Open Access

Application of the advanced lung cancer inflammation index for patients with coronavirus disease 2019 pneumonia: Combined risk prediction model with advanced lung cancer inflammation index, computed tomography and chest radiograph

  • Authors:
    • Akitoshi Inoue
    • Hiroaki Takahashi
    • Tatsuya Ibe
    • Hisashi Ishii
    • Yuhei Kurata
    • Yoshikazu Ishizuka
    • Bolorkhand Batsaikhan
    • Yoichiro Hamamoto
  • View Affiliations

  • Published online on: April 12, 2022     https://doi.org/10.3892/etm.2022.11315
  • Article Number: 388
  • Copyright : © Inoue et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY 4.0].

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Abstract

The purpose of the present study was to evaluate the feasibility of applying the advanced lung cancer inflammation index (ALI) in patients with coronavirus disease 2019 (COVID‑19) and to establish a combined ALI and radiologic risk prediction model for disease exacerbation. The present study included patients diagnosed with COVID‑19 infection in our single institution from March to October 2020. Patients without clinical information and/or chest computed tomography (CT) upon admission were excluded. A radiologist assessed the CT severity score and abnormality on chest radiograph. The combined ALI and radiologic risk prediction model was developed via random forest classification. Among 79 patients (age, 43±19 years; male/female, 45:34), 72 experienced improvement and seven patients experienced exacerbation after admission. Significant differences were observed between the improved and exacerbated groups in the ALI (median, 47.6 vs. 13.2; P=0.011), frequency of chest radiograph abnormality (24.7 vs. 83.3%; P<0.001), and chest CT score (CCTS; median, 1 vs. 9; P<0.001). For the accuracy of predicting exacerbation, the receiver‑operating characteristic curve analysis demonstrated an area under the curve of 0.79 and 0.92 for the ALI and CCTS, respectively. The combined ALI and radiologic risk prediction model had a sensitivity of 1.00 and a specificity of 0.81. Overall, ALI alone and CCTS alone modestly predicted the exacerbation of COVID‑19, and the combined ALI and radiologic risk prediction model exhibited decent sensitivity and specificity.
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June-2022
Volume 23 Issue 6

Print ISSN: 1792-0981
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Spandidos Publications style
Inoue A, Takahashi H, Ibe T, Ishii H, Kurata Y, Ishizuka Y, Batsaikhan B and Hamamoto Y: Application of the advanced lung cancer inflammation index for patients with coronavirus disease 2019 pneumonia: Combined risk prediction model with advanced lung cancer inflammation index, computed tomography and chest radiograph. Exp Ther Med 23: 388, 2022
APA
Inoue, A., Takahashi, H., Ibe, T., Ishii, H., Kurata, Y., Ishizuka, Y. ... Hamamoto, Y. (2022). Application of the advanced lung cancer inflammation index for patients with coronavirus disease 2019 pneumonia: Combined risk prediction model with advanced lung cancer inflammation index, computed tomography and chest radiograph. Experimental and Therapeutic Medicine, 23, 388. https://doi.org/10.3892/etm.2022.11315
MLA
Inoue, A., Takahashi, H., Ibe, T., Ishii, H., Kurata, Y., Ishizuka, Y., Batsaikhan, B., Hamamoto, Y."Application of the advanced lung cancer inflammation index for patients with coronavirus disease 2019 pneumonia: Combined risk prediction model with advanced lung cancer inflammation index, computed tomography and chest radiograph". Experimental and Therapeutic Medicine 23.6 (2022): 388.
Chicago
Inoue, A., Takahashi, H., Ibe, T., Ishii, H., Kurata, Y., Ishizuka, Y., Batsaikhan, B., Hamamoto, Y."Application of the advanced lung cancer inflammation index for patients with coronavirus disease 2019 pneumonia: Combined risk prediction model with advanced lung cancer inflammation index, computed tomography and chest radiograph". Experimental and Therapeutic Medicine 23, no. 6 (2022): 388. https://doi.org/10.3892/etm.2022.11315