgroup analyses are more credible and valuable than <em>post-hoc</em> analyses.</p><p><strong>Riassunto</strong></p><p>Nella pratica clinica i pazienti sono generalmente più complessi rispetto alle popolazioni studiate nei trial clinici. Si rendono necessari pertanto strumenti di analisi che integrino i trial clinici. In questo articolo vengono esaminati alcuni punti di rilevante importanza nella definizione di una corretta applicabilità dei risultati dei trial clinici al mondo reale. Il primo punto riguarda il ruolo e i limiti degli studi osservazionali. Il secondo tratta delle analisi degli eventi ricorrenti, una modalità di analisi dei trial clinici che rende i risultati più aderenti alla vita reale, nella consapevolezza che limitare i dati di outcome al primo evento sia riduttivo rispetto alla necessità di stabilire che l’intervento studiato nel trial confermi la sua efficacia anche sugli eventi successivi al primo. Il terzo punto riguarda la controversa questione delle analisi per sottogruppi, uno strumento utile per generare ipotesi, ma discutibile quando impiegato per rimediare a trial con risultati negativi o estendere i risultati di trial positivi a sottopopolazioni particolari di pazienti. </p>

scholarly journals A cost/benefit analysis of clinical trial designs for COVID-19 vaccine candidates

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0244418
Author(s):  
Donald A. Berry ◽  
Scott Berry ◽  
Peter Hale ◽  
Leah Isakov ◽  
Andrew W. Lo ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Trial Design ◽  
Time Course ◽  
Randomized Clinical Trials ◽  
Cost Benefit Analysis ◽  
Clinical Trial Design ◽  
Cost Benefit ◽  
Vaccine Candidates ◽  
Net Benefits

We compare and contrast the expected duration and number of infections and deaths averted among several designs for clinical trials of COVID-19 vaccine candidates, including traditional and adaptive randomized clinical trials and human challenge trials. Using epidemiological models calibrated to the current pandemic, we simulate the time course of each clinical trial design for 756 unique combinations of parameters, allowing us to determine which trial design is most effective for a given scenario. A human challenge trial provides maximal net benefits—averting an additional 1.1M infections and 8,000 deaths in the U.S. compared to the next best clinical trial design—if its set-up time is short or the pandemic spreads slowly. In most of the other cases, an adaptive trial provides greater net benefits.

scholarly journals A Cost/Benefit Analysis of Clinical Trial Designs for COVID-19 Vaccine Candidates

2020 ◽  
Author(s):  
Donald Berry ◽  
Scott Berry ◽  
Peter Hale ◽  
Leah Isakov ◽  
Andrew Lo ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Trial Design ◽  
Time Course ◽  
Randomized Clinical Trials ◽  
Cost Benefit Analysis ◽  
Clinical Trial Design ◽  
Cost Benefit ◽  
Vaccine Candidates ◽  
Net Benefits

We compare and contrast the expected duration and number of infections and deaths averted among several designs for clinical trials of COVID-19 vaccine candidates, including traditional randomized clinical trials and adaptive and human challenge trials. Using epidemiological models calibrated to the current pandemic, we simulate the time course of each clinical trial design for 504 unique combinations of parameters, allowing us to determine which trial design is most effective for a given scenario. A human challenge trial provides maximal net benefits---averting an additional 1.1M infections and 8,000 deaths in the U.S. compared to the next best clinical trial design---if its set-up time is short or the pandemic spreads slowly. In most of the other cases, an adaptive trial provides greater net benefits.

scholarly journals Reporting of harms in oncological clinical study reports submitted to the European Medicines Agency compared to trial registries and publications—a methodological review

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Asger S. Paludan-Müller ◽  
Perrine Créquit ◽  
Isabelle Boutron
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Clinical Study ◽  
Primary Source ◽  
European Medicines Agency ◽  
Clinical Trial Registries ◽  
Number Of Patients ◽  
Journal Publications ◽  
Clinical Study Reports ◽  
Completeness Of Reporting

