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Development and validation of nomogram to predict risk of survival in patients with laryngeal squamous cell carcinoma.

ABSTRACT: To the best of our knowledge, this is the first study established a nomogram to predict survival probability in Asian patients with LSCC. A risk prediction nomogram for patients with LSCC, incorporating easily assessable clinicopathologic factors, generates more precise estimations of the survival probability when compared TNM stage alone, but still need additional data before being used in clinical application. BACKGROUND:Due to a wide variation of tumor behavior, prediction of survival in laryngeal squamous cell carcinoma (LSCC) patients received curative-intent surgery is an important but formidable challenge. We attempted to establish a nomogram to precisely predict survival probability in LSCC patients. METHODS:A total of 369 consecutive LSCC patients underwent curative resection between 2008 and 2012 at Hunan Province Cancer Hospital were included in the present study. Subsequently, 369 LSCC patients were assigned to a training set (N=261) and a validation set (N=108) at random. On the basis of multivariable Cox regression analysis results, we developed a nomogram. The predictive accuracy and discriminative ability of the nomogram were confirmed by calibration curve and a concordance index (C-index), and compared with TNM stage system by C-index, receiver operating characteristic (ROC) analysis. RESULTS:Six independent parameters to predict prognosis were age, pack years, N-stage, lymph node ratio (LNR), anemia and albumin, which were all assembled into the nomogram. The calibration curve verified excellent models' concordance. The C-index of the nomogram was 0.73 (0.68-0.78), and the area under curve (AUC) of nomogram in predicting overall survival (OS) was 0.766, which were significantly higher than traditional TNM stage. Decision curve analysis further demonstrated that our nomogram had a larger net benefit than the TNM stage. CONCLUSION:A risk prediction nomogram for patients with LSCC, incorporating easily assessable clinicopathologic factors, generates more precise estimations of the survival probability when compared TNM stage alone, but still need additional data before being used in clinical application.

SUBMITTER: Cui J

PROVIDER: S-EPMC7432998 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Development and validation of nomogram to predict risk of survival in patients with laryngeal squamous cell carcinoma.

Cui Jie J Wang Liping L Zhong Waisheng W Chen Zhen Z Tan Xiaojun X Yang Hong H Chen Jie J Liu Genglong G

Bioscience reports 20200801 8

To the best of our knowledge, this is the first study established a nomogram to predict survival probability in Asian patients with LSCC. A risk prediction nomogram for patients with LSCC, incorporating easily assessable clinicopathologic factors, generates more precise estimations of the survival probability when compared TNM stage alone, but still need additional data before being used in clinical application.<h4>Background</h4>Due to a wide variation of tumor behavior, prediction of survival ...[more]

PMID: 32744320

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Project description:BackgroundLong noncoding RNAs (lncRNAs), which have little or no ability to encode proteins, have attracted special attention due to their potential role in cancer disease. We aimed to establish a lncRNA signature and a nomogram incorporating the genomic and clinicopathologic factors to improve the accuracy of survival prediction for laryngeal squamous cell carcinoma (LSCC).MethodsA LSCC RNA-sequencing (RNA-seq) dataset and the matched clinicopathologic information were downloaded from The Cancer Genome Atlas (TCGA). Using univariable Cox regression and least absolute shrinkage and selection operator (LASSO) analysis, we developed a thirteen-lncRNA signature related to prognosis. On the basis of multivariable Cox regression analysis results, a nomogram integrating the genomic and clinicopathologic predictors was built. The predictive accuracy and discriminative ability of the inclusive nomogram were confirmed by calibration curve and a concordance index (C-index), and compared with the TNM staging system by C-index and receiver operating characteristic (ROC) analysis. Decision curve analysis (DCA) was conducted to evaluate the clinical value of our nomogram.ResultsThirteen overall survival- (OS-) related lncRNAs were identified, and the signature consisting of the selected thirteen lncRNAs could effectively divide patients into high-risk and low-risk subgroups, with area under curves (AUC) of 0.89 (3-year OS) and 0.885 (5-year OS). Independent factors derived from multivariable analysis to predict survival were margin status, tumor status, and lncRNA signature, which were all assembled into the nomogram. The calibration curve for the survival probability showed that the predictions based on the nomogram coincided well with actual observations. The C-index of the nomogram was 0.82 (0.77-0.87), and the area under curve (AUC) of the nomogram in predicting overall survival (OS) was 0.938, both of which were significantly higher than the traditional TNM stage. Decision curve analysis further demonstrated that our nomogram had larger net benefit than TNM stage.ConclusionAn inclusive nomogram for patients with LSCC, comprising genomic and clinicopathologic variables, generates more accurate estimations of the survival probability when compared with TNM stage alone, but more data are needed before the nomogram is used in clinical practice.

