A nomogram for the prediction of overall survival in patients with stage II and III non‑small cell lung cancer using a population‑based study

Liao, Yi; Wang, Xue; Zhong, Ping; Yin, Guofang; Fan, Xiaoxuan; Huang, Chengliang

doi:10.3892/ol.2019.10977

Cited by 16 publications

(14 citation statements)

References 43 publications

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“…Whether radiotherapy has a beneficial effect on the prognosis of patients is debated. In particular, the reported effects of radiotherapy on prognosis for different stages of lung cancer are inconsistent (30,31).…”

Section: Discussionmentioning

confidence: 99%

The Positive Lymph Node Ratio Predicts Survival in T1−4N1−3M0 Non-Small Cell Lung Cancer: A Nomogram Using the SEER Database

2020

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Background: An increasing number of studies have shown that the positive lymph node ratio (pLNR) can be used to evaluate the prognosis of non-small cell lung cancer (NSCLC) patients. To determine the predictive value of the pLNR, we collected data from the Surveillance, Epidemiology, and End Results (SEER) database and performed a retrospective analysis. Methods: We collected survival and clinical information on patients with T 1−4 N 1−3 M 0 NSCLC diagnosed between 2010 and 2016 from the SEER database and screened them according to inclusion and exclusion criteria. X-tile software was used to obtain the best cutoff value for the pLNR. Then, we randomly divided patients into a training set and a validation set at a ratio of 7:3. Pearson's correlation coefficient, tolerance and the variance inflation factor (VIF) were used to detect collinearity between variables. Univariate and multivariate Cox regression analyses were used to identify significant prognostic factors, and nomograms was constructed to visualize the results. The concordance index (C-index), calibration curves, and decision curve analysis (DCA) were used to assess the predictive ability of the nomogram. We divided the patient scores into four groups according to the interquartile interval and constructed a survival curve using Kaplan-Meier analysis. Results: A total of 6,245 patients were initially enrolled. The best cutoff value for the pLNR was determined to be 0.55. The nomogram contained 13 prognostic factors, including the pLNR. The pLNR was identified as an independent prognostic factor for both overall survival (OS) and cancer-specific survival (CSS). The C-index was 0.703 (95% CI, 0.695-0.711) in the training set and 0.711 (95% CI, 0.699-0.723) in the validation set. The calibration curves and DCA also indicated the good predictability of the nomogram. Risk stratification revealed a statistically significant difference among the four groups of patients divided according to quartiles of risk score. Conclusion: The nomogram containing the pLNR can accurately predict survival in patients with T 1−4 N 1−3 M 0 NSCLC.

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Section: Discussionmentioning

confidence: 99%

The Positive Lymph Node Ratio Predicts Survival in T1−4N1−3M0 Non-Small Cell Lung Cancer: A Nomogram Using the SEER Database

2020

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“…To identify independent risk factors, univariate Cox regression analysis was used for all variables. Further, factors with statistical significance according to the results of the univariate Cox regression analysis were included in the multivariate Cox regression analysis (described as the hazard ratio with 95% confidence intervals [CIs] together with the p-value) [15]. p < 0.05 indicated statistical significance.…”

Section: Discussionmentioning

confidence: 99%

Non-SMC Condensin I Complex Subunit H (NCAPH) Is Associated with Lymphangiogenesis and Drug Resistance in Oral Squamous Cell Carcinoma

Shimomura

Sasahira

Nakashima

et al. 2019

JCM

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Background: Head and neck cancer, including oral squamous cell carcinoma (OSCC), is the sixth most common malignancy. OSCC has strong invasive ability, and its malignant potential is closely associated with local expansion and lymph node metastasis. Furthermore, local or nodal recurrence worsens OSCC prognosis. In our previous cDNA microarray analysis, non-structural maintenance of chromosome (SMC) condensin I complex subunit H (NCAPH) was identified as an upregulated gene in recurrent OSCC. Although NCAPH has several functions in tumors, its role in OSCC is unknown. Methods: In this study, we examined NCAPH expression in OSCC and performed a functional analysis of human OSCC cells. Results: NCAPH expression was higher in OSCC than in normal oral mucosa. In immunohistochemistry using 142 OSCC specimens, the immunostaining of NCAPH was strongly associated with nodal metastasis and lymphatic infiltration. In multivariate analysis using the Cox proportional hazards model, NCAPH expression was an independent poor prognostic indicator for OSCC. Moreover, NCAPH promoted the migration and adhesion of endothelial cells to OSCC cells and promoted the resistance to platinum anticancer drugs. Conclusions: Our present findings suggest that NCAPH is a novel diagnostic and therapeutic target in OSCC.

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“…Clear clinical risk grouping is important for making treatment plan and evaluating prognosis. Precision medicine is a medical model that customizes treatment plans for patients according to their characteristics in genome, phenotype, and biomarkers [17].…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Lncrnas-Based Nomogram for Survival Prediction in Neuroblastoma Patients

Y¹,

Jin²,

Xiang³

2021

Preprint

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BackgroundTreatment of neuroblastoma is evolving toward precision medicine. LncRNAs can be used as prognostic biomarkers in many types of cancer.MethodsBased on the RNA-seq data from GSE49710, we built a lncRNAs-based risk score using the least absolute shrinkage and selection operation (LASSO) regression. Cox regression, receiver operating characteristic curves were used to evaluate the association of the LASSO risk score with overall survival. Nomograms were created and then validated in an external cohort from TARGET database. Gene set enrichment analysis was performed to identify the significantly changed biological pathways. ResultsThe 16-lncRNAs-based LASSO risk score was used to separate patients into high-risk and low-risk groups. In GSE49710 cohort, the high-risk group exhibited a poorer OS than those in the low-risk group (P<0.001). Moreover, multivariate Cox regression analysis demonstrated that LASSO risk score was an independent risk factor (HR=6.201;95%CI:2.536-15.16). The similar prognostic powers of the 16-lncRNAs were also achieved in the external cohort and in stratified analysis. In addition, a nomogram was established and worked well both in the internal validation cohort (C-index=0.831) and external validation cohort (C-index=0.773). The calibration plot indicated the good clinical utility of the nomogram. Gene set enrichment analysis (GSEA) indicated that high-risk group was related with cancer recurrence, metastasis and inflammatory associated pathways.ConclusionThe lncRNA-based LASSO risk score is a promising and potential prognostic tool in predicting the survival of patients with neuroblastoma. The nomogram combined the lncRNAs and clinical parameters allows for accurate risk assessment in guiding clinical management.

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A nomogram for the prediction of overall survival in patients with stage II and III non‑small cell lung cancer using a population‑based study

Cited by 16 publications

References 43 publications

The Positive Lymph Node Ratio Predicts Survival in T1−4N1−3M0 Non-Small Cell Lung Cancer: A Nomogram Using the SEER Database

The Positive Lymph Node Ratio Predicts Survival in T1−4N1−3M0 Non-Small Cell Lung Cancer: A Nomogram Using the SEER Database

Non-SMC Condensin I Complex Subunit H (NCAPH) Is Associated with Lymphangiogenesis and Drug Resistance in Oral Squamous Cell Carcinoma

Development and Validation of a Lncrnas-Based Nomogram for Survival Prediction in Neuroblastoma Patients

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