Abstract Background An accurate and comprehensive assessment of harms is a fundamental part of an accurate weighing of benefits and harms of an intervention when making treatment decisions; however, harms are known to be underreported in journal publications. Therefore, we sought to compare the completeness of reporting of harm data, discrepancies in harm data reported, and the delay to access results of oncological clinical trials between three sources: clinical study reports (CSRs), clinical trial registries and journal publications. Methods We used the EMA clinical data website to identify all trials submitted to the EMA between 2015 and 2018. We retrieved all CSRs and included all phase II, II/III or III randomised controlled trials (RCTs) assessing targeted therapy and immunotherapy for cancer. We then identified related records in clinical trial registries and journals. We extracted harms data for eight pre-specified variables and determined the completeness of reporting of harm data in each of the three sources. Results We identified 42 RCTs evaluating 13 different drugs. Results were available on the EMA website in CSRs for 37 (88%) RCTs, ClinicalTrials.gov for 36 (86%), the European Clinical Trials Register (EUCTR) for 20 (48%) and in journal publications for 32 (76%). Harms reporting was more complete in CSRs than other sources. We identified marked discrepancies in harms data between sources, e.g. the number of patients discontinuing due to adverse events differed in CSRs and clinical trial registers for 88% of trials with data in both sources. For CSRs and publications, the corresponding number was 90%. The median (interquartile range) delay between the primary trial completion date and access to results was 4.34 (3.09–7.22) years for CSRs, 2.94 (1.16–4.52) years for ClinicalTrials.gov, 5.39 (4.18–7.33) years for EUCTR and 2.15 (0.64–5.04) years for publications. Conclusions Harms of recently approved oncological drugs were reported more frequently and in more detail in CSRs than in trial registries and journal publications. Systematic reviews seeking to address harms of oncological treatments should ideally use CSRs as the primary source of data; however, due to problems with access, this is currently not feasible.

scholarly journals Clinical trial research on COVID-19 in Germany – a systematic analysis

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 913
Author(s):  
Julian Hirt ◽  
Abeelan Rasadurai ◽  
Matthias Briel ◽  
Pascal Düblin ◽  
Perrine Janiaud ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Research Agenda ◽  
Randomized Clinical Trials ◽  
Median Number ◽  
First Year ◽  
Industry Funding ◽  
Systematic Analysis ◽  
Clinical Trial Research ◽  
German Contribution

Background: In 2020, the COVID-19 pandemic led to an unprecedented volume of almost 3,000 clinical trials registered worldwide. We aimed to describe the COVID-19 clinical trial research agenda in Germany during the first year of the pandemic. Methods: We identified randomized clinical trials assessing interventions to treat or prevent COVID-19 that were registered in 2020 and recruited or planned to recruit participants in Germany. We requested recruitment information from trial investigators as of April 2021. Results: In 2020, 65 trials were completely (n=27) or partially (n=38) conducted in Germany. Most trials investigated interventions to treat COVID-19 (86.2%; 56/65), in hospitalized patients (67.7%; 44/65), with industry funding (53.8%; 35/65). Few trials were completed (21.5%; 14/65). Overall, 187,179 participants were planned to be recruited (20,696 in Germany), with a median number of 106 German participants per trial (IQR 40 to 345).  From the planned German participants, 13.4%  were recruited (median 15 per trial (IQR 0 to 44). Conclusions: The overall German contribution to the worldwide COVID-19 clinical trial research agenda was modest. Few trials delivered urgently needed evidence. Most trials did not meet recruitment goals. Evaluation and international comparison of the challenges for conducting clinical trials in Germany is needed.

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.

Extracorporeal Membrane Oxygenation and the Play the Winner Rule

PEDIATRICS ◽  
1985 ◽  
Vol 76 (4) ◽  
pp. 622-623
Author(s):  
NIGEL PANETH ◽  
SYLVAN WALLENSTEIN
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Extracorporeal Membrane Oxygenation ◽  
Randomized Clinical Trial ◽  
Conventional Treatment ◽  
Randomized Clinical Trials ◽  
Ethical Problem ◽  
Therapeutic Trial ◽  
Membrane Oxygenation ◽  
Treatment Comparisons

The therapeutic trial comparing extracorporeal membrane oxygenation with conventional treatment in neonatal respiratory failure reported by Bartlett et al (Pediatrics 1985;76:479-487) uses a method of comparing treatments unlikely to be familiar to most pediatricians. Known as the "randomized play the winner" method, it has thus far been little used in clinical research. Most clinical investigators consider the conventional randomized clinical trial to be the last word in treatment comparisons. But randomized clinical trials are costly, cumbersome, and to some observers less than ideal ethically. The ethical problem arises from the fact that during a "successful" randomized clinical trial (ie, one that demonstrates a significant advantage to one treatment) about half of the trial subjects will receive a treatment which, at the end of the trial, will be known to be inferior.

