scholarly journals The trade-off between impartiality and freedom in the 21st Century Cures Act

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
David Fraile Navarro ◽  
Niccolò Tempini ◽  
David Teira

Randomized controlled trials test new drugs using various debiasing devices to prevent participantsfrom manipulating the trials. But participants often dislike controls, arguing that they impose apaternalist constraint on their legitimate preferences. The 21st Century Cures Act, passed by USCongress in 2016, encourages the Food and Drug Administration to use alternative testing methods,incorporating participants’ preferences, for regulatory purposes. We discuss, from a historicalperspective, the trade-off between trial impartiality and participants’ freedom. We argue that the onlyway out is considering which methods improve upon the performance of conventional trials inkeeping dangerous or inefficacious compounds out of pharmaceutical markets.

Author(s):  
Mical Paul ◽  
Stephan Harbarth ◽  
Angela Huttner ◽  
Guy E Thwaites ◽  
Ursula Theuretzbacher ◽  
...  

Abstract Randomized controlled trials (RCTs) conducted by the industry are expensive, especially trials conducted for registration of new drugs for multidrug-resistant (MDR) bacteria. Lower-cost investigator-initiated trials have recently been successful in recruiting patients with severe infections caused by MDR bacteria. In this personal viewpoint, we contrast the aims, methods and resulting costs of industry-led and investigator-initiated trials and ask whether contemporary registration trial costs are justified. Contract research organizations, delivering and monitoring industry-sponsored trials at a significant cost, have little incentive to make trials more efficient or less expensive. The value of universal monitoring of all trial data is questionable. We propose that clinical trial networks play a more influential role in RCT design and planning, lead adaptive risk-based trial monitoring, and work with the industry to maximize efficient recruitment and lower costs in registration trials for the approval of new antimicrobials.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lajos Katona ◽  
István Bitter ◽  
Pál Czobor

AbstractRandomized controlled trials (RCTs) have been considered as gold standard for establishing the efficacy and safety of investigational new drugs; nonetheless, the generalizability of their findings has been questioned. To address this issue, an increasing number of naturalistic studies and real-world database analyses have been conducted. The question of how much information from these two approaches is congruent or discrepant with each other is of great importance for the clinical practice. To answer this question, we focused on data from the antipsychotic (AP) treatment of schizophrenia. Our aim was two-fold: to conduct a meta-analysis of real-world studies (RWS), and to compare the results of RWS meta-analysis with previously published meta-analyses of RCTs. The principal measure of effectiveness was all-cause treatment discontinuation for both RWS and RCTs (when not available, then drop out for RCTs). We included publications for 8 selected APs (oral formulations of amisulpride, aripiprazole, clozapine, haloperidol, olanzapine, quetiapine, risperidone, and long-acting injectable (LAI) risperidone). We identified 11 RWS and 7 RCT meta-analyses for inclusion. Our results indicated that the RWS yielded statistically conclusive and consistent findings across individual investigations. For the overwhelming majority of the comparisons where both RWS and RCT meta-analyses were available, there was good congruency between the RWS and the RCT results. Our results support that RCTs, despite their limitations, provide evidence which is generalizable to real-world settings. This is an important finding for both regulators and clinicians. RWS can provide guidance for situations where no evidence is available from double-blind clinical trials.


2017 ◽  
Vol 53 (4) ◽  
pp. 724-731 ◽  
Author(s):  
Nigel E Drury ◽  
Akshay J Patel ◽  
Nicola K Oswald ◽  
Cher-Rin Chong ◽  
John Stickley ◽  
...  

Methodology ◽  
2017 ◽  
Vol 13 (2) ◽  
pp. 41-60
Author(s):  
Shahab Jolani ◽  
Maryam Safarkhani

Abstract. In randomized controlled trials (RCTs), a common strategy to increase power to detect a treatment effect is adjustment for baseline covariates. However, adjustment with partly missing covariates, where complete cases are only used, is inefficient. We consider different alternatives in trials with discrete-time survival data, where subjects are measured in discrete-time intervals while they may experience an event at any point in time. The results of a Monte Carlo simulation study, as well as a case study of randomized trials in smokers with attention deficit hyperactivity disorder (ADHD), indicated that single and multiple imputation methods outperform the other methods and increase precision in estimating the treatment effect. Missing indicator method, which uses a dummy variable in the statistical model to indicate whether the value for that variable is missing and sets the same value to all missing values, is comparable to imputation methods. Nevertheless, the power level to detect the treatment effect based on missing indicator method is marginally lower than the imputation methods, particularly when the missingness depends on the outcome. In conclusion, it appears that imputation of partly missing (baseline) covariates should be preferred in the analysis of discrete-time survival data.


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