Development and validation of TreatHSP-QoL: a patient-reported outcome measure for health-related quality of life in hereditary spastic paraplegia.
Health-related quality of life
Hereditary spastic paraplegia
Patient-centered outcome measure
Journal
Orphanet journal of rare diseases
ISSN: 1750-1172
Titre abrégé: Orphanet J Rare Dis
Pays: England
ID NLM: 101266602
Informations de publication
Date de publication:
02 Jan 2024
02 Jan 2024
Historique:
received:
29
09
2023
accepted:
19
12
2023
medline:
4
1
2024
pubmed:
4
1
2024
entrez:
3
1
2024
Statut:
epublish
Résumé
Hereditary spastic paraplegia (HSP) is a rare neurodegenerative disease that lacks specific and validated patient-centered outcome measures (PCOMs). We aimed to develop and validate a health-related quality of life (HRQoL) questionnaire specific to HSP ("TreatHSP-QoL") that could be used as a PCOM. The pilot-items of the TreatHSP-QoL (45 five-level Likert scale items, with values per item between 0 and 4) were developed based on a qualitative data analysis of 54 semi-structured interviews, conducted in person with 36 HSP patients and 18 caregivers. It was then reduced and modified through the validation process to 25 items. The main validation was performed using the online questionnaire in 242 HSP patients and 56 caregivers. The exploratory factor analysis defined five subdomains. Cronbach's alpha ranged from 0.57 to 0.85 for the subdomains and reached 0.85 for the total score. The test-retest Pearson correlation reached 0.86 (95% Confidence Interval (CI) [0.79, 0.91]). Pearson correlations with the EuroQol-5 Dimension (5 levels) (EQ-5D-5L) and Friedreich Ataxia Rating Scale-Activities of Daily Living (FARS-ADL) questionnaires varied strongly among the subdomains, with the total scores reaching 0.53 (95% CI [0.42, 0.61]) and -0.45 (95% CI [- 0.55, - 0.35]), respectively. The caregiver-patient response Pearson correlation ranged between 0.64 and 0.82 for subdomains and reached 0.65 (95% CI [0.38, 0.81]) for the total score. TreatHSP-QoL can be used in high-quality clinical trials and clinical practice as a disease-specific PCOM (i.e., HRQoL measure) and is also applicable as a proxy questionnaire. Score values between 0 and 100 can be reached, where higher value represents better HRQoL. The Pearson correlations to the EQ-5D-5L and FARS-ADL support the additional value and need of HSP-specific PCOM, while non-specific QoL-assessment and specific clinical self-assessment tools already exist. All in all, the results demonstrate good validity and reliability for this new patient-centered questionnaire for HSP.
Sections du résumé
BACKGROUND
BACKGROUND
Hereditary spastic paraplegia (HSP) is a rare neurodegenerative disease that lacks specific and validated patient-centered outcome measures (PCOMs). We aimed to develop and validate a health-related quality of life (HRQoL) questionnaire specific to HSP ("TreatHSP-QoL") that could be used as a PCOM.
RESULTS
RESULTS
The pilot-items of the TreatHSP-QoL (45 five-level Likert scale items, with values per item between 0 and 4) were developed based on a qualitative data analysis of 54 semi-structured interviews, conducted in person with 36 HSP patients and 18 caregivers. It was then reduced and modified through the validation process to 25 items. The main validation was performed using the online questionnaire in 242 HSP patients and 56 caregivers. The exploratory factor analysis defined five subdomains. Cronbach's alpha ranged from 0.57 to 0.85 for the subdomains and reached 0.85 for the total score. The test-retest Pearson correlation reached 0.86 (95% Confidence Interval (CI) [0.79, 0.91]). Pearson correlations with the EuroQol-5 Dimension (5 levels) (EQ-5D-5L) and Friedreich Ataxia Rating Scale-Activities of Daily Living (FARS-ADL) questionnaires varied strongly among the subdomains, with the total scores reaching 0.53 (95% CI [0.42, 0.61]) and -0.45 (95% CI [- 0.55, - 0.35]), respectively. The caregiver-patient response Pearson correlation ranged between 0.64 and 0.82 for subdomains and reached 0.65 (95% CI [0.38, 0.81]) for the total score.
CONCLUSIONS
CONCLUSIONS
TreatHSP-QoL can be used in high-quality clinical trials and clinical practice as a disease-specific PCOM (i.e., HRQoL measure) and is also applicable as a proxy questionnaire. Score values between 0 and 100 can be reached, where higher value represents better HRQoL. The Pearson correlations to the EQ-5D-5L and FARS-ADL support the additional value and need of HSP-specific PCOM, while non-specific QoL-assessment and specific clinical self-assessment tools already exist. All in all, the results demonstrate good validity and reliability for this new patient-centered questionnaire for HSP.
