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A population analysis of delayed ejaculation using a claims database: characteristics and national trends in prevalence, incidence, and pharmacotherapy

International Journal of Impotence Research volume 37, pages 471–476 (2025)Cite this article

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Abstract

We investigated the prevalence, incidence, and rates of pharmacological treatment of delayed ejaculation using the TriNetX Diamond Network. We included all men evaluated in the inpatient, outpatient, and emergency settings. Prevalence was determined by comparing the number of men diagnosed with delayed ejaculation to the entire population. Incidence was determined by comparing the number of men diagnosed with delayed ejaculation without a prior diagnosis to the overall population without a prior diagnosis. Rates of pharmacologic treatment were calculated by comparing the number of men who received a prescription to the total number of men with delayed ejaculation. Trends in prevalence and incidence were compared using six-month intervals, while trends in pharmacologic treatment were compared using one-year intervals. A total of 23,164 adult males were diagnosed with delayed ejaculation from 2013 to 2019. During the final six-month interval (July to December 2019), 2,747 of 16,496,744 men received a delayed ejaculation diagnosis, and 1,375 of 16,488,270 men without a prior diagnosis were diagnosed with delayed ejaculation. In 2019, only 916 of 4,733 (19.4%) men diagnosed with delayed ejaculation received any prescription, with the most common being testosterone (9.5%), bupropion (6.6%), and buspirone (2.3%). Prevalence, incidence and pharmacologic treatment all had increasing trends.

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Fig. 1: Trends in prevalence for DE.
Fig. 2: Trends in incidence for DE.
Fig. 3

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Data availability

Data regarding any of the subjects in the study has not been previously published. Data will be made available to the editors of the journal for review or query upon request.

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Authors and Affiliations

  1. John Sealy School of Medicine, The University of Texas Medical Branch at Galveston, Galveston, TX, USA

    Brian Liao & Steven Banner

  2. Division of Urology, Department of Surgery, The University of Texas Medical Branch at Galveston, Galveston, TX, USA

    Corey Able, Ali A. Nasrallah, Kevin Vu, Joseph Sonstein & Laith Alzweri

  3. The Robert Larner M.D. College of Medicine, The University of Vermont, Burlington, VT, USA

    Clemens An

  4. The James Buchanan Brady Urological Institute, Johns Hopkins Medicine, Baltimore, MD, USA

    Taylor P. Kohn

Authors
  1. Brian Liao
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  2. Corey Able
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  4. Clemens An
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  5. Ali A. Nasrallah
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  7. Joseph Sonstein
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  8. Laith Alzweri
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  9. Taylor P. Kohn
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Contributions

Brian Liao: Idea generation, data collection, data analysis, manuscript writing, manuscript editing. Corey Able: Idea generation, data collection, data analysis, manuscript writing, manuscript editing. Steven Banner: Manuscript writing, manuscript editing. Clemens An: Manuscript writing, manuscript editing. Ali Nasrallah: Manuscript writing, manuscript editing. Kevin Vu: Manuscript writing, manuscript editing. Joseph Sonstein: Idea refinement, manuscript editing. Laith Alzweri: Idea refinement, manuscript editing. Taylor Kohn: Idea refinement, data analysis, manuscript editing.

Corresponding author

Correspondence to Taylor P. Kohn.

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Competing interests

The authors declare no competing interests.

Ethics approval

The process by which the data was de-identified is attested to through a formal determination by a qualified expert as defined in Section §164.514(b)(1) of the HIPAA Privacy Rule. Because studies using TriNetX de-identified patient records do not involve the collection, use, or transmittal of individually identifiable data, the qualified expert has determined these studies are exempted from the need of Institutional Review Board review. Any patient counts less than 10 are obfuscated to ensure patient anonymity, and only aggregate patient counts and statistical summaries are provided.

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Liao, B., Able, C., Banner, S. et al. A population analysis of delayed ejaculation using a claims database: characteristics and national trends in prevalence, incidence, and pharmacotherapy. Int J Impot Res 37, 471–476 (2025). https://doi.org/10.1038/s41443-024-00937-z

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