Induction-concurrent chemoradiotherapy with or without sintilimab in patients with locoregionally advanced nasopharyngeal carcinoma in China (CONTINUUM): a multicentre, open-label, parallel-group, randomised, controlled, phase 3 trial.

BACKGROUND: Anti-PD-1 therapy and chemotherapy is a recommended first-line treatment for recurrent or metastatic nasopharyngeal carcinoma, but the role of PD-1 blockade remains unknown in patients with locoregionally advanced nasopharyngeal carcinoma. We assessed the addition of sintilimab, a PD-1 inhibitor, to standard chemoradiotherapy in this patient population. METHODS: This multicentre, open-label, parallel-group, randomised, controlled, phase 3 trial was conducted at nine hospitals in China. Adults aged 18-65 years with newly diagnosed high-risk non-metastatic stage III-IVa locoregionally advanced nasopharyngeal carcinoma (excluding T3-4N0 and T3N1) were eligible. Patients were randomly assigned (1:1) using blocks of four to receive gemcitabine and cisplatin induction chemotherapy followed by concurrent cisplatin radiotherapy (standard therapy group) or standard therapy with 200 mg sintilimab intravenously once every 3 weeks for 12 cycles (comprising three induction, three concurrent, and six adjuvant cycles to radiotherapy; sintilimab group). The primary endpoint was event-free survival from randomisation to disease recurrence (locoregional or distant) or death from any cause in the intention-to-treat population. Secondary endpoints included adverse events. This trial is registered with ClinicalTrials.gov (NCT03700476) and is now completed; follow-up is ongoing. FINDINGS: Between Dec 21, 2018, and March 31, 2020, 425 patients were enrolled and randomly assigned to the sintilimab (n=210) or standard therapy groups (n=215). At median follow-up of 41·9 months (IQR 38·0-44·8; 389 alive at primary data cutoff [Feb 28, 2023] and 366 [94%] had at least 36 months of follow-up), event-free survival was higher in the sintilimab group compared with the standard therapy group (36-month rates 86% [95% CI 81-90] vs 76% [70-81]; stratified hazard ratio 0·59 [0·38-0·92]; p=0·019). Grade 3-4 adverse events occurred in 155 (74%) in the sintilimab group versus 140 (65%) in the standard therapy group, with the most common being stomatitis (68 [33%] vs 64 [30%]), leukopenia (54 [26%] vs 48 [22%]), and neutropenia (50 [24%] vs 46 [21%]). Two (1%) patients died in the sintilimab group (both considered to be immune-related) and one (<1%) in the standard therapy group. Grade 3-4 immune-related adverse events occurred in 20 (10%) patients in the sintilimab group. INTERPRETATION: Addition of sintilimab to chemoradiotherapy improved event-free survival, albeit with higher but manageable adverse events. Longer follow-up is necessary to determine whether this regimen can be considered as the standard of care for patients with high-risk locoregionally advanced nasopharyngeal carcinoma. FUNDING: National Natural Science Foundation of China, Key-Area Research and Development Program of Guangdong Province, Natural Science Foundation of Guangdong Province, Overseas Expertise Introduction Project for Discipline Innovation, Guangzhou Municipal Health Commission, and Cancer Innovative Research Program of Sun Yat-sen University Cancer Center. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Radiomics-based nomogram guides adaptive de-intensification in locoregionally advanced nasopharyngeal carcinoma following induction chemotherapy.

OBJECTIVES: This study aimed to construct a radiomics-based model for prognosis and benefit prediction of concurrent chemoradiotherapy (CCRT) versus intensity-modulated radiotherapy (IMRT) in locoregionally advanced nasopharyngeal carcinoma (LANPC) following induction chemotherapy (IC). MATERIALS AND METHODS: A cohort of 718 LANPC patients treated with IC + IMRT or IC + CCRT were retrospectively enrolled and assigned to a training set (n = 503) and a validation set (n = 215). Radiomic features were extracted from pre-IC and post-IC MRI. After feature selection, a delta-radiomics signature was built with LASSO-Cox regression. A nomogram incorporating independent clinical indicators and the delta-radiomics signature was then developed and evaluated for calibration and discrimination. Risk stratification by the nomogram was evaluated with Kaplan-Meier methods. RESULTS: The delta-radiomics signature, which comprised 19 selected features, was independently associated with prognosis. The nomogram, composed of the delta-radiomics signature, age, T category, N category, treatment, and pre-treatment EBV DNA, showed great calibration and discrimination with an area under the receiver operator characteristic curve of 0.80 (95% CI 0.75-0.85) and 0.75 (95% CI 0.64-0.85) in the training and validation sets. Risk stratification by the nomogram, excluding the treatment factor, resulted in two groups with distinct overall survival. Significantly better outcomes were observed in the high-risk patients with IC + CCRT compared to those with IC + IMRT, while comparable outcomes between IC + IMRT and IC + CCRT were shown for low-risk patients. CONCLUSION: The radiomics-based nomogram can predict prognosis and survival benefits from concurrent chemotherapy for LANPC following IC. Low-risk patients determined by the nomogram may be potential candidates for omitting concurrent chemotherapy during IMRT. CLINICAL RELEVANCE STATEMENT: The radiomics-based nomogram was constructed for risk stratification and patient selection. It can help guide clinical decision-making for patients with locoregionally advanced nasopharyngeal carcinoma following induction chemotherapy, and avoid unnecessary toxicity caused by overtreatment. KEY POINTS: • The benefits from concurrent chemotherapy remained controversial for locoregionally advanced nasopharyngeal carcinoma following induction chemotherapy. • Radiomics-based nomogram achieved prognosis and benefits prediction of concurrent chemotherapy. • Low-risk patients defined by the nomogram were candidates for de-intensification.

