Opinion: The National Institutes of Health needs to better balance funding distributions among US institutions

Why are clinical trials of deep brain stimulation terminated? An analysis of clinicaltrials.gov

Background

Although deep brain stimulation (DBS) has established uses for patients with movement disorders and epilepsy, it is under consideration for a wide range of neurologic and neuropsychiatric conditions.

Objective

To review successful and unsuccessful DBS clinical trials and identify factors associated with early trial termination.

Methods

The ClinicalTrials.gov database was screened for all studies related to DBS. Information regarding condition of interest, study aim, trial design, trial success, and, if applicable, reason for failure was collected. Trials were compared and logistic regression was utilized to identify independent factors associated with trial termination.

Results

Of 325 identified trials, 79.7% were successful and 20.3% unsuccessful. Patient recruitment, sponsor decision, and device issues were the most cited reasons for termination. 242 trials (74.5%) were interventional with 78.1% successful. There was a statistically significant difference between successful and unsuccessful trials in number of funding sources (p = 0.0375). NIH funding was associated with successful trials while utilization of other funding sources (academic institutions and community organizations) was associated with unsuccessful trials. 83 trials (25.5%) were observational with 84.0% successful; there were no statistically significant differences between successful and unsuccessful observational trials.

Conclusion

One in five clinical trials for DBS were found to be unsuccessful, most commonly due to patient recruitment difficulties. The source of funding was the only factor associated with trial success. As DBS research continues to grow, understanding the current state of clinical trials will help design successful future studies, thereby minimizing futile expenditures of time, cost, and patient engagement.

Scientometric analysis of trends in global research on acne treatment

Acne or acne vulgaris is the most common chronic inflammatory disease of the sebaceous follicles.

Objectives

The present study aims to identify the main lines of research in the field of acne treatment using reproducible scientometric methods. In this article, we reviewed the following research trends: facial acne, different antibiotics, retinoids, anti-inflammatory drugs, epidermal growth factor receptor inhibitors therapy, and associated diseases.

Methods

The analysis of publications from the PubMed collection was carried out from 1871 to 2022. All data were analyzed using Microsoft Excel. The evolution of the terminological portrait of the disease is shown.

Results

Trends in the use of various groups of antibiotics, retinoids, anti-inflammatory drugs, and photodynamic therapy for acne treatment have been found. There is a growing interest in clindamycin and doxycycline (polynomial and exponential growth, respectively). The effects of isotretinoin are also being studied more frequently (active linear growth). The publication of studies on spironolactone is increasing (linear growth). There is also a steady interest in the use of epidermal growth factor receptor inhibitors in the recent years. There is active research on acne and polycystic ovary syndrome (exponential growth).

Limitations

Only articles in English were selected. The most frequent terms were considered.

Conclusions

The dynamics of publication activity in the field of acne was considered. The aim of the current scientometric study was to analyze the global trends in acne treatments. The trend analysis made it possible to identify the most explored areas of research, as well as indicate those areas in dermatology in which interest is declining.

Dispersion of NIH Funding to Departments of Surgery is Contracting

INTRODUCTION

NIH funding to departments of surgery reported as benchmark Blue Ridge Institute for Medical Research (BRIMR) rankings are unclear.

METHODS

We analyzed inflation-adjusted BRIMR-reported NIH funding to departments of surgery and medicine between 2011 and 2021.

RESULTS

NIH funding to departments of surgery and medicine both increased 40% from 2011 to 2021 ($325 million to $454 million; $3.8 billion to $5.3 billion, P < 0.001 for both). The number of BRIMR-ranked departments of surgery decreased 14% during this period while departments of medicine increased 5% (88 to 76 versus 111 to 116; P < 0.001). There was a greater increase in the total number of medicine PIs versus surgery PIs during this period (4377 to 5224 versus 557 to 649; P < 0.001). These trends translated to further concentration of NIH-funded PIs in medicine versus surgery departments (45 PIs/program versus 8.5 PIs/program; P < 0.001). NIH funding and PIs/program in 2021 were respectively 32 and 20 times greater for the top versus lowest 15 BRIMR-ranked surgery departments ($244 million versus $7.5 million [P < 0.01]; 20.5 versus 1.3 [P < 0.001]). Twelve (80%) of the top 15 surgery departments maintained this ranking over the 10-year study period.

