Hostname: page-component-77c89778f8-vsgnj Total loading time: 0 Render date: 2024-07-21T15:22:12.682Z Has data issue: false hasContentIssue false

QUALITY OF SAMPLE SIZE ESTIMATION IN TRIALS OF MEDICAL DEVICES: HIGH-RISK DEVICES FOR NEUROLOGICAL CONDITIONS AS EXAMPLE

Published online by Cambridge University Press:  15 May 2017

Britta Olberg
Affiliation:
Medical Consultancy Department, German Federal Joint Committee, Department of Health Care Management, Berlin University of Technologyb.olberg@campus.tu-berlin.de
Matthias Perleth
Affiliation:
Medical Consultancy Department, German Federal Joint Committee
Katja Felgentraeger
Affiliation:
Medical Consultancy Department, German Federal Joint Committee
Sandra Schulz
Affiliation:
Medical Consultancy Department, German Federal Joint Committee
Reinhard Busse
Affiliation:
Department of Health Care Management, Berlin University of Technology

Abstract

Background: The aim of this study was to assess the quality of reporting sample size calculation and underlying design assumptions in pivotal trials of high-risk medical devices (MDs) for neurological conditions.

Methods: Systematic review of research protocols for publicly registered randomized controlled trials (RCTs). In the absence of a published protocol, principal investigators were contacted for additional data. To be included, trials had to investigate a high-risk MD, registered between 2005 and 2015, with indications stroke, headache disorders, and epilepsy as case samples within central nervous system diseases. Extraction of key methodological parameters for sample size calculation was performed independently and peer-reviewed.

Results: In a final sample of seventy-one eligible trials, we collected data from thirty-one trials. Eighteen protocols were obtained from the public domain or principal investigators. Data availability decreased during the extraction process, with almost all data available for stroke-related trials. Of the thirty-one trials with sample size information available, twenty-six reported a predefined calculation and underlying assumptions. Justification was given in twenty and evidence for parameter estimation in sixteen trials. Estimates were most often based on previous research, including RCTs and observational data. Observational data were predominantly represented by retrospective designs. Other references for parameter estimation indicated a lower level of evidence.

Conclusions: Our systematic review of trials on high-risk MDs confirms previous research, which has documented deficiencies regarding data availability and a lack of reporting on sample size calculation. More effort is needed to ensure both relevant sources, that is, original research protocols, to be publicly available and reporting requirements to be standardized.

