Generating EQ-5D-3L health utility scores from the Edinburgh Postnatal Depression Scale: a perinatal mapping study.
EQ-5D
Edinburgh Postnatal Depression Scale
Mapping
Perinatal depression
Utility
Journal
The European journal of health economics : HEPAC : health economics in prevention and care
ISSN: 1618-7601
Titre abrégé: Eur J Health Econ
Pays: Germany
ID NLM: 101134867
Informations de publication
Date de publication:
24 Apr 2023
24 Apr 2023
Historique:
received:
30
01
2023
accepted:
11
04
2023
medline:
24
4
2023
pubmed:
24
4
2023
entrez:
24
04
2023
Statut:
aheadofprint
Résumé
Perinatal depression (PND) describes depression experienced by parents during pregnancy or in the first year after a baby is born. The EQ-5D instrument (a generic measure of health status) is not often collected in perinatal research, however disease-specific measures, such as the Edinburgh Postnatal Depression Scale (EPDS) are widely used. Mapping can be used to estimate generic health utility index values from disease-specific measures like the EPDS. To develop a mapping algorithm to estimate EQ-5D utility index values from the EPDS. Patient-level data from the BaBY PaNDA study (English observational cohort study) provided 1068 observations with paired EPDS and EQ-5D (3-level version; EQ-5D-3L) responses. We compared the performance of six alternative regression model types, each with four specifications of covariates (EPDS score and age: base, squared, and cubed). Model performance (ability to predict utility values) was assessed by ranking mean error, mean absolute error, and root mean square error. Algorithm performance in 3 external datasets was also evaluated. There was moderate correlation between EPDS score and utility values (coefficient: - 0.42). The best performing model type was a two-part model, followed by ordinary least squared. Inclusion of squared and cubed covariates improved model performance. Based on graphs of observed and predicted utility values, the algorithm performed better when utility was above 0.6. This direct mapping algorithm allows the estimation of health utility values from EPDS scores. The algorithm has good external validity but is likely to perform better in samples with higher health status.
Sections du résumé
BACKGROUND
BACKGROUND
Perinatal depression (PND) describes depression experienced by parents during pregnancy or in the first year after a baby is born. The EQ-5D instrument (a generic measure of health status) is not often collected in perinatal research, however disease-specific measures, such as the Edinburgh Postnatal Depression Scale (EPDS) are widely used. Mapping can be used to estimate generic health utility index values from disease-specific measures like the EPDS.
OBJECTIVE
OBJECTIVE
To develop a mapping algorithm to estimate EQ-5D utility index values from the EPDS.
METHODS
METHODS
Patient-level data from the BaBY PaNDA study (English observational cohort study) provided 1068 observations with paired EPDS and EQ-5D (3-level version; EQ-5D-3L) responses. We compared the performance of six alternative regression model types, each with four specifications of covariates (EPDS score and age: base, squared, and cubed). Model performance (ability to predict utility values) was assessed by ranking mean error, mean absolute error, and root mean square error. Algorithm performance in 3 external datasets was also evaluated.
RESULTS
RESULTS
There was moderate correlation between EPDS score and utility values (coefficient: - 0.42). The best performing model type was a two-part model, followed by ordinary least squared. Inclusion of squared and cubed covariates improved model performance. Based on graphs of observed and predicted utility values, the algorithm performed better when utility was above 0.6.
CONCLUSIONS
CONCLUSIONS
This direct mapping algorithm allows the estimation of health utility values from EPDS scores. The algorithm has good external validity but is likely to perform better in samples with higher health status.
Identifiants
pubmed: 37093502
doi: 10.1007/s10198-023-01589-4
pii: 10.1007/s10198-023-01589-4
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Research for Patient Benefit Programme
ID : NIHR203474
Informations de copyright
© 2023. The Author(s).
