scholarly journals What type of clinical evidence is needed to assess medical devices?

2016 ◽  
Vol 25 (141) ◽  
pp. 259-265 ◽  
Author(s):  
Rosanna Tarricone ◽  
Paola Roberta Boscolo ◽  
Patrizio Armeni
Keyword(s):  
Medical Therapy ◽  
Real World ◽  
Clinical Evidence ◽  
Experimental Studies ◽  
Bias Reduction ◽  
Economic Evaluations ◽  
Real World Data ◽  
Relevant Evidence ◽  
Randomised Controlled ◽  
Matching Techniques

The objective of this mini-review is to discuss the role of real-world studies as a source of clinical evidence when experimental studies, such as randomised controlled trials (RCTs), are not available. Waiting for RCT evidence when the technology is diffusing could be anti-economical, inefficient from the policy perspective and methodologically questionable.We explain how real-world studies could provide relevant evidence to decision makers. Matching techniques are discussed as a viable solution for bias reduction.We describe a case study concerning a cost-effectiveness analysis based on real-world data of a technology already in use: Mitraclip combined with medical therapy versus medical therapy alone in patients with moderate-to-severe mitral regurgitation. The CEA has encountered the scepticism of most reviewers, due not to the statistical methodology but to the fact that the study was observational and not experimental. Editors and reviewers converged in considering real-world economic evaluations premature in the absence of a RCT, even if in the meantime the technology had been implanted >30 000 times. We believe there is a need to acknowledge the importance of real-world studies, and engage the scientific community in the promotion and use of clinical evidence produced through observational studies.

scholarly journals The Value of Real-World Data in Understanding Prostate Cancer Risk and Improving Clinical Care: Examples from Swedish Registries

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 875
Author(s):  
Kerri Beckmann ◽  
Hans Garmo ◽  
Ingela Franck Lissbrant ◽  
Pär Stattin
Keyword(s):  
Prostate Cancer ◽  
Real World ◽  
Clinical Care ◽  
Prostate Cancer Risk ◽  
Real World Data ◽  
Level Of Evidence ◽  
World Data ◽  
Cancer Data ◽  
Using Data ◽  
Randomised Controlled

Real-world data (RWD), that is, data from sources other than controlled clinical trials, play an increasingly important role in medical research. The development of quality clinical registers, increasing access to administrative data sources, growing computing power and data linkage capacities have contributed to greater availability of RWD. Evidence derived from RWD increases our understanding of prostate cancer (PCa) aetiology, natural history and effective management. While randomised controlled trials offer the best level of evidence for establishing the efficacy of medical interventions and making causal inferences, studies using RWD offer complementary evidence about the effectiveness, long-term outcomes and safety of interventions in real-world settings. RWD provide the only means of addressing questions about risk factors and exposures that cannot be “controlled”, or when assessing rare outcomes. This review provides examples of the value of RWD for generating evidence about PCa, focusing on studies using data from a quality clinical register, namely the National Prostate Cancer Register (NPCR) Sweden, with longitudinal data on advanced PCa in Patient-overview Prostate Cancer (PPC) and data linkages to other sources in Prostate Cancer data Base Sweden (PCBaSe).

Sodium-glucose transporter 2 inhibition and cardiovascular events in patients with diabetes: information from clinical trials and observational real-world data

2018 ◽  
Vol 132 (18) ◽  
pp. 2003-2012 ◽  
Author(s):  
Giulia Ferrannini ◽  
Lars Rydén
Keyword(s):  
Real World ◽  
Glucose Transporter ◽  
Sglt2 Inhibitors ◽  
European Medicines Agency ◽  
Real World Data ◽  
Glucose Transporter 2 ◽  
Patients With Diabetes ◽  
Cv Disease ◽  
Intervention Trials ◽  
Randomised Controlled

