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.

A novel immune checkpoint-related gene signature for predicting overall survival and immune status in triple-negative breast cancer.

Background: Triple-negative breast cancer (TNBC) is a highly aggressive subtype and only some of patients could benefit from the immunotherapy. The present study aims to investigate the expression pattern and prognostic value of immune checkpoint genes (ICGs) in TNBC and develop a novel ICGs-signature to predict the prognosis and immune status in TNBC. Methods: ICGs expression profiles and clinical characteristics of TNBC samples were obtained from The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was employed to construct a multi-gene signature for predicting the prognostic outcome. The risk scores were calculated based on the coefficients of each ICG in LASSO-Cox regression model. The median score was considered as the cut-off value to divide the TNBC patients into a high-risk group and a low-risk group. The Kaplan-Meier survival curves were generated to further explore the association between the risk scores and prognostic outcomes. Finally, single sample gene set enrichment analysis (ssGSEA) was conducted to evaluate the immune status and immunophenoscore (IPS) score was used for the quantitative evaluation of tumor immunogenicity. Results: PDCD1, PDCD1LG2 and KIR3DL2 were included in the ICGs-signature model and the risk scores were calculated for each sample according to the coefficients in LASSO-Cox regression. Patients in high-risk group were associated with unfavorable prognosis. The receiver operating characteristic (ROC) curves showed the area under the curve (AUC) values for predicting 1-, 2- and 3-year overall survival (OS) by ICGs-signature were 0.925,0.822 and 0.835, respectively. The adaptive immunity cells and innate immunity cells were significantly abundant in the low-risk group, and low-risk patients tended to have higher IPS scores of PD-1, CTLA4, PD-L1 and PD-L2. Conclusions: A novel ICGs-signature was developed and validated, which may be not only served as a robust prognostic marker, but also a potential indicator reflecting immunotherapy response.

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.

Detailed analysis of recovery process of cranial nerve palsy after IMRT-based comprehensive treatment in nasopharyngeal carcinoma.

BACKGROUND: Cranial nerve (CN) palsy due to cancer involvement has been considered as an unfavorable prognostic factor for patients with nasopharyngeal carcinoma (NPC). We assessed the role of IMRT based treatment on the recovery of CN palsy and investigated the prognostic value of complete recovery of CN palsy. METHODS: A total of 115 NPC patients with cancer-related CN palsy were included in the study. We referred CTCAE version 5.0 to evaluate the grade of CN palsy. RESULTS: All patients with grade 1 CN palsy recovered completely during the 2 years of follow-up after definite treatment. Most grade 2 palsy could change gradually to grade 1 palsy or complete recovery during 2 years of follow-up. Patients with more than 2 symptoms of CN palsy had poor 3-year disease-free survival (DFS) than these with 1 or 2 symptoms (60.3% vs. 84.9%, HR 0.25, 95% CI 0.07-0.89, P = 0.001). There were no significant differences for PFS, OS, DMFS and LRFS between patients with complete recovery and non-complete recovery from CN palsy after receiving IMRT based comprehensive treatment. CONCLUSIONS: IMRT based comprehensive treatment could effectively promote the recovery of tumor-related CN palsy for NPC patient. More than 2 symptoms of CN palsy was a poor prognostic factor for DFS of NPC patients. The prognostic role of complete recovery of CN palsy was not identified in our study.

Predicting Disease-Free Survival With Multiparametric MRI-Derived Radiomic Signature in Cervical Cancer Patients Underwent CCRT.

Prognostic biomarkers that can reliably predict the disease-free survival (DFS) of locally advanced cervical cancer (LACC) are needed for identifying those patients at high risk for progression, who may benefit from a more aggressive treatment. In the present study, we aimed to construct a multiparametric MRI-derived radiomic signature for predicting DFS of LACC patients who underwent concurrent chemoradiotherapy (CCRT). METHODS: This multicenter retrospective study recruited 263 patients with International Federation of Gynecology and Obetrics (FIGO) stage IB-IVA treated with CCRT for whom pretreatment MRI scans were performed. They were randomly divided into two groups: primary cohort (n = 178) and validation cohort (n = 85). The LASSO regression and Cox proportional hazard regression were conducted to construct the radiomic signature (RS). According to the cutoff of the RS value, patients were dichotomized into low- and high-risk groups. Pearson's correlation and Kaplan-Meier analysis were conducted to evaluate the association between the RS and DFS. The RS, the clinical model incorporating FIGO stage and lymph node metastasis by the multivariate Cox proportional hazard model, and a combined model incorporating RS and clinical model were constructed to estimate DFS individually. RESULTS: The final radiomic signature consisted of four radiomic features: T2W_wavelet-LH_ glszm_Size Zone NonUniformity, ADC_wavelet-HL-first order_ Median, ADC_wavelet-HH-glrlm_Long Run Low Gray Level Emphasis, and ADC_wavelet _LL_gldm_Large Dependence High Gray Emphasis. Higher RS was significantly associated with worse DFS in the primary and validation cohorts (both p<0.001). The RS demonstrated better prognostic performance in predicting DFS than the clinical model in both cohorts (C-index, 0.736-0.758 for RS, and 0.603-0.649 for clinical model). However, the combined model showed no significant improvement (C-index, 0.648, 95% CI, 0.571-0.685). CONCLUSIONS: The present study indicated that the multiparametric MRI-derived radiomic signature could be used as a non-invasive prognostic tool for predicting DFS in LACC patients.