Références
Shorey, S., Chee, C.Y.I., Ng, E.D., Chan, Y.H., Tam, W.W.S., Chong, Y.S.: Prevalence and incidence of postpartum depression among healthy mothers: A systematic review and meta-analysis. J. Psychiatr. Res. 104, 235–248 (2018). https://doi.org/10.1016/j.jpsychires.2018.08.001
doi: 10.1016/j.jpsychires.2018.08.001
pubmed: 30114665
NHS England: Perinatal mental health, https://www.england.nhs.uk/mental-health/perinatal/
Office for National Statistics: Birth characteristics in England and Wales: 2020, https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/livebirths/bulletins/birthcharacteristicsinenglandandwales/2020
Bauer, A., Knapp, M., Parsonage, M.: Lifetime costs of perinatal anxiety and depression. J. Affect. Disord. 192, 83–90 (2016)
doi: 10.1016/j.jad.2015.12.005
pubmed: 26707352
World Health Organization: International Statistical Classification of Diseases and Related Health Problems 10th Revision, https://icd.who.int/browse10/2016/en# /
Howard, L.M., Molyneaux, E., Dennis, C.-L., Rochat, T., Stein, A., Milgrom, J.: Non-psychotic mental disorders in the perinatal period. The Lancet. 384, 1775–1788 (2014). https://doi.org/10.1016/S0140-6736(14)61276-9
doi: 10.1016/S0140-6736(14)61276-9
Littlewood, E., Ali, S., Dyson, L., Keding, A., Ansell, P., Bailey, D., Bates, D., Beresford-Dent, J., Clarke, A., Gascoyne, S., Gray, C., Hackney, L., Hewitt, C., Hutchinson, D., Jefferson, L., Mann, R., Marshall, D., McMillan, D., North, A., Nutbrown, S., Peckham, E., Pervin, J., Richardson, Z., Swan, K., Taylor, H., Waterhouse, B., Wills, L., Woodhouse, R., Gilbody, S.: Identifying perinatal depression with case-finding instruments : a mixed-methods study (BaBY PaNDA – Born and Bred in Yorkshire PeriNatal Depression Diagnostic Accuracy). NIHR Health Services and Delivery Research. 1–244 (2018)
Hutchens, B.F., Kearney, J.: Risk Factors for Postpartum Depression: An Umbrella Review. Journal of Midwifery & Women’s Health. 65, 96–108 (2020). https://doi.org/10.1111/jmwh.13067
doi: 10.1111/jmwh.13067
Slomian, J., Honvo, G., Emonts, P., Reginster, J.-Y., Bruyère, O.: Consequences of maternal postpartum depression: A systematic review of maternal and infant outcomes. Womens Health. (2019). https://doi.org/10.1177/1745506519844044
doi: 10.1177/1745506519844044
Wisner, K.L., Sit, D.K.Y., McShea, M.C., Rizzo, D.M., Zoretich, R.A., Hughes, C.L., Eng, H.F., Luther, J.F., Wisniewski, S.R., Costantino, M.L., Confer, A.L., Moses-Kolko, E.L., Famy, C.S., Hanusa, B.H.: Onset Timing, Thoughts of Self-harm, and Diagnoses in Postpartum Women With Screen-Positive Depression Findings. JAMA Psychiat. 70, 490–498 (2013). https://doi.org/10.1001/jamapsychiatry.2013.87
doi: 10.1001/jamapsychiatry.2013.87
Lydsdottir, L.B., Howard, L.M., Olafsdottir, H., Thome, M., Tyrfingsson, P., Sigurdsson, J.F.: The Mental Health Characteristics of Pregnant Women With Depressive Symptoms Identified by the Edinburgh Postnatal Depression Scale. J Clin Psychiatry. 75, 11633 (2014). https://doi.org/10.4088/JCP.13m08646
doi: 10.4088/JCP.13m08646
Molyneaux, E., Howard, L.M., McGeown, H.R., Karia, A.M., Trevillion, K.: Antidepressant treatment for postnatal depression. Adv. Psychiatr. Treat. 20, 368 (2014)
doi: 10.1192/apt.20.6.368
Dennis, C.-L., Hodnett, E.D.: Psychosocial and psychological interventions for treating postpartum depression. Cochrane Database Syst. Rev. 4, 2007–2009 (2007). https://doi.org/10.1002/14651858.CD006116.pub2.Copyright
doi: 10.1002/14651858.CD006116.pub2.Copyright
Petrillo, L.F., Nonacs, R.M., Viguera, A.C., Cohen, L.S.: Course of psychiatric illness during pregnancy and the postpartum. Mood and anxiety disorders during pregnancy and postpartum. 24, 1–15 (2005)
