The Role of Post-Neoadjuvant Chemotherapy Tumor Volume for Prognostication and Treatment Guidance in Loco-Regionally Advanced Nasopharyngeal Carcinoma

Early Prediction of Death Risk in Progressive Nasopharyngeal Carcinoma Using Radiomics Nomogram Based on Clinical Semantic Multi-Parameter Magnetic Resonance Imaging

Aims/Background Patients with recurrent or/and metastatic nasopharyngeal carcinoma (NPC) have a notably low survival rate. Our primary objective in this study is to establish a comprehensive nomogram model based on clinical factors, semantic features, and multi-parameter magnetic resonance imaging (MRI) radiomic features, and to predict the risk of mortality in patients with progressive NPC following intensity-modulated radiation therapy. Methods A retrospective study, including 110 patients with recurrent or/and metastatic NPC who underwent treatment at the Zhejiang Cancer Hospital between June 2012 and December 2016, was conducted. Comprehensive reviews of clinical and pre-treatment MRI data were undertaken. Patients were categorized into two groups based on their mortality status within a 5 year-frame: the non-death group (54 cases) and the death group (56 cases). Radiomic features were extracted from patients' MRIs and the best feature set was selected. Each patient was assigned a radiomic score (Rad-Score). A combined model was constructed using multivariate binary logistic regression, incorporating Rad-Score, semantic features, and clinical data. Receiver operating characteristic (ROC) curves and calibration plots were generated to evaluate the predictive performance of the radiomic feature model, the clinical-semantic feature model, and the combined model for predicting death risk in patients with progressive NPC. A nomogram based on the combined model was constructed. Results Gender, invasion of the carotid sheath by the primary tumour, tumour volume, and progression time showed statistically significant differences between the two groups (p < 0.05). There were statistically significant differences between the three models in the death and non-death groups (p < 0.001). The area under the curve (AUC) value for the radiomic feature model was 0.861 (95% confidence interval [CI]: 0.783-0.920), while the AUC value for the clinical-semantic feature model was 0.797 (95% CI: 0.709-0.868). The combined model demonstrated the highest efficacy for predicting death risk in NPC patients, with an AUC value of 0.904 (95% CI: 0.832-0.952), accuracy of 0.818, sensitivity of 0.857, specificity of 0.870, negative predictive value of 0.778, and positive predictive value of 0.857. Conclusion The combined model incorporating clinical features, semantic features and multi-parameter MRI radiomic features is a highly valuable tool for predicting death risk in patients with progressive NPC, providing a quantitative approach to aiding in early clinical intervention and treatment.

Individualised cumulative cisplatin dose for locoregionally advanced nasopharyngeal carcinoma patients based on induction chemotherapy response and tumour volume

Background and objectives

To evaluate the prognostic value of an integrated model consisting of tumour response to induction chemotherapy (IC) and gross tumour volume (GTV) after IC in nasopharyngeal carcinoma (NPC) and elucidate optimal cumulative cisplatin dose (CCD) in concurrent chemoradiotherapy (CCRT) for different subgroups.

Design and methods

This retrospective study enrolled 896 patients with NPC diagnosed from 2010 to 2017 receiving IC plus radiotherapy. The primary endpoint was disease-free survival (DFS). Cut-off points for GTV were combined with IC response to develop an integrated model. Propensity score matching (PSM) was used to adjust for potential confounders. Survival outcomes and acute toxicity were compared between the different CCD groups.

Results

Unsatisfactory IC response and large GTV after IC were correlated with poor survival outcomes; the AUC increased to 0.668 when these factors were incorporated. The integrated model classified patients into three groups. After PSM, radiotherapy alone and CCRT demonstrated similar efficacy in the low-risk group (complete response (CR)/partial response (PR) and GTV <68 cm3 after IC). In the intermediate-risk group (CR/PR but GTV ⩾68 cm3), CCD of >200 mg/m2 and 101-200 mg/m2 increased the 5-year DFS rates (83.7% vs 81.1% vs 65.3%, p = 0.042). In the high-risk group (stable disease/progressive disease and any GTV), the use of different CCDs did not result in significantly different survival outcomes (p = 0.793). Additionally, high CCD was significantly associated with increased incidence of grade 1-4 acute toxicity.

Conclusion

The integrated model incorporating IC response and GTV after IC demonstrates satisfactory value in risk stratification and the potential to guide individualised decision-making in CCD selection. Balancing toxicity and efficacy, RT alone seems to be the optimal treatment for patients in low-risk groups and 200 mg/m2 might be the optimal dose for intermediate-risk groups. Moreover, increasing CCD does not benefit patients in high-risk groups, and treatment options for these patients require further consideration.

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.

Optimal Time-to-Surgery Recommendations Based on Primary Tumor Volume Regression for Patients with Resectable Esophageal Cancer after Neoadjuvant Chemoradiotherapy: A Retrospective Study

BACKGROUND

Neoadjuvant chemoradiotherapy (NCRT) has shown promise in improving the prognosis of individuals with locally advanced esophageal squamous cell carcinoma (LA-ESCC). However, the factors influencing tumor response and long-term survival in these patients remain unknown. The optimal timing for surgery after the completion of radiotherapy in LA-ESCC remains controversial. Therefore, this study was designed to identify biomarkers and to determine the optimal post-NCRT time-to-surgery (TTS) for patients with LA-ESCC.

