Evidence map›Paper›PMID 33093950›Full record

ArticleF1000Research2020

Measurement, modeling and QALYs.

Paul C Langley, Stephen P McKenna

Abstract read
In one paragraph

Article in F1000Research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–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

17 citing papers in PubMed.

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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

2 authors.

Paul C LangleyCollege of Pharmacy, University of Minnesota, Minneapolis, USA.ORCID 0000-0002-9092-1246
Stephen P McKennaDepartment of Population Health, University of Manchester, Manchester, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the past 30 years, a mainstay of health technology assessment has been the creation of modeled incremental cost-per-quality adjusted life year (QALY) claims. These are intended to inform resource allocation decisions. Unfortunately, the reliance on the construction of QALYs from generic utility scales is misplaced. Those advocating QALY-based lifetime modeled claims fail to appreciate the limitations placed on these constructs by the axioms of fundamental measurement. Utility scales, such as those created by the EQ-5D-3L instrument, are nothing more than multidimensional, ordinal scales. Such scales cannot support basic arithmetic operations. Interval scales can support addition and subtraction; ratio scales the further operations of multiplication and division. Those who advocate the construction of QALYs fail to appreciate that such an operation is only possible if the utility scale is unidimensional and has ratio properties with a true zero. The utility measures available do not meet these requirements. As we cannot produce meaningful utility values, the QALY is an invalid construct. Consequently, cost-per-incremental QALY claims are impossible to sustain and the application of cost-per QALY thresholds meaningless. As utility is a latent, unidimensional variable, the best a measure of utility could achieve would be unidimensionality and interval scaling properties. Where such measures are available, they could support claims for response to therapy. Consequently, there would be no need to continue constructing imaginary lifetime value assessment frameworks. Admitting that the QALY is a fatally flawed construct means rejecting 30 years of cost-per-QALY models.

Indexed as

Quality-Adjusted Life YearsCost-Benefit AnalysisImaginary QALYimpossible modelsordinal scores

Identifiers

PMID33093950
PMCPMC7533730

What OpenQuestion holds

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LicenceCC BY
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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.