Identifiants
pubmed: 38167479
doi: 10.1186/s13023-023-03012-w
pii: 10.1186/s13023-023-03012-w
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2Subventions
Organisme : Bundesministerium für Bildung und Forschung
ID : 01GM1905C
Organisme : Bundesministerium für Bildung und Forschung
ID : 01GM1905A
Informations de copyright
© 2023. The Author(s).
Références
Klebe S, Stevanin G, Depienne C. Clinical and genetic heterogeneity in hereditary spastic paraplegias: from SPG1 to SPG72 and still counting. Rev Neurol (Paris). 2015;171:505–30.
pubmed: 26008818
doi: 10.1016/j.neurol.2015.02.017
Hellberg C, Alinder E, Jaraj D, Puschmann A. Nationwide prevalence of primary dystonia, progressive ataxia and hereditary spastic paraplegia. Parkinsonism Relat Disord. 2019;69:79–84.
pubmed: 31706130
doi: 10.1016/j.parkreldis.2019.10.028
Ruano L, Melo C, Silva MC, Coutinho P. The global epidemiology of hereditary ataxia and spastic paraplegia: a systematic review of prevalence studies. Neuroepidemiology. 2014;42:174–83.
pubmed: 24603320
doi: 10.1159/000358801
Racis L, Tessa A, Di Fabio R, Storti E, Agnetti V, Casali C, et al. The high prevalence of hereditary spastic paraplegia in Sardinia, insular Italy. J Neurol. 2014;261:52–9.
pubmed: 24141732
doi: 10.1007/s00415-013-7151-4
Parodi L, Coarelli G, Stevanin G, Brice A, Durr A. Hereditary ataxias and paraparesias: clinical and genetic update. Curr Opin Neurol. 2018;31:462–71.
pubmed: 29847346
doi: 10.1097/WCO.0000000000000585
Darios F, Coarelli G, Durr A. Genetics in hereditary spastic paraplegias: Essential but not enough. Curr Opin Neurobiol. 2022;72:8–14.
pubmed: 34403957
doi: 10.1016/j.conb.2021.07.005
Lallemant-Dudek P, Darios F, Durr A. Recent advances in understanding hereditary spastic paraplegias and emerging therapies. Fac Rev [Internet]. 2021 [cited 2023 Jul 10];10. Available from: https://facultyopinions.com/prime/reports/b/10/27/
Schüle R, Wiethoff S, Martus P, Karle KN, Otto S, Klebe S, et al. Hereditary spastic paraplegia: clinicogenetic lessons from 608 patients: hereditary spastic paraplegia. Ann Neurol. 2016;79:646–58.
pubmed: 26856398
doi: 10.1002/ana.24611
Elsayed LEO, Eltazi IZ, Ahmed AE, Stevanin G. Insights into clinical, genetic, and pathological aspects of hereditary spastic paraplegias: a comprehensive overview. Front Mol Biosci. 2021;8: 690899.
pubmed: 34901147
pmcid: 8662366
doi: 10.3389/fmolb.2021.690899
Heneghan C, Goldacre B, Mahtani KR. Why clinical trial outcomes fail to translate into benefits for patients. Trials. 2017;18:122.
pubmed: 28288676
pmcid: 5348914
doi: 10.1186/s13063-017-1870-2
Siow S-F, Yeow D, Rudaks LI, Jia F, Wali G, Sue CM, et al. Outcome measures and biomarkers for clinical trials in hereditary spastic paraplegia: a scoping review. Genes. 2023;14:1756.
pubmed: 37761896
pmcid: 10530989
doi: 10.3390/genes14091756
Schule R, Holland-Letz T, Klimpe S, Kassubek J, Klopstock T, Mall V, et al. The spastic paraplegia rating scale (SPRS): a reliable and valid measure of disease severity. Neurology. 2006;67:430–4.
pubmed: 16894103
doi: 10.1212/01.wnl.0000228242.53336.90
Morel T, Cano SJ. Measuring what matters to rare disease patients – reflections on the work by the IRDiRC taskforce on patient-centered outcome measures. Orphanet J Rare Dis. 2017;12:171.
pubmed: 29096663
pmcid: 5667521
doi: 10.1186/s13023-017-0718-x
WHOQOL Group. The World Health Organization quality of life assessment (WHOQOL): Position paper from the World Health Organization. Soc Sci Med. 1995;41:1403–9.