Predicting response to immunotherapy plus chemotherapy in patients with esophageal squamous cell carcinoma using non-invasive Radiomic biomarkers.

OBJECTIVES: To develop and validate a radiomics model for evaluating treatment response to immune-checkpoint inhibitor plus chemotherapy (ICI + CT) in patients with advanced esophageal squamous cell carcinoma (ESCC). METHODS: A total of 64 patients with advance ESCC receiving first-line ICI + CT at two centers between January 2019 and June 2020 were enrolled in this study. Both 2D ROIs and 3D ROIs were segmented. ComBat correction was applied to minimize the potential bias on the results due to different scan protocols. A total of 788 features were extracted and radiomics models were built on corrected/uncorrected 2D and 3D features by using 5-fold cross-validation. The performance of the radiomics models was assessed by its discrimination, calibration and clinical usefulness with independent validation. RESULTS: Five features and support vector machine algorithm were selected to build the 2D uncorrected, 2D corrected, 3D uncorrected and 3D corrected radiomics models. The 2D radiomics models significantly outperformed the 3D radiomics models in both primary and validation cohorts. When ComBat correction was used, the performance of 2D models was better (p = 0.0059) in the training cohort, and significantly better (p < 0.0001) in the validation cohort. The 2D corrected radiomics model yielded the optimal performance and was used to build the nomogram. The calibration curve of the radiomics model demonstrated good agreement between prediction and observation and the decision curve analysis confirmed the clinical utility. CONCLUSIONS: The easy-to-use 2D corrected radiomics model could facilitate noninvasive preselection of ESCC patients who would benefit from ICI + CT.

Radiomics on multi-modalities MR sequences can subtype patients with non-metastatic nasopharyngeal carcinoma (NPC) into distinct survival subgroups.

OBJECTIVES: To explore and evaluate the feasibility of radiomics in stratifying nasopharyngeal carcinoma (NPC) into distinct survival subgroups through multi-modalities MRI. METHODS: A total of 658 patients (training cohort: 424; validation cohort: 234) with non-metastatic NPC were enrolled in the retrospective analysis. Each slice was considered as a sample and 4863 radiomics features on the tumor region were extracted from T1-weighted, T2-weighted, and contrast-enhanced T1-weighted MRI. Consensus clustering and manual aggregation were performed on the training cohort to generate a baseline model and classification reference used to train a support vector machine classifier. The risk of each patient was defined as the maximum risk among the slices. Each patient in the validation cohort was assigned to the risk model using the trained classifier. Harrell's concordance index (C-index) was used to measure the prognosis performance, and differences between subgroups were compared using the log-rank test. RESULTS: The training cohort was clustered into four groups with distinct survival patterns. Each patient was assigned to one of the four groups according to the estimated risk. Our method gave a performance (C-index = 0.827, p < .004 and C-index = 0.814, p < .002) better than the T-stage (C-index = 0.815, p = .002 and C-index = 0.803, p = .024), competitive to and more stable than the TNM staging system (C-index = 0.842, p = .003 and C-index = 0.765, p = .050) in the training cohort and the validation cohort. CONCLUSIONS: Through investigating a large one-institutional cohort, the quantitative multi-modalities MRI image phenotypes reveal distinct survival subtypes. KEY POINTS: • Radiomics phenotype of MRI revealed the subtype of nasopharyngeal carcinoma (NPC) patients with distinct survival patterns. • The slice-wise analysis method on MRI helps to stratify patients and provides superior prognostic performance over the TNM staging method. • Risk estimation using the highest risk among slices performed better than using the majority risk in prognosis.

Correction to: Radiomics on multi-modalities MR sequences can subtype patients with non-metastatic nasopharyngeal carcinoma (NPC) into distinct survival subgroups.

The original version of this article, published on 14 March 2019, unfortunately contained a mistake.