Type
Assessments
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. Baeyens, H, Poupez, C, Slegers, P, et al. Towards a guided and phased introduction of high-risk medical devices in belgium; KCE report 249. 2015. https://kce.fgov.be/sites/default/files/page_documents/KCE249_High-risk%20medical%20devices_Report.pdf (accessed September 17, 2015).Google Scholar
2. Persistence Market research. Neurostimulation Devices Market: Global Industry Analysis and Forecast to 2020 [Press Release]. http://www.mynewsdesk.com/us/persistence-market-research-2/pressreleases/neurostimulation-devices-market-global-industry-analysis-and-forecast-to-2020-1054197 (accessed September 17, 2015).Google Scholar
3. Storz, P, Kolpatzik, K, Perleth, M, et al. Future relevance of genetic testing: A systematic horizon scanning analysis. Int J Technol Assess Health Care. 2007;23:495504.Google Scholar
4. Mills, EJ, Wu, P, Gagnier, J, et al. The quality of randomized trial reporting in leading medical journals since the revised CONSORT statement. Contemp Clin Trials. 2005;26:480487.CrossRefGoogle ScholarPubMed
5. International Conference on Harmonisation. ICH harmonised tripartite guideline. Statistical principles for clinical trials E9; Current Step 4, version dated 5 February 1998. http://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Efficacy/E9/Step4/E9_Guideline.pdf (accessed September 17, 2015).Google Scholar
6. Weaver, CS, Leonardi-Bee, J, Bath-Hextall, FJ, et al. Sample size calculations in acute stroke trials: A systematic review of their reporting, characteristics, and relationship with outcome. Stroke. 2004;35:12161224.Google Scholar
7. Chan, AW, Hrobjartsson, A, Jorgensen, KJ, et al. Discrepancies in sample size calculations and data analyses reported in randomised trials: Comparison of publications with protocols. BMJ. 2008;337:a2299.Google Scholar
8. Reveiz, L, Cortes-Jofre, M, Asenjo Lobos, C, et al. Influence of trial registration on reporting quality of randomized trials: Study from highest ranked journals. J Clin Epidemiol. 2010;63:12161222.CrossRefGoogle ScholarPubMed
9. Wieseler, B, Wolfram, N, McGauran, N, et al. Completeness of reporting of patient-relevant clinical trial outcomes: Comparison of unpublished clinical study reports with publicly available data. PLoS Med. 2013;10:e1001526.Google Scholar
10. Julious, S. Sample sizes for clinical trials. Boca Raton: Chapman and Hall/CRC; 2009.Google Scholar
11. Campbell, M, Machin, D, Walters, S. Medical statistics. A textbook of health science. 4th ed. Chichester: John Wiley & Sons; 2007.Google Scholar
12. Boutron, I, Moher, D, Altman, DG, et al. Extending the CONSORT statement to randomized trials of nonpharmacologic treatment: Explanation and elaboration. Ann Intern Med. 2008;148:295309.Google Scholar
13. Jones, G, Abbasi, K. Trial protocols at the BMJ. BMJ 2004;329:1360.CrossRefGoogle ScholarPubMed
14. McNamee, D, James, A, Kleinert, S. Protocol review at The Lancet. Lancet. 2008;372:189190.CrossRefGoogle ScholarPubMed
15. Charles, P, Giraudeau, B, Dechartres, A, et al. Reporting of sample size calculation in randomised controlled trials: Review. BMJ. 2009;338:b1732.Google Scholar
16. Clark, T, Berger, U, Mansmann, U. Sample size determinations in original research protocols for randomised clinical trials submitted to UK research ethics committees: Review. BMJ. 2013;346:f1135.Google Scholar
17. Rutterford, C, Taljaard, M, Dixon, S, et al. Reporting and methodological quality of sample size calculations in cluster randomized trials could be improved: A review. J Clin Epidemiol. 2015;68:716723.Google Scholar
18. Toerien, M, Brookes, ST, Metcalfe, C, et al. A review of reporting of participant recruitment and retention in RCTs in six major journals. Trials. 2009;10:52.CrossRefGoogle ScholarPubMed
19. European Commission, Directorate-General for Health and Food Safety. MEDICAL DEVICES: Guidance document. Classification of medical devices. MEDDEV 2.4/1 Rev.9 .2010. http://ec.europa.eu/health/medical-devices/files/meddev/2_4_1_rev_9_classification_en.pdf (accessed September 17, 2015).Google Scholar
20. Moher, D, Hopewell, S, Schulz, KF, et al. CONSORT 2010 explanation and elaboration: Updated guidelines for reporting parallel group randomised trials. BMJ. 2010;340:c869.Google Scholar
21. Castonguay, V, Wilson, MK, Diaz-Padilla, I, et al. Estimation of expectedness: Predictive accuracy of standard therapy outcomes in randomized phase 3 studies in epithelial ovarian cancer. Cancer. 2015;121:413422.CrossRefGoogle ScholarPubMed
22. Rathi, VK, Krumholz, HM, Masoudi, FA, et al. Characteristics of clinical studies conducted over the total product life cycle of high-risk therapeutic medical devices receiving FDA premarket approval in 2010 and 2011. JAMA. 2015;314:604612.Google Scholar
23. Olberg, B, Perleth, M, Busse, R. The new regulation to investigate potentially beneficial diagnostic and therapeutic methods in Germany: Up to international standard? Health Policy. 2014;117:135145.Google Scholar
24. EUnetHTA. Public consultation on the second draft of: Core protocol Pilot for Additional Evidence Generation (AEG). 2015. http://www.eunethta.eu/news/closed-public-consultation-second-draft-core-protocol-pilot-additional-evidence-generation-aeg (accessed September 19, 2015).Google Scholar
25. Chan, AW, Tetzlaff, JM, Gotzsche, PC, et al. SPIRIT 2013 explanation and elaboration: Guidance for protocols of clinical trials. BMJ. 2013;346:e7586.Google Scholar
Supplementary material: File

Olberg supplementary material

Table S3

Download Olberg supplementary material(File)
File 21.2 KB
Supplementary material: File

Olberg supplementary material

Table S2

Download Olberg supplementary material(File)
File 76.3 KB
Supplementary material: File

Olberg supplementary material

Table S4

Download Olberg supplementary material(File)
File 56.9 KB
Supplementary material: File

Olberg supplementary material

Table S1

Download Olberg supplementary material(File)
File 42.5 KB