METHODS

This retrospective study included patients with resectable LA-ESCC who underwent NCRT between May 2017 and June 2021. The tumor shrinkage rate was calculated as the difference between the pre- and post-primary gross tumor volume (GTVp) divided by the pre-GTVp. Univariate and multivariate Cox regression analyses and Kaplan-Meier curves were used to calculate overall survival (OS) and progression-free survival (PFS).

RESULTS

We collected data from 248 patients with resectable LA-ESCC who underwent computed tomography (CT) scans before the initiation of treatment. The median follow-up time was 37.7 months. The optimal cutoff of tumor shrinkage was 45%. In the univariate and multivariate analyses, we found a significant association between the tumor shrinkage rate and PFS (p = 0.001). Among the subgroup of patients who responded to treatment, extending the TTS was associated with improved OS (p = 0.037) and PFS (p = 0.028).

CONCLUSIONS

For patients with resectable LA-ESCC, the tumor shrinkage rate is an independent prognostic factor for PFS. Thus, for responders, prolonging TTS is recommended to obtain a better OS.

Evaluation of a novel model incorporating serological indicators into the conventional TNM staging system for nasopharyngeal carcinoma

BACKGROUND

Non-anatomical factors significantly affect treatment guidance and prognostic prediction in nasopharyngeal carcinoma (NPC) patients. Here, we developed a novel survival model by combining conventional TNM staging and serological indicators.

METHODS

We retrospectively enrolled 10,914 eligible patients with nonmetastatic NPC over 2009-2017 and randomly divided them into training (n = 7672) and validation (n = 3242) cohorts. The new staging system was constructed based on T category, N category, and pretreatment serological markers by using recursive partitioning analysis (RPA).

RESULTS

In multivariate Cox analysis, pretreatment cell-free Epstein-Barr virus (cfEBV) DNA levels of >2000 copies/mL [HROS (95 % CI) = 1.78 (1.57-2.02)], elevated lactate dehydrogenase (LDH) levels [HROS (95 % CI) = 1.64 (1.41-1.92)], and C-reactive protein-to-albumin ratio (CAR) of >0.04 [HROS (95 % CI) = 1.20 (1.07-1.34)] were associated with negative prognosis (all P < 0.05). Through RPA, we stratified patients into four risk groups: RPA I (n = 3209), RPA II (n = 2063), RPA III (n = 1263), and RPA IV (n = 1137), with 5-year overall survival (OS) rates of 93.2 %, 86.0 %, 80.6 %, and 71.9 % (all P < 0.001), respectively. Compared with the TNM staging system (eighth edition), RPA risk grouping demonstrated higher prognostic prediction efficacy in the training [area under the curve (AUC) = 0.661 vs. 0.631, P < 0.001] and validation (AUC = 0.687 vs. 0.654, P = 0.001) cohorts. Furthermore, our model could distinguish sensitive patients suitable for induction chemotherapy well.

CONCLUSION

Our novel RPA staging model outperformed the current TNM staging system in prognostic prediction and clinical decision-making. We recommend incorporating cfEBV DNA, LDH, and CAR into the TNM staging system.

Tumor volume instead of recurrent T category predicts clinical outcome of patients with locally recurrent nasopharyngeal carcinoma salvaged by carbon ion radiation therapy

BACKGROUND

Although carbon ion radiation therapy (CIRT) substantially improves the overall survival (OS) of patients with LR-NPC, approximately 40% of the patients may develop local recurrence. The purpose of study is to assess the value of tumor volume (TV) as a predictive tool to guide individualized CIRT.

METHODS

Consecutive patients with LR-NPC treated using CIRT at Shanghai Proton and Heavy Ion Center between April 2015 and May 2019 were included. TV before CIRT was delineated and calculated. The generalized additive Cox model was used to examine the relationship between TV and OS and local progression-free survival (LPFS). A cutoff value of tumor volume was identified to best discriminate patients with different 2-year OS rates, using receiver operating characteristic (ROC) analysis.

RESULTS

A total of 157 patients were enrolled. The median tumor volume was 22.49 (2.52-90.13) ml. In the univariable analyses, tumor volume was significantly associated with OS (p < 0.001) and LPFS (p = 0.01). The relationships with OS (p = 0.009) and LPFS (p = 0.020) remained significant in multivariable analyses. Using ROC analysis, a TV of 26.69 ml was identified to predict the 2-year OS rate. To facilitate potential clinical use, 25 ml was designated as the final cutoff value. The 2-year OS and LPFS rates were 88.6 % vs 62.3 %, and 54.7 % vs 35.5 %, for patients with a TV ≤ 25 ml and > 25 ml, respectively.

CONCLUSION

Tumor volume could predict the OS and LPFS of patients. We propose that tumor volume should be considered in the risk stratification and CIRT-based treatment for patients with LR-NPC.

Predictive function of tumor burden-incorporated machine-learning algorithms for overall survival and their value in guiding management decisions in patients with locally advanced nasopharyngeal carcinoma

Objective

Accurate prognostic predictions and personalized decision-making on induction chemotherapy (IC) for individuals with locally advanced nasopharyngeal carcinoma (LA-NPC) remain challenging. This research examined the predictive function of tumor burden-incorporated machine-learning algorithms for overall survival (OS) and their value in guiding treatment in patients with LA-NPC.