Cardiovascular (CV) disease (CVD) is the main cause of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM). Despite optimal glycaemic control, standard antihyperglycaemic therapy failed to impact CV events in intervention trials; therefore, the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA) issued a guidance to the pharmaceutical industry to specifically assess the CV outcomes and safety of new glucose-lowering drugs. Amongst them, sodium-glucose transporter 2 (SGLT2) inhibitors proved to not only provide good tolerance, few adverse effects, and good glycometabolic control, but also striking reduction in the risk of CV events. In this review, data from the main randomised controlled trials are presented, including post-hoc analyses looking into several aspects of CV protection. Moreover, the main findings from observational real-world studies to date are described, overall reassuring as regards to CV safety and efficacy of SGLT2 inhibitors. Finally, several mechanisms which might contribute to the cardioprotective effect of SGLT2 inhibition are depicted, including findings from recent mechanistic studies.

scholarly journals The Expanding Role of Real-World Evidence Trials in Health Care Decision Making

2019 ◽  
Vol 14 (1) ◽  
pp. 174-179 ◽  
Author(s):  
David C. Klonoff
Keyword(s):  
Real World ◽  
Clinical Evidence ◽  
Real World Data ◽  
Medical Products ◽  
Advantages And Disadvantages ◽  
Randomized Controlled ◽  
Real World Evidence ◽  
Care Decision

Real-world evidence (RWE) is the clinical evidence about benefits or risks of medical products derived from analyzing real world data (RWD), which are data collected through routine clinical practice. This article discusses the advantages and disadvantages of RWE studies, how these studies differ from randomized controlled trials (RCTs), how to overcome barriers to current skepticism about RWE, how FDA is using RWE, how to improve the quality of RWE, and finally the future of RWE trials.

scholarly journals Protocol for data extraction: how real-world data have been used in the National Institute for Health and Care Excellence appraisals of cancer therapy

BMJ Open ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. e055985
Author(s):  
Jiyeon Kang ◽  
John Cairns
Keyword(s):  
Real World ◽  
Data Extraction ◽  
Systematic Research ◽  
London School ◽  
Real World Data ◽  
World Data ◽  
Data Extraction Tool ◽  
Potential Benefits ◽  
Critical Components ◽  
Randomised Controlled

IntroductionDue to the limitations of relying on randomised controlled trials, the potential benefits of real-world data (RWD) in enriching evidence for health technology assessment (HTA) are highlighted. Despite increased interest in RWD, there is limited systematic research investigating how RWD have been used in HTA. The main purpose of this protocol is to extract relevant data from National Institute for Health and Care Excellence (NICE) appraisals in a transparent and reproducible manner in order to determine how NICE has incorporated a broader range of evidence in the appraisal of oncology medicines.Methods and analysisThe appraisals issued between January 2011 and May 2021 are included following inclusion criteria. The data extraction tool newly developed for this research includes the critical components of economic evaluation. The information is extracted from identified appraisals in accordance with extraction rules. The data extraction tool will be validated by a second researcher independently. The extracted data will be analysed quantitatively to investigate to what extent RWD have been used in appraisals. This is the first protocol to enable data to be extracted comprehensively and systematically in order to review the use of RWD.Ethics and disseminationThis study is approved by the Ethics Committee of the London School of Hygiene and Tropical Medicine on 14 November 2019 (17315). Results will be published in peer-reviewed journals.

Estimating the Critical Parameter in Almost Stochastic Dominance from Insurance Deductibles

2020 ◽  
Author(s):  
Yi-Chieh Huang ◽  
Kamhon Kan ◽  
Larry Y. Tzeng ◽  
Kili C. Wang
Keyword(s):  
Real World ◽  
Upper Bound ◽  
Stochastic Dominance ◽  
Critical Parameter ◽  
Experimental Studies ◽  
Decision Makers ◽  
The Other ◽  
Real World Data ◽  
Upper Bound Estimate ◽  
Almost Stochastic Dominance

