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Equine veterinary journal2025; doi: 10.1111/evj.14513

Development of a health-related quality-of-life assessment tool for equines with pituitary pars intermedia dysfunction.

Abstract: Clinical signs of pituitary pars intermedia dysfunction (PPID) are frequently mistaken for 'normal' ageing and may not be optimally assessed. Objective quality of life (QoL) assessment could improve clinical decision-making. Objective: To develop an owner-reported health-related quality-of-life (HRQoL) assessment tool for equines with PPID. To assess factors associated with HRQoL scores. Methods: Quantitative, cross-sectional study. Methods: HRQoL tool development followed a standard psychometric process of item (any aspect of PPID and its management that could impact QoL) identification (following interviews with veterinarians, owners and clinical record reviews), selection (online owner questionnaire) and refinement (statistical analyses; chi-squared and Cronbach's alpha). General Linear Models were used to identify factors associated with HRQoL scores. Results: Forty-two items associated with PPID were identified. Thirty-seven items were selected for the online questionnaire. In total, 612 complete responses (n = 343 PPID and n = 269 non-PPID horses) were obtained. Through stepwise statistical item refinement, 24 items remained in the final HRQoL tool (overall Cronbach's α = 0.835). HRQoL scores ranged from 0 (best) to 1 (worst) QoL. Median (interquartile range) HRQoL scores were 0.33 (0.22-0.44) and 0.20 (0.14-0.27) for PPID and non-PPID horses respectively. HRQoL scores for all horses were worse if they had PPID (p < 0.001) or other chronic medical conditions and were older (p < 0.015). For PPID horses specifically, HRQoL scores were also worse if they had other chronic medical conditions (p = 0.02), but HRQoL scores were not associated with current PPID treatment (treated vs. untreated horses with a PPID diagnosis), bodyweight, age, breed, sex or years since diagnosis. Conclusions: Limited numbers of untreated PPID horses. Conclusions: The HRQoL tool is valid and reliable for use in horses with PPID and can be applied in further research. PPID horses with another chronic disease had worse HRQoL scores, which should be considered in other studies evaluating disease impact.
Publication Date: 2025-05-02 PubMed ID: 40314080DOI: 10.1111/evj.14513Google Scholar: Lookup
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  • Journal Article

Summary

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The research is about the development of an assessment tool that assesses the quality of life in horses diagnosed with pituitary pars intermedia dysfunction (PPID). The tool was developed through a standardized data collection process and statistical analysis. It was found to be reliable and valid.

Objective and Methods

The research’s primary objective was to develop an assessment tool to determine the health-related quality of life (HRQoL) in horses suffering from PPID. This tool’s aim is to enhance clinical decisions since PPID symptoms are often mistaken for normal aging. The study used quantitative and cross-sectional methods.

The tool development followed a standard psychometric process.

  • Item Identification – At this stage, each aspect of PPID and its management that could impact HRQoL was identified through interviews with veterinarians, owners, and clinical record reviews.
  • Selection – An online questionnaire was used to select 37 out of 42 identified items.
  • Refinement – The statistical analysis was carried out using chi-squared and Cronbach’s alpha. General Linear Models were further used to identify the factors associated with HRQoL scores.

Results

The completion of the online questionnaire resulted in 612 responses, 343 for PPID and 269 for non-PPID horses. As per the statistical item refinement, 24 items remained in the final HRQoL tool.

The HRQoL scores ranged from 0, representing the best quality of life, to 1, the worst. The median HRQoL scores were 0.33 for PPID horses and 0.20 for non-PPID horses. The HRQoL scores were worse for all horses if they had PPID, were older, or had other chronic medical conditions. However, the scores for PPID horses were not influenced by the current PPID treatment, bodyweight, age, breed, sex, or years since diagnosis.

Conclusion

The number of untreated PPID horses was limited in this study. Nonetheless, the developed HRQoL tool proved to be valid and reliable for use in horses with PPID. The study also discovered that PPID horses with another chronic disease had worse HRQoL scores. This finding recommends considering these results in other studies evaluating disease impact. The tool can be applied in further research.

