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Background <p>To evaluate the prognostic role of the preoperative pan-immune-inflammation value (PIV) index in patients with oral squamous cell carcinoma (OSCC) after undergoing radical resection and to develop a prognostic prediction model for these patients.</p> Methods <p>A large cohort study was conducted between January 2015 and March 2022. Univariate and multivariate Cox regression was used to assess the prognostic value of PIV, and propensity score matching (PSM) analysis was used to adjust for potential confounders. Randomized survival forest (RSF) was used to assess the relative importance of preoperative PIV in prognostic prediction. Finally, a Nomogram model was plotted to predict the prognosis of oral cancer patients.</p> Results <p>A total of 779 patients were enrolled and followed up (mean follow-up time 34.14 ± 24.39). High PIV was significantly associated with worse survival in OSCC patients (hazard ratio [HR] = 1.62, 95% confidence interval [CI]: 1.15–2.29, <i>P</i> = 0.006). The same trend was observed in PSM (HR = 1.55,95% CI: 1.03–2.23, <i>P</i> = 0.035). RSF showed that PIV ranked third in the importance ranking of all prognostic factors. The calibration curves indicated that the Nomogram model was superior in predicting the prognostic 1-, 3-, and 5-year survival of oral cancer patients.</p> Conclusions <p>PIV is an independent predictor of prognosis in patients with oral squamous cell carcinoma, and a column-line graphical model based on PIV can effectively predict prognosis.</p>

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Predictive value of preoperative pan-immune-inflammation value index in the prognosis of oral cancer patients undergoing radical resection

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年1月24日

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  • Weihai Huang,
  • Yulan Lin,
  • Enling Xu,
  • Yanmei Ji,
  • Jing Wang,
  • Fengqiong Liu,
  • Fa Chen,
  • Yu Qiu,
  • Bin Shi,
  • Lisong Lin,
  • Baochang He

摘要

Background

To evaluate the prognostic role of the preoperative pan-immune-inflammation value (PIV) index in patients with oral squamous cell carcinoma (OSCC) after undergoing radical resection and to develop a prognostic prediction model for these patients.

Methods

A large cohort study was conducted between January 2015 and March 2022. Univariate and multivariate Cox regression was used to assess the prognostic value of PIV, and propensity score matching (PSM) analysis was used to adjust for potential confounders. Randomized survival forest (RSF) was used to assess the relative importance of preoperative PIV in prognostic prediction. Finally, a Nomogram model was plotted to predict the prognosis of oral cancer patients.

Results

A total of 779 patients were enrolled and followed up (mean follow-up time 34.14 ± 24.39). High PIV was significantly associated with worse survival in OSCC patients (hazard ratio [HR] = 1.62, 95% confidence interval [CI]: 1.15–2.29, P = 0.006). The same trend was observed in PSM (HR = 1.55,95% CI: 1.03–2.23, P = 0.035). RSF showed that PIV ranked third in the importance ranking of all prognostic factors. The calibration curves indicated that the Nomogram model was superior in predicting the prognostic 1-, 3-, and 5-year survival of oral cancer patients.

Conclusions

PIV is an independent predictor of prognosis in patients with oral squamous cell carcinoma, and a column-line graphical model based on PIV can effectively predict prognosis.