Knowing how small a violation of stochastic dominance rules would be accepted by most individuals is a prerequisite to applying almost stochastic dominance criteria. Unlike previous laboratory-experimental studies, this paper estimates an acceptable violation of stochastic dominance rules with 939,690 real world data observations on a choice of deductibles in automobile theft insurance. We find that, for all policyholders in the sample who optimally chose a low deductible, the upper bound estimate of the acceptable violation ratio is 0.0014, which is close to zero. On the other hand, considering that most decision makers, such as 99% (95%) of the policyholders in the sample, optimally chose the low deductible, the upper bound estimate of the acceptable violation ratio is 0.0405 (0.0732). Our results provide reference values for the acceptable violation ratio for applying almost stochastic dominance rules. This paper was accepted by Manel Baucells, decision analysis.

scholarly journals A systematic review of ICD complications in randomised controlled trials versus registries: is our ‘real-world’ data an underestimation?

Open Heart ◽  
2015 ◽  
Vol 2 (1) ◽  
pp. e000198 ◽  
Author(s):  
Vivienne A Ezzat ◽  
Victor Lee ◽  
Syed Ahsan ◽  
Anthony W Chow ◽  
Oliver Segal ◽  
...  
Keyword(s):  
Systematic Review ◽  
Real World ◽  
Randomised Controlled Trials ◽  
Controlled Trials ◽  
Real World Data ◽  
World Data ◽  
Randomised Controlled

scholarly journals 'Real-world' clinical trials in diabetes care: meaningful or meaningless?

2021 ◽  
Author(s):  
Philip Home
Keyword(s):  
Clinical Trials ◽  
Real World ◽  
Diabetes Care ◽  
Glucose Control ◽  
Observational Studies ◽  
Economic Evaluations ◽  
Secondary Literature ◽  
Blinded Study ◽  
Baseline Factors ◽  
Randomised Controlled

So-called 'real-world' studies seem increasingly popular in diabetes care, as are the economic evaluations in secondary literature based upon them. The term is usually used for pharmacoepidemiological uncontrolled observational studies of different designs. Interpretation of the study findings is, however, badly undermined by the very reasons that the randomised controlled blinded study was invented – namely, non-medication study effects and biases in investigator selection and behaviour. In diabetes studies, glucose control seems particularly susceptible to such effects, perhaps through changes in patient motivation and education. Further, insulin studies are heavily influenced by baseline factors such as the site of starting insulin, the health circumstances of the patient at the time and the clinician involved. It is rare to see these issues adequately addressed or attempts made to understand their influence. In this article an attempt is made to discuss some of the issues further.

scholarly journals Economic Evaluations Informed Exclusively by Real World Data: A Systematic Review

2020 ◽  
Vol 17 (4) ◽  
pp. 1171 ◽  
Author(s):  
Elizabeth Parody-Rúa ◽  
Maria Rubio-Valera ◽  
César Guevara-Cuellar ◽  
Ainhoa Gómez-Lumbreras ◽  
Marc Casajuana-Closas ◽  
...  
Keyword(s):  
Systematic Review ◽  
Real World ◽  
Web Of Science ◽  
Health Economic Evaluation ◽  
Hospital Setting ◽  
Economic Evaluations ◽  
Real World Data ◽  
World Data ◽  
Source Of Information

Economic evaluations using Real World Data (RWD) has been increasing in the very recent years, however, this source of information has several advantages and limitations. The aim of this review was to assess the quality of full economic evaluations (EE) developed using RWD. A systematic review was carried out through articles from the following databases: PubMed, Embase, Web of Science and Centre for Reviews and Dissemination. Included were studies that employed RWD for both costs and effectiveness. Methodological quality of the studies was assessed using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. Of the 14,011 studies identified, 93 were included. Roughly half of the studies were carried out in a hospital setting. The most frequently assessed illnesses were neoplasms while the most evaluated interventions were pharmacological. The main source of costs and effects of RWD were information systems. The most frequent clinical outcome was survival. Some 47% of studies met at least 80% of CHEERS criteria. Studies were conducted with samples of 100–1000 patients or more, were randomized, and those that reported bias controls were those that fulfilled most CHEERS criteria. In conclusion, fewer than half the studies met 80% of the CHEERS checklist criteria.

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