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Development and validation of a new comorbidity index for patients with head and neck squamous cell carcinoma in Japan.

Yukinori TakenakaNorihiko TakemotoRyohei OyaNaoki AshidaTakahiro KitamuraKotaro ShimizuKazuya TakemuraTakahiro MichibaAtsushi HanamotoMotoyuki SuzukiYoshifumi YamamotoAtsuhiko UnoHidenori Inohara
Published in: Scientific reports (2017)
Due to habitual drinking and smoking and advanced age at diagnosis, patients with head and neck squamous cell carcinoma (HNSCC) frequently present with comorbidities. Several comorbidity indices have been developed and validated for HNSCC. However, none have become the standard method. In this study, we developed a new comorbidity index for Japanese patients with HNSCC, which was validated against an independent data set. A Cox proportional hazards analysis of 698 patients identified dementia, connective tissue diseases, and second primary malignancies in the oesophagus, head and neck, lungs, and stomach as prognostic comorbidities for overall survival. The Osaka head and neck comorbidity index (OHNCI) was generated from the weighted points of these comorbidities. In the independent data set, the 5-year overall survival rates for the low, moderate, and high scoring OHNCI groups were 62.1%, 64.3%, and 37.7%, respectively. In the multivariate analysis, the high scoring OHNCI group was an independent prognostic factor for overall survival (hazard ratio: 1.81, 95% confidence interval: 1.05-3.13; P = 0.031). The model including the OHNCI exhibited a higher prognostic capability compared to those including other commonly used comorbidity indices. The OHNCI could become the primary choice for comorbidity assessment in patients with HNSCC in Japan.
Keyphrases
  • prognostic factors
  • electronic health record
  • free survival
  • big data
  • data analysis
  • magnetic resonance imaging
  • machine learning
  • artificial intelligence
  • decision making
  • deep learning