Health Related Quality of Life norm data of the Italian general population: results using the EQ-5D-3L and EQ-5D-5L instruments

Scalone, L; Cortesi, P.A.; Ciampichini, Roberta; Cesana, Giancarlo; Mantovani, LG

doi:10.2427/11457

Cited by 33 publications

(3 citation statements)

References 46 publications

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“…Higher values = better HRQoL. EQ‐5D‐5L population norm data are from Azzi 2020 for France, 125 Grochtdreis 2019 for Germany, 126 Scalone 2015 for Italy, 127 and Hernandez 2018 for Spain 128 . EQ‐5D‐5L population norm data are not available for the UK/England and data from a mixed disease population was used instead (Richardson 129 ).…”

Section: Resultsmentioning

confidence: 99%

Dravet syndrome: A systematic literature review of the illness burden

Strzelczyk,

Lagae,

Wilmshurst

et al. 2023

Epilepsia Open

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ObjectiveWe performed a systematic literature review and narrative synthesis according to a pre‐registered protocol (Prospero: CRD42022376561) to identify the evidence associated with the burden of illness in Dravet syndrome (DS), a developmental and epileptic encephalopathy characterised by drug‐resistant epilepsy with neurocognitive and neurobehavioural impairment.MethodsWe searched MEDLINE, Embase and APA PsychInfo, Cochrane's database of systematic reviews, and Epistemonikos from inception to June 2022. Non‐interventional studies reporting on epidemiology (incidence, prevalence and mortality), patient and caregiver health‐related quality of life (HRQoL), direct and indirect costs and healthcare resource utilisation were eligible. Two reviewers independently carried out the screening. Pre‐specified data were extracted and a narrative synthesis was conducted.ResultsOverall, 49 studies met the inclusion criteria. The incidence varied from 1:15,400–1:40,900, and the prevalence varied from 1.5 per 100,000 to 6.5 per 100,000. Mortality was reported in 3.7–20.8% of DS patients, most commonly due to sudden unexpected death in epilepsy and status epilepticus. Patient HRQoL, assessed by caregivers, was lower than in non‐DS epilepsy patients; mean scores (0 [worst] to 100/1 [best]) were 62.1 for the Kiddy KINDL/ Kid‐KINDL, 46.5–54.7 for the PedsQL and 0.42 for the EQ‐5D‐5L. Caregivers, especially mothers, were severely affected, with impacts on their time, energy, sleep, career, and finances, while siblings were also affected. Symptoms of depression were reported in 47% to 70% of caregivers. Mean total direct costs were high across all studies, ranging from $11,048 to $77,914 per patient per year (PPPY), with inpatient admissions being a key cost driver across most studies. Mean costs related to lost productivity were only reported in three publications, ranging from approximately $19,000 to $20,000 PPPY ($17,596 for mothers versus $1,564 for fathers). High seizure burden was associated with higher resource utilisation, costs and poorer HRQoL.SignificanceThe burden of DS on patients, caregivers, the healthcare system and society is profound, reflecting the severe nature of the syndrome. Future studies will be able to assess the impact that newly approved therapies have on reducing the burden of DS.

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Section: Resultsmentioning

confidence: 99%

Dravet syndrome: A systematic literature review of the illness burden

Strzelczyk,

Lagae,

Wilmshurst

et al. 2023

Epilepsia Open

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“…General population utilities adjusted by age and gender were used for healthy patients [21], while utilities specific for adenoma, CRC stage I-II, stage III, and stage IV (Table 1) were used according to a previous cost-effectiveness model developed for Italy [16].…”

Section: Utility Datamentioning

confidence: 99%

Cost-utility analysis of real-time artificial intelligence-assisted colonoscopy in Italy

