Prognostic models for early and late tumor progression prediction in nasopharyngeal carcinoma: An analysis of 8292 endemic cases.

OBJECTIVES: The time for posttreatment tumor progression differs between nasopharyngeal carcinoma (NPC) patients. Herein, we established effective nomograms for predicting early tumor progression (ETP) and late tumor progression (LTP) in NPC patients. METHODS: We retrospectively enrolled 8292 NPC patients (training cohort: n = 6219; validation cohort: n = 2073). The ELP and LTP were defined as the time to tumor progression ≤24 and >24 months after treatment, respectively. RESULTS: The ETP and LTP accounted for 52.6 and 47.4% of the total patient cohort, respectively. Patients who developed ETP had markedly worse overall survival (OS) versus patients who suffered from LTP (5-year OS: 26.2% vs. 59.7%, p < 0.001). Further, we identified 10/6 predictive factors significantly associated with ETP/LTP via logistic regression analyses. These indicators were used separately to construct two predictive nomograms for ETP and LTP. In the training group, the ETP nomogram [Harrell Concordance Index (C-index) value: 0.711 vs. 0.618; p < 0.001] and LTP nomogram (C-index value: 0.701 vs. 0.612; p < 0.001) were significantly superior for risk stratification than the TNM staging. These results were supported in the validation group with a C-index value of 0.753 and 0.738 for the ETP and LTP nomograms, respectively. High-risk patients defined by ETP/LTP nomograms had shorter progression-free survival than low-risk patients (all p < 0.001). CONCLUSION: The established nomograms can help in ELP or LTP risk stratification for NPC patients. Our current results might also provide insights into individualized treatment decisions and designing surveillance strategies for NPC patients.

Development of a Nomogram Model for Treatment of Nonmetastatic Nasopharyngeal Carcinoma.

Importance: Because of tumor heterogeneity, overall survival (OS) differs significantly among individuals with nasopharyngeal carcinoma (NPC), even among those with the same clinical stage. Relying solely on TNM staging to guide treatment remains imperfect. Objectives: To establish a comprehensive nomogram to estimate individualized OS and to explore stratified treatment regimens for risk subgroups in nonmetastatic NPC. Design, Setting, and Participants: This cohort study included 8093 patients diagnosed with NPC at a single center in China from April 2009 to December 2015. The sample was split into a training cohort (5398 participants [66.7%]) and validation cohort (2695 [33.3%]). Data were analyzed in May 2020. Exposures: Age, T stage, N stage, Epstein-Barr virus (EBV) DNA level, serum lactate dehydrogenase (LDH) levels, and albumin (ALB) levels. Main Outcomes and Measures: The primary end point was OS. The nomogram for estimating OS was generated based on multivariate Cox proportional hazards regression. The performance of the nomogram was quantified using Harrell concordance index (C index), the area under the curve (AUC) of the receiver operating characteristic curve, and a calibration curve. OS rates were established using the Kaplan-Meier method, and intersubgroup differences were examined by the log-rank test. Results: Among the 8093 participants, 5688 (70.3%) were men, and the median age at diagnosis was 45 years (range, 7-85 years). Six variables (age, T stage, N stage, EBV DNA levels, LDH levels, and ALB levels) were identified through multivariate Cox regression and incorporated into a nomogram to estimate OS. The resulting nomogram showed excellent discriminative ability and significantly outperformed the eighth edition of the American Joint Committee on Cancer/Union for International Cancer Control TNM staging system for estimating OS (C index, 0.716 [95% CI, 0.698-0.734] vs 0.643 [95% CI, 0.624-0.661]; P < .001; AUC, 0.717 [95% CI, 0.698-0.737] vs 0.643 [95% CI, 0.623-0.662]; P < .001), and the calibration curves showed satisfactory agreement between the actual and nomogram-estimated OS rates. The validation cohort confirmed the results. Patients were stratified into 4 risk groups based on the 25th, 50th, and 75th percentile score values estimated from the nomogram. The 4 nomogram-defined risk groups demonstrated significantly different intergroup OS (3-year OS rates: risk group 1, 1328 of 1345 [98.7%]; risk group 2, 1289 of 1341 [96.1%]; risk group 3, 1222 of 1321 [92.5%]; risk group 4, 1173 of 1391 [84.3%]; P < .001). These risk groups were associated with the efficacy of different treatment regimens. For example, for risk group 4, induction chemotherapy with concurrent chemoradiotherapy was associated with a significantly better OS than concurrent chemoradiotherapy (log-rank P = .008) and intensity-modulated radiotherapy alone (log-rank P < .001). Conclusions and Relevance: In this study, the proposed nomogram model enabled individualized prognostication of OS and could help to guide risk-adapted treatment for patients with nonmetastatic NPC.