Predicting distant metastasis in nasopharyngeal carcinoma using gradient boosting tree model based on detailed magnetic resonance imaging reports.

BACKGROUND: Development of distant metastasis (DM) is a major concern during treatment of nasopharyngeal carcinoma (NPC). However, studies have demonstrated improved distant control and survival in patients with advanced NPC with the addition of chemotherapy to concomitant chemoradiotherapy. Therefore, precise prediction of metastasis in patients with NPC is crucial. AIM: To develop a predictive model for metastasis in NPC using detailed magnetic resonance imaging (MRI) reports. METHODS: This retrospective study included 792 patients with non-distant metastatic NPC. A total of 469 imaging variables were obtained from detailed MRI reports. Data were stratified and randomly split into training (50%) and testing sets. Gradient boosting tree (GBT) models were built and used to select variables for predicting DM. A full model comprising all variables and a reduced model with the top-five variables were built. Model performance was assessed by area under the curve (AUC). RESULTS: Among the 792 patients, 94 developed DM during follow-up. The number of metastatic cervical nodes (30.9%), tumor invasion in the posterior half of the nasal cavity (9.7%), two sides of the pharyngeal recess (6.2%), tubal torus (3.3%), and single side of the parapharyngeal space (2.7%) were the top-five contributors for predicting DM, based on their relative importance in GBT models. The testing AUC of the full model was 0.75 (95% confidence interval [CI]: 0.69-0.82). The testing AUC of the reduced model was 0.75 (95%CI: 0.68-0.82). For the whole dataset, the full (AUC = 0.76, 95%CI: 0.72-0.82) and reduced models (AUC = 0.76, 95%CI: 0.71-0.81) outperformed the tumor node-staging system (AUC = 0.67, 95%CI: 0.61-0.73). CONCLUSION: The GBT model outperformed the tumor node-staging system in predicting metastasis in NPC. The number of metastatic cervical nodes was identified as the principal contributing variable.

Evolutionary route of nasopharyngeal carcinoma metastasis and its clinical significance.

It is critical to understand factors associated with nasopharyngeal carcinoma (NPC) metastasis. To track the evolutionary route of metastasis, here we perform an integrative genomic analysis of 163 matched blood and primary, regional lymph node metastasis and distant metastasis tumour samples, combined with single-cell RNA-seq on 11 samples from two patients. The mutation burden, gene mutation frequency, mutation signature, and copy number frequency are similar between metastatic tumours and primary and regional lymph node tumours. There are two distinct evolutionary routes of metastasis, including metastases evolved from regional lymph nodes (lymphatic route, 61.5%, 8/13) and from primary tumours (hematogenous route, 38.5%, 5/13). The hematogenous route is characterised by higher IFN-γ response gene expression and a higher fraction of exhausted CD8+ T cells. Based on a radiomics model, we find that the hematogenous group has significantly better progression-free survival and PD-1 immunotherapy response, while the lymphatic group has a better response to locoregional radiotherapy.

Establishment and Validation of a Novel MRI Radiomics Feature-Based Prognostic Model to Predict Distant Metastasis in Endemic Nasopharyngeal Carcinoma.

Purpose: We aimed to establish a prognostic model based on magnetic resonance imaging (MRI) radiomics features for individual distant metastasis risk prediction in patients with nasopharyngeal carcinoma (NPC). Methods: Regression analysis was applied to select radiomics features from T1-weighted (T1-w), contrast-enhanced T1-weighted (T1C-w), and T2-weighted (T2-w) MRI scans. All prognostic models were established using a primary cohort of 518 patients with NPC. The prognostic ability of the radiomics, clinical (based on clinical factors), and merged prognostic models (integrating clinical factors with radiomics) were identified using a concordance index (C-index). Models were tested using a validation cohort of 260 NPC patients. Distant metastasis-free survival (DMFS) were calculated by using the Kaplan-Meier method and compared by using the log-rank test. Results: In the primary cohort, seven radiomics prognostic models showed similar discrimination ability for DMFS to the clinical prognostic model (P=0.070-0.708), while seven merged prognostic models displayed better discrimination ability than the clinical prognostic model or corresponding radiomics prognostic models (all P<0.001). In the validation cohort, the C-indices of seven radiomics prognostic models (0.645-0.722) for DMFS prediction were higher than in the clinical prognostic model (0.552) (P=0.016 or <0.001) or in corresponding merged prognostic models (0.605-0.678) (P=0.297 to 0.857), with T1+T1C prognostic model (based on Radscore combinations of T1 and T1C Radiomics models) showing the highest C-index (0.722). In the decision curve analysis of the validation cohort for all prognostic models, the T1+T1C prognostic model displayed the best performance. Conclusions: Radiomics models, especially the T1+T1C prognostic model, provided better prognostic ability for DMFS in patients with NPC.

MRI-based radiomics models can improve prognosis prediction for nasopharyngeal carcinoma with neoadjuvant chemotherapy.

