Development and validation of a nomogram to predicting the efficacy of PD‑1/PD‑L1 inhibitors in patients with nasopharyngeal carcinoma

• Yao Chen ^[1] ; Dubo Chen ^[1] ; Ruizhi Wang ^[1] ; Shuhua Xie ^[1] ; Hao Huang ^[1] ; Xueping Wang ^[2]
  1. [1] First Affiliated Hospital of Sun Yat-sen University

     First Affiliated Hospital of Sun Yat-sen University

     China

     
  2. [2] Sun Yat-sen University Cancer Center

     Sun Yat-sen University Cancer Center

     China

     
• Localización: Clinical & translational oncology, ISSN 1699-048X, Vol. 26, Nº. 10, 2024, págs. 2601-2607
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • Purpose With the treatment of nasopharyngeal carcinoma (NPC) by PD-1/PD-L1 inhibitors used widely in clinic, it becomes very necessary to anticipate whether patients would benefit from it. We aimed to develop a nomogram to evaluate the efficacy of anti-PD-1/PD-L1 in NPC patients.

    Methods Totally 160 NPC patients were enrolled in the study. Patients were measured before the first PD-1/PD-L1 inhibitors treatment and after 8–12 weeks of immunotherapy by radiological examinations to estimate the effect. The least absolute shrinkage and selection operator (LASSO) logistic regression was used to screen hematological markers and establish a predictive model. The nomogram was internally validated by bootstrap resampling and externally validated. Performance of the model was evaluated using concordance index, calibration curve, decision curve analysis and receiver operation characteristic curve.

    Results Patients involved were randomly split into training cohort ang validation cohort. Based on Lasso logistic regression, systemic immune-inflammation index (SII) and ALT to AST ratio (LSR) were selected to establish a predictive model. The C-index of training cohort and validating cohort was 0.745 and 0.760. The calibration curves and decision curves showed the precise predictive ability of this nomogram. The benefit of the model showed in decision curve was better than TNM stage. The area under the curve (AUC) value of training cohort and validation cohort was 0.745 and 0.878, respectively.

    Conclusion The predictive model helped evaluating efficacy with high accuracy in NPC patients treated with PD-1/PD-L1 inhibitors.