Frontiers in Oncology (Sep 2021)

Advanced Lung Cancer Inflammation Index Predicts Survival Outcomes of Patients With Oral Cavity Cancer Following Curative Surgery

  • Yao-Te Tsai,
  • Cheng-Ming Hsu,
  • Cheng-Ming Hsu,
  • Geng-He Chang,
  • Ming-Shao Tsai,
  • Yi-Chan Lee,
  • Ethan I. Huang,
  • Ethan I. Huang,
  • Chia-Hsuan Lai,
  • Ku-Hao Fang

DOI
https://doi.org/10.3389/fonc.2021.609314
Journal volume & issue
Vol. 11

Abstract

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AimThe aim of our study was to investigate the prognostic value of preoperative advanced lung cancer inflammation index (ALI) and to establish prognostic nomograms for the prediction of survival outcomes in patients with oral cavity squamous cell carcinoma (OSCC).Materials and MethodsA total of 372 patients who received primary curative surgery for OSCC during 2008–2017 at a tertiary referral center were enrolled. We used the receiver operating characteristic curve to determine the optimal cutoff point of ALI. Through a Cox proportional hazards model and Kaplan–Meier analysis, we elucidated the ALI–overall survival (OS) and ALI–disease-free survival (DFS) associations. Prognostic nomograms based on ALI and the results of multivariate analysis were created to predict the OS and DFS. We used the concordance indices (C-indices) and calibration plots to assess the discriminatory and predictive ability.ResultsThe results revealed that the ALI cutoff was 33.6, and 105 and 267 patients had ALI values of <33.6 and ≥33.6, respectively. ALI < 33.6 significantly indicated lower OS (44.0% vs. 80.1%, p < 0.001) and DFS (33.6% vs. 62.8%; p < 0.001). In multivariate analysis, ALI < 33.6 was independently associated with poor OS and DFS (both p < 0.001). The C-indices of established nomograms were 0.773 and 0.674 for OS and DFS, respectively; moreover, the calibration plots revealed good consistency between nomogram-predicted and actual observed OS and DFS.ConclusionALI is a promising prognostic biomarker in patients undergoing primary surgery for OSCC; moreover, ALI-based nomograms may be a useful prognostic tool for individualized OS and DFS estimations.

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