Camacho, E.M., Shields, G.E.: Cost-effectiveness of interventions for perinatal anxiety and/or depression: A systematic review. BMJ Open. 8, e022022 (2018). https://doi.org/10.1136/bmjopen-2018-022022
doi: 10.1136/bmjopen-2018-022022
pubmed: 30099399
pmcid: 6089324
National Institute of Health and Care Excellence (NICE): Guide to the Methods of Technology Appraisal. National Institute for Clinical Excellence (2013)
The EuroQoL Group: EQ-5D Products, http://www.euroqol.org/eq-5d-products.html
Wisløff, T., Hagen, G., Hamidi, V., Movik, E., Klemp, M., Olsen, J.A.: Estimating QALY Gains in Applied Studies: A Review of Cost-Utility Analyses Published in 2010. Pharmacoeconomics 32, 367–375 (2014). https://doi.org/10.1007/s40273-014-0136-z
doi: 10.1007/s40273-014-0136-z
pubmed: 24477679
pmcid: 3964297
Cox, J.L., Holden, J.M., Sagovsky, R.: Detection of Postnatal Depression: Development of the 10-item Edinburgh Postnatal Depression scale. Br. J. Psychiatry 150, 782–786 (1987). https://doi.org/10.1192/bjp.150.6.782
doi: 10.1192/bjp.150.6.782
pubmed: 3651732
Hewitt, C.E., Gilbody, S.M., Brealey, S., Paulden, M., Palmer, S., Mann, R., Green, J., Morrell, J., Barkham, M., Light, K.: Methods to identify postnatal depression in primary care: an integrated evidence synthesis and value of information analysis. (2009)
Longworth, L., Rowen, D.: Mapping to Obtain EQ-5D Utility Values for Use in NICE Health Technology Assessments. Value in Health. 16, 202–210 (2013). https://doi.org/10.1016/j.jval.2012.10.010
doi: 10.1016/j.jval.2012.10.010
pubmed: 23337232
Dakin, H., Abel, L.: HERC database of mapping studies, Version 8.0, https://ora.ox.ac.uk/objects/uuid:0cea46c4-1ac9-4a25-b9f4-145b9a63336e , (2020)
Dakin, H., Abel, L., Burns, R., Yang, Y.: Review and critical appraisal of studies mapping from quality of life or clinical measures to EQ-5D: an online database and application of the MAPS statement. Health Qual. Life Outcomes 16, 31 (2018). https://doi.org/10.1186/s12955-018-0857-3
doi: 10.1186/s12955-018-0857-3
pubmed: 29433510
pmcid: 5810002
Wailoo, A.J., Hernandez-Alava, M., Manca, A., Mejia, A., Ray, J., Crawford, B., Botteman, M., Busschbach, J.: Mapping to Estimate Health-State Utility from Non–Preference-Based Outcome Measures: An ISPOR Good Practices for Outcomes Research Task Force Report. Value in Health. 20, 18–27 (2017). https://doi.org/10.1016/j.jval.2016.11.006
doi: 10.1016/j.jval.2016.11.006
pubmed: 28212961
Littlewood, E., Ali, S., Ansell, P., Dyson, L., Gascoyne, S., Hewitt, C., Keding, A., Mann, R., McMillan, D., Morgan, D., Swan, K., Waterhouse, B., Gilbody, S.: Identification of depression in women during pregnancy and the early postnatal period using the Whooley questions and the Edinburgh Postnatal Depression Scale: protocol for the Born and Bred in Yorkshire: PeriNatal Depression Diagnostic Accuracy (BaBY PaN. BMJ Open 6, e011223 (2016)
doi: 10.1136/bmjopen-2016-011223
pubmed: 27297012
pmcid: 4916566
Devlin, N.J., Brooks, R.: EQ-5D and the EuroQol Group: Past, Present and Future. Appl Health Econ Health Policy. 15, 127–137 (2017). https://doi.org/10.1007/s40258-017-0310-5
doi: 10.1007/s40258-017-0310-5
pubmed: 28194657
pmcid: 5343080
Dolan, P.: Modeling Valuations for EuroQol Health States. Medical Care. 1095–1108 (1997). https://doi.org/10.1097/00005650-199711000-00002
Cox, J.: Thirty years with the Edinburgh Postnatal Depression Scale: voices from the past and recommendations for the future. Br. J. Psychiatry 214, 127–129 (2019). https://doi.org/10.1192/bjp.2018.245
doi: 10.1192/bjp.2018.245
pubmed: 30774059
Levis, B., Negeri, Z., Sun, Y., Benedetti, A., Thombs, B.D.: Accuracy of the Edinburgh Postnatal Depression Scale (EPDS) for screening to detect major depression among pregnant and postpartum women: systematic review and meta-analysis of individual participant data. BMJ. 371, m4022 (2020). https://doi.org/10.1136/bmj.m4022
