ArticleLancet regional health. Americas2025
Inequity of NIH cancer funding in the United States: an ecological study predicting funding based on disease burden from 2008 through 2023.
Article in Lancet regional health. Americas, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Government funding for uterine cancer research lags behind rising incidence.Gynecologic oncology reports · 2026Article
- Disparities in Lung Cancer Health Outcomes and Access to Lung Cancer Screening Between Rural and Urban Areas in the U.S.Cancers · 2026Review
- Thirty years of NCI thyroid cancer research investment (1996-2025): a longitudinal portfolio analysis of funding trends, molecular target emphasis and thematic evolution.Frontiers in oncology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Disease burden has been used to predict National Institutes of Health (NIH) funding but included diseases with little underlying relationship. Here we focus on cancers to create a more appropriate model to allow for more targeted scrutinization of funding allocation. Methods: An ecological study using NIH funding data (2008-2023) was performed. Inclusion of cancers was based on their presence in the NIH Research Portfolio Online Reporting Tool and the 2021 Global Burden of Disease (GBD) study. Disability-adjusted life years (DALY) were collected and to evaluate the impact of public interest, Google Trends data was used. Multivariable linear regression determined appropriate funding based on disease burden and public interest. To quantify how each cancer's funding differed from model predictions residual values were used to calculate the percent over/under funding. Findings: Fifteen cancers met inclusion criteria. Neuroblastoma had the greatest ratio of funding to DALYs per 100,000 people (US$14,000,000) while lung cancer had the lowest (US$300,000). Stomach cancer was the most underfunded (197.9% [95% CI: 136.0%, 276.2%]) while brain cancer was the most overfunded (64.1% [95% CI: 53.8%, 72.1%]). Even at their lowest funding values in the study period brain, breast, and colorectal cancer all had greater than 40% overfunding. Contrarily, the lowest annual funding for leukemia, uterine, and stomach cancer received less than 150% of expected funding. Despite its overfunding brain cancer had an increase in DALYs in the study period. Interpretation: Modeling by disease category demonstrated disparities in funding indicating the need for reevaluation for possible funding inequities. The year-by-year approach taken in this study will drive the ability for future research to better understand NIH funding decisions. Additionally, the role of public interest in research funding needs to be further evaluated to ensure that popularity does not override disease burden, in funding decisions. Funding: No Funding.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.