Jenkinson C, Fitzpatrick R, Peto V, Greenhall R, Hyman N. The Parkinson’s Disease Questionnaire (PDQ-39): development and validation of a Parkinson’s disease summary index score. Age Ageing. 1997;26:353–7.
pubmed: 9351479
doi: 10.1093/ageing/26.5.353
Schootemeijer S, Van Der Kolk NM, Bloem BR, De Vries NM. Current perspectives on aerobic exercise in people with parkinson’s disease. Neurotherapeutics. 2020;17:1418–33.
pubmed: 32808252
pmcid: 7851311
doi: 10.1007/s13311-020-00904-8
Fan J, Lu W, Tan W, Liu X, Wang Y, Wang N, et al. Effectiveness of acupuncture for anxiety among patients with parkinson disease: a randomized clinical trial. JAMA Netw Open. 2022;5: e2232133.
pubmed: 36129711
pmcid: 9494193
doi: 10.1001/jamanetworkopen.2022.32133
Coratti G, Cutrona C, Pera MC, Bovis F, Ponzano M, Chieppa F, et al. Motor function in type 2 and 3 SMA patients treated with Nusinersen: a critical review and meta-analysis. Orphanet J Rare Dis. 2021;16:430.
pubmed: 34645478
pmcid: 8515709
doi: 10.1186/s13023-021-02065-z
Jacobi H, Du Montcel ST, Bauer P, Giunti P, Cook A, Labrum R, et al. Long-term evolution of patient-reported outcome measures in spinocerebellar ataxias. J Neurol. 2018;265:2040–51.
pubmed: 29959555
doi: 10.1007/s00415-018-8954-0
Schmitz-Hübsch T, Coudert M, Giunti P, Globas C, Baliko L, Fancellu R, et al. Self-rated health status in spinocerebellar ataxia-Results from a European multicenter study. Mov Disord. 2010;25:587–95.
pubmed: 20175183
doi: 10.1002/mds.22740
Braschinsky M, Rannikmäe K, Krikmann Ü, Lüüs S-M, Raidvee A, Gross-Paju K, et al. Health-related quality of life in patients with hereditary spastic paraplegia in Estonia. Spinal Cord. 2011;49:175–81.
pubmed: 20498662
doi: 10.1038/sc.2010.61
Klimpe S, Schüle R, Kassubek J, Otto S, Kohl Z, Klebe S, et al. Disease severity affects quality of life of hereditary spastic paraplegia patients: HRQoL in HSP. Eur J Neurol. 2012;19:168–71.
pubmed: 21631647
doi: 10.1111/j.1468-1331.2011.03443.x
Amprosi M, Indelicato E, Eigentler A, Fritz J, Nachbauer W, Boesch S. Toward the definition of patient-reported outcome measurements in hereditary spastic paraplegia. Neurol Genet. 2023;9: e200052.
pubmed: 36636734
pmcid: 9832334
doi: 10.1212/NXG.0000000000200052
Bentler PM, Bonett DG. Significance tests and goodness of fit in the analysis of covariance structures. Psychol Bull. 1980;88:588–606.
doi: 10.1037/0033-2909.88.3.588
Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model Multidiscip J. 1999;6:1–55.
doi: 10.1080/10705519909540118
Browne MW, Cudeck R. Alternative ways of assessing model fit. Sociol Methods Res. 1992;21:230–58.
doi: 10.1177/0049124192021002005
Janssen B, Szende A. Population Norms for the EQ-5D. In: Szende A, Janssen B, Cabases J, editors. Self-Rep Popul Health Int Perspect Based EQ-5D [Internet]. Dordrecht: Springer Netherlands; 2014 [cited 2023 Nov 30]. p. 19–30. Available from: http://link.springer.com/ https://doi.org/10.1007/978-94-007-7596-1_3
Janssen MF, Szende A, Cabases J, Ramos-Goñi JM, Vilagut G, König HH. Population norms for the EQ-5D-3L: a cross-country analysis of population surveys for 20 countries. Eur J Health Econ. 2019;20:205–16.
pubmed: 29445941
doi: 10.1007/s10198-018-0955-5
Hansen T, Blekesaune M. The age and well-being “paradox”: a longitudinal and multidimensional reconsideration. Eur J Ageing. 2022;19:1277–86.
pubmed: 36506681
pmcid: 9729496
doi: 10.1007/s10433-022-00709-y
Ellert U, Lampert T, Ravens-Sieberer U. Messung der gesundheitsbezogenen Lebensqualität mit dem SF-8: Eine Normstichprobe für Deutschland. Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz. 2005;48:1330–7.
