Academic Journal
Privacy rights and improving knowledge are not hierarchical needs: data protection and good epidemiologic standard (DP_GOES) checklist for retrospective observational studies using secondary data.
| Τίτλος: | Privacy rights and improving knowledge are not hierarchical needs: data protection and good epidemiologic standard (DP_GOES) checklist for retrospective observational studies using secondary data. |
|---|---|
| Συγγραφείς: | Corrao G; Emeritus Professor in Medical Statistics, University of Milano-Bicocca, Milan, Italy.; National Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, Italy.; Operative Centre for Health Data, Welfare Department, Lombardy Region, Milan, Italy., Greco M; European Patients' Forum, Brussels, Belgium., Leoni O; Operative Centre for Health Data, Welfare Department, Lombardy Region, Milan, Italy., Franchi M; National Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, Italy. matteo.franchi@unimib.it.; Unit of Biostatistics, Epidemiology and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy. matteo.franchi@unimib.it.; Dipartimento di Statistica e Metodi Quantitativi, Università degli Studi di Milano-Bicocca, Via Bicocca degli Arcimboldi, 8, Edificio U7, Milano, 20126, Italy. matteo.franchi@unimib.it. |
| Πηγή: | BMC medical research methodology [BMC Med Res Methodol] 2026 Mar 06; Vol. 26 (1). Date of Electronic Publication: 2026 Mar 06. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: BioMed Central Country of Publication: England NLM ID: 100968545 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2288 (Electronic) Linking ISSN: 14712288 NLM ISO Abbreviation: BMC Med Res Methodol Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: London : BioMed Central, [2001- |
| Ιατρικοί όροι (MeSH): | Checklist*/standards , Checklist*/methods , Confidentiality*/standards , Observational Studies as Topic*/standards , Observational Studies as Topic*/methods , Computer Security*/standards , Privacy*, Humans ; Retrospective Studies ; Secondary Data Analysis |
| Περίληψη: | Starting with the Nuremberg Code in 1947, several guidelines were developed to formulate rules to guide research on humans and safeguard the rights and well-being of subjects participating in clinical research. In recent years, retrospective observational studies based on disease and drug registries, surveillance systems, hospital-based data lakes and platforms, and unstructured data have gained progressively greater attention in the medical literature. Although several guidelines and checklists are currently available to develop and evaluate a protocol for observational studies, issues concerning ethical considerations, data protection and data access have been often ignored. We propose the Data Protection and Good Epidemiologic Standard (DP_GOES) checklist for the development and evaluation of the protocol of observational, retrospective studies based on secondary data. The checklist is divided into four parts, 9 sections and 68 items, and should help to verify whether the study protocol respects the constraints of the regulatory requirements and provisions of data protection authorities, while ensuring that the study may generate robust evidence potentially useful to promote health, supplying more effective healthcare, and guaranteeing system sustainability. The DP_GOES checklist represents a novel and integrative contribution, as it systematically combines epidemiological research standards with data protection principles. Its practical value lies in offering a structured and operational tool that supports both researchers and evaluators in conducting and assessing retrospective observational studies based on secondary data in a rigorous, transparent, and ethically accepted manner. (© 2026. The Author(s).) |
| Competing Interests: | Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: GC received research support from the European Community (EC), the Italian Agency of Drugs (AIFA), and the Italian Ministry for University and Research (MIUR). He took part in a variety of projects that were funded by pharmaceutical companies (i.e. Novartis, GSK, Roche, AMGEN and BMS). He also received honoraria as a member of the advisory board to Roche. The other authors do not report any competing interest. |
