CT-Based Radiomics Nomogram for Prediction of Progression-Free Survival in Locoregionally Advanced Nasopharyngeal Carcinoma

Abstract

Purpose

We aimed to construct of a nomogram to predict progression-free survival (PFS) in locoregionally advanced nasopharyngeal carcinoma (LA-NPC) with risk stratification using computed tomography (CT) radiomics features and clinical factors.

Patients and Methods

A total of 311 patients diagnosed with LA-NPC (stage III–IVa) at our hospital between 2010 and 2014 were included. The region of interest (ROI) of the primary nasopharyngeal mass was manually outlined. Independent sample t-test and LASSO-logistic regression were used for selecting the most predictive radiomics features of PFS, and to generate a radiomics signature. A nomogram was built with clinical factors and radiomics features, and the risk stratification model was tested accordingly.

Results

In total, 20 radiomics features most associated with prognosis were selected. The radiomics nomogram, which integrated the radiomics signature and significant clinical factors, showed excellent performance in predicting PFS, with C-index of 0.873 (95% CI: 0.803~0.943), which was better than that of the clinical nomogram (C-index, 0.729, 95% CI: 0.620~0.838) as well as of the TNM staging system (C-index, 0.689, 95% CI: 0.592–0.787) in validation cohort. The calibration curves and the decision curve analysis (DCA) plot obtained suggested satisfying accuracy and clinical utility of the model. The risk stratification tool was able to predict differences in prognosis of patients in different risk categories (p<0.001).

Conclusion

CT-based radiomics features, an in particular, radiomics nomograms, have the potential to become an accurate and reliable tool for assisting with prognosis prediction of LA-NPC.

Keywords:

• computed tomography
• locoregionally advanced nasopharyngeal carcinoma
• radiomics
• nomogram

Acknowledgments

This work was supported by the Key Research and Development Program Project of Guangxi Zhuang Autonomous Region [Grant No. GuikeAB18221007]; and The Independent Project of Key Laboratory of Early Prevention & Treatment for Regional High‐Incidence‐Tumor [Grant No. GKE-ZZ202014]; Guangxi Science and Technology Department research program [Grant No. AB18126031]; Wu Jieping Medical Foundation Clinical Research [Grant No. 320.6750.2020-08-15]; and Zhejiang Xinmiao Talent Plan Project in 2020 [Grant No.2020R410006].

Abbreviations

PFS, progression-free survival; LA-NPC, locoregionally advanced nasopharyngeal carcinoma; CT, computed tomography; ROI, the region of interest; C-index, consistency index; DCA, the decision curve analysis; NPC, nasopharyngeal carcinoma; IMRT, intensity-modulated radiotherapy; IC, Induction chemotherapy; CCRT, Concurrent Chemoradiotherapy; AC, Adjuvant chemotherapy; GLCM, gray level co-generation matrix; GLRLM, gray level length run length matrix; GLSZM, gray level size zone matrix; NGTDM, neighborhood gray tone difference matrix; GLDM, gray level dependence matrix; ICC, Intraclass correlation coefficient; Hb, hemoglobin; NLR, neutrophil to lymphocyte ratio; PLR, platelet to lymphocyte ratio; ALP, alkaline phosphatase; LDH, lactate dehydrogenase.

Ethical Approval and Consent to Participate

This study was approved by the Ethics Committee of Guangxi Medical University Cancer Hospital (LW2021034), in compliance with the Declaration of Helsinki. Due to the retrospective nature of the study, the risk to patients in this study is not greater than the minimum risk, so patient consent to review their medical records is not applicable. All patient information is anonymous.

Disclosure

The authors report no conflicts of interest in this work.