pubmed: 16270186
doi: 10.1007/s00103-005-1168-5
Hopman WM, Harrison MB, Coo H, Friedberg E, Buchanan M, VanDenKerkhof EG. Associations between chronic disease, age and physical and mental health status. Chronic Dis Can. 2009;29:108–16.
pubmed: 19527569
doi: 10.24095/hpcdp.29.3.03
Ferreira PL, Pereira LN, Antunes P, Ferreira LN. EQ-5D-5L Portuguese population norms. Eur J Health Econ. 2023;24:1411–20.
pubmed: 36630005
doi: 10.1007/s10198-022-01552-9
Van Wilder L, Charafeddine R, Beutels P, Bruyndonckx R, Cleemput I, Demarest S, et al. Belgian population norms for the EQ-5D-5L, 2018. Qual Life Res. 2022;31:527–37.
pubmed: 34406577
doi: 10.1007/s11136-021-02971-6
Luo N, Johnson JA, Shaw JW, Feeny D, Coons SJ. Self-reported health status of the general adult U. S. population as assessed by the EQ-5D and Health Utilities Index. Med Care. 2005;43:1078–86.
pubmed: 16224300
doi: 10.1097/01.mlr.0000182493.57090.c1
Nasim A, Haq NU, Riaz S, Khan SI, Khuda F, Sipra MF, et al. Factors and Predictors of health related quality of life of the general population of Pakistan. Front Public Health. 2022;10: 819088.
pubmed: 36062098
pmcid: 9432806
doi: 10.3389/fpubh.2022.819088
Golicki D, Niewada M. EQ-5D-5L Polish population norms. Arch Med Sci. 2017;1:191–200.
doi: 10.5114/aoms.2015.52126
Park C-H, Park E, Oh H-M, Lee S-J, Park S-H, Jung T-D. Health-related quality of life according to sociodemographic characteristics in the South Korean population. Int J Environ Res Public Health. 2022;19:5223.
pubmed: 35564617
pmcid: 9100159
doi: 10.3390/ijerph19095223
Prevolnik Rupel V, Ogorevc M. EQ-5D-5L Slovenian population norms. Health Qual Life Outcomes. 2020;18:333.
pubmed: 33028345
pmcid: 7542912
doi: 10.1186/s12955-020-01584-w
Clemens S, Begum N, Harper C, Whitty JA, Scuffham PA. A comparison of EQ-5D-3L population norms in Queensland, Australia, estimated using utility value sets from Australia, the UK and USA. Qual Life Res. 2014;23:2375–81.
pubmed: 24676898
doi: 10.1007/s11136-014-0676-x
De Ligt KM, Aaronson NK, Liegl G, Nolte S, the EORTC Quality of Life Group. Updated normative data for the EORTC QLQ-C30 in the general Dutch population by age and sex: a cross-sectional panel research study. Qual Life Res. 2023;32:2477–87.
pubmed: 37031427
pmcid: 10393831
doi: 10.1007/s11136-023-03404-2
Sullivan T, Turner RM, Derrett S, Hansen P. New Zealand Population Norms for the EQ-5D-5L Constructed From the Personal Value Sets of Participants in a National Survey. Value Health. 2021;24:1308–18.
pubmed: 34452711
doi: 10.1016/j.jval.2021.04.1280
Yang Z, Busschbach J, Liu G, Luo N. EQ-5D-5L norms for the urban Chinese population in China. Health Qual Life Outcomes. 2018;16:210.
pubmed: 30409137
pmcid: 6225616
doi: 10.1186/s12955-018-1036-2
Nunnally JC, Bernstein IH. Psychometric theory. 3rd ed. New York: McGraw-Hill; 1994.
DeVellis RF. Scale development: theory and applications. 4th ed. Los Angeles: SAGE; 2017.
Hair JF, editor. Multivariate data analysis: a global perspective. 7th ed. Pearson; 2010.
Skevington SM, Lotfy M, O’Connell KA. The World Health Organization’s WHOQOL-BREF quality of life assessment: Psychometric properties and results of the international field trial. A Report from the WHOQOL Group. Qual Life Res. 2004;13:299–310.
pubmed: 15085902
doi: 10.1023/B:QURE.0000018486.91360.00
Khanna D, Khadka J, Mpundu-Kaambwa C, Lay K, Russo R, Ratcliffe J, et al. Are we agreed? Self- versus proxy-reporting of paediatric health-related quality of life (HRQoL) Using generic preference-based measures: A systematic review and meta-analysis. Pharmacoeconomics. 2022;40:1043–67.
pubmed: 35997957
pmcid: 9550745
doi: 10.1007/s40273-022-01177-z
Rapkin BD, Schwartz CE. Toward a theoretical model of quality-of-life appraisal: Implications of findings from studies of response shift. Health Qual Life Outcomes. 2004;2:14.