| References: | Nuremberg Military Tribunal. Nuremberg Code JAMA. 1996;276:1691. Krugman S. The Willowbrook hepatitis studies revisited: Ethical aspects. Rev Infect Dis. 1986;8:157–62. (PMID: 395242310.1093/clinids/8.1.157) Beecher HK. Ethics and clinical research. N Engl J Med. 1966;274:1354–60. (PMID: 532735210.1056/NEJM196606162742405) World Medical Association. Declaration of Helsinki - Ethical Principles for Medical Research Involving Human Subjects. Available from: https://www.wma.net/policies-post/wma-declaration-of-helsinki/ . Last accessed on 2024 Nov 21. European Medicine Agency. ICH E6 (R2.) Good clinical practice - Scientific guideline. Available from: https://www.ema.europa.eu/en/ich-e6-r2-good-clinical-practice-scientific-guideline . Last accessed on 2024 Nov 21. Garrard E, Dawson A. What is the role of the research ethics committee? Paternalism, inducements, and harm in research ethics. J Med Ethics. 2005;31:419–23. (PMID: 15994364173418010.1136/jme.2004.010447) Malone M, Ferguson P, Rogers A, Mackenzie IS, Rorie DA, MacDonald TM. When innovation outpaces regulations: The legal challenges for direct-to-patient supply of investigational medicinal products. Br J Clin Pharmacol. 2022;88:1115–42. (PMID: 3439002210.1111/bcp.15040) European Commission. Directorate General For Health And Food Safety. Question and Answers on the interplay between the Clinical Trials Regulation and the General Data Protection Regulation. Available from: https://health.ec.europa.eu/document/download/c3042973-b36d-4094-a1fb-a6fc980f065e_en . Last accessed on 2024 Nov 21. Haendel MA, Chute CG, Robinson PN. Classification, Ontology, and Precision Medicine. N Engl J Med. 2018;379:1452–62. (PMID: 30304648650384710.1056/NEJMra1615014) Nardini C, Osmani V, Cormio P, Frosini A, Turrini M, Lionis C, et al. The evolution of personalized healthcare and the pivotal role of European regions in its implementation. Per Med. 202;18(3):283–94. Grol R. Successes and failures in the implementation of evidence-based guidelines for clinical practice. Med Care. 2001;39(8 Suppl 2):II46–54. (PMID: 11583121) Chari A, Romanus D, Palumbo A, Blazer M, Farrelly E, Raju A, et al. Randomized Clinical Trial Representativeness and Outcomes in Real-World Patients: Comparison of 6 Hallmark Randomized Clinical Trials of Relapsed/Refractory Multiple Myeloma. Clin Lymphoma Myeloma Leuk. 2020;20:8–17. (PMID: 3172283910.1016/j.clml.2019.09.625) Corrao G, Mancia G. Research strategies in treatment of hypertension: value of retrospective real-life data. Eur Heart J. 2022;43:3312–22. (PMID: 3513488510.1093/eurheartj/ehab899) Lythgoe MP, Desai A, Gyawali B, et al. Cancer therapy approval timings, review speed, and publication of pivotal registration trials in the US and Europe, 2010–2019. JAMA Netw Open. 2022;5:e2216183. (PMID: 35687337918795210.1001/jamanetworkopen.2022.16183) Banzi R, Gerardi C, Bertele’ V, Garattini S. Conditional approval of medicines by the EMA. BMJ 2017;357:j2062. Berger ML, Mamdani M, Atkins D, Johnson ML. Good research practices for comparative effectiveness research: defining, reporting and interpreting nonrandomized studies of treatment effects using secondary data sources: the ISPOR Good Research Practices for Retrospective Database Analysis Task Force Report–Part I. Value Health. 2009;12:1044–52. (PMID: 1979307210.1111/j.1524-4733.2009.00600.x) Cox E, Martin BC, Van Staa T, Garbe E, Siebert U, Johnson ML. Good research practices for comparative effectiveness research: approaches to mitigate bias and confounding in the design of nonrandomized studies of treatment effects using secondary data sources: the International Society for Pharmacoeconomics and Outcomes Research Good Research Practices for Retrospective Database Analysis Task Force Report–Part II. Value Health. 2009;12:1053–61. (PMID: 1974429210.1111/j.1524-4733.2009.00601.x) Sørensen HT, Sabroe S, Olsen J. A Framework for Evaluation of Secondary Data Sources for Epidemiological Research. Int J Epidemiol. 1996;25:435–42. (PMID: 911957110.1093/ije/25.2.435) Schneeweiss S. Learning from big health care data. N Engl J Med. 2014;370:2161–3. (PMID: 2489707910.1056/NEJMp1401111) Kassell L. Paper Technologies, Digital Technologies: Working With Early Modern Medical Records. In: Whitehead A, Woods A, Atkinson S, Macnaughton J, Richards J, editors. The Edinburgh Companion to the Critical Medical Humanities. Edinburgh: Edinburgh University; 2016. Jun 30. Chapter 6. Schneeweiss S, Avorn J. A review of uses of health care utilization databases for epidemiologic research on therapeutics. J Clin Epidemiol. 2005;58:323–37. (PMID: 1586271810.1016/j.jclinepi.2004.10.012) National disease registries for. Adv health care Lancet. 