Hassan

Povero²,

Pradelli³

et al. 2023

Endosc Int Open

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Background. Artificial intelligence (AI)-assisted colonoscopy proved to be effective compared with colonoscopy alone in an average-risk population. Aim. To evaluate the cost-utility of GI GENIUS, the first marketed real-time AI system in an Italian high-risk population. Methods. A 1-year cycle cohort Markov model was developed to simulate the disease evolution of a cohort of Italian individuals positive to fecal immunochemical test, aged 50 years, undergoing colonoscopy with or without the AI system. Adenoma or colorectal cancer (CRC) were identified according to detection rates specific for each technique. Costs were estimated from the Italian National Health Service perspective. Results. Colonoscopy+AI system was dominant with respect to standard colonoscopy. The GI GENIUS system prevented 155 CRC cases (-2.7%), 77 CRC-related deaths (-2.8%), and improved quality of life (+0.027QALY) with respect to colonoscopy alone. The increase in screening cost (+€10.50) and care for adenoma (+€3.53) was offset by the savings in cost of care for CRC (-€28.37) leading to a total savings of €14.34 per patient. Probabilistic sensitivity analysis confirmed the cost-efficacy of the AI system (almost 80% probability). Conclusions. The implementation of AI detection tools in colonoscopy after FIT+ seems to be a cost-saving strategy for preventing CRC incidence and mortality.

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“…The EQ-5D-5L population norms and sociodemographic characteristics have been reported and validated in many countries such as Germany [ 17 ], Italy [ 18 , 19 ], Japan [ 20 ], Poland [ 21 ], Spain [ 22 ], Uruguay [ 23 ], Vietnam [ 24 ] and the United Kingdom (UK) [ 11 ]. Although population norms for EQ-5D-5L have been developed for South Australia [ 25 ], none have been created for the general Australian population.…”

Section: Introductionmentioning

confidence: 99%

Australian population norms for health-related quality of life measured using the EQ-5D–5L, and relationships with sociodemographic characteristics

Redwood,

Currow,

Kochovska

et al. 2023

Qual Life Res

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Background Measuring health related quality-of-life (HRQoL) of the general population is essential to establish a reference for health outcome evaluations. This study sought to establish EQ-5D-5L population norms in Australia and to investigate the heterogeneity of HRQoL between sociodemographic variables. Methods A cross-sectional study comprising of a representative sample of Australia’s general population (n = 9958) aged 18 or older. Recruitment quotas were set for the Australian census population by age, sex, state/territory of residence and rurality. Participants were recruited by Qualtrics through its database of over 800,000 registered panel members and asked to value their own state of health using the EQ-5D-5L domains and the EuroQol-Visual Analogue Scale (EQ-VAS). An Australian value set developed using Discreet Choice Experiment was used to calculate utility scores. Results The estimated mean EQ-5D-5L index for Australia’s general population was 0.86 (standard deviation [SD] 0.19), and the EQ-VAS score was estimated as 73.2 (SD 21.7). 23.9% of the study population reported being in the best health state (11,111). Younger people, current smokers, people who are unemployed and people with more financial stress reported a lower EQ-5D-5L index score (p < 0.001). Residents in the major cities, inner regional and outer regional Australia reported higher health utility scores than those residing in remote and very remote Australia. Conclusions This is the first Australian study to apply the EQ-5D-5L in a nationally representative sample. The EQ-5D-5L Australian population norms obtained can be used as reference scores for future population health evaluations and comparisons. The findings facilitate a national reference for clinical, economic, and policy decision-making processes and provide a fuller understanding of the Australian population’s HRQoL.

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Health Related Quality of Life norm data of the Italian general population: results using the EQ-5D-3L and EQ-5D-5L instruments

Cited by 33 publications

References 46 publications

Dravet syndrome: A systematic literature review of the illness burden

Dravet syndrome: A systematic literature review of the illness burden

Cost-utility analysis of real-time artificial intelligence-assisted colonoscopy in Italy

Australian population norms for health-related quality of life measured using the EQ-5D–5L, and relationships with sociodemographic characteristics

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