CONCLUSIONS

Although NIH funding to departments of surgery and medicine is growing at a similar rate, departments of medicine and top-funded surgery departments have greater funding and concentration of PIs/program versus surgery departments overall and lowest-funded surgery departments. Strategies used by top-performing departments to obtain and maintain funding may assist less well-funded departments in obtaining extramural research funding, thus broadening the access of surgeon-scientists to perform NIH-supported research.

Higher-order rich-club phenomenon in collaborative research grant networks

Modern scientific work, including writing papers and submitting research grant proposals, increasingly involves researchers from different institutions. In grant collaborations, it is known that institutions involved in many collaborations tend to densely collaborate with each other, forming rich clubs. Here we investigate higher-order rich-club phenomena in networks of collaborative research grants among institutions and their associations with research impact. Using publicly available data from the National Science Foundation in the US, we construct a bipartite network of institutions and collaborative grants, which distinguishes among the collaboration with different numbers of institutions. By extending the concept and algorithms of the rich club for dyadic networks to the case of bipartite networks, we find rich clubs both in the entire bipartite network and the bipartite subnetwork induced by the collaborative grants involving a given number of institutions up to five. We also find that the collaborative grants within rich clubs tend to be more impactful in a per-dollar sense than the control. Our results highlight advantages of collaborative grants among the institutions in the rich clubs.

Systemic racial disparities in funding rates at the National Science Foundation

Concerns about systemic racism at academic and research institutions have increased over the past decade. Here, we investigate data from the National Science Foundation (NSF), a major funder of research in the United States, and find evidence for pervasive racial disparities. In particular, white principal investigators (PIs) are consistently funded at higher rates than most non-white PIs. Funding rates for white PIs have also been increasing relative to annual overall rates with time. Moreover, disparities occur across all disciplinary directorates within the NSF and are greater for research proposals. The distributions of average external review scores also exhibit systematic offsets based on PI race. Similar patterns have been described in other research funding bodies, suggesting that racial disparities are widespread. The prevalence and persistence of these racial disparities in funding have cascading impacts that perpetuate a cumulative advantage to white PIs across all of science, technology, engineering, and mathematics.

An Analysis of Otolaryngology's NIH Research Funding Compared to Other Specialties

OBJECTIVE

To compare NIH funding in the field of Otolaryngology to other medical and surgical specialties between 2009 and 2019.

METHODS

Data was collected from the NIH RePORTER database on funding dollars received by each specialty from 2009 to 2019. Along with data on total active physicians per specialty using the Physician Specialty Data Book, comparisons were drawn between Otolaryngology and other medical and surgical specialties with regards to trends in total funding and NIH funding dollars per physician. The distributions of grant funding, within Otolaryngology from various NIH institutes among principal investigators, organizations, and subspecialties were further explored.

RESULTS

There were 3810 grants (1147 unique projects) for a total of $1 276 198 555 funded by the NIH to Otolaryngology departments from 2009 to 2019. Statistically insignificant funding increases (P > .05) caused otolaryngology to fall from first to fourth in funding among studied specialties. The National Institute on Deafness and Other Communication Disorders funded 57% of all unique projects, and 57.2% of all unique NIH projects were otology related. Most projects were basic science related. The top 10 principal investigators obtained 22.3% of the total NIH funding for Otolaryngology. The top 3 organizations over the studied period comprised 26.55% of the total funding, generating a combined 729 grants. Among principal investigators, 63.0% had a PhD degree, 25.3% had an MD, and 9.6% had an MD/PhD.

CONCLUSION AND RELEVANCE

NIH funding in Otolaryngology has remained stable and is highly concentrated among a small number of organizations, geographic regions, and principal investigators. Recent initiatives by academic communities have sought to address funding disparities by incorporating diversity and inclusion into clinician-scientist pipelines. We urge our colleagues to strive toward identification of the factors that contribute to successful acquisition of funding and implementation of a more conducive institutional infrastructure to produce research.

Gene-Targeted Therapies in Pediatric Neurology: Challenges and Opportunities in Diagnosis and Delivery

BACKGROUND

Gene-targeted therapies are becoming a reality for infants and children with diseases of the nervous system. Rapid scientific advances have led to disease-modifying or even curative treatments. However, delays and gaps in diagnosis, inequitable delivery, and the need for long-term surveillance pose unresolved challenges.

OBJECTIVE AND METHODS

The goal of the Child Neurology Society Research Committee was to evaluate and provide guidance on the obstacles, opportunities, and uncertainties in gene-targeted therapies for pediatric neurological disease. The Child Neurology Society Research Committee engaged in collaborative, iterative literature review and committee deliberations to prepare this consensus statement.