Methods

Individuals with LA-NPC were reviewed retrospectively. Tumor burden signature-based OS prediction models were established using a nomogram and two machine-learning methods, the interpretable eXtreme Gradient Boosting (XGBoost) risk prediction model, and DeepHit time-to-event neural network. The models' prediction performances were compared using the concordance index (C-index) and the area under the curve (AUC). The patients were divided into two cohorts based on the risk predictions of the most successful model. The efficacy of IC combined with concurrent chemoradiotherapy was compared to that of chemoradiotherapy alone.

Results

The 1 221 eligible individuals, assigned to the training (n = 813) or validation (n = 408) set, showed significant respective differences in the C-indices of the XGBoost, DeepHit, and nomogram models (0.849 and 0.768, 0.811 and 0.767, 0.730 and 0.705). The training and validation sets had larger AUCs in the XGBoost and DeepHit models than the nomogram model in predicting OS (0.881 and 0.760, 0.845 and 0.776, and 0.764 and 0.729, P < 0.001). IC presented survival benefits in the XGBoost-derived high-risk but not low-risk group.

Conclusion

This research used machine-learning algorithms to create and verify a comprehensive model integrating tumor burden with clinical variables to predict OS and determine which patients will most likely gain from IC. This model could be valuable for delivering patient counseling and conducting clinical evaluations.

The value of integrating tumor volume and plasma Epstein-Barr virus DNA load during sequential chemoradiotherapy for prognostic prediction and therapeutic guidance in high-risk locoregionally advanced nasopharyngeal carcinoma

OBJECTIVES

To investigate the value of integrating primary gross tumor volume (GTVp) and gross tumor volume of nodes (GTVn) after induction chemotherapy (IC) and dynamic changes in plasma cell-free Epstein-Barr virus DNA (cfEBV DNA) during sequential chemoradiotherapy (CRT) in high-risk locoregionally advanced nasopharyngeal carcinoma (LA-NPC).

MATERIALS AND METHODS

We retrospectively reviewed 988 patients with LA-NPC undergoing IC plus concurrent chemoradiotherapy (CCRT) between 2014 and 2018. The entire cohort was divided into four subgroups according to tumor volume and the cfEBV DNA load. Using a supervised statistical clustering approach, we stratified the subgroups into three clusters. Overall survival (OS), disease-free survival (DFS), distant metastasis-free survival (DMFS) and locoregional relapse-free survival (LRRFS) were calculated using Kaplan-Meier analysis and inter-group differences were compared using the log-rank test.

RESULTS

We observed that GTVp & GTVn and cfEBV DNApostIC & cfEBV DNApostCRT were powerful prognostic factors for OS (p = 0.004, p < 0.001, p < 0.001, and p < 0.001, respectively). The survival curves of the three clusters were significantly different. The 5-year OS for the low-risk, intermediate-risk and high-risk clusters were 97.0%, 86.2% and 77.1% (all P values < 0.001), respectively. The risk stratification system showed better predictive performance than the current tumor-node-metastasis (TNM) classification for OS (area under curve [AUC]: 0.653 versus 0.560, p < 0.001), DFS (AUC: 0.639 versus 0.540, p < 0.001), DMFS (AUC: 0.628 versus 0.535, p < 0.001) and LRRFS (AUC: 0.616 versus 0.513, p < 0.001).

CONCLUSION

Both tumor volume and the cfEBV DNA level during sequential CRT are effective prognostic indicators for patients with high-risk LA-NPC. The developed risk stratification system incorporating above factors improved survival prediction and demonstrated potential value in decision-making.

Therapeutic Evaluation of Induction Chemotherapy for Locoregionally Advanced Nasopharyngeal Carcinoma With Low-risk N Stage : A Multicenter Retrospective Study From Nonendemic Region of China

OBJECTIVES

The role of induction chemotherapy (IC) remains ambiguous in a patient with T3-4N0-1 nasopharyngeal carcinoma (NPC) according to data from the endemic area of China. Here, we conducted a multicenter retrospective study to investigate the value of adding IC to concurrent chemoradiotherapy (CCRT) for T3-4N0-1 NPC from Northwest China.

METHODS

Data were extracted in 3 hospitals from Northwest China between May 1, 2010 and August 30, 2018. The Kaplan-Meier method was used to estimate the endpoints. Survival curves were compared using the log-rank test. Initial propensity matching was conducted with a 1:1 match of IC + CCRT to CCRT. The primary endpoint of this study was overall survival (OS).

RESULTS

A total of 108 patients with staging T3-4N0-1 were included in this study. The median follow-up time was 50 months (range: 6 to 118 months). IC followed by CCRT did not significantly improve OS compared with CCRT in the whole cohort (89.5% vs 77.6%, hazard ratio: 0.41, 95% CI: 0.16-1.04, P = 0.100). But significantly better OS was found when a well-balanced propensity score-matched cohort was analyzed. Adjusted 4-year OS was 89.5% for IC followed by CCRT versus 71.1% for CCRT (hazard ratio: 0.30, 95% CI: 0.11-0.80, P = 0.027). No significant differences were detected in side effects between the two groups.

CONCLUSION

This study suggested IC followed by CCRT had the potential to further improve OS in patients with T3-4N0-1M0 NPC from Northwest China compared with CCRT. However, prospective studies with a large sample are warranted to confirm the results.

Gemcitabine Versus Docetaxel Plus Cisplatin as Induction Chemotherapy in Nasopharyngeal Carcinoma

OBJECTIVES

To compare tumor volume reduction after induction chemotherapy (IC) with gemcitabine plus cisplatin (GP) and docetaxel plus cisplatin (DP) and to evaluate the influence on subsequent radiotherapy in locoregionally advanced nasopharyngeal carcinoma (NPC).