Cite This Article

APA
Bouquet A, Nicol C, Knowles EJ, Schofield I, Menzies-Gow NJ. (2025). Development of a health-related quality-of-life assessment tool for equines with pituitary pars intermedia dysfunction. Equine Vet J. https://doi.org/10.1111/evj.14513

Publication

ISSN: 2042-3306
NlmUniqueID: 0173320
Country: United States
Language: English

Researcher Affiliations

Bouquet, Aline
  • Department of Clinical Science and Services, The Royal Veterinary College, Hertfordshire, UK.
Nicol, Christine
  • Department of Pathobiology and Population Sciences, The Royal Veterinary College, Hertfordshire, UK.
Knowles, Edward J
  • Department of Clinical Science and Services, The Royal Veterinary College, Hertfordshire, UK.
  • Bell Equine Veterinary Clinic, Kent, UK.
Schofield, Imogen
  • CVS Group plc, Norfolk, UK.
Menzies-Gow, Nicola J
  • Department of Clinical Science and Services, The Royal Veterinary College, Hertfordshire, UK.

Grant Funding

  • CVS Group plc

References

This article includes 50 references
  1. Mellor DJ, Beausoleil NJ. Extending the “five domains” model for animal welfare assessment to incorporate positive welfare states. Anim Welf 2015;24(3):241–253.
    doi: 10.7120/09627286.24.3.241google scholar: lookup
  2. Mellor DJ. Updating animal welfare thinking: moving beyond the “five freedoms” towards “a life worth living”. Animals 2016;6(3):21.
    doi: 10.3390/ani6030021google scholar: lookup
  3. Mellor DJ, Beausoleil NJ, Littlewood KE, McLean AN, McGreevy PD, Jones B. The 2020 five domains model: including human–animal interactions in assessments of animal welfare. Animals 2020;10(10):1870.
    doi: 10.3390/ani10101870google scholar: lookup
  4. Long M, Dürnberger C, Jenner F, Kelemen Z, Auer U, Grimm H. Quality of life within horse welfare assessment tools: informing decisions for chronically ill and geriatric horses. Animals 2022;12(14):1822.
    doi: 10.3390/ani12141822google scholar: lookup
  5. Yeates JW. Is “a life worth living” a concept worth having?. Anim Welf 2011;20(3):397–406.
    doi: 10.1017/s0962728600002955google scholar: lookup
  6. Menzies‐Gow NJ, Banse HE, Duff A, Hart N, Ireland JL, Knowles EJ. BEVA primary care clinical guidelines: diagnosis and management of equine pituitary pars intermedia dysfunction. Equine Vet J 2024;56(2):220–242.
    doi: 10.1111/evj.14009google scholar: lookup
  7. Ireland JL, McGowan CM. Epidemiology of pituitary pars intermedia dysfunction: a systematic literature review of clinical presentation, disease prevalence and risk factors. Vet J 2018;235:22–33.
  8. Ireland JL, Clegg PD, McGowan CM, Duncan JS, McCall S, Platt L. Owners' perceptions of quality of life in geriatric horses: a cross‐sectional study. Anim Welf 2011;20(4):483–495.
    doi: 10.1017/s0962728600003122google scholar: lookup
  9. Long M, Grimm H, Jenner F, Cavalleri JMV, Springer S. “How long is life worth living for the horse?” A focus group study on how Austrian equine stakeholders assess quality of life for chronically ill or old horses. BMC Vet Res 2024;20(1):347.
  10. McGowan C. Welfare of aged horses. Animals 2011;1(4):366–376.
    doi: 10.3390/ani1040366google scholar: lookup
  11. Pickard AS, Knight SJ. Proxy evaluation of health‐related quality of life: a conceptual framework for understanding multiple proxy perspectives. Med Care 2005;43(5):493–499.
  12. Tzannes S, Hammond MF, Murphy S, Sparkes A, Blackwood L. Owners “perception of their cats” quality of life during COP chemotherapy for lymphoma. J Feline Med Surg 2008;10(1):73–81.
  13. Schofield I, O'Neill DG, Brodbelt DC, Church DB, Geddes RF, Niessen SJM. Development and evaluation of a health‐related quality‐of‐life tool for dogs with Cushing's syndrome. J Vet Intern Med 2019;33(6):2595–2604.