Matthey, S., Henshaw, C., Elliott, S., Barnett, B.: Variability in use of cut-off scores and formats on the Edinburgh Postnatal Depression Scale - Implications for clinical and research practice. Archives of Women’s Mental Health. 9, 309–315 (2006). https://doi.org/10.1007/s00737-006-0152-x
doi: 10.1007/s00737-006-0152-x
pubmed: 17013761
Mukuria, C., Rowen, D., Harnan, S., Rawdin, A., Wong, R., Ara, R., Brazier, J.: An Updated Systematic Review of Studies Mapping (or Cross-Walking) Measures of Health-Related Quality of Life to Generic Preference-Based Measures to Generate Utility Values. Appl Health Econ Health Policy. 17, 295–313 (2019). https://doi.org/10.1007/s40258-019-00467-6
doi: 10.1007/s40258-019-00467-6
pubmed: 30945127
Brazier, J.E., Yang, Y., Tsuchiya, A., Rowen, D.L.: A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures. Eur. J. Health Econ. 11, 215–225 (2010)
doi: 10.1007/s10198-009-0168-z
pubmed: 19585162
Hernández Alava, M., Wailoo, A.J., Ara, R.: Tails from the Peak District: Adjusted Limited Dependent Variable Mixture Models of EQ-5D Questionnaire Health State Utility Values. Value in Health. 15, 550–561 (2012). https://doi.org/10.1016/j.jval.2011.12.014
doi: 10.1016/j.jval.2011.12.014
pubmed: 22583466
Downe, S., Finlayson, K., Melvin, C., Spiby, H., Ali, S., Diggle, P., Gyte, G., Hinder, S., Miller, V., Slade, P., Trepel, D., Weeks, A., Whorwell, P., Williamson, M.: Self-hypnosis for intrapartum pain management in pregnant nulliparous women: a randomised controlled trial of clinical effectiveness. BJOG Int. J. Obstet. Gynaecol. 122, 1226–1234 (2015). https://doi.org/10.1111/1471-0528.13433
doi: 10.1111/1471-0528.13433
Longhi, E., Murray, L., Wellsted, D., Hunter, R., MacKenzie, K., Taylor-Colls, S., Fongay, P., Fearon, P.: Minding the Baby - Home-visiting programme for vulnerable young mothers: Results of a randomised controlled trial in the UK. NSPCC Learning in parternship with UCL (2019)
Sharp, D.J., Chew-Graham, C., Tylee, A., Lewis, G., Howard, L., Anderson, I., Abel, K., Turner, K.M., Hollinghurst, S.P., Tallon, D., McCarthy, A., Peters, T.J.: A pragmatic randomised controlled trial to compare antidepressants with a community-based psychosocial intervention for the treatment of women with postnatal depression: the RESPOND trial. Health technology assessment (Winchester, England). 14, iii–iv, ix–xi, 1–153 (2010). https://doi.org/10.3310/hta14430
Ara, R., Brazier, J.E.: Using health state utility values from the general population to approximate baselines in decision analytic models when condition-specific data are not available. Value Health. 14, 539–545 (2011). https://doi.org/10.1016/j.jval.2010.10.029
doi: 10.1016/j.jval.2010.10.029
pubmed: 21669378
Camacho, E.M., Shields, G., Lovell, K., Coventry, P.A., Morrison, A.P., Davies, L.M.: A (five-)level playing field for mental health conditions?: exploratory analysis of EQ-5D-5L-derived utility values. Qual. Life Res. 27, 717–724 (2017). https://doi.org/10.1007/s11136-017-1768-1
doi: 10.1007/s11136-017-1768-1
pubmed: 29248995
pmcid: 5845602
Collins, B.: Results from a Well-Being Survey in the North West of England: Inequalities in EQ-5D–Derived Quality-Adjusted Life Expectancy Are Mainly Driven by Pain and Mental Health. Value Health. 20, 174–177 (2017). https://doi.org/10.1016/j.jval.2016.08.004
doi: 10.1016/j.jval.2016.08.004
pubmed: 28212959
Bay, F., Sayiner, F.D.: Perception of traumatic childbirth of women and its relationship with postpartum depression. Women Health 61, 479–489 (2021). https://doi.org/10.1080/03630242.2021.1927287
doi: 10.1080/03630242.2021.1927287
pubmed: 33980127