Literature DB >> 26051697

Comparing cutaneous research funded by the US National Institutes of Health (NIH) with the US skin disease burden.

Erika L Hagstrom1, Shivani Patel2, Chante Karimkhani3, Lindsay N Boyers4, Hywel C Williams5, Roderick J Hay6, Martin A Weinstock7, April W Armstrong8, Cory A Dunnick9, David J Margolis10, Robert P Dellavalle11.   

Abstract

BACKGROUND: Disease burden should be an important component for guiding research funding.
OBJECTIVE: We sought to examine the relationship between dermatologic research funded from 2012 to 2013 by the National Institutes of Health (NIH) and US skin disease burden as measured by disability-adjusted life years in the Global Burden of Disease 2010 study.
METHODS: A cross-sectional analysis was independently performed by 2 researchers who matched projects from the 2012 to 2013 NIH Research Portfolio Online Reporting Tools with 15 skin conditions and their respective disability-adjusted life years from Global Burden of Disease 2010.
RESULTS: The NIH funded 1108 projects spanning the 15 skin conditions. Melanoma received almost half of the total skin condition budget (49.5%). Melanoma, nonmelanoma skin cancer, and leprosy were funded above what would be suggested by their disease burden, whereas dermatitis, acne vulgaris, pruritus, urticaria, decubitus ulcer, fungal skin diseases, alopecia areata, cellulitis, and scabies appeared underfunded. Bacterial skin diseases, viral skin diseases, and psoriasis were well matched with disease burden. LIMITATIONS: Disease burden is one of many factors that may be used to guide priority-setting decisions.
CONCLUSION: Skin disease burden measured by disability-adjusted life year metrics partially correlates with NIH funding prioritization. Comparing US disease burden with NIH funding suggests possible underfunded and overfunded skin diseases. Published by Elsevier Inc.

Entities:  

Keywords:  National Institutes of Health; dermatitis; disability-adjusted life years; disease burden; leprosy; melanoma; priority setting; skin conditions

Mesh:

Year:  2015        PMID: 26051697     DOI: 10.1016/j.jaad.2015.04.039

Source DB:  PubMed          Journal:  J Am Acad Dermatol        ISSN: 0190-9622            Impact factor:   11.527


  10 in total

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2.  Machine learning workflow to enhance predictions of Adverse Drug Reactions (ADRs) through drug-gene interactions: application to drugs for cutaneous diseases.

Authors:  Kalpana Raja; Matthew Patrick; James T Elder; Lam C Tsoi
Journal:  Sci Rep       Date:  2017-06-16       Impact factor: 4.379

3.  A systematic review of scabies transmission models and data to evaluate the cost-effectiveness of scabies interventions.

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Journal:  PLoS Negl Trop Dis       Date:  2019-03-08

4.  Development of R7BP inhibitors through cross-linking coupled mass spectrometry and integrated modeling.

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Journal:  Commun Biol       Date:  2019-09-13

5.  Risk factors of chronic urticaria among nurses with insomnia: A nationwide population-based study.

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Journal:  Medicine (Baltimore)       Date:  2019-12       Impact factor: 1.889

6.  Development and Validation of a Simple Model to Predict the Risk of Nonmelanoma Skin Cancer on Screening Total Body Skin Examination.

Authors:  Rebecca I Hartman; Yun Xue; Ryan Karmouta; Elizabeth Tkachenko; Sara J Li; David G Li; Cara Joyce; Arash Mostaghimi
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7.  Healthcare Utilization and Costs Among US Adolescents With Alopecia Areata.

Authors:  Markqayne Ray; Elyse Swallow; Kavita Gandhi; Christopher Carley; Vanja Sikirica; Travis Wang; Nicolae Done; James Signorovitch; Arash Mostaghimi
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Review 8.  The Nexus Between Diabetes and Depression: A Narrative Review.

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9.  Limited alignment of publicly competitive disease funding with disease burden in Japan.

Authors:  Shuhei Nomura; Daisuke Yoneoka; Shiori Tanaka; Ryoko Makuuchi; Haruka Sakamoto; Aya Ishizuka; Haruyo Nakamura; Anna Kubota; Kenji Shibuya
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Review 10.  Dermatology on the global stage: The role of dermatologists in international health advocacy and COVID-19 research.

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  10 in total

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