A nomogram to predict prognosis after surgery in early stage non-small cell lung cancer in elderly patients

Sun, Fenghao; Ma, Ke; Yang, Xiaodong; Li, Ming; Shi, Yu; Zhan, Cheng; Jiang, Wei; Wang, Qun

doi:10.1016/j.ijsu.2017.04.024

Cited by 45 publications

(29 citation statements)

References 25 publications

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“…As far as we know, the nomogram has been applied to predict the survival status of various cancers 22 - 24 . Since the nomogram quantifies risk by combining and illustrating the relative importance of various prognostic factors and has been used in clinical oncology assessment.…”

Section: Discussionmentioning

confidence: 99%

A Prognostic Nomogram for Cervical Cancer after Surgery from SEER Database

Wang¹,

Yang²,

Wang³

et al. 2018

J. Cancer

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Background: To develop and validate a nomogram based on the conventional measurements and log of odds between the number of positive lymph node and the number of negative lymph node (LODDS) in predicting prognosis for cervical cancer patients after surgery.Methods: A total of 8202 cervical cancer patients with pathologically confirmed between 2004 and 2014 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. All the patients were divided into training (n=3603) and validation (n=4599) cohorts based on consecutive age of diagnosis. Demographic and clinical pathological factors were evaluated the association with overall survival (OS). Parameters significantly correlating with OS were used to create a nomogram. An independent external validation cohort was subsequently used to assess the predictive performance of the model.Results: In the training set, age at diagnosis, race, marital status, tumor grade, FIGO stage, histology, size and LODDS were correlated significantly with outcome and used to develop a nomogram. The calibration curve for probability of survival showed excellent agreement between prediction by nomogram and actual observation in the training cohort, with a bootstrap-corrected concordance index of 0.749(95% CI, 0.731-0.767). Importantly, our nomogram performed favorably compared to the currently utilized FIGO model, with concordance indices of 0.786 (95% CI, 0.764 to 0.808) vs 0.685 (95%CI, 0.660 to 0.710) for OS in the validation cohort, respectively.Conclusions: By incorporating LODDS, our nomogram may be superior to the currently utilized FIGO staging system in predicting OS in cervical cancer patients after surgery.

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Section: Discussionmentioning

confidence: 99%

A Prognostic Nomogram for Cervical Cancer after Surgery from SEER Database

Wang¹,

Yang²,

Wang³

et al. 2018

J. Cancer

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“…The results of multivariate analysis were used to structure a nomogram and concordance index (c‐index), and calibration plots were used to evaluate model performance. In addition, nomograms were used to compare the predicted survival with the observed survival . Simultaneously, patients from FDZSH were used as a validation cohort, and the total points for each patient in the validation cohort were calculated according to the established nomogram.…”

Section: Methodsmentioning

confidence: 99%

Analysis of the clinicopathological characteristics, genetic phenotypes, and prognostic of pure mucinous adenocarcinoma

Chen

et al. 2019

Cancer Medicine

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Background: Primary pure mucinous adenocarcinoma of the lung (PMA) is a rare subtype. However, correlations between clinicopathological features and genetic phenotypes with survival have not been described comprehensively. Methods: Pure mucinous adenocarcinoma patient information collected from the Surveillance, Epidemiology, and End Results (SEER) database, the Department of Thoracic Surgery, Zhongshan Hospital, Fudan University (FDZSH), and the Cancer Genome Atlas (TCGA) were extracted, evaluated, and compared with other lung adenocarcinomas (LUAD) patient data. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed to explore the functional importance of underlying molecular changes. Overall survival (OS) was evaluated with the Kaplan-Meier method. Univariate and multivariate analysis through Cox proportional hazard regression identified risk factors that predicted OS, and the results were used to construct a nomogram to predict OS for PMA patients. Results: Overall, 3622 patients, 41 patients, and 15 patients with PMA were identified from the SEER, FDZSH, and TCGA databases, respectively. There were 345 differentially expressed genes, 30 differentially mutated genes and 72 differentially methylated genes were identified between PMA and other LUAD samples. In the SEER database, PMA had a better prognosis compared to other LUAD. Compared with patients with other LUAD, patients with PMA exhibited unique clinicopathological features, including fewer grade III/IV tumors, less pleural invasion, more early-stage cancer, and more lower lobe carcinomas. Multivariate analyses showed that age, race, T stage, N stage, surgery, and chemotherapy were independent risk factors. The nomogram had a calibration index of 0.724. Conclusions: Our research identified unique clinicopathological characteristics and genetic phenotypes for PMA and other LUAD. The nomogram accurately predicted OS. K E Y W O R D S clinicopathological features, genetic analysis, nomogram, pure mucinous adenocarcinoma, the surveillance, epidemiology, and end results 518 | CHEN Et al. How to cite this article: Chen Z, Li M, Ma K, et al. Analysis of the clinicopathological characteristics, genetic phenotypes, and prognostic of pure mucinous adenocarcinoma. Cancer Med. 2020;9:517-529. https ://

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“…Tumor-node-metastasis (TNM) system is widely used to estimate the outcome of patients with NSCLC in current clinical practice. However, a completely different prognosis may occur in patients with the same TNM stage [ 3 ] .Other traditional clinicopathologic factors including age, sex, pathological type and tumor grade have been reported to correlate to the prognosis of NSCLC [ 4 ]. Moreover, it is also believed that tremendous heterogeneity between patients exists in the biology underlying NSCLC.…”

Section: Introductionmentioning

confidence: 99%

A molecular and staging model predicts survival in patients with resected non-small cell lung cancer

et al. 2018

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BackgroundThe current TNM staging system is far from perfect in predicting the survival of individual non-small cell lung cancer (NSCLC) patients. In this study, we aim to combine clinical variables and molecular biomarkers to develop a prognostic model for patients with NSCLC.MethodsCandidate molecular biomarkers were extracted from the Gene Expression Omnibus (GEO), and Cox regression analysis was performed to determine significant prognostic factors. The survival prediction model was constructed based on multivariable Cox regression analysis in a cohort of 152 NSCLC patients. The predictive performance of the model was assessed by the Area under the Receiver Operating Characteristic Curve (AUC) and Kaplan–Meier survival analysis.ResultsThe survival prediction model consisting of two genes (TPX2 and MMP12) and two clinicopathological factors (tumor stage and grade) was developed. The patients could be divided into either high-risk group or low-risk group. Both disease-free survival and overall survival were significantly different among the diverse groups (P < 0.05). The AUC of the prognostic model was higher than that of the TNM staging system for predicting survival.ConclusionsWe developed a novel prognostic model which can accurately predict outcomes for patients with NSCLC after surgery.Electronic supplementary materialThe online version of this article (10.1186/s12885-018-4881-9) contains supplementary material, which is available to authorized users.

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A nomogram to predict prognosis after surgery in early stage non-small cell lung cancer in elderly patients

Abstract: The nomogram developed in this study demonstrated its discrimination capability to predict the 3- and 5-year OS rates of elderly patients with early stage NSCLC based on individual characteristics.

Cited by 45 publications

References 25 publications

A Prognostic Nomogram for Cervical Cancer after Surgery from SEER Database

A Prognostic Nomogram for Cervical Cancer after Surgery from SEER Database

Analysis of the clinicopathological characteristics, genetic phenotypes, and prognostic of pure mucinous adenocarcinoma

A molecular and staging model predicts survival in patients with resected non-small cell lung cancer

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