STUDY DESIGN

Retrospective clinical study.

METHODS

Patients who received GP or DP IC followed by concurrent chemoradiotherapy (CCRT) were retrospectively enrolled. Propensity score matching (PSM) was adopted to control the balance between the GP and DP groups.

RESULTS

A total of 41 patients treated with GP and 53 patients treated with DP were enrolled. After matching, 33 sub-pairs of 66 patients were generated in the post-PSM cohort. As compared with DP, GP was superior in its gross tumor volume of the nasopharynx (GTVnx) reduction (28.88% vs. 18.73%; P = .014) but equivalent in its gross tumor volume of the lymph nodes (GTVnd) reduction (37.58% vs. 29.79%; P = .229). Univariate and multivariate analyses confirmed that the chemotherapy regimen was an independent factor associated with the reduction in GTVnx (P = .011). The GP group exhibited advantages in the dosimetric parameters of the planning target volume of high-risk volume and low-risk volume (PTV1 and PTV2), lenses, temporal lobes, and parotid glands. Univariate and multivariate analyses confirmed that chemotherapy regimen was an independent factor associated with the dosimetric parameters of PTV1, PTV2, lenses, temporal lobes, and parotid glands.

CONCLUSION

GP regimen achieves a greater GTVnx reduction than DP regimen and has an advantage in the dosimetry of subsequent CCRT.

LEVEL OF EVIDENCE

3 Laryngoscope, 132:2379-2387, 2022.

Prognostic significance of MRI-based late-course tumor volume in locoregionally advanced nasopharyngeal carcinoma

Background

To validate tumor volume-based imaging markers for predicting local recurrence-free survival (LRFS) in locoregionally advanced nasopharyngeal carcinoma patients, who underwent induction chemotherapy followed by definitive intensity-modulated radiotherapy.

Methods

We enrolled 145 patients with stage III–IVA nasopharyngeal carcinoma in this retrospective study. Pre-treatment tumor volume (V_pre) and late-course volume (LCV) were measured based on the MRIs scanned before treatment and during the first 3 days in the sixth week of radiotherapy, respectively. The volume regression rate (VRR) was calculated according to V_pre and LCV. Receiver operating characteristic (ROC) curves were used to identify the cut-off best separating patient subgroups in assessing the prognostic value of V_pre, LCV and VRR. The Kaplan–Meier method was used for survival analysis. Prognostic analyses were performed using univariate and multivariate COX proportional hazard models.

Results

The LCV was 5.3 ± 0.5 (range 0–42.1) cm³; The VRR was 60.4 ± 2.2% (range 2.9–100.0). The median follow-up period was 36 months (range 6–98 months). The cut-off value of LCV determined by the ROC was 6.8 cm³ for LRFS prediction (sensitivity 68.8%; specificity 79.8%). The combination of LCV and VRR for LRFS prediction (AUC = 0.79, P < 0.001, 95% CI 0.67–0.90), LCV (AUC = 0.74, P = 0.002, 95% CI 0.60–0.88) and V_pre (AUC = 0.71, P = 0.007, 95% CI 0.56–0.85) are better than T category (AUC = 0.64, P = 0.062, 95% CI 0.50–0.79) alone. Patients with LCV ≤ 6.8 cm³ had significantly longer LRFS (P < 0.001), disease-free survival (DFS, P < 0.001) and overall survival (OS, P = 0.005) than those with LCV > 6.8 cm³. Multivariate Cox regression showed LCV was the only independent prognostic factor for local control (HR = 7.80, 95% CI 2.69–22.6, P < 0.001).

Conclusions

LCV is a promising prognostic factor for local control and chemoradiosensitivity in patients with locoregionally advanced NPC. The LCV, and the combination of LCV with VRR are more robust predictors for patient survival than T category.

[Pre- and post-chemotherapy tumor volumes: New prognostic factors in nasopharyngeal carcinoma]

PURPOSE

The pre- and post-induction chemotherapy tumor volumes of nasopharyngeal carcinomas may be prognostic indicators for adapting the therapeutic strategy. The objective of our study is to assess the prognostic impact of pre- and post-induction chemotherapy volumes in patients treated for locally advanced nasopharyngeal carcinomas.

PATIENTS AND METHODS

This is a retrospective study including 52 patients with locally advanced nasopharyngeal carcinoma treated with 3 courses of induction chemotherapy (TPF) followed by intensity modulated radiotherapy associated with concomitant chemotherapy.

RESULTS

The median initial and post induction chemotherapy total volumes were 92.3 and 41.5mL, respectively. At 3 years, the LRFS, DMFS, DFS and OS were respectively 85.9%, 63.5%, 56.8% and 67.8%. In multivariate study, the combination of a high initial volume (>100mL) and post-chemotherapy volume (>35mL) was an independent factor for LRFS, DMFS, DFS and OS. The total baseline volume had a better predictive prognostic value for DFS and OS than the TNM classification (8th edition 2017).

CONCLUSION

The prognostic weight of tumor and nodal volumes was greater than the TNM classification (8th edition). The pre- and post-chemotherapy tumor volumes allow selecting a high-risk patients' subgroup "high initial and post chemotherapy volumes" in which it would be advisable to offer more intensive treatment regimens.