RESULTS

We identified important challenges for gene-targeted therapies that require resource investments, infrastructure development, and strategic planning. Barriers include inequities in diagnosis and delivery of therapies, high costs, and a need for long-term surveillance of efficacy and safety, including systematic tracking of unanticipated effects. Key uncertainties regarding technical aspects and usage of gene-targeted therapies should be addressed, and characterization of new natural histories of diseases will be needed. Counterbalanced with these obstacles and uncertainties is the tremendous potential being demonstrated in treatments and clinical trials of gene-targeted therapies.

CONCLUSIONS

Given that gene-targeted therapies for neurological diseases are in their earliest phase, the pediatric neurology community can play a vital role in their guidance and implementation. This role includes facilitating development of infrastructure and guidelines; ensuring efficient, equitable, and ethical implementation of treatments; and advocating for affordable and broad access for all children.

National Institutes of Health Funding Trends to Ophthalmology Departments at U.S. Medical Schools

PURPOSE

To analyze trends in National Institutes of Health (NIH) funding in ophthalmology and characterize its distribution to departments and principal investigators (PIs) affiliated with U.S. medical schools.

DESIGN

Longitudinal descriptive analysis.

METHODS

We queried publically accessible data from the Blue Ridge Institute for Medical Research and NIH RePORTER to determine annual funding trends in ophthalmology from 2009 to 2020. To characterize the distribution of funding, we further ranked the top departments and principal investigators (PIs). Department websites (among other online resources) were utilized to extract characteristics of the latter cohort.

RESULTS

After adjusting for inflation, we observed a modest 9% increase in median NIH funding to academic ophthalmology departments between 2009 and 2020. In the same time period, among individual PIs, this translated to a 9% decline in median funding. Our results among both departments and PIs indicated a persistent inequality in NIH funding. In 2020, 10 ophthalmology departments received 44% of total funding, which is consistent with findings from prior years. Our ranking of PIs by average annual NIH funding indicated a disproportionate representation of males (76%) and PhDs (58%) in the top 50.

CONCLUSIONS

Overall, the results of this investigation suggest NIH funding remains limited for individual investigators, reflecting the increasingly competitive nature of the grant application process. Systemic alterations will be required to reverse these trends. If not accomplished, nascent and established researchers alike will continue to endure challenges in obtaining and maintaining funding.

An experimental test of the effects of redacting grant applicant identifiers on peer review outcomes

Background:

Blinding reviewers to applicant identity has been proposed to reduce bias in peer review.

Methods:

This experimental test used 1200 NIH grant applications, 400 from Black investigators, 400 matched applications from White investigators, and 400 randomly selected applications from White investigators. Applications were reviewed by mail in standard and redacted formats.

Results:

Redaction reduced, but did not eliminate, reviewers’ ability to correctly guess features of identity. The primary, preregistered analysis hypothesized a differential effect of redaction according to investigator race in the matched applications. A set of secondary analyses (not preregistered) used the randomly selected applications from White scientists and tested the same interaction. Both analyses revealed similar effects: Standard format applications from White investigators scored better than those from Black investigators. Redaction cut the size of the difference by about half (e.g. from a Cohen’s d of 0.20–0.10 in matched applications); redaction caused applications from White scientists to score worse but had no effect on scores for Black applications.

Conclusions:

Grant-writing considerations and halo effects are discussed as competing explanations for this pattern. The findings support further evaluation of peer review models that diminish the influence of applicant identity.

Funding:

Funding was provided by the NIH.

NIH funding trends for neurosurgeon-scientists from 1993-2017: Biomedical workforce implications for neurooncology

INTRODUCTION

Neurosurgeons represent 0.5% of all physicians and currently face a high burden of disease. Physician-scientists are essential to advance the mission of National Academies of Science (NAS) and National Institutes of Health (NIH) through discovery and bench to bedside translation. We investigated trends in NIH neurosurgeon-scientist funding over time as an indicator of physician-scientist workforce training.

METHODS

We used NIH Research Portfolio Online Reporting Tools (RePORTER) to extract grants to neurosurgery departments and neurosurgeons from 1993 to 2017. Manual extraction of each individual grant awardee was conducted.

RESULTS

After adjusting for U.S. inflation (base year: 1993), NIH funding to neurosurgery departments increased yearly (P < 0.00001). However, neurosurgeon-scientists received significantly less NIH funding compared to scientists (including basic scientists and research only neurosurgeons) (P = 0.09). The ratio of neurosurgeon-scientists to scientists receiving grants was significantly reduced (P = 0.002). Interestingly, the percentage of oncology-related neurosurgery grants significantly increased throughout the study period (P = 0.002). The average number of grants per neurosurgeon-scientists showed an upward trend (P < 0.001); however, the average number of grants for early-career neurosurgeon-scientists, showed a significant downward trend (P = 0.05).

