Patient preferences in genetic newborn screening for rare diseases: study protocol

. 2024 Apr 19 ; 14 (4) : e081835. [epub] 20240419

Jazyk angličtina Země Anglie, Velká Británie Médium electronic

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid38643010

INTRODUCTION: Rare diseases (RDs) collectively impact over 30 million people in Europe. Most individual conditions have a low prevalence which has resulted in a lack of research and expertise in this field, especially regarding genetic newborn screening (gNBS). There is increasing recognition of the importance of incorporating patients' needs and general public perspectives into the shared decision-making process regarding gNBS. This study is part of the Innovative Medicine Initiative project Screen4Care which aims at shortening the diagnostic journey for RDs by accelerating diagnosis for patients living with RDs through gNBS and the use of digital technologies, such as artificial intelligence and machine learning. Our objective will be to assess expecting parent's perspectives, attitudes and preferences regarding gNBS for RDs in Italy and Germany. METHODS AND ANALYSIS: A mixed method approach will assess perspectives, attitudes and preferences of (1) expecting parents seeking genetic consultation and (2) 'healthy' expecting parents from the general population in two countries (Germany and Italy). Focus groups and interviews using the nominal group technique and ranking exercises will be performed (qualitative phase). The results will inform the treatment of attributes to be assessed via a survey and a discrete choice experiment (DCE). The total recruitment sample will be 2084 participants (approximatively 1000 participants in each country for the online survey). A combination of thematic qualitative and logit-based quantitative approaches will be used to analyse the results of the study. ETHICS AND DISSEMINATION: This study has been approved by the Erlangen University Ethics Committee (22-246_1-B), the Freiburg University Ethics Committee (23-1005 S1-AV) and clinical centres in Italy (University of FerraraCE: 357/2023/Oss/AOUFe and Hospedale Bambino Gesu: No.2997 of 2 November 2023, Prot. No. _902) and approved for data storage and handling at the Uppsala University (2022-05806-01). The dissemination of the results will be ensured via scientific journal publication (open access).

Zobrazit více v PubMed

Nguengang Wakap S, Lambert DM, Olry A, et al. . Estimating cumulative point prevalence of rare diseases: analysis of the Orphanet database. Eur J Hum Genet 2020;28:165–73. 10.1038/s41431-019-0508-0 PubMed DOI PMC

Hay E, Elmslie F, Lanyon P, et al. . The diagnostic Odyssey in rare diseases; a task and finish group report for the Department of health and social care. NIHR Open Res 2022. 10.3310/nihropenres.1115171.1 DOI

Marwaha S, Knowles JW, Ashley EA. A guide for the diagnosis of rare and Undiagnosed disease: beyond the Exome. Genome Med 2022;14. 10.1186/s13073-022-01026-w PubMed DOI PMC

Ferreira CR. The burden of rare diseases. American J of Med Genetics Pt A 2019;179:885–92. 10.1002/ajmg.a.61124 PubMed DOI

Gokdemir Y, Eyuboglu TS, Emiralioglu N, et al. . Geographical barriers to timely diagnosis of cystic fibrosis and anxiety level of parents during newborn screening in Turkey. Pediatr Pulmonol 2021;56:3223–31. 10.1002/ppul.25586 PubMed DOI

Grob R, Roberts S, Timmermans S. Families’ experiences with newborn screening: A critical source of evidence. Hastings Cent Rep 2018;48 Suppl 2:S29–31. 10.1002/hast.881 PubMed DOI

Bailey DB, Bishop E, Raspa M, et al. . Caregiver opinions about fragile X population screening. Genetics in Medicine 2012;14:115–21. 10.1038/gim.0b013e31822ebaa6 PubMed DOI PMC

van Dijk T, Kater A, Jansen M, et al. . Expanding neonatal Bloodspot screening: A multi-Stakeholder perspective. Front Pediatr 2021;9. 10.3389/fped.2021.706394 PubMed DOI PMC