Induction chemotherapy followed by radical chemoradiotherapy for patients with stage IV non-metastatic nasopharyngeal carcinoma: 11-Year Experience in a tertiary centre

INTRODUCTION

T4 nasopharyngeal carcinoma (NPC) with close proximity to critical organs at risk (OARs) is usually underdosed during radiotherapy in order to respect radiation constraints. N3 disease has high risk of distant metastasis. Induction chemotherapy (IC) provides advantages of sparing of OARs during subsequent chemoradiotherapy (CCRT) and early eradication of micrometastasis. However, factors predicting successes of IC in this patient group are not well-studied.

METHODS

104 T4 or N3 NPC patients were retrospectively reviewed during 2007-2018. They were planned for IC followed by CCRT using intensity-modulated radiotherapy.

RESULTS

In the whole group, five-year failure-free survival (FFS), locoregional failure-free survival (LRFS), distant failure-free survival (DFFS) and overall survival (OS) were 40.9%, 45.7%, 46.9% and 53.6% respectively. Isolated marginal failure rate was 5% (4/80) among patients with primary tumours located close to critical OARs. Pre-IC gross tumour volume primary (GTVp) total volume > 110 cm³ correlated with worse five-year LRFS (OR 6.37, P = 0.008), DFFS (OR 8.89, P = 0.003) and OS (OR 50.12, P < 0.001). In the T4 subgroup, IC improved D100% GTVp from 61.39 Gy to 64.71 Gy (P < 0.001) and V100% GTVp from 98.78% to 99.28% (P < 0.001).

CONCLUSION

Our study demonstrated improved dosimetric parameters and low isolated marginal failure rate. It supported the use of IC and CCRT for tumours located close to critical OARs. Further research is warranted to compare predictive roles of pre- and post-IC tumour volumes. For high-risk patients being defined by pre-IC volume or other prognostic models, treatment escalation should be considered.

Necrotic reshaping of the glioma microenvironment drives disease progression

Glioblastoma is the most common primary brain tumor and has a dismal prognosis. The development of central necrosis represents a tipping point in the evolution of these tumors that foreshadows aggressive expansion, swiftly leading to mortality. The onset of necrosis, severe hypoxia and associated radial glioma expansion correlates with dramatic tumor microenvironment (TME) alterations that accelerate tumor growth. In the past, most have concluded that hypoxia and necrosis must arise due to "cancer outgrowing its blood supply" when rapid tumor growth outpaces metabolic supply, leading to diffusion-limited hypoxia. However, growing evidence suggests that microscopic intravascular thrombosis driven by the neoplastic overexpression of pro-coagulants attenuates glioma blood supply (perfusion-limited hypoxia), leading to TME restructuring that includes breakdown of the blood-brain barrier, immunosuppressive immune cell accumulation, microvascular hyperproliferation, glioma stem cell enrichment and tumor cell migration outward. Cumulatively, these adaptations result in rapid tumor expansion, resistance to therapeutic interventions and clinical progression. To inform future translational investigations, the complex interplay among environmental cues and myriad cell types that contribute to this aggressive phenotype requires better understanding. This review focuses on contributions from intratumoral thrombosis, the effects of hypoxia and necrosis, the adaptive and innate immune responses, and the current state of targeted therapeutic interventions.

Efficiency of high cumulative cisplatin dose in high- and low-risk patients with locoregionally advanced nasopharyngeal carcinoma

BACKGROUND

The optimal cumulative cisplatin dose (CCD) during radiation therapy for locoregionally advanced nasopharyngeal carcinoma (LA-NPC) patients receiving induction chemotherapy (IC) plus CCRT remains controversial. This study aimed to explore the treatment efficiency of CCD for high-and low-risk patients with LA-NPC.

METHODS

Data from 472 LA-NPC patients diagnosed from 2014 to 2018 and treated with IC plus CCRT were reviewed. After propensity score matching, the therapeutic effects of a CCD > 200 and CCD ≤ 200 mg/m² were evaluated comparatively. Five factors selected by multivariate analysis were incorporated to develop a nomogram. Subgroup analysis was conducted to explore the role of different CCDs in nomogram-defined high- and low-risk groups. Additionally, acute toxicities were evaluated comparatively between the high- and low-CCD groups.

RESULTS

After matching, there was no difference between different CCD groups for all patients in terms of 3-year overall survival (OS), distant metastasis-free survival (DMFS), locoregional recurrence-free survival (LRRFS), or progression-free survival (PFS). A nomogram was built by integrating pretreatment EBV DNA, clinical stage, and post-IC EBV DNA, post-IC primary gross tumor and lymph node volumes obtained a C-index of 0.674. The high-risk group determined by the nomogram had poorer 3-year PFS, OS, DMFS, and LRRFS than the low-risk group. A total of CCD > 200 mg/m² increased the survival rates of 3-year PFS and DMFS (PFS: 72.5% vs. 54.4%, p = 0.012; DMFS: 81.9% vs. 61.5%, p = 0.014) in the high-risk group but not in the low-risk group. Moreover, the high CCD increased treatment-related acute toxicities.

CONCLUSIONS

A high CCD was associated with better 3-year PFS and DMFS rates than a low dose for high-risk patients but could not produce a survival benefit for low-risk patients.

Application Value of Magnetic Resonance Radiomics and Clinical Nomograms in Evaluating the Sensitivity of Neoadjuvant Chemotherapy for Nasopharyngeal Carcinoma

Objective

To predict the sensitivity of nasopharyngeal carcinoma (NPC) to neoadjuvant chemotherapy (NACT) based on magnetic resonance (MR) radiomics and clinical nomograms prior to NACT.