DCE-MRI Quantitative Parameters as Predictors of Treatment Response in Patients With Locally Advanced Cervical Squamous Cell Carcinoma Underwent CCRT.

PURPOSE: To evaluate the predictive value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) quantitative parameters in treatment response to concurrent chemoradiotherapy (CCRT) for locally advanced cervical squamous cell carcinoma (LACSC). METHODS AND MATERIALS: LACSC patients underwent CCRT had DCE-MRI before (e0) and after 3 days of treatment (e3). Extended Tofts Linear model with a user arterial input function was adopted to generate quantitative measurements. Endothelial transfer constant (Ktrans), reflux rate (Kep), fractional extravascular extracellular space volume (Ve), and fractional plasma volume (Vp) were calculated, and percentage changes ΔKtrans, ΔKep, ΔVe, and ΔVp were computed. The correlations of these measurements with the tumor regression rate were analyzed. The predictive value of these parameters on treatment outcome was generated by the receiver operating characteristic (ROC) curve. Univariate and multivariate logistic regression analyses were conducted to find the independent variables. RESULTS: Ktrans-e0, Kep -e0, ΔKtrans, and ΔVe were positively correlated with the tumor regression rate. Mean values of Ktrans-e0, Ktrans-e3, ΔKtrans, and ΔVe were higher in the non-residual tumor group than residual tumor group and were independent prognostic factors for predicting residual tumor occurrence. Ktrans-e3 showed the highest area under the curve (AUC) for treatment response prediction. CONCLUSIONS: Quantitative parameters at e0 and e3 from DCE-MRI could be used as potential indicators for predicting treatment response of LACSC.

Potentialities of multi-b-values diffusion-weighted imaging for predicting efficacy of concurrent chemoradiotherapy in cervical cancer patients.

BACKGROUND: To testify whether multi-b-values diffusion-weighted imaging (DWI) can be used to ultra-early predict treatment response of concurrent chemoradiotherapy (CCRT) in cervical cancer patients and to assess the predictive ability of concerning parameters. METHODS: Fifty-three patients with biopsy proved cervical cancer were retrospectively recruited in this study. All patients underwent pelvic multi-b-values DWI before and at the 3rd day during treatment. The apparent diffusion coefficient (ADC), true diffusion coefficient (Dslow), perfusion-related pseudo-diffusion coefficient (Dfast), perfusion fraction (f), distributed diffusion coefficient (DDC) and intravoxel diffusion heterogeneity index(α) were generated by mono-exponential, bi-exponential and stretched exponential models. Treatment response was assessed based on Response Evaluation Criteria in Solid Tumors (RECIST v1.1) at 1 month after the completion of whole CCRT. Parameters were compared using independent t test or Mann-Whitney U test as appropriate. Receiver operating characteristic (ROC) curves was used for statistical evaluations. RESULTS: ADC-T0 (p = 0.02), Dslow-T0 (p <  0.01), DDC-T0 (p = 0.03), ADC-T1 (p <  0.01), Dslow-T1 (p <  0.01), ΔADC (p = 0.04) and Δα (p <  0.01) were significant lower in non-CR group patients. ROC analyses showed that ADC-T1 and Δα exhibited high prediction value, with area under the curves of 0.880 and 0.869, respectively. CONCLUSIONS: Multi-b-values DWI can be used as a noninvasive technique to assess and predict treatment response in cervical cancer patients at the 3rd day of CCRT. ADC-T1 and Δα can be used to differentiate good responders from poor responders.