DOI QR코드

DOI QR Code

Nomogram plot for predicting chronic otitis media in Korean adults

  • Received : 2017.05.25
  • Accepted : 2017.07.05
  • Published : 2017.07.31

Abstract

Nomogram is useful for predicting the prevalence of each patient through the scoring system without a complex formula. Because there are few studies on chronic otitis media (COM) in adults, this study aims to identify the relevant risk factors for COM in Korean adults and to build a nomogram for the risk factors. The Health Interview Survey data subset, derived from the Sixth Korean National Health and Nutrition Examination Survey (KNHANES VI), was used to evaluate the participants. Of the participants, the weighted prevalence of COM was 5.3%. Residence, earphone use, atopic dermatitis, allergic rhinitis, chronic rhinosinusitis, and subjective hearing status were identified as risk factors for COM. Using 6 risk factors, we propose a nomogram for COM, and use AUC to verify the discrimination of the nomogram.

Keywords

References

  1. Ahn, J. H. (2013). Nomogram for prediction of prostate cancer in Korean men with serum prostate-specific antigen less than 10ng/mL, Master's Degree Thesis, Pusan National University, Busan.
  2. Collaborators (2015). Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for the global burden of disease study 2013. The Lancet, 385, 117-171. https://doi.org/10.1016/S0140-6736(14)61682-2
  3. Engel, J. A., Straetemans, M. and Zielhuis, G. A. (2005). Birth characteristics and recurrent otitis media with effusion in young children. International Journal of Pediatric Otorhinolaryngology, 69, 533-540. https://doi.org/10.1016/j.ijporl.2004.11.026
  4. Gozal, D., Kheirandish-Gozal, L., Capdevila, O. S., Dayyat, E. and Kheirandish, E. (2008). Prevalence of recurrent otitis media in habitually snoring school-aged children. Sleep Medicine, 9, 549-554. https://doi.org/10.1016/j.sleep.2007.08.002
  5. Gultekin, E., Develioglu, O. N., Yener, M., Ozdemir, I and Kulekci, M. (2010). Prevalence and risk factors for persistent otitis media with effusion in primary school children in Istanbul, Turkey. Auris Nasus Larynx, 37, 145-149. https://doi.org/10.1016/j.anl.2009.05.002
  6. Han J. Y. and Park H. S. (2016). Prevalence of allergic diseases and its related factors in Korean adolescents-Using data from the 2013 Korea youth risk behavior web-based survey. Journal of the Korean Data & Information Science Society, 27, 155-168. https://doi.org/10.7465/jkdi.2016.27.1.155
  7. Iasonos, A., Schrag, D., Raj, G. V. and Panageas, K. S. (2008). How to build and interpret a nomogram for cancer prognosis. Journal of Clinical Oncology, 26, 1364-1370. https://doi.org/10.1200/JCO.2007.12.9791
  8. Kim, S. H., Shin, K., Kim, H. Y., Cho, Y. J., Noh, J. K., Suh, J. S. and Yang, W. I. (2014). Postoperative nomogram to predict the probability of metastasis in Enneking stage IIB extremity osteosarcoma. BioMed Cental Cancer, 12, 666.
  9. Lee, J. W., Park, M. R. and Yu, H. N. (2005). Statistical method for bioscience research, freedom academy, Seoul.
  10. Lee, J. Y. and Kim, H. J. (2014). Identification of major risk factors association with respiratory diseases by data mining. Journal of the Korean Data & Information Science Society, 25, 373-384. https://doi.org/10.7465/jkdi.2014.25.2.373
  11. Lee, K. M., Kim, W. J. and Yun, S. J. (2009). A clinical nomogram construction method using genetic algorithm and nave Bayesian technique. Journal of Korean Institute of Intelligent Systems, 19, 769-801.
  12. Park, M., Lee, J. S., Lee, J. H., Oh, S. H. and Park, M. K. (2015). Prevalence and risk factors of chronic otitis media: the Korean national health and nutrition examination survey 2010-2012. PLoS ONE, 10, 1-13.
  13. Park, R. J. and Moon, J. D. (2014). Prevalence and risk factors of tinnitus: The Korean national health and nutrition examination survey 2010011, a cross-sectional study. Clinical Otolaryngology, 39, 89-94. https://doi.org/10.1111/coa.12232
  14. Pearce, J. and Ferrier, S. (2000). Evaluating the predictive performance of habitat models developed using logistic. Ecological Modelling, 133, 225-245. https://doi.org/10.1016/S0304-3800(00)00322-7
  15. Qureishi, A., Lee Y., Belfield, K., Birchall, J. P. and Daniel, M. (2014). Update on otitis media - prevention and treatment. Infection and Drug Resistance, 7, 15-24.
  16. Teele D. W., Klein J. O. and Rosner B. (1989) Epidemiology of otitis media during the first seven years of life in children in greater Boston: a prospective, cohort study. The Journal of Infectious Diseases, 160, 83-94. https://doi.org/10.1093/infdis/160.1.83
  17. Van Zon, A., Van der Heijden, G. J., Van Dongen, T. M. A, Burton, M. J. and Schilder, A. G M. (2013). Antibiotics for otitis media with effusion in children. Clinical Otolaryngology, 38, 54-55. https://doi.org/10.1111/coa.12068
  18. Yang, D. (2014). Build prognostic nomograms for risk assessment using SAS. In Proceedings of SAS Global Forum 2013. Paper 264013. http://support.sas.com/resources/papers/proceedings13/264-2013.pdf.
  19. Yeo, S. G., Park, D. C., Eun, Y. G. and Cha, C. I. (2007). The role of allergic rhinitis in the development of otitis media with effusion: effect on eustachian tube function. American Journal of Otolaryngology, 28, 148-152. https://doi.org/10.1016/j.amjoto.2006.07.011