Materials and Methods

From January 2014 to July 2015, 284 consecutive patients with pathologically confirmed NPC underwent 3.0 T MR imaging (MRI) before initiating NACT. The patients’ data were randomly assigned to a training set (n = 200) or a test set (n = 84) at a ratio of 7:3. The clinical data included sex, tumor (T) stage, lymph node (N) stage, American Joint Committee on Cancer (AJCC) stage, and the plasma concentration of Epstein–Barr virus (EBV) DNA. The regions of interest (ROI) were manually segmented on the axial T2-weighted imaging (T2WI) and enhanced T1-weighted imaging (T1WI) sequences using ITK-SNAP software. The radiomics data were post-processed using AK software. Moreover, the Maximum Relevance Minimum Redundancy (mRMR) algorithm and the Least Absolute Shrinkage and Selection Operator (LASSO) were adopted for dimensionality reduction to screen for the features that best predicted the treatment efficacy, and clinical risk factors were used in combination with radiomics scores (Rad-scores) to construct the clinical radiomics-based nomogram. DeLong’s test was utilized to compare the area under the curve (AUC) values of the clinical radiomics-based nomogram, radiomics model, and clinical nomogram. Decision curve analysis (DCA) was employed to evaluate each model’s net benefit.

Results

The clinical nomogram was constructed based on data from patients who were randomly assigned according to T2WI and enhanced T1WI sequences. In the training set, the T2WI sequence-based clinical radiomics nomogram and the radiomics model outperformed the clinical nomogram in predicting the NACT efficacy (AUC, 0.81 vs. 0.60, p = 0.001279 and 0.76 vs. 0.60, p = 0.03026). These findings were well-verified in the test set. The enhanced T1WI sequence-based clinical radiomics nomogram exhibited better performance in predicting treatment efficacy than the clinical nomogram (AUC, 0.79 vs. 0.62, respectively; p = 0.0000834). The DCA revealed that the T2WI and clinical radiomics-based nomograms resulted in a net benefit in predicting the NACT efficacy.

Conclusion

The clinical radiomics-based nomogram improved the prediction of NACT efficacy, with the T2WI sequence-based clinical radiomics achieving the best effect.

Residual Volume of Lymph Nodes During Chemoradiotherapy Based Nomogram to Predict Survival of Nasopharyngeal Carcinoma Patient Receiving Induction Chemotherapy

Purpose

To accurately stratify nasopharyngeal carcinoma (NPC) patients who were benefit from induction chemotherapy (IC) followed by chemoradiotherapy (CCRT), we established residual volume of lymph nodes during chemoradiotherapy based nomogram to predict survival for NPC patients.

Methods

Cox regression analysis were used to evaluate predictive effects of tumor volume parameters. Multivariate Cox regression analysis was used to identify the prognostic factors, and nomogram models were developed to predict survival of NPC patients receiving IC followed by CCRT.

Results

Compared with other tumor volumetric parameters, midRT GTVnd was the best predictive factor for OS (HR: 1.043, 95%CI: 1.031-1.055), PFS (HR: 1.040, 95%CI: 1.030- 1.051), and DMFS (HR: 1.046, 95%CI: 1.034 – 1.059) according to the HR of Cox regression analysis. Based on multivariate analysis, three nomograms included midRT GTVnd were constructed to predict 4-year survival. The C-index of nomograms for each survival endpoints were as follow (training cohort vs. validation cohort): 0.746 vs. 0.731 for OS; 0.747 vs. 0.735 for PFS; 0.768 vs. 0.729 for DMFS, respectively. AUC showed a good discriminative ability. Calibration curves demonstrated a consistence between actual results and predictions. Decision curve analysis (DCA) showed that the nomograms had better clinical predictive effects than current TNM staging system.

Conclusion

We identified the best volumetric indicator associated with prognosis was the residual volume of lymph nodes at the fourth week of chemoradiotherapy for patients receiving IC followed by CCRT. We developed and validated three nomograms to predict specific probability of 4-year OS, PFS and DMFS for NPC patient receiving IC followed by CCRT.

Establishment of a Prognostic Nomogram for Patients With Locoregionally Advanced Nasopharyngeal Carcinoma Incorporating TNM Stage, Post-Induction Chemotherapy Tumor Volume and Epstein-Barr Virus DNA Load

Objectives

To establish and validate an effective nomogram to predict clinical outcomes for patients with locoregionally advanced nasopharyngeal carcinoma (LA-NPC).

Materials and Methods

The clinicopathological parameters and follow-up information of 402 locoregionally advanced NPC patients (training cohort, n = 302; validation cohort, n = 100) were retrospectively enrolled. The nomogram was built with the important prognostic variables identified by Cox regression analysis. Overall survival (OS) and progression-free survival (PFS) were the primary and secondary endpoints, respectively. The predictive power and clinical utility of the nomogram were assessed using the Harrell concordance index (C-index), calibration curve, and decision curve analysis. We compared the eighth staging system model with the nomogram to analyze whether the model could improve the accuracy of prognosis

Results

Epstein–Barr virus (EBV) DNA load, the gross tumor volume (GTVnx), and cervical lymph node tumor volume (GTVnd) after induction chemotherapy were the independent predictors of OS and PFS. The calibration curves indicated superb agreement between the nomogram-predicted probabilities and observed actual probabilities of survival. The C-index and area under the receiver operator characteristic curve (AUC) of the nomogram integrating these significant factors and N stage, and TNM stage were higher than those of the eighth TNM system alone. In addition, the decision curve analyses demonstrated the clinical value and higher overall net benefit of the nomogram. High-risk groups identified by the nomogram had significantly poorer OS and PFS than the low-risk group (p < 0.05).

