Introduction There have been several reports on the role of human papillomavirus (HPV) in the etiology of breast cancer. To our knowledge, this is first study to use disease-disease association data-mining approach to analyzing viral warts and breast cancer to be conducted in Taiwanese population. Materials and methods We analyzed the Taiwan's National Health Insurance database (NHIDM data comprising of 23 million patient data) to examine the association between viral warts and female breast carcinoma. The patients were categorized into three groups: breast cancer only, viral warts only, and those with both breast cancer and viral warts. The Cox proportion hazard regression analysis was used to measure the effect of HPV on the time to breast cancer diagnosis. Multivariable analyzes and stratified analyzes using hazard ratios (HRs) were presented with 95% confidence intervals (CIs) after adjusting for age, and CCI. Result Among 807,578 HPV population, we identified 6014 breast cancer cases. The HPV group was associated with a significantly higher risk of developing breast cancer (HR, 1.18; 95% CI, 1.15–1.21; p < 0.001) compared with the non-HPV group. HPV patients with age group 18–39 was slightly higher risk of breast cancer occurrence (HR, 1.07; 95% CI, 1.01–1.13; p < .05). The risk of breast cancer in 10-year incidence was 7% higher for females less than 40 years and 23% for over 40 year's patients when compared with non-HPV patients of the same age group. Conclusion Our study indicates that women who develop viral warts are at a significantly higher risk of developing breast cancer than women who have not diagnosed with viral warts. Thus, the presence of viral warts is a potential risk to breast cancer. Therefore, we suggest patients diagnosed with viral warts may get early screening for breast cancer.

Original languageEnglish
Pages (from-to)203-207
Number of pages5
JournalComputer Methods and Programs in Biomedicine
Publication statusPublished - Jun 1 2017

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Health Informatics


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