Development and validation of a prognostic nomogram for the pre-treatment prediction of early metachronous metastasis in endemic nasopharyngeal carcinoma: a big-data intelligence platform-based analysis.

BACKGROUND: Early failure of cancer treatment generally indicates a poor prognosis. Here, we aim to develop and validate a pre-treatment nomogram to predict early metachronous metastasis (EMM) in nasopharyngeal carcinoma (NPC). METHODS: From 2009 to 2015, a total of 9461 patients with NPC (training cohort: n = 7096; validation cohort: n = 2365) were identified from an institutional big-data research platform. EMM was defined as time to metastasis within 2 years after treatment. Early metachronous distant metastasis-free survival (EM-DMFS) was the primary endpoint. A nomogram was established with the significant prognostic factors for EM-DMFS determined by multivariate Cox regression analyses in the training cohort. The Harrell Concordance Index (C-index), area under the receiver operator characteristic curve (AUC), and calibration curves were applied to evaluate this model. RESULTS: EMM account for 73.5% of the total metachronous metastasis rate and is associated with poor long-term survival in NPC. The final nomogram, which included six clinical variables, achieved satisfactory discriminative performance and significantly outperformed the traditional tumor-node-metastasis (TNM) classification for predicting EM-DMFS: C-index: 0.721 versus 0.638, p < 0.001; AUC: 0.730 versus 0.644, p < 0.001. The calibration curves showed excellent agreement between the predicted and actual EM-DMFS. The nomogram can stratify patients into three risk groups with distinct EM-DMFS (2-year DMFS: 96.8% versus 90.1% versus 80.3%, p < 0.001). A validation cohort supported the results. The three identified risk groups are correlated with the efficacy of different treatment regimens. CONCLUSION: Our established nomogram can reliably predict EMM in patients with NPC and might aid in formulating risk-adapted treatment decisions and personalized patient follow-up strategies.

Engulfment and Cell Motility Protein 1 Protects Against DSS-induced Colonic Injury in Mice via Rac1 Activation.

BACKGROUND AND AIMS: Mucosal healing is an emerging therapeutic goal that could result in clinical remission of inflammatory bowel disease [IBD]. We sought to determine the role of engulfment and cell motility protein 1 [ELMO1] in wound healing in vitro and in vivo and to investigate the underlying pathways. METHODS: RNA transcriptome sequencing was performed to detect the expression profiles of mRNA between inflamed tissues and corresponding non-inflamed tissues of IBD patients, followed by Gene Expression Omnibus [GEO] datasets and western blot analysis. The effects of ELMO1 overexpression or knockdown on cell migration and proliferation were determined. The dependence of these effects on Rac1 was assessed using a Rac1 inhibitor [NSC23766] and a Rac1 pull-down assay. We identified the underlying pathways involved by Gene Ontology [GO] analysis. A dextran sulphate sodium [DSS]-induced colitis model was established to evaluate the role of ELMO1 in colonic mucosal healing. RESULTS: ELMO1 was upregulated in inflamed tissues compared with corresponding non-inflamed tissues. ELMO1 overexpression increased cell migration in a Rac1-dependent manner. Depletion of ELMO1, or NSC23766 administration, abolished this effect. GO analysis revealed that ELMO1 overexpression preferentially affected pathways involved in cytoskeletal regulation and wound healing, which was demonstrated by enhanced F-actin staining and increased numbers of extending lamellipodia in cells overexpressing ELMO1. In DSS-induced colitis, systemic delivery of pSin-EF2-ELMO1-Pur attenuated colonic inflammation and promoted recovery from colonic injury. The protective effect of ELMO1 was dependent on Rac1 activation. CONCLUSIONS: ELMO1 protects against DSS-induced colonic injury in mice through its effect on epithelial migration via Rac1 activation.