pubmed: 15023229
pmcid: 408464
doi: 10.1186/1477-7525-2-14
Sprangers MAG, Schwartz CE. Integrating response shift into health-related quality of life research: a theoretical model. Soc Sci Med. 1999;48:1507–15.
pubmed: 10400253
doi: 10.1016/S0277-9536(99)00045-3
Real RGL, Herbert C, Kotchoubey B, Wessig C, Volkmann J, Kübler A. Psychophysiological correlates of coping and quality of life in patients with ALS. Clin Neurophysiol. 2014;125:955–61.
pubmed: 24210996
doi: 10.1016/j.clinph.2013.09.040
Herschbach P. The “Well-being paradox” in quality-of-life research (Article in German). PPmP - Psychother · Psychosom · Med Psychol. 2002;52:141–50.
Houchin C, Wild D, Horblyuk R. PDB36 THE TRANSLATION AND LINGUISTIC VALIDATION OF THE SATISFACTION WITH ORAL ANTI-DIABETIC AGENTS (SOADA) QUESTIONNAIRE. Value Health. 2006;9:A235.
doi: 10.1016/S1098-3015(10)63306-2
Kuliś D, Whittaker C, Greimel E, Bottomley A, Koller M, the EORTC Quality of Life Group. Reviewing back translation reports of questionnaires: the EORTC conceptual framework and experience. Expert Rev Pharmacoecon Outcomes Res. 2017;17:523–30.
pubmed: 28974101
doi: 10.1080/14737167.2017.1384316
Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the process of cross-cultural adaptation of self-report measures. Spine. 2000;25:3186–91.
pubmed: 11124735
doi: 10.1097/00007632-200012150-00014
Brod M, Tesler LE, Christensen TL. Qualitative research and content validity: developing best practices based on science and experience. Qual Life Res. 2009;18:1263–78.
pubmed: 19784865
doi: 10.1007/s11136-009-9540-9
Lasch KE, Marquis P, Vigneux M, Abetz L, Arnould B, Bayliss M, et al. PRO development: rigorous qualitative research as the crucial foundation. Qual Life Res. 2010;19:1087–96.
pubmed: 20512662
pmcid: 2940042
doi: 10.1007/s11136-010-9677-6
Basch E, Bennett AV. Patient-reported outcomes in clinical trials of rare diseases. J Gen Intern Med. 2014;29:801–3.
pmcid: 4124120
doi: 10.1007/s11606-014-2892-z
Hennink M, Kaiser BN. Sample sizes for saturation in qualitative research: A systematic review of empirical tests. Soc Sci Med. 2022;292: 114523.
pubmed: 34785096
doi: 10.1016/j.socscimed.2021.114523
Guest G, Bunce A, Johnson L. How Many interviews are enough?: An experiment with data saturation and variability. Field Methods. 2006;18:59–82.
doi: 10.1177/1525822X05279903
Rattray J, Jones MC. Essential elements of questionnaire design and development. J Clin Nurs. 2007;16:234–43.
pubmed: 17239058
doi: 10.1111/j.1365-2702.2006.01573.x
Subramony SH, May W, Lynch D, Gomez C, Fischbeck K, Hallett M, et al. Measuring Friedreich ataxia: Interrater reliability of a neurologic rating scale. Neurology. 2005;64:1261–2.
pubmed: 15824358
doi: 10.1212/01.WNL.0000156802.15466.79
Lynch DR, Farmer JM, Tsou AY, Perlman S, Subramony SH, Gomez CM, et al. Measuring Friedreich ataxia: Complementary features of examination and performance measures. Neurology. 2006;66:1711–6.
pubmed: 16769945
doi: 10.1212/01.wnl.0000218155.46739.90
Feng Y-S, Kohlmann T, Janssen MF, Buchholz I. Psychometric properties of the EQ-5D-5L: a systematic review of the literature. Qual Life Res. 2021;30:647–73.
pubmed: 33284428
doi: 10.1007/s11136-020-02688-y
Ferguson E, Cox T. Exploratory factor analysis: a users’guide. Int J Sel Assess. 1993;1:84–94.
doi: 10.1111/j.1468-2389.1993.tb00092.x
Wolf EJ, Harrington KM, Clark SL, Miller MW. Sample Size Requirements for Structural Equation Models: An Evaluation of Power, Bias, and Solution Propriety. Educ Psychol Meas. 2013;73:913–34.
doi: 10.1177/0013164413495237
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, [Internet]. Vienna, Austria; 2021. Available from: https://www.R-project.org/