CONCLUSION

Over the past 23 years, despite the overall increasing trends in the number of NIH grants awarded to neurosurgery departments overall, the proportion of neurosurgeon-scientists that were awarded NIH grants compared to scientists demonstrates a declining trend. This observed shift is disproportionate in the number of NIH grants awarded to senior level compared to early-career neurosurgeon-scientists, with more funding allocated towards neurosurgical-oncology-related grants.

Federal funding allocation on HIV/AIDS research in the United States (2008-2018): an exploratory study using Big Data

Literature suggests that federal funding allocation for HIV-related research in the US may not align with HIV disease burden but is influenced by structural disparities. This study sought to examine how federal funding allocation is associated with HIV disease burden and research capacity of states by applying Big Data integration, text mining, and statistics. Using text mining, we identified 20,678 HIV-related federal projects from 2008 to 2018 in NIH ExPORTER, which were then integrated with data from AtlasPlus and US Census Bureau. We developed Gini coefficients to assess the inequality of funding and the Generalized Estimating Equations model to examine the associations between funding allocation and (1) state HIV disease burden, (2) state research capacity, and (3) geographic regions, respectively. The Gini coefficients (0.60 to 0.80) suggest a highly skewed funding distribution. Funding allocation was not associated with state HIV disease burden (p = 0.269) but HIV research capacity (p = 0.000). The South (with the heaviest HIV disease burden) did not receive significantly more federal funding. Our findings for the first time identified disparities of federal funding allocation, suggesting that federal agencies favor states of high research capacity over heavy disease burden, which may reinforce the HIV-related health disparities.

Optimal Allocation of Research Funds under a Budget Constraint

Purpose. Health economic evaluations that include the expected value of sample information support implementation decisions as well as decisions about further research. However, just as decision makers must consider portfolios of implementation spending, they must also identify the optimal portfolio of research investments. Methods. Under a fixed research budget, a decision maker determines which studies to fund; additional budget allocated to one study to increase the study sample size implies less budget available to collect information to reduce decision uncertainty in other implementation decisions. We employ a budget-constrained portfolio optimization framework in which the decisions are whether to invest in a study and at what sample size. The objective is to maximize the sum of the studies' population expected net benefit of sampling (ENBS). We show how to determine the optimal research portfolio and study-specific levels of investment. We demonstrate our framework with a stylized example to illustrate solution features and a real-world application using 6 published cost-effectiveness analyses. Results. Among the studies selected for nonzero investment, the optimal sample size occurs at the point at which the marginal population ENBS divided by the marginal cost of additional sampling is the same for all studies. Compared with standard ENBS optimization without a research budget constraint, optimal budget-constrained sample sizes are typically smaller but allow more studies to be funded. Conclusions. The budget constraint for research studies directly implies that the optimal sample size for additional research is not the point at which the ENBS is maximized for individual studies. A portfolio optimization approach can yield higher total ENBS. Ultimately, there is a maximum willingness to pay for incremental information that determines optimal sample sizes.

NIH funding trends to US medical schools from 2009 to 2018

Total NIH funding dollars have increased from 2009–2018. We questioned whether this growth has occurred proportionately around the country and throughout allopathic medical schools. Therefore, we compared the trend in NIH grant funding from 2009 to 2018 for United States allopathic medical schools among historically top-funded schools, private and public schools, and by region of the country. Changes in both unadjusted and real funding dollars over time revealed a significant difference. Region was the only significant factor for mean percent change in funding from 2009–2018, with the Western region showing a 33.79% increase in purchasing power. The Northeastern region showed a -6.64% decrease in purchasing power while the Central and Southern regions reported changes of 2.46% and -6.08%, respectively. The mean percent increases were more proportional and nonsignificant in the public vs. private institutions comparison, at -3.41% and 4.75%, respectively. Likewise, the top-funded institutions vs. other institutions comparisons demonstrated modest, nonsignificant differences. However, although the relative changes might be proportional, the absolute increases evidence a pattern of growing cumulative advantage that favor the highest-funded institutions and private institutions. The potential consequences of this disproportionate increase include health science education, biomedical research, and patient access disparities in large parts of the country. The NIH and the scientific community should explore potential solutions in its funding models.