    doi: 10.1111/jvim.15639google scholar: lookup
  14. Föllmi J, Steiger A, Walzer C, Robert N, Geissbühler U, Wenker C. A scoring system to evaluate physical condition and quality of life in geriatric zoo mammals. Anim Welf 2023;16(3):309–318.
  15. Howard DL, Lancaster B, de Grauw J. Development and preliminary validation of an equine brief pain inventory for owner assessment of chronic pain due to osteoarthritis in horses. Animals 2024;14(2):181.
    doi: 10.3390/ani14020181google scholar: lookup
  16. British Veterinary Association. Vets speaking up for animal welfare. BVA—Animal Welfare Strategy. [cited 2024 Sep 15].
  17. Sommerville R, Brown AF, Upjohn M. A standardised equine‐based welfare assessment tool used for six years in low and middle income countries. PLoS One 2018;13(2):e0192354.
  18. Harvey AM, Beausoleil NJ, Ramp D, Mellor DJ. A ten‐stage protocol for assessing the welfare of individual non‐captive wild animals: free‐roaming horses (Equus ferus caballus) as an example. Animals 2020;10(1):148.
    doi: 10.3390/ani10010148google scholar: lookup
  19. AWIN. AWIN welfare assessment protocol for horses. 2015.
    doi: 10.13130/awin_horses_2015google scholar: lookup
  20. Viksten SM, Visser EK, Nyman S, Blokhuis HJ. Developing a horse welfare assessment protocol. Anim Welf 2017;26(1):59–65.
    doi: 10.7120/09627286.26.1.059google scholar: lookup
  21. Parker RA, Yeates JW. Assessment of quality of life in equine patients. Equine Vet J 2012;44(2):244–249.
  22. Sobol O, Sattarov K, Butryn‐Boka N. Specific features of using life quality assessment tools for geriatric horses: literature review. Sci Horiz 2023;26(1):121–128.
  23. Hays RD, Anderson R, Revicki D. Psychometric considerations in evaluating health‐related quality of life measures. Qual Life Res 1993;2(6):441–449.
    doi: 10.1007/bf00422218google scholar: lookup
  24. Niessen SJM, Powney S, Guitian J, Niessen APM, Pion PD, Shaw JAM. Evaluation of a quality‐of‐life tool for cats with diabetes mellitus. J Vet Intern Med 2010;24(5):1098–1105.
  25. Tuyttens FAM, de Graaf S, Heerkens JLT, Jacobs L, Nalon E, Ott S. Observer bias in animal behaviour research: can we believe what we score, if we score what we believe?. Anim Behav 2014;90:273–280.
  26. Bateson M, Martin P. Measuring behaviour. 4th ed. Cambridge: Cambridge University Press; 2021.
  27. Grafen A, Hails R. Modern statistics for the life sciences. Oxford: Oxford University Press; 2002.
  28. Dalla Costa E, Minero M, Lebelt D, Stucke D, Canali E, Leach MC. Development of the horse grimace scale (HGS) as a pain assessment tool in horses undergoing routine castration. PLoS One 2014;9(3):e92281.
  29. Belshaw Z, Asher L, Harvey ND, Dean RS. Quality of life assessment in domestic dogs: an evidence‐based rapid review. Vet J 2015;206(2):203–212.
  30. Gildea E, Scales‐Theobald E, Thompson J, Cook A, Forde K, Skingley G. Development and validation of a quality of life and treatment satisfaction measure in canine osteoarthritis. Front Vet Sci 2024;11:1377019.
  31. Wells JR, Hillier A, Holland R, Mwacalimba K, Noli C, Pantr C. Development and validation of a questionnaire to assess owner and canine quality‐of‐life and treatment satisfaction in canine allergic dermatitis. Vet Dermatol 2024;35(4):386–399.
    doi: 10.1111/vde.13242google scholar: lookup
  32. Favrot C, Linek M, Mueller R, Zini E. Development of a questionnaire to assess the impact of atopic dermatitis on health‐related quality of life of affected dogs and their owners. Vet Dermatol 2010;21(1):64–70.
