Treatment effects may remain the same even when trial participants differed from the target population

Bradburn, Mike; Lee, Ellen Cecilia; White, David; Hind, Daniel; Waugh, Norman; Cooke, Dennis; Hopkins, David; Mansell, Peter; Heller, Simon

doi:10.1016/j.jclinepi.2020.05.001

Cited by 12 publications

(5 citation statements)

References 67 publications

(87 reference statements)

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“…Representativeness in clinical trials has been debated, and providing the mechanism through which treatment is effective is constant, there is no reason to suspect that the relative effect of treatment will be different between different disease aetiologies. It is likely however that the absolute risks of decompensation, and therefore the absolute risk reductions for a constant relative treatment effect, will vary according to disease aetiology 40,41 …”

Section: Discussionmentioning

confidence: 99%

“…It is likely however that the absolute risks of decompensation, and therefore the absolute risk reductions for a constant relative treatment effect, will vary according to disease aetiology. [40,41] The microsimulation studies done to parallel the Bayesian analyses suggest that we should begin to consider treatments in compensated cirrhosis as risk reduction therapies, analogous to those given to prevent cardiovascular disease events in patients at high risk. [29] The delay of decompensation is a clinically important goal in the natural history of cirrhosis, and considering therapy as reducing risk rather than as a "cure" of liver disease represents an important shift in the thinking that might inform the development of future treatment strategies and clinical trials.…”

Section: Implications For Clinical Practicementioning

confidence: 99%

See 1 more Smart Citation

Quantifying the benefit of nonselective beta-blockers in the prevention of hepatic decompensation: A Bayesian reanalysis of the PREDESCI trial

Rowe¹,

Villanueva²,

Shearer³

et al. 2023

Hepatology

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Background and Aims: Beta-blockers have been studied for the prevention of variceal bleeding and, more recently, for the prevention of all-cause decompensation. Some uncertainties regarding the benefit of beta-blockers for the prevention of decompensation remain. Bayesian analyses enhance the interpretation of trials. The purpose of this study was to provide clinically meaningful estimates of both the probability and magnitude of the benefit of beta-blocker treatment across a range of patient types.

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Section: Discussionmentioning

confidence: 99%

Section: Implications For Clinical Practicementioning

confidence: 99%

Quantifying the benefit of nonselective beta-blockers in the prevention of hepatic decompensation: A Bayesian reanalysis of the PREDESCI trial

Rowe¹,

Villanueva²,

Shearer³

et al. 2023

Hepatology

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“…The statistical model of analyses, prespecified in the experimental design, can then allow for different between-treatment effects in the two HER2 subgroups. Similarly, when there is a mechanistic rationale for investigating interactions between treatment and certain baseline patient covariates, such as sex or race, statistical inferences should be based on a prespecified regression model that includes such interactions [2,8,130]. For example, inferences may consider different between-treatment effects for male and female patients.…”

Section: Representativeness and Inclusivenessmentioning

confidence: 99%

Interpreting Randomized Controlled Trials

Msaouel,

Lee,

Thall

2023

Cancers

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This article describes rationales and limitations for making inferences based on data from randomized controlled trials (RCTs). We argue that obtaining a representative random sample from a patient population is impossible for a clinical trial because patients are accrued sequentially over time and thus comprise a convenience sample, subject only to protocol entry criteria. Consequently, the trial’s sample is unlikely to represent a definable patient population. We use causal diagrams to illustrate the difference between random allocation of interventions within a clinical trial sample and true simple or stratified random sampling, as executed in surveys. We argue that group-specific statistics, such as a median survival time estimate for a treatment arm in an RCT, have limited meaning as estimates of larger patient population parameters. In contrast, random allocation between interventions facilitates comparative causal inferences about between-treatment effects, such as hazard ratios or differences between probabilities of response. Comparative inferences also require the assumption of transportability from a clinical trial’s convenience sample to a targeted patient population. We focus on the consequences and limitations of randomization procedures in order to clarify the distinctions between pairs of complementary concepts of fundamental importance to data science and RCT interpretation. These include internal and external validity, generalizability and transportability, uncertainty and variability, representativeness and inclusiveness, blocking and stratification, relevance and robustness, forward and reverse causal inference, intention to treat and per protocol analyses, and potential outcomes and counterfactuals.

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“…Age, place of residence, cultural sensitivities, digital gap and issues of literacy and language are mentioned among barriers to participation in biobanks (Prictor, Teare, and Kaye 2018 ). ‘Volunteer effect’ is another reason for recruitment bias; those who decide to volunteer may differ in some important traits compared with those who do not volunteer (Fry et al 2017 , Bradburn et al 2020 ). Recruitment bias infringes on the principle of justice, influences representativity of biobank collections and has implications for the generalizability of research results and ability to reach full statistical power.…”

Section: Typology Of Risksmentioning

confidence: 99%

Biobanking and risk assessment: a comprehensive typology of risks for an adaptive risk governance

Akyüz

Chassang

Goisauf

et al. 2021

Life Sci Soc Policy

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Biobanks act as the custodians for the access to and responsible use of human biological samples and related data that have been generously donated by individuals to serve the public interest and scientific advances in the health research realm. Risk assessment has become a daily practice for biobanks and has been discussed from different perspectives. This paper aims to provide a literature review on risk assessment in order to put together a comprehensive typology of diverse risks biobanks could potentially face. Methodologically set as a typology, the conceptual approach used in this paper is based on the interdisciplinary analysis of scientific literature, the relevant ethical and legal instruments and practices in biobanking to identify how risks are assessed, considered and mitigated. Through an interdisciplinary mapping exercise, we have produced a typology of potential risks in biobanking, taking into consideration the perspectives of different stakeholders, such as institutional actors and publics, including participants and representative organizations. With this approach, we have identified the following risk types: economic, infrastructural, institutional, research community risks and participant’s risks. The paper concludes by highlighting the necessity of an adaptive risk governance as an integral part of good governance in biobanking. In this regard, it contributes to sustainability in biobanking by assisting in the design of relevant risk management practices, where they are not already in place or require an update. The typology is intended to be useful from the early stages of establishing such a complex and multileveled biomedical infrastructure as well as to provide a catalogue of risks for improving the risk management practices already in place.

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Treatment effects may remain the same even when trial participants differed from the target population

Abstract: Please refer to published version for the most recent bibliographic citation information. If a published version is known of, the repository item page linked to above, will contain details on accessing it.

Cited by 12 publications

References 67 publications

Quantifying the benefit of nonselective beta-blockers in the prevention of hepatic decompensation: A Bayesian reanalysis of the PREDESCI trial

Quantifying the benefit of nonselective beta-blockers in the prevention of hepatic decompensation: A Bayesian reanalysis of the PREDESCI trial

Interpreting Randomized Controlled Trials

Biobanking and risk assessment: a comprehensive typology of risks for an adaptive risk governance

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