Development and Validation of a Nomogram for Predicting Survival in Patients With Resected Non–Small-Cell Lung Cancer

“…Through incorporating significant factors, nomograms could provide an estimated probability of an event, such as death or recurrence, which is tailored to the profile of individual patients. Nomograms have been considered as reliable tools to predict the clinical outcomes in many cancer types (14)(15)(16). The prediction of the nomogram has been proved to be more precise than the current staging systems in several types of cancer (15,16).…”

Section: Introductionmentioning

confidence: 99%

Nomogram prediction for the survival of the patients with small cell lung cancer

et al. 2017

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Background: Small cell lung cancer (SCLC) is a subtype of lung cancer with poor prognosis. In this study, we aimed to build a nomogram to predict the survival of individual with SCLC by incorporating significant clinical parameters. Methods:The patients with SCLC were enrolled from the First Affiliated Hospital of Guangzhou Medical University (GMUFAH) between 2009 and 2013. We identified and incorporated the independent prognostic factors to build a nomogram to predict the survival of SCLC patients. The predictive accuracy and discriminative ability of the nomogram were evaluated by concordance index (C-index) and calibration curve.We also compared the accuracy of the built model with the 7 th AJCC TNM and VALSG staging system. The nomogram was further validated in an independent cohort of 80 patients with SCLC from Cancer Center of Guangzhou Medical University (GMUCC) between 2009 and 2013.Results: A total of 275 patients with SCLC were included in the primary cohort, and seven independent prognostic factors were identified including age, N stage, metastasis status, histology, platelets to lymphocyte ratio (PLR), neuron specific enolase (NSE) and CYFRA21-1 as independent prognostic factors after using Cox regression model. A nomogram incorporating these prognostic factors was subsequently built. The calibration curves for possibilities of 1-, 2-year overall survival (OS) revealed optimal agreement between nomogram prediction and actual observation. The C-index of this nomogram was higher than that of TNM Conclusions:In this study, we established and validated a novel nomogram for the prediction of OS for the patients with SCLC. This model could provide more accurate individual prediction of survival probability of SCLC than the existing staging systems.

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“…Based on its histologic appearance, lung cancer can generally be classified into two major types: small-cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) [2]. In comparison with the SCLC, the NSCLC is relatively insensitive to chemotherapy and accounts for between 85% and 90% of lung-cancer deaths [3,4]. Presently, the main clinical therapeutic options in NSCLC management include surgery, radiotherapy and chemotherapy.…”

Section: Introductionmentioning

confidence: 99%

Co-delivery of VP-16 and Bcl-2-targeted antisense on PEG-grafted oMWCNTs for synergistic in vitro anti-cancer effects in non-small and small cell lung cancer

Heger

Polanská

Křížková

et al. 2017

Colloids and Surfaces B: Biointerfaces

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Development and Validation of a Nomogram for Predicting Survival in Patients With Resected Non–Small-Cell Lung Cancer

Abstract: We established and validated a novel nomogram that can provide individual prediction of OS for patients with resected NSCLC. This practical prognostic model may help clinicians in decision making and design of clinical studies.

Cited by 545 publications

References 31 publications

A Model to Predict the Use of Surgical Resection for Advanced-Stage Non-Small Cell Lung Cancer Patients

A Model to Predict the Use of Surgical Resection for Advanced-Stage Non-Small Cell Lung Cancer Patients

Nomogram prediction for the survival of the patients with small cell lung cancer

Co-delivery of VP-16 and Bcl-2-targeted antisense on PEG-grafted oMWCNTs for synergistic in vitro anti-cancer effects in non-small and small cell lung cancer

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