Evidence map›Paper›PMID 18370565›Full record

ArticlePharmacoEconomics2008

The use of QALY weights for QALY calculations: a review of industry submissions requesting listing on the Australian Pharmaceutical Benefits Scheme 2002-4.

Paul A Scuffham, Jennifer A Whitty, Andrew Mitchell, Rosalie Viney

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Article in PharmacoEconomics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Discrete choice experiments to generate utility values for multi-attribute utility instruments: a systematic review of methods.The European journal of health economics : HEPAC : health economics in prevention and care · 2020
    Pooled it
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  5. Trial
  6. An Australian Value Set for the EQ-5D-Y-3L.Health and quality of life outcomes · 2025
    Article
  7. EQ-5D Brazilian population norms.Health and quality of life outcomes · 2021
    Article
  8. Discrepancies between proxy estimates and patient reported, health related, quality of life: minding the gap between patient and clinician perceptions in heart failure.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2021
    Article
  9. Article
  10. Article
  11. QLU-C10D: a health state classification system for a multi-attribute utility measure based on the EORTC QLQ-C30.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2016
    Article
  12. Article
  13. Valuing EQ-5D health states for Sri Lanka.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2015
    Article
  14. Article
  15. A comparison of EQ-5D-3L population norms in Queensland, Australia, estimated using utility value sets from Australia, the UK and USA.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2014
    Article
  16. Article
  17. Review
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  19. Article
  20. Family quality of life in dementia: a qualitative approach to family-identified care priorities.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2011
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Paul A ScuffhamSchool of Medicine, Griffith University, Meadowbrook, Queensland, Australia. p.scuffham@griffith.edu.au
Jennifer A Whitty
Andrew Mitchell
Rosalie Viney

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundQALYs combine survival and health-related quality of life (QOL) into a single index, enabling judgements about the relative value for money of healthcare interventions.

objectiveTo investigate the methods used for estimating QALY weights included in submissions by industry for listing of their products on the Australian Pharmaceutical Benefits Scheme. STUDY

designRetrospective descriptive review of submissions considered by the Pharmaceutical Benefits Advisory Committee (PBAC) 2002-4. DATA SOURCES: The database of submissions considered at PBAC meetings was obtained from the Pharmaceutical Evaluation Section of the Australian Government Department of Health and Ageing. Further information on each included submission was obtained in the form of the Pharmaceutical Evaluation Section commentary (expert report) on the submission.

methodsSubmissions to the PBAC over 2002-4 presenting QALYs as an outcome measure were reviewed to identify the methods used to obtain preference-based QALY weights. Information was analyzed according to the approach taken to obtain QALY weights (multi-attribute utility instrument [MAUI], health state valuation [HSV] experiment for scaling the health states, or non-preference-based approach); the population from whom the QALY weights were obtained; the appropriateness of the population for the instrument; the recommendation made by the PBAC; and the main indicated category for use of the pharmaceutical. The approach and the population were classified as 'more appropriate' and 'less appropriate'. The 'more appropriate' approaches were where a MAUI was administered to patients who were currently experiencing the health states being valued, or when an HSV experiment was undertaken in either the general population to value a health state derived from clinical and QOL studies or a population of patients to value their own health state. All other approaches were considered 'less appropriate'.

resultsMAUIs were used in 39% of approaches reporting QALYs; the most frequently used MAUI was the EQ-5D. HSV experiments were used in 36% of the approaches and generally drawn from the published literature. Non-preference-based approaches (24%) included rating scales, mapping transformations and consensus opinions. Responses from patients were used in 58% of the approaches, followed by healthcare professionals and investigators (24% and 9%, respectively). Healthcare professionals and investigators' responses were frequently used in non-preference-based approaches. Submissions for nervous system, infectious disease and neoplasms disease areas were less likely to have presented QALY weights derived from a 'more appropriate' approach. Of the approaches using 'more appropriate' populations and techniques, 56% were rejected by the PBAC compared with 66% of those using 'less appropriate' approaches.

conclusionsThe variability in the quality of QALY weights is troubling. The PBAC guidelines that applied over the period studied neither encouraged nor discouraged cost-utility analyses and provided only brief guidance on how QALY studies should be conducted. A consistent approach to the application of standard methods should be used when the QALY is used to inform decisions on resource allocation. The new PBAC guidelines released in 2006 provide more extensive guidance on derivation of QALY estimates and are more encouraging of the presentation of cost-utility analysis. MAUIs offer a straightforward approach to obtaining QALY weights, and ideally should be used routinely in relevant comparative randomized trials to assess patients' health states.

Indexed as

Policy MakingQuality-Adjusted Life YearsAustraliaCost-Benefit AnalysisHealth Services ResearchHumansResource AllocationRetrospective Studies

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.