Treatment results and prognostic factors of patients undergoing postoperative radiotherapy for laryngeal squamous cell carcinoma

Applying a nomogram based on preoperative CT to predict early recurrence of laryngeal squamous cell carcinoma after surgery

PURPOSE

To identify the value of a computed tomography (CT)-based radiomics model to predict probability of early recurrence (ER) in patients diagnosed with laryngeal squamous cell carcinoma (LSCC) after surgery.

MATERIALS AND METHOD

Pre-operative CT scans of 140 LSCC patients treated by surgery are reviewed and selected. These patients are randomly split into the training set (n = 97) and test set (n = 43). The regions of interest of each patient were delineated manually by two senior radiologists. Radiomics features are extracted from CT images acquired in non-enhanced, arterial, and venous phases. Variance threshold, one-way ANOVA, and least absolute shrinkage and selection operator algorithm are used for feature selection. Then, radiomics models are built with five algorithms namely, k-nearest neighbor (KNN), logistic regression (LR), linear support vector machine (LSVM), radial basis function SVM (RSVM), and polynomial SVM (PSVM). Clinical factors are selected using univariate and multivariate logistic regressions. Last, a radiomics nomogram incorporating the radiomics signature and clinical factors is built to predict ER and its efficiency is evaluated by receiver operating characteristic (ROC) curve and calibration curve. Decision curve analysis (DCA) is also used to evaluate clinical usefulness.

RESULTS

Four features are remarkably associated with ER in patients with LSCC. Applying to test set, the area under the ROC curves (AUCs) of KNN, LR, LSVM, RSVM, and PSVM are 0.936, 0.855, 0.845, 0.829, and 0.794, respectively. The radiomics nomogram shows better discrimination (with AUC: 0.939, 95% CI: 0.867-0.989) than the best radiomics model and the clinical model. Predicted and actual ERs in the calibration curves are in good agreement. DCA shows that the radiomics nomogram is clinically useful.

CONCLUSION

The radiomics nomogram, as a noninvasive prediction tool, exhibits favorable performance for ER prediction of LSCC patients after surgery.

Prediction of the mechanism of miRNAs in laryngeal squamous cell carcinoma based on the miRNA-mRNA regulatory network

In this study, a bioinformatics analysis is conducted to screen differentially expressed miRNAs and mRNAs in laryngeal squamous cell carcinoma (LSCC). Based on this information, we explored the possible roles of miRNAs in the pathogenesis of LSCC. The RNA-Seq data from 79 laryngeal cancer samples in the Gene Expression Omnibus (GEO) database were sorted. Differentially expressed miRNAs and mRNAs in LSCC are screened using the PERL programming language, and it was analysed by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The miRNA-mRNA regulatory network of LSCC is constructed using Cytoscape software. Then, quantitative real-time PCR (QRT- PCR), Cell Counting Kit-8 (CCK8) and flow cytometry analysis we are used to further validate key miRNAs. We identified 99 differentially expressed miRNAs and 2,758 differentially expressed mRNAs in LSCC tissues from the GEO database. Four more important miRNAs displaying a high degree of connectivity are selected, these results suggest that they play an important role in the pathogenesis of LSCC. As shown in the present study, we identified specific miRNA-mRNA networks associated with the occurrence and development of LSCC through bioinformatics analysis. We found a miRNA molecule closely related to LSCC based on miRNA-mRNA network: miR-140-3p was down-regulated in LSCC. In addition, the potential antitumor effect of miR-140-3p in LSCC was verified in the experiment, and it was proved that overexpression of miR-140-3p could inhibit the proliferation of LSCC cells and promote cell apoptosis, suggesting that miR-140-3p may be a potential tumor marker in LSCC.

Evaluation of CT-based radiomics signature and nomogram as prognostic markers in patients with laryngeal squamous cell carcinoma

Background

The aim of this study was to evaluate the prognostic value of radiomics signature and nomogram based on contrast-enhanced computed tomography (CT) in patients after surgical resection of laryngeal squamous cell carcinoma (LSCC).

Methods

All patients (n = 136) were divided into the training cohort (n = 96) and validation cohort (n = 40). The LASSO regression method was performed to construct radiomics signature from CT texture features. Then a radiomics nomogram incorporating the radiomics signature and clinicopathologic factors was established to predict overall survival (OS). The validation of nomogram was evaluated by calibration curve, concordance index (C-index) and decision curve.

Results

Based on three selected texture features, the radiomics signature showed high C-indexes of 0.782 (95%CI: 0.656–0.909) and 0.752 (95%CI, 0.614–0.891) in the two cohorts. The radiomics nomogram had significantly better discrimination capability than cancer staging in the training cohort (C-index, 0.817 vs. 0.682; P = 0.009) and validation cohort (C-index, 0.913 vs. 0.699; P = 0.019), as well as a good agreement between predicted and actual survival in calibration curves. Decision curve analysis also suggested improved clinical utility of radiomics nomogram.

Conclusions

Radiomics signature and nomogram showed favorable prediction accuracy for OS, which might facilitate the individualized risk stratification and clinical decision-making in LSCC patients.

T4a laryngeal cancer survival: retrospective institutional analysis and systematic review

OBJECTIVES/HYPOTHESIS

To assess the survival outcomes of a homogeneous group of pT4a laryngeal cancer patients treated at our institution by primary total laryngectomy and neck dissection with adjuvant therapy when indicated, and to systematically review studies reporting overall survival outcomes in T4a laryngeal cancer.

STUDY DESIGN

Systematic review of PubMed and Embase databases.

METHODS

Records of 108 laryngeal cancer patients treated by total laryngectomy were reviewed. pT4a cases treated by primary total laryngectomy between 1998 and 2010 were included. Overall and disease-free survival at 2 and 5 years were reported. A systematic review was performed including all published studies reporting overall survival outcomes by treatment modality in T4 laryngeal cancer patients.

RESULTS

Thirty cases met the inclusion criteria. At 2 years, overall and disease-free survival were 81.3% and 78%, respectively. The 5-year overall and disease-free survival rates were 60%. The systematic review retrieved 24 articles. Overall survival at 2 years ranged from 12% to 21.2% with radiotherapy, <30% to 65% with chemoradiotherapy, and from 30% to 100% with surgery. At 5 years, it ranged from 0% to 75% with radiotherapy, 16% to 50.4% with chemoradiotherapy, and 10% to 80.9% with surgery.

CONCLUSIONS

Primary total laryngectomy provides a high survival rate for pT4a laryngeal cancer patients. Randomized controlled trials including homogenous patients are still needed before shifting to organ preservation protocols in these patients.

LEVEL OF EVIDENCE

NA.