Chavez-Yenter D, Vagher J, Clayton MF, et al. . Being Proactive, not reactive”: exploring perceptions of genetic testing among white, Latinx, and Pacific Islander populations. J Community Genet 2021;12:617–30. 10.1007/s12687-021-00542-3 PubMed DOI PMC

Perobelli S, Zanolla L, Tamanini A, et al. . Inconclusive cystic fibrosis neonatal screening results: Long‐Term Psychosocial effects on parents. Acta Paediatr 2009;98:1927–34. 10.1111/j.1651-2227.2009.01485.x PubMed DOI

Pruniski B, Lisi E, Ali N. Newborn screening for pompe disease: impact on families. J Inherit Metab Dis 2018;41:1189–203. 10.1007/s10545-018-0159-2 PubMed DOI

Bailey DB, Berry-Kravis E, Gane LW, et al. . Fragile X newborn screening: lessons learned from a Multisite screening study. Pediatrics 2017;139:S216–25. 10.1542/peds.2016-1159H PubMed DOI

Reinstein E. Challenges of using next generation sequencing in newborn screening. Genet Res (Camb) 2015;97:e21. 10.1017/S0016672315000178 PubMed DOI PMC

Grob R. Qualitative research on expanded Prenatal and newborn screening: robust but marginalized. Hastings Cent Rep 2019;49 Suppl 1:S72–81. 10.1002/hast.1019 PubMed DOI PMC

Friedman JM, Cornel MC, Goldenberg AJ, et al. . Genomic newborn screening: public health policy considerations and recommendations. BMC Med Genomics 2017;10:9. 10.1186/s12920-017-0247-4 PubMed DOI PMC

Knoppers BM, Sénécal K, Borry P, et al. . Whole-genome sequencing in newborn screening programs. Sci Transl Med 2014. 10.1126/scitranslmed.3008494 PubMed DOI

Ozdemir S, Finkelstein E, Lee JJ, et al. . Understanding patient preferences in anti-VEGF treatment options for age-related macular degeneration. PLoS One 2022;17:e0272301. 10.1371/journal.pone.0272301 PubMed DOI PMC

Moultrie RR, Paquin R, Rini C, et al. . Parental views on newborn next generation sequencing: implications for decision support. Matern Child Health J 2020;24:856–64. 10.1007/s10995-020-02953-z PubMed DOI

Bombard Y, Miller FA, Hayeems RZ, et al. . Public views on participating in newborn screening using genome sequencing. Eur J Hum Genet 2014;22:1248–54. 10.1038/ejhg.2014.22 PubMed DOI PMC

Plass AMC, van El CG, Pieters T, et al. . Neonatal screening for treatable and Untreatable disorders: prospective parents’ opinions. Pediatrics 2010;125:e99–106. 10.1542/peds.2009-0269 PubMed DOI

Bailey DB, Lewis MA, Harris SL, et al. . Design and evaluation of a decision aid for inviting parents to participate in a fragile X newborn screening pilot study. J Genet Couns 2013;22:108–17. 10.1007/s10897-012-9511-0 PubMed DOI

Miller FA, Hayeems RZ, Bombard Y, et al. . Public perceptions of the benefits and risks of newborn screening. Pediatrics 2015;136:e413–23. 10.1542/peds.2015-0518 PubMed DOI

Wright SJ, Ulph F, Lavender T, et al. . Understanding midwives’ preferences for providing information about newborn Bloodspot screening. MDM Policy Pract 2018;3. 10.1177/2381468317746170 PubMed DOI PMC

Loeber JG, Platis D, Zetterström RH, et al. . Neonatal screening in Europe Revisited: an ISNS perspective on the current state and developments since 2010. Int J Neonatal Screen 2021;7. 10.3390/ijns7010015 PubMed DOI PMC

Gray JAM, Patnick J, Blanks RG. Maximising benefit and minimising harm of screening. BMJ 2008;336:480–3. 10.1136/bmj.39470.643218.94 PubMed DOI PMC

la Marca G, Carling RS, Moat SJ, et al. . Current state and innovations in newborn screening: continuing to do good and avoid harm. Int J Neonatal Screen 2023;9. 10.3390/ijns9010015 PubMed DOI PMC