  33. Hague N, Durham AE, Menzies‐Gow NJ. Pergolide dosing compliance and factors affecting the laboratory control of equine pituitary pars intermedia dysfunction. Vet Rec 2021;189(1):e142.
    doi: 10.1002/vetr.142google scholar: lookup
  34. Bijsmans ES, Jepson RE, Syme HM, Elliott J, Niessen SJM. Psychometric validation of a general health quality of life tool for cats used to compare healthy cats and cats with chronic kidney disease. J Vet Intern Med 2016;30(1):183–191.
    doi: 10.1111/jvim.13656google scholar: lookup
  35. Schofield I. Primary‐care perspectives on Cushing's syndrome in dogs: a new era embracing big data, machine‐learning and quality‐of‐life [dissertation]. London: Royal Veterinary College, University of London; 2021.
  36. Browne JP, O'Boyle CA, Mcgee HM, Mcdonald NJ, Joyce CRB. Development of a direct weighting procedure for quality of life domains. Qual Life Res 1997;6(4):301–309.
  37. Pearlman RA, Uhlmann RF. Quality of life in chronic diseases: perceptions of elderly patients. Gerontol 1988;43:M25–M30.
    doi: 10.1093/geronj/43.2.m25google scholar: lookup
  38. Janse AJ, Uiterwaal CSPM, Gemke RJBJ, Kimpen JLL, Sinnema G. A difference in perception of quality of life in chronically ill children was found between parents and pediatricians. J Clin Epidemiol 2005;58(5):495–502.
  39. April KT, Feldman DE, Platt RW, Duffy CM. Comparison between children with juvenile Idiopathic arthritis (JIA) and their parents concerning perceived quality of life. Qual Life Res 2006;15(4):655–661.
    doi: 10.1007/s11136-005-3690-1google scholar: lookup
  40. Furtado T, Perkins E, Pinchbeck G, McGowan C, Watkins F, Christley R. Exploring horse owners' understanding of obese body condition and weight management in UK leisure horses. Equine Vet J 2021;53(4):752–762.
    doi: 10.1111/evj.13360google scholar: lookup
  41. Furtado T, Perkins E, Pinchbeck G, McGowan C, Watkins F, Christley R. Hidden in plain sight: uncovering the obesogenic environment surrounding the UK's leisure horses. Anthrozoos 2021;34(4):491–506.
  42. Rioja‐Lang FC, Connor M, Bacon H, Dwyer CM. Determining a welfare prioritization for horses using a Delphi method. Animals 2020;10(4):647.
    doi: 10.3390/ani10040647google scholar: lookup
  43. Horseman SV, Buller H, Mullan S, Whay HR. Current welfare problems facing horses in Great Britain as identified by equine stakeholders. PLoS One 2016;11(8):e0160269.
  44. Smith R, Furtado T, Brigden C, Pinchbeck G, Perkins E. A qualitative exploration of UK leisure horse owners' perceptions of equine wellbeing. Animals 2022;12(21):2937.
    doi: 10.3390/ani12212937google scholar: lookup
  45. Rohrbach BW, Stafford JR, Clermont RSW, Reed SM, Schott HC, Andrews FM. Diagnostic frequency, response to therapy, and long‐term prognosis among horses and ponies with pituitary par intermedia dysfunction, 1993–2004. J Vet Intern Med 2012;26(4):1027–1034.
  46. McFarlane D. Advantages and limitations of the equine disease, pituitary pars intermedia dysfunction as a model of spontaneous dopaminergic neurodegenerative disease. Ageing Res Rev 2007;6(1):54–63.
    doi: 10.1016/j.arr.2007.02.001google scholar: lookup
  47. Choi BC, Pak AW, CDC. A catalog of biases in questionnaires. Prev Chronic Dis 2005;2(1):A13.
  48. Sedgwick P. What is recall bias?. BMJ 2012;344(May):e3519.
    doi: 10.1136/bmj.e3519google scholar: lookup
  49. Coughlin SS. Recall bias in epidemiologic studies. J Clin Epidemiol 1990;43(1):87–91.
  50. van Alten S, Domingue BW, Faul J, Galama T, Marees AT. Reweighting UK Biobank corrects for pervasive selection bias due to volunteering. Int J Epidemiol 2024;53(3):dyae054.
    doi: 10.1093/ije/dyae054google scholar: lookup

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