Conclusions

The multidimensional nomogram incorporating TNM stage, EBV DNA load, and tumor volume after induction chemotherapy led to a more precise prognostic prediction and could be helpful for stratifying risk and guiding treatment decisions in locoregionally advanced NPC patients who have undergone induction chemotherapy and concurrent chemoradiation.

Development and validation of a web-based calculator to predict individualized conditional risk of site-specific recurrence in nasopharyngeal carcinoma: Analysis of 10,058 endemic cases

Background

Conditional survival (CS) provides dynamic prognostic estimates by considering the patients existing survival time. Since CS for endemic nasopharyngeal carcinoma (NPC) is lacking, we aimed to assess the CS of endemic NPC and establish a web‐based calculator to predict individualized, conditional site‐specific recurrence risk.

Methods

Using an NPC‐specific database with a big‐data intelligence platform, 10,058 endemic patients with non‐metastatic stage I–IVA NPC receiving intensity‐modulated radiotherapy with or without chemotherapy between April 2009 and December 2015 were investigated. Crude CS estimates of conditional overall survival (COS), conditional disease‐free survival (CDFS), conditional locoregional relapse‐free survival (CLRRFS), conditional distant metastasis‐free survival (CDMFS), and conditional NPC‐specific survival (CNPC‐SS) were calculated. Covariate‐adjusted CS estimates were generated using inverse probability weighting. A prediction model was established using competing risk models and was externally validated with an independent, non‐metastatic stage I–IVA NPC cohort undergoing intensity‐modulated radiotherapy with or without chemotherapy (n = 601) at another institution.

Results

The median follow‐up of the primary cohort was 67.2 months. The 5‐year COS, CDFS, CLRRFS, CDMFS, and CNPC‐SS increased from 86.2%, 78.1%, 89.8%, 87.3%, and 87.6% at diagnosis to 87.3%, 87.7%, 94.4%, 96.0%, and 90.1%, respectively, for an existing survival time of 3 years since diagnosis. Differences in CS estimates between prognostic factor subgroups of each endpoint were noticeable at diagnosis but diminished with time, whereas an ever‐increasing disparity in CS between different age subgroups was observed over time. Notably, the prognoses of patients that were poor at diagnosis improved greatly as patients survived longer. For individualized CS predictions, we developed a web‐based model to estimate the conditional risk of local (C‐index, 0.656), regional (0.667), bone (0.742), lung (0.681), and liver (0.711) recurrence, which significantly outperformed the current staging system (P < 0.001). The performance of this web‐based model was further validated using an external validation cohort (median follow‐up, 61.3 months), with C‐indices of 0.672, 0.736, 0.754, 0.663, and 0.721, respectively.

Conclusions

We characterized the CS of endemic NPC in the largest cohort to date. Moreover, we established a web‐based calculator to predict the CS of site‐specific recurrence, which may help to tailor individualized, risk‐based, time‐adapted follow‐up strategies.

Combining tumor response and personalized risk assessment: Potential for adaptation of concurrent chemotherapy in locoregionally advanced nasopharyngeal carcinoma in the intensity-modulated radiotherapy era

BACKGROUND AND PURPOSE

In the intensity-modulated radiotherapy (IMRT) era, the role of concurrent chemoradiotherapy (CCRT) after induction chemotherapy (IC) in locoregionally advanced nasopharyngeal carcinoma (LANPC) is undetermined, while concerns exist about CCRT-associated excessive toxicity. We aimed to combine tumor response and risk assessment to guide decisions about concurrent chemotherapy.

MATERIALS AND METHODS

From April 2009 to December 2015, 744 LANPC patients treated with CCRT/IMRT after IC were included. Matching techniques were performed for treatment effect evaluation. Tumor response to IC was used for patient stratification. A nomogram was built based on multivariable Cox regression analysis to predict overall survival (OS).

RESULTS

After IC, 508 patients (68.3%) had favorable tumor response (complete or partial response), among whom IC + CCRT achieved significantly superior 5-year disease-free survival and OS than IC + IMRT (82.2% vs. 72.5%, P = 0.025; 89.2% vs. 79.9%, P = 0.025). However, no significant difference was found in patients with unfavorable response (both P > 0.05). For favorable responders, a nomogram was built integrating age, smoking, T category, N category, pretreatment Epstein-Barr virus DNA and treatment modality. The concordance index was 0.713 and calibration was good. The nomogram determined three risk groups with distinct OS. High-risk patients benefited from CCRT after IC regarding disease-free survival, OS and distant metastasis-free survival, whereas low- and intermediate-risk patients did not.

CONCLUSIONS

For LANPC patients with unfavorable response to IC, subsequent CCRT seems inadequate, rendering intensification necessary. For favorable responders with low risk, IC + IMRT represents a reasonable de-intensification approach, although confirmation by prospective data is needed.

