Evidence map›Paper›PMID 36156148›Full record

ArticleJAMA network open2022

Association of Research and Development Investments With Treatment Costs for New Drugs Approved From 2009 to 2018.

Olivier J Wouters, Lucas A Berenbrok, Meiqi He, Yihan Li, Inmaculada Hernandez

Abstract read
In one paragraph

Article in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Macro- and micro-influencers of antimicrobial costs…What do stewardship programs need to know?Antimicrobial stewardship & healthcare epidemiology : ASHE · 2025
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Annual Wholesale Acquisition Costs of Novel Drugs Relative to US County-Level House Prices.The Journal of pharmacy technology : jPT : official publication of the Association of Pharmacy Technicians · 2024
    Article
  7. Article
  8. Article
  9. Review
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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

5 authors.

Olivier J WoutersDepartment of Health Policy, London School of Economics and Political Science, London, United Kingdom.
Lucas A BerenbrokDepartment of Pharmacy and Therapeutics, University of Pittsburgh School of Pharmacy, Pittsburgh, Pennsylvania.
Meiqi HeDivision of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla.
Yihan LiDepartment of Pharmacy and Therapeutics, University of Pittsburgh School of Pharmacy, Pittsburgh, Pennsylvania.
Inmaculada HernandezDivision of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Drug companies frequently claim that high prices are needed to recoup spending on research and development. If high research and development costs justified high drug prices, then an association between these 2 measures would be expected. Objective: To examine the association between treatment costs and research and development investments for new therapeutic agents approved by the US Food and Drug Administration (FDA) from 2009 to 2018. Design, Setting, and Participants: This cross-sectional study analyzed 60 drugs approved by the FDA between January 1, 2009, and December 31, 2018, for which data on research and development investments and list or net prices were available. Data sources included the FDA and SSR Health databases. Main Outcomes and Measures: The primary independent variable was estimated research and development investment. The outcome was standardized treatment costs (ie, annual treatment costs for both chronic and cycle drugs, and treatment costs for the maximum length of treatment recommended for acute drugs). Standardized treatment costs were estimated separately using list and net prices obtained from SSR Health at the time of launch and in 2021. To test the association between research and development investments and treatment costs, correlation coefficients were estimated and linear regression models were fitted that controlled for other factors that were associated with treatment costs, such as orphan status. Two models were used: a fully adjusted model that was adjusted for all variables in the data set associated with treatment costs and a parsimonious model in which highly correlated variables were excluded. Results: No correlation was observed between estimated research and development investments and log-adjusted treatment costs based on list prices at launch (R = -0.02 and R2 = 0.0005; P = .87) or net prices 1 year after launch (R = 0.08 and R2 = 0.007; P = .73). This result held when 2021 prices were used to estimate treatment costs. The linear regression models showed no association between estimated research and development investments and log-adjusted treatment costs at launch (β = 0.002 [95% CI, -0.02 to 0.02; P = .84] in the fully adjusted model; β = 0.01 [95% CI, -0.01 to 0.03; P = .46] in the parsimonious model) or from 2021 (β = -0.01 [95% CI, -0.03 to 0.01; P = .30] in the fully adjusted model; β = -0.004 [95% CI, -0.02 to 0.02; P = .66] in the parsimonious model). Conclusions and Relevance: Results of this study indicated that research and development investments did not explain the variation in list prices for the 60 drugs in this sample. Drug companies should make further data available to support their claims that high drug prices are needed to recover research and development investments, if they are to continue to use this argument to justify high prices.

Indexed as

Drug CostsDrug IndustryCosts and Cost AnalysisCross-Sectional StudiesHumansResearch

Identifiers

PMID36156148
PMCPMC9513642

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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.