Hammond J, Klapwijk JE, Riedijk S, et al. . Assessing women’s preferences towards tests that may reveal uncertain results from prenatal Genomic testing: development of attributes for a discrete choice experiment, using a mixed-methods design. PLoS One 2022;17:e0261898. 10.1371/journal.pone.0261898 PubMed DOI PMC

Buchanan J, Hill M, Vass CM, et al. . Factors that impact on women’s Decision‐Making around Prenatal Genomic tests: an international discrete choice survey. Prenat Diagn 2022;42:934–46. 10.1002/pd.6159 PubMed DOI PMC

Hensher DA, Rose JM, Greene WH. In: Applied choice analysis. Cambridge, UK: Cambridge University Press, Available: https://www.cambridge.org/core/product/identifier/9781316136232/type/book [accessed 30 Apr 2015].

Hiligsmann M, van Durme C, Geusens P, et al. . Nominal group technique to select attributes for discrete choice experiments: an example for drug treatment choice in osteoporosis. Patient Prefer Adherence 2013;7:133–9. 10.2147/PPA.S38408 PubMed DOI PMC

Reed Johnson F, Lancsar E, Marshall D, et al. . Constructing experimental designs for discrete-choice experiments: report of the ISPOR conjoint analysis experimental design good research practices task force. Value Health 2013;16:3–13. 10.1016/j.jval.2012.08.2223 PubMed DOI

Bridges JFP, Hauber AB, Marshall D, et al. . Conjoint analysis applications in health--a checklist: a report of the ISPOR good research practices for conjoint analysis task force. Value Health 2011;14:403–13. 10.1016/j.jval.2010.11.013 PubMed DOI

Kessels R, Jones B, Goos P, et al. . An efficient algorithm for constructing Bayesian optimal choice designs. Journal of Business & Economic Statistics 2009;27:279–91. 10.1198/jbes.2009.0026 DOI

Louviere JJ, Islam T, Wasi N, et al. . Designing discrete choice experiments: do optimal designs come at a price J Consum Res 2008;35:360–75. 10.1086/586913 DOI

Marshall D, Bridges JFP, Hauber B, et al. . Conjoint analysis applications in health - how are studies being designed and reported?: an update on current practice in the published literature between 2005 and 2008. Patient 2010;3:249–56. 10.2165/11539650-000000000-00000 PubMed DOI

Louviere JJ, Hensher DA, Swait JD. In: Stated Choice Methods; analysis and application. Cambridge: Cambridge University Press, Available: https://www.cambridge.org/core/product/identifier/9780511753831/type/book

de Bekker-Grob EW, Donkers B, Jonker MF, et al. . Sample size requirements for discrete-choice experiments in Healthcare: a practical guide. Patient 2015;8:373–84. 10.1007/s40271-015-0118-z PubMed DOI PMC

de Bekker-Grob EW, Donkers B, Bliemer MCJ, et al. . Can Healthcare choice be predicted using stated preference data? Social Science & Medicine 2020;246. 10.1016/j.socscimed.2019.112736 PubMed DOI

Rose JM, Bliemer MJC. Constructing efficient stated choice experimental Desings. Transp Rev 2009;9:1–31.

Merlo G, van Driel M, Hall L. Systematic review and validity assessment of methods used in discrete choice experiments of primary Healthcare professionals. Health Econ Rev 2020;10. 10.1186/s13561-020-00295-8 PubMed DOI PMC

Annunziata MA, Muzzatti B, Altoè G. Defining hospital anxiety and depression scale (HADS) structure by Confirmatory factor analysis: a contribution to validation for Oncological settings. Ann Oncol 2011;22:2330–3. 10.1093/annonc/mdq750 PubMed DOI

Hinz A, Brähler E. Normative values for the hospital anxiety and depression scale (HADS) in the general German population. J Psychosom Res 2011;71:74–8. 10.1016/j.jpsychores.2011.01.005 PubMed DOI

Najít záznam

Citační ukazatele

Nahrávání dat ...

Možnosti archivace

Nahrávání dat ...