A Prognostic Predictive System Based on Deep Learning for Locoregionally Advanced Nasopharyngeal Carcinoma

BACKGROUND

Images from magnetic resonance imaging (MRI) are crucial unstructured data for prognostic evaluation in nasopharyngeal carcinoma (NPC). We developed and validated a prognostic system based on the MRI features and clinical data of locoregionally advanced NPC (LA-NPC) patients to distinguish low-risk patients with LA-NPC for whom concurrent chemoradiotherapy (CCRT) is sufficient.

METHODS

This multicenter, retrospective study included 3444 patients with LA-NPC from January 1, 2010, to January 31, 2017. A 3-dimensional convolutional neural network was used to learn the image features from pretreatment MRI images. An eXtreme Gradient Boosting model was trained with the MRI features and clinical data to assign an overall score to each patient. Comprehensive evaluations were implemented to assess the performance of the predictive system. We applied the overall score to distinguish high-risk patients from low-risk patients. The clinical benefit of induction chemotherapy (IC) was analyzed in each risk group by survival curves.

RESULTS

We constructed a prognostic system displaying a concordance index of 0.776 (95% confidence interval [CI] = 0.746 to 0.806) for the internal validation cohort and 0.757 (95% CI = 0.695 to 0.819), 0.719 (95% CI = 0.650 to 0.789), and 0.746 (95% CI = 0.699 to 0.793) for the 3 external validation cohorts, which presented a statistically significant improvement compared with the conventional TNM staging system. In the high-risk group, patients who received induction chemotherapy plus CCRT had better outcomes than patients who received CCRT alone, whereas there was no statistically significant difference in the low-risk group.

CONCLUSIONS

The proposed framework can capture more complex and heterogeneous information to predict the prognosis of patients with LA-NPC and potentially contribute to clinical decision making.

Comparison of induction chemotherapy plus concurrent chemoradiotherapy and induction chemotherapy plus radiotherapy in locally advanced nasopharyngeal carcinoma

BACKGROUND

Induction chemotherapy plus concurrent chemoradiotherapy (IC + CCRT) is a standard treatment regimen for locally advanced nasopharyngeal carcinoma (LA-NPC). However, the increased acute toxicity of this intensified chemotherapy may counteract its efficacy. The results of studies focusing on the omission of concurrent chemotherapy (CC) regimens are controversial. Therefore, we carried out a meta-analysis to elucidate the efficacy and toxicity of IC + CCRT versus IC plus radiotherapy alone (IC + RT) for LA-NPC.

METHODS

Studies available on PubMed, Embase, Cochrane Library and ClinicalTrails.gov were independently searched by two investigators from inception to March 1, 2020. Review Manager software 5.3 (RevMan 5.3) was employed to calculate pooled hazard ratios (HRs), risk ratios (RRs) and 95% confidence intervals (CIs).

RESULTS

Eight studies with a total of 2605 patients were analysed. The results showed that no significant difference between IC + RT and IC + CCRT for disease-free survival (HR = 1.09, 95% CI: 0,85-1.39, P = 0.50), overall survival (HR = 0.92, 95% CI: 0.78-1.09, P = 0.34), local recurrence-free survival (HR = 1.26, 95% CI: 0.95-1.67; P = 0.10), or distant metastasis-free survival (HR = 1.03, 95% CI: 0.84-1.26, P = 0.79). Notably, the incidence of treatment-related grade 3/4 acute haematological toxicity during radiation was higher in the IC + CCRT group. Subgroup analysis showed similar survival outcomes for IC + CCRT and IC + RT with and without the two-dimensional RT technique.

CONCLUSIONS

IC + RT was as effective as IC + CCRT for the management of LA-NPC. The IC + RT regimen has the possibility of replacing the IC + CCRT regimen for LA-NPC in the future due to the lower toxicity, although more high-level evidence is urgently needed for verification.

Prognostic value of the tumor volume reduction rate after neoadjuvant chemotherapy in patients with locoregional advanced nasopharyngeal carcinoma

PURPOSE

Aim of this study was to evaluate the prognostic value of the tumor volume reduction rate (TVRR) of neoadjuvant chemotherapy (NACT) in patients with locoregional advanced nasopharyngeal carcinoma (NPC).

METHODS

We collected the clinical data of 263 patients with locoregional advanced NPC receiving NACT and subsequent radiotherapy from two hospitals: a training cohort (n = 130) was obtained from one hospital and a validation cohort was obtained the other hospital (n = 133). By follow-up and calculating the TVRR of all patients, the prognostic value of the TVRR was analyzed though a univariate and multivariate Cox regression model. A cut-off point of the TVRR relating to survival was explored by means of the Youden index, and the prognostic value of the TNM stage plus TVRR was measured by creating receiver operating characteristic (ROC) curves.

RESULTS

12.6%, a cut-off point of TVRR, was found to best predict DFS. Patients with a TVRR > 12.6% had better DFS (hazard ratio, 0.160, 95% confidence interval 0.072-0.354; P < 0.001), LRRFS (0.064, 0.013-0.310; 0.001) and DMFS (0.274, 0.106-0.711; 0.008) than patients with a TVRR ≤ 12.6%. The TVRR was a significant independent prognostic factor for OS, DFS, LRRFS and DMFS. Combining the TVRR and TNM stage enhanced the ability to predict DFS and LRRFS.

CONCLUSIONS

The TVRR of NACT is an independent prognostic factor for patients with locoregional advanced NPC receiving radiotherapy. Adding the TVRR to the original TNM staging system improves the prognostic value for locoregional advanced NPC.