Evidence map›Paper›PMID 21599035›Full record

ReviewPharmacoEconomics2011

Using QALYs in cancer: a review of the methodological limitations.

Martina Garau, Koonal K Shah, Anne R Mason, Qing Wang, Adrian Towse, Michael F Drummond

Abstract readReview
PubMed Publisher
In one paragraph

Review in PharmacoEconomics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 5 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

36 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Dimensions Used in Instruments for QALY Calculation: A Systematic Review.International journal of environmental research and public health · 2021
    Pooled it
  2. Whom should we ask? A systematic literature review of the arguments regarding the most accurate source of information for valuation of health states.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2020
    Pooled it
  3. Pooled it
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  6. Trial
  7. Cancer-specific or generic preference-based measures in oncology? A validity comparison across six commonly diagnosed cancers.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026
    Article
  8. Differences in health state valuation for small, low-risk thyroid cancer between general population and cancer survivors: a cross-sectional analysis.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025
    Article
  9. Trajectory of quality of life among patients with cancer at the end of life: a longitudinal survey study.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025
    Article
  10. Assessing the reliability of a novel cancer-specific multi-attribute utility instrument (FACT-8D) and comparing its validity to EQ-5D-5L in colorectal cancer patients.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024
    Article
  11. Chinese utility weights for the EORTC cancer-specific utility instrument QLU-C10D.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024
    Article
  12. Review
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  15. Trimodal therapy vs. radical cystectomy for muscle-invasive bladder cancer: A Markov microsimulation model.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2022
    Article
  16. Article
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  20. Testing alternative regression models to predict utilities: mapping the QLQ-C30 onto the EQ-5D-5L and the SF-6D.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2018
    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

6 authors.

Martina GarauOffice of Health Economics, London, UK.
Koonal K Shah
Anne R Mason
Qing Wang
Adrian Towse
Michael F Drummond

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objective of this paper is to examine how well the QALY captures the health gains generated by cancer treatments, with particular focus on the methods for constructing QALYs preferred by the UK National Institute for Health and Clinical Excellence (NICE). Data were obtained using a keyword search of the MEDLINE database and a hand search of articles written by leading researchers in the subject area (with follow up of the references in these articles). Key arguments were discussed and developed at an oncology workshop in September 2009 at the Office of Health Economics. Three key issues emerged. First, the EQ-5D, NICE's preferred measure of health-related quality of life (QOL) in adults, has been found to be relatively insensitive to changes in health status of cancer patients. Second, the time trade-off, NICE's preferred technique for estimating the values of health states, involves making assumptions that are likely to be violated in end-of-life scenarios. Third, the practice of using valuations of members of the general population, as recommended by NICE, is problematic because such individuals typically display a misunderstanding of what it is really like for patients to live with cancer. Because of the way in which it is constructed, the QALY shows important limitations in terms of its ability to accurately capture the value of the health gains deemed important by cancer patients. A research agenda for addressing these limitations is proposed.

Indexed as

Health StatusQuality-Adjusted Life YearsAdultHealth PolicyHumansNeoplasmsQuality of Life

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.