2011;378:2050. Xoxi E, Facey KM, Cicchetti A. The Evolution of AIFA Registries to Support Managed Entry Agreements for Orphan Medicinal Products in Italy. Front Pharmacol. 2021;12:699466. (PMID: 34456724838617310.3389/fphar.2021.699466) Klaucke DN, Buehler JW, Thacker SB et al. Guidelines for Evaluating Surveillance Systems. U.S. CDC. Morbidity and Mortality Weekly Report 1988/37(S-5);1–18 Available from: https://www.cdc.gov/mmwr/preview/mmwrhtml/00001769.htm . Last accessed on 2024 Nov 21. Lin Z, Yin Y, Liu L, Wang D. SciSciNet: A large-scale open data lake for the science of science research. Sci Data. 2023;10:315. (PMID: 372640141023509310.1038/s41597-023-02198-9) Galiti D, Linardou H, Agelaki S, Karampeazis A, Tsoukalas N, Psyrri A, et al. Exploring the Use of a Digital Platform for Cancer Patients to Report Their Demographics, Disease and Therapy Characteristics, Age, and Educational Disparities: An Early-Stage Feasibility Study. Curr Oncol. 2023;30:7608–19. (PMID: 376230321045304710.3390/curroncol30080551) Whybra P, Spezi E. Sensitivity of standardised radiomics algorithms to mask generation across different software platforms. Sci Rep. 2023;13:14419. (PMID: 376601351047506210.1038/s41598-023-41475-w) Chakraborty G, Pagolu M, Garla S. Text mining and analysis practical methods, examples, and case studies using SAS<sup>®</sup>. Cary, North Carolina, USA: SAS Institute Inc.; 2013. Kuznetsov V, Lee HK, Maurer-Stroh S, Molnár MJ, Pongor S, Eisenhaber B, et al. How bioinformatics influences health informatics: usage of biomolecular sequences, expression profiles and automated microscopic image analyses for clinical needs and public health. Health Inf Sci Syst. 2013;1:2. (PMID: 25825654433611110.1186/2047-2501-1-2) Cheung CC, Krahn AD, Andrade JG. The emerging role of wearable technologies in detection of arrhythmia. Can J Cardiol. 2018;34:1083–7. (PMID: 30049358) Cheong SHR, Ng YJX, Lau Y, Lau ST. Wearable technology for early detection of COVID-19: a systematic scoping review. Prev Med 2022;162107170. Quantin C, Jaquet-Chiffelle DO, Coatrieux G, Benzenine E, Allaert FA. Medical record search engines, using pseudonymised patient identity: an alternative to centralised medical records. Int J Med Inf. 2011;80:e6–11. (PMID: 10.1016/j.ijmedinf.2010.10.003) Kotecha D, Asselbergs FW, Achenbach S, Innovative Medicines Initiative BigData@Heart Consortium, et al. European Society of Cardiology, CODE-EHR international consensus group. CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research. BMJ. 2022;378:e069048. (PMID: 36562446940375310.1136/bmj-2021-069048) Anglemyer A, Horvath HT, Bero L. Healthcare outcomes assessed with observational study designs compared with those assessed in randomized trials. Cochrane Database Syst Rev. 2014;2014:MR000034. (PMID: 247823228191367) de Kok JWTM, de la Hoz MÁA, de Jong Y, Brokke V, Elbers PWG, Thoral P, Collaborator group, van der Horst ICC, Xu M, Celi LA, van Bussel BCT, Borrat X, et al. A guide to sharing open healthcare data under the General Data Protection Regulation. Sci Data. 2023;10:404. (PMID: 373557511029065210.1038/s41597-023-02256-2) Wirth FN, Meurers T, Johns M, Prasser F. Privacy-preserving data sharing infrastructures for medical research: systematization and comparison. BMC Med Inf Decis Mak. 2021;21:242. (PMID: 10.1186/s12911-021-01602-x) Brandt M, Franconi L, Guerke C, Hundepool A, Lucarelli M, Mol J et al. Last accessed on. Guidelines for the Checking of Output Based on Microdata Research, 2010. Available at: https://uwe-repository.worktribe.com/output/983615/guidelines-for-the-checking-of-output-based-on-microdata-research . 2024 Nov 21. Desai T, Ritchie F, Welpton R. Five Safes: designing data access for research. University of the West of England. Faculty of Business and Law. Economics Working Paper Series 1601. Available at: https://www2.uwe.ac.uk/faculties/BBS/Documents/1601.pdf . Last accessed on 2024 Nov 21. Grimes DA, Schulz KF. Bias and causal associations in observational research. Lancet. 2002;359:248–52. (PMID: 1181257910.1016/S0140-6736(02)07451-2) Velentgas P, Dreyer NA, Nourjah P, Smith SR, Torchia MM, editors. Developing a Protocol for Observational Comparative Effectiveness Research: A User’s Guide. Rockville (MD): Agency for Healthcare Research and Quality (US); 2013. p. 23469377. Swaen GMH, Langendam M, Weyler J, Burger H, Siesling S, Atsma WJ, et al. Responsible Epidemiologic Research Practice: a guideline developed by a working group of the Netherlands Epidemiological Society. J Clin Epidemiol. 