Simulation Modeling as a Decision-Making Aid in Economic Evaluation for Randomized Clinical Trials

2011 ◽  
pp. 1738-1758
Author(s):  
Tillal Eldabi ◽  
Robert D. Macredie ◽  
Ray J. Paul
Keyword(s):  
Clinical Trial ◽  
Decision Making ◽  
Clinical Trials ◽  
Economic Evaluation ◽  
Simulation Model ◽  
Randomized Clinical Trial ◽  
Simulation Modeling ◽  
Randomized Clinical Trials ◽  
Healthcare Systems ◽  
Modeling Process

This chapter reports on the use of simulation in supporting decision-making about what data to collect in a randomized clinical trial (RCT). We show how simulation also allows the identification of critical variables in the RCT by measuring their effects on the simulation model’s “behavior.” Healthcare systems pose many of the challenges, including difficulty in understanding the system being studied, uncertainty over which data to collect, and problems of communication between problem owners. In this chapter we show how simulation also allows the identification of critical variables in the RCT by measuring their effects on the simulation model’s “behavior.” The experience of developing the simulation model leads us to suggest simple but extremely valuable lessons. The first relates to the inclusion of stakeholders in the modeling process and the accessibility of the resulting models. The ownership and confidence felt by stakeholders in our case is, we feel, extremely important and may provide an example to others developing models.

scholarly journals Surveillance in inflammatory bowel disease: is chromoendoscopy the only way to go? A systematic review and meta-analysis of randomized clinical trials

2020 ◽  
Vol 08 (05) ◽  
pp. E578-E590
Author(s):  
Ricardo Hannum Resende ◽  
Igor Braga Ribeiro ◽  
Diogo Turiani Hourneaux de Moura ◽  
Facundo Galetti ◽  
Rodrigo Silva de Paula Rocha ◽  
...  
Keyword(s):  
Systematic Review ◽  
Clinical Trials ◽  
Randomized Clinical Trials ◽  
Narrow Band ◽  
Narrow Band Imaging ◽  
Meta Analysis ◽  
Mean Difference ◽  
Procedure Time ◽  
High Definition ◽  
Number Of Patients

Abstract Background and study aims Ulcerative colitis (UC) and Crohn’s disease (CD) have higher risk of colorectal cancer (CRC). Guidelines recommend dysplasia surveillance with dye-spraying chromoendoscopy (DCE). The aim of this systematic review and meta-analysis was to review all randomized clinical trials (RCTs) available and compare the efficacy of different endoscopic methods of surveillance for dysplasia in patients with UC and CD. Methods Databases searched were Medline, EMBASE, Cochrane and SCIELO/LILACS. It was estimated the risk difference (RD) for dichotomous outcomes (number of patients diagnosed with one or more dysplastic lesions, total number of dysplastic lesions diagnosed and number of dysplastic lesions detected by targeted biopsies) and mean difference for continuous outcomes (procedure time). Results This study included 17 RCTs totaling 2,457 patients. There was superiority of DCE when compared to standard-definiton white light endoscopy (SD-WLE). When compared with high-definition (HD) WLE, no difference was observed in all outcomes (number of patients with dysplasia (RD 0.06; 95 % CI [–0.01, 0.13])). Comparing other techniques, no difference was observed between DCE and virtual chromoendoscopy (VCE – including narrow-band imaging [NBI], i-SCAN and flexible spectral imaging color enhancement), in all outcomes except procedure time (mean difference, 6.33 min; 95 % CI, 1.29, 11.33). DCE required a significantly longer procedure time compared with WLE (mean difference, 7.81 min; 95 % CI, 2.76, 12.86). Conclusions We found that dye-spraying chromoendoscopy detected more patients and dysplastic lesions than SD-WLE. Although no difference was observed between DCE and HD-WLE or narrow-band imaging, the main outcomes favored numerically dye-spraying chromoendoscopy, except procedure time. Regarding i-SCAN, FICE and auto-fluorescence imaging, there is still not enough evidence to support or not their recommendation.

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