Evidence map›Paper›PMID 21142275›Full record

ArticlePharmacoEconomics2011

Accounting for the drug life cycle and future drug prices in cost-effectiveness analysis.

Martin Hoyle

Abstract read
PubMed Publisher
In one paragraph

Article in PharmacoEconomics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
18.0field-weighted citation impact, top 1% of its field
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

14 citing papers in PubMed, 53 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. The price of curing cancer.BMC health services research · 2021
    Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. The value of innovation under value-based pricing.Journal of market access & health policy · 2016
    Article
  10. New Zealand's drug development industry.International journal of environmental research and public health · 2013
    Review
  11. Article
  12. Multicohort models in cost-effectiveness analysis: why aggregating estimates over multiple cohorts can hide useful information.Medical decision making : an international journal of the Society for Medical Decision Making · 2013
    Article
  13. Article
  14. Review
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

1 author at 1 institution in 1 country.

Martin HoylePeninsula Medical School, University of Exeter, Exeter, UK. martin.hoyle@pms.ac.uk
Peninsula College of Medicine and Dentistry · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Economic evaluations of health technologies typically assume constant real drug prices and model only the cohort of patients currently eligible for treatment. It has recently been suggested that, in the UK, we should assume that real drug prices decrease at 4% per annum and, in New Zealand, that real drug prices decrease at 2% per annum and at patent expiry the drug price falls. It has also recently been suggested that we should model multiple future incident cohorts. In this article, the cost effectiveness of drugs is modelled based on these ideas. Algebraic expressions are developed to capture all costs and benefits over the entire life cycle of a new drug. The lifetime of a new drug in the UK, a key model parameter, is estimated as 33 years, based on the historical lifetime of drugs in England over the last 27 years. Under the proposed methodology, cost effectiveness is calculated for seven new drugs recently appraised in the UK. Cost effectiveness as assessed in the future is also estimated. Whilst the article is framed in mathematics, the findings and recommendations are also explained in non-mathematical language. The 'life-cycle correction factor' is introduced, which is used to convert estimates of cost effectiveness as traditionally calculated into estimates under the proposed methodology. Under the proposed methodology, all seven drugs appear far more cost effective in the UK than published. For example, the incremental cost-effectiveness ratio decreases by 46%, from £61, 900 to £33, 500 per QALY, for cinacalcet versus best supportive care for end-stage renal disease, and by 45%, from £31,100 to £17,000 per QALY, for imatinib versus interferon-α for chronic myeloid leukaemia. Assuming real drug prices decrease over time, the chance that a drug is publicly funded increases over time, and is greater when modelling multiple cohorts than with a single cohort. Using the methodology (compared with traditional methodology) all drugs in the UK and New Zealand are predicted to be more cost effective. It is suggested that the willingness-to-pay threshold should be reduced in the UK and New Zealand. The ranking of cost effectiveness will change with drugs assessed as relatively more cost effective and medical devices and surgical procedures relatively less cost effective than previously thought. The methodology is very simple to implement. It is suggested that the model should be parameterized for other countries.

Indexed as

Cost-Benefit AnalysisDrug CostsHumansUnited Kingdom

Identifiers

PMID21142275
OpenAlexW2074469579

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.