2018;100:111–9. (PMID: 2943286210.1016/j.jclinepi.2018.02.010) Wang SV, Pottegård A, Crown W, et al. HARmonized Protocol Template to Enhance Reproducibility of hypothesis evaluating real-world evidence studies on treatment effects: A good practices report of a joint ISPE/ISPOR task force. Pharmacoepidemiol Drug Saf. 2023;32:44–55. (PMID: 3621511310.1002/pds.5507) Hoffmann W, Latza U, Baumeister SE, Brünger M, Buttmann-Schweiger N, Hardt J, et al. Guidelines and recommendations for ensuring Good Epidemiological Practice (GEP): a guideline developed by the German Society for Epidemiology. Eur J Epidemiol. 2019;34:301–17. (PMID: 30830562644750610.1007/s10654-019-00500-x) Alba S, Verdonck K, Lenglet A, Rumisha SF, Wienia M, Teunissen I, et al. Bridging research integrity and global health epidemiology (BRIDGE) statement: guidelines for good epidemiological practice. BMJ Glob Health. 2020;5:e003236. (PMID: 33115859759420710.1136/bmjgh-2020-003236) Berger ML, Dreyer N, Anderson F, Towse A, Sedrakyan A, Normand SL. Prospective observational studies to assess comparative effectiveness: the ISPOR good research practices task force report. Value Health. 2012;15:217–30. (PMID: 2243375210.1016/j.jval.2011.12.010) Fronteira I. How to design a (good) epidemiological observational study: epidemiological research protocol at a glance. Acta Med Port. 2013;26:731–6. (PMID: 2438826110.20344/amp.4315) Altpeter E, Burnand B, Capkun G, Carrel R, Cerutti B, Mäusezahl-Feuz M, et al. Swiss Society for Public Health Epidemiology Group. Essentials of good epidemiological practice. Soz Praventivmed. 2005;50:12–27. (PMID: 1577301810.1007/s00038-004-4008-8) Andrews EA, Avorn J, Bortnichak EA, Chen R, Dai WS, Dieck GS, et al. ISPE. Guidelines for Good Epidemiology Practices for drug, device, and vaccine research in the United States. Pharmacoepidemiol Drug Saf. 1996;5:333–8. (PMID: 1507382010.1002/(SICI)1099-1557(199609)5:5<333::AID-PDS244>3.0.CO;2-5) Public Policy Committee. International Society of Pharmacoepidemiology. Guidelines for good pharmacoepidemiology practice (GPP). Pharmacoepidemiol Drug Saf. 2016;25:2–10. (PMID: 10.1002/pds.3891) Food and Drug Administration. Best Practices for Conducting and Reporting Pharmacoepidemiologic Safety Studies Using Electronic Healthcare Data Sets. FDA-2011-D-0057. Available at https://www.fda.gov/regulatory-information/search-fda-guidance-documents/best-practices-conducting-and-reporting-pharmacoepidemiologic-safety-studies-using-electronic . Last accessed on 2024 Nov 21. European Medicine Agency. ICH M14 guideline on general principles on plan, design and analysis of pharmacoepidemiological studies that utilize real-world data for safety assessment of medicines – Scientific guideline. Available at: https://www.ema.europa.eu/en/ich-m14-guideline-general-principles-plan-design-analysis-pharmacoepidemiological-studies-utilize-real-world-data-safety-assessment-medicines-scientific-guideline . Last accessed on 2024 Nov 21. Malmsiø D, Frost A, Hróbjartsson A. A scoping review finds that guides to authors of protocols for observational epidemiological studies varied highly in format and content. J Clin Epidemiol. 2023;154:156–66. (PMID: 3656397110.1016/j.jclinepi.2022.12.012) Porter ME, Teisberg EO. How physicians can change the future of health care. JAMA. 2007;297:1103–11. (PMID: 1735603110.1001/jama.297.10.1103) Dove ES. Confidentiality, public interest, and the human right to science: when can confidential information be used for the benefit of the wider community? J Law Biosci. 2023;10:lsad013. (PMID: 373231341026693310.1093/jlb/lsad013) Document 32014R0536. Regulation (EU) No 536/2014 of the European Parliament and of the Council of 16 April 2014 on clinical trials on medicinal products for human use, and repealing Directive 2001/20/EC Text with EEA relevance. Available at: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32014R0536 . Last accessed on 2024 Nov 21. Mills JL. Data torturing. N Engl J Med. 1993;329:1196–9. (PMID: 816679210.1056/NEJM199310143291613) |
| Contributed Indexing: | Keywords: Checklist; Data protection; Good practice; Observational studies; Privacy-by-design; Retrospective; Secondary data |
| Entry Date(s): | Date Created: 20260305 Date Completed: 20260710 Latest Revision: 20260710 |
| Update Code: | 20260726 |
| PubMed Central ID: | PMC13077908 |
| DOI: | 10.1186/s12874-026-02818-z |
| PMID: | 41787337 |
| Βάση Δεδομένων: | MEDLINE |
καταχωρήστε σχόλιο πρώτοι!