BACKGROUND: The purpose of this study was to explore the prognostic value of imaging features and related models in nasopharyngeal carcinoma (NPC) patients that received neoadjuvant chemotherapy. MATERIALS AND METHODS: We systematically reviewed the data of 110 NPC patients who received radiotherapy and neoadjuvant chemotherapy. The patients were randomly divided into the training cohort (n = 88) and the verification cohort (n = 22). The imaging data collected in this study were screened via Pyramidics and used to construct prediction models based on histology and clinical nomographs. The models' accuracy was evaluated via calibration curves and the consistency index (C-index). In addition, we also explored the correlation between radiomics expression patterns, quantitative histological characteristics, and clinical data and then constructed a model to predict the prognosis of NPC. RESULTS: The models that integrated radiomics contours with all the clinical data were superior to those based on the clinical data alone (C-index 0.746 vs. C-index 0.814, respectively) and the calibration curves showed good consistency. The heat map showed that the radiomics expression pattern and selected histological characteristics were correlated with the clinical stage, T stage, and N stage (p < 0.05), and no radiomics feature was associated with lactate dehydrogenase expression, lymphocyte count, or mononuclear cell count. CONCLUSION: MRI-based radiomics can significantly improve the efficacy of traditional TNM staging and clinical data in predicting the progression-free survival (PFS) of patients with advanced NPC, which may provide an opportunity for precision medicine.

Extent of paranasal sinus involvement and its prognostic value in nasopharyngeal carcinoma: Proposed modification in the current UICC/AJCC staging system.

PURPOSE: This study aimed to evaluate the prognostic value of paranasal sinus involvement (PSI) in NPC and to explore its appropriate position in the current AJCC staging system. MATERIALS AND METHODS: Pretreatment MRI of 1317 patients with NPC treated with intensity-modulated radiotherapy (IMRT) between January 2010, and January 2013, were reviewed retrospectively. Survival was compared between patients with PSI-slight (sinus bone wall erosion only) and PSI-severe (tumor penetrated into sinus cavity). Multivariable analysis was performed to identify the independent predictors of survival. RESULTS: The study included 1317 patients (median age 46 years; range, 11-78 years). PSI-slight was present in 15.2% (200/1317) patients and PSI-severe in 20.0% (263/1317) patients. Overall survival (OS), distant metastasis-free survival (DMFS), loco-regional recurrence-free survival (LRFS), and progression-free survival (PFS) were significantly lower in patients with PSI-severe (all P < .05). In multivariable analysis, PSI-severe was an independent prognostic factor for OS, DMFS, LRFS, and PFS (all P < .05). 96 AJCC T3 category patients with PSI-severe were reclassified as T4 category. The revised T category had significantly better predictive value (higher C-index) than that the AJCC system for survival (OS, 0.661 vs. 0.652; DMFS, 0.655 vs. 0.650; and PFS, 0.625 vs. 0.625; P < .05 for all). CONCLUSION: PSI-severe is an independent negative prognostic factor in nasopharyngeal carcinoma, which is recommended to be classified as T4 category in the 8th AJCC staging system for NPC.

Subclassification of skull-base invasion for nasopharyngeal carcinoma using cluster, network and survival analyses: A double-center retrospective investigation.

PURPOSE: To investigate the prognostic value of skull-base invasion (SBI) for nasopharyngeal carcinoma (NPC), propose a subclassification of SBI. METHODS: 792 and 433 patients with pathologically proven NPC and complete clinical and magnetic resonance imaging records at Sun Yat-sen University Cancer Center and Foshan Hospital were enrolled, and investigated using heat map/cluster, network and survival analyses. RESULTS: The results of heat map/cluster analyses and network analysis showed that T3 patients with pterygoid process and/or base of the sphenoid bone invasion (T3 slight) had better treatment outcomes than those with other SBIs (T3 severe). Significant differences were observed between T3-slight and T3-severe groups with regard to 5-year overall survival (OS) (93.0% vs. 83.5%, p = 0.014) and progression-free survival (PFS) (82.5% vs. 74.1%, p = 0.044) rates. No significant difference was observed between T3-slight group and T2 patients with regard to 5-year OS (93.0% vs. 84.7%, p = 0.062) and PFS (82.5% vs. 78.9%, p = 0.459) rates. Therefore, we downgraded patients with T3 slight to T2, yielding a new T classification sample. The survival curves of the 5-year OS and PFS rates of T2 and T3 were more reasonable after sample redistribution than those before sample redistribution. The differences in the 5-year OS and PFS rates between T2 and T3 patients after sample redistribution approached significance (p = 0.075 and 0.051, respectively). CONCLUSIONS: Different types of SBIs had different effects on the prognosis for NPC. We recommend patients with T3 slight not be defined as T3 but, rather, as T2.