Project description:BackgroundLack of adequate objectivity and universality, available models are still difficult to be applied to clinical practice in predicting occult cervical metastasis of early oral squamous cell carcinoma (OSCC). Taking abnormal metabolic state into consideration, the current model is helpful to distinguish those patients with or without occult cervical metastasis.MethodsThis study retrospectively analyzed 330 OSCC patients initially diagnosed cT1-2N0M0 stage and received neck dissection from January 2020 to July 2022. The occult cervical metastasis was identified by pathological examination.. After screening independent risk factors using logistic regression, patients were divided into training and validation cohorts at the ratio of 2:1 randomly, and a novel diagnostic model was constructed. Performances of this model were evaluated by the area under the curve (AUC), calibrating curve, decision curve analysis (DCA) and clinical impact curve (CIC).ResultsOf the 330 included patients {age mean [standard deviation (SD)], 61.24 (12.99) years; 202 (61.2%) males}, 49 (14.8%) had occult nodal metastasis. Five variables, including body mass index (BMI) [high odds ratio (OR): 1.132; 95% confidence interval (CI): 1.019-1.258, P=0.021], primary tumor site (tongue & floor of mouth (TF) OR: 3.756; 95% CI: 1.295-10.898, P=0.015), depth of invasion (DOI) (5-10 mm OR: 2.973; 95% CI: 1.266-6.981; P=0.012), pathological differentiation (Poor differentiation OR: 2.65; 95% CI: 1.341-5.239; P=0.005), and diabetes (OR: 3.123; 95% CI: 1.23-7.929; P=0.017) were screened to establish the predictive model. In training cohort (n=220), this model achieved an AUC of 0.814 and had a sensitivity of 78.1% and specificity of 70.2%. Calibration plots showed favorable consistency between the prediction of the model and actual observations (Hosmer-Lemeshow value >0.05). Decision curve analysis (DCA) and clinical impact curve (CIC) showed the model was clinically useful and had better discriminative ability under the threshold probability of 0.5. Above evaluations were verified in the validation cohort (n=110). Compared to previous reported models, the concordance index (C-index), net reclassification index (NRI), and integrated discrimination improvement (IDI) values were superior in both training and validation cohorts (P<0.05).ConclusionsThis constructed model might have reference value for clinicians in making neck management decisions of early OSCC patients.

Project description:BackgroundAutophagy, a highly conserved self-digesting process, has been deeply involved in the development and progression of oral squamous cell carcinoma (OSCC). However, the prognostic value of autophagy-related genes (ARGs) for OSCC still remains unclear. Our study set out to develop a multigene expression signature based on ARGs for individualized prognosis assessment in OSCC patients.MethodsBased on The Cancer Genome Atlas (TCGA) database, we identified prognosis-related ARGs through univariate COX regression analysis. Then we performed the least absolute shrinkage and selection operator (LASSO) regression analysis to identify an optimal autophagy-related multigene signature with the subsequent validation in testing set, GSE41613 and GSE42743 datasets.ResultsWe identified 36 prognosis-related ARGs for OSCC. Subsequently, the multigene signature based on 13 prognostic ARGs was constructed and successfully divided OSCC patients into low and high-risk groups with significantly different overall survival in TCGA training set (p < 0.0001). The autophagy signature remained as an independent prognostic factor for OSCC in univariate and multivariate Cox regression analyses. The area under the curve (AUC) values of the receiver operating characteristic (ROC) curves for 1, 3, and 5-year survival were 0.758, 0.810, 0.798, respectively. Then the gene signature was validated in TCGA testing set, GSE41613 and GSE42743 datasets. Moreover, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and single-sample gene set enrichment analysis (ssGSEA) revealed the underlying biological characteristics and signaling pathways associated with this signature in OSCC. Finally, we constructed a nomogram by combining the gene signature with multiple clinical parameters (age, gender, TNM-stage, tobacco, and alcohol history). The concordance index (C-index) and calibration plots demonstrated favorable predictive performance of our nomogram.ConclusionIn summary, we identified and verified a 13-ARGs prognostic signature and nomogram, which provide individualized prognosis evaluation and show insight for potential therapeutic targets for OSCC.

Project description:ObjectiveWith the increasing incidence and mortality of laryngeal squamous cell carcinoma worldwide, researchers continue to search for novel prognostic factors and treatment methods for preventing early laryngeal squamous cell carcinoma from becoming advanced laryngeal squamous cell carcinoma. This study aims to determine if tumor budding is an independent risk factor associated with the survival of patients with laryngeal squamous cell carcinoma.Methods268 cases of laryngeal squamous cell carcinoma were studied, and tumor budding was analyzed for associations with clinicopathological features and clinical outcomes.ResultsTumor budding was divided into low-grade tumor budding (0-6/0.785 mm2) and high-grade tumor budding (≥7/0.785 mm2) based on the results of the receiver operating characteristics curve analysis. Logistic regression analysis showed that smaller tumor cell nests, the low levels of tumor-infiltrating lymphocytes, and higher pathological T staging were the risk factors for high-grade tumor budding (p < 0.05). In the low-grade tumor budding group, there was no statistic difference in survival between patients without tumor budding and those with 1-6/0.785 mm2 tumor budding. Multivariate survival analysis showed high-grade tumor budding (p < 0.001) was independent prognostic factors for disease-free survival and overall survival in laryngeal squamous cell carcinoma. High-grade tumor budding was also an independent prognostic factor for disease-free survival (p = 0.037) and overall survival (p = 0.009) in T1-2N0 laryngeal squamous cell carcinoma.ConclusionsSmaller tumor cell nests, the low levels of tumor-infiltrating lymphocytes, and higher pathological T staging were closely associated with high-grade tumor budding in laryngeal squamous cell carcinoma. High-grade tumor budding may be an adverse risk factor that affects not only the disease-free survival and overall survival of laryngeal squamous cell carcinoma patients but also the survival of T1-2N0 laryngeal squamous cell carcinoma patients.Level of evidenceLevel 4.

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Development and validation of nomogram to predict risk of survival in patients with laryngeal squamous cell carcinoma.

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Development and validation of nomogram to predict risk of survival in patients with laryngeal squamous cell carcinoma.

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