scholarly journals A prognostic model for elderly patients with squamous non-small cell lung cancer: a population-based study

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Siying Chen ◽  
Chunxia Gao ◽  
Qian Du ◽  
Lina Tang ◽  
Haisheng You ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Elderly Patients ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Prognostic Model ◽  
Small Cell ◽  
The Novel ◽  
Seer Database ◽  
Small Cell Lung ◽  
Ajcc Stage

Abstract Background Squamous cell carcinoma (SCC) is a main pathological type of non-small cell lung cancer. It is common among elderly patients with poor prognosis. We aimed to establish an accurate nomogram to predict survival for elderly patients (≥ 60 years old) with SCC based on the Surveillance, Epidemiology, and End Results (SEER) database. Methods The gerontal patients diagnosed with SCC from 2010 to 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. The independent prognostic factors were identified using multivariate Cox proportional hazards regression analysis, which were utilized to conduct a nomogram for predicting survival. The novel nomogram was evaluated by Concordance index (C-index), calibration curves, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA). Results 32,474 elderly SCC patients were included in the analysis, who were randomly assigned to training cohort (n = 22,732) and validation cohort (n = 9742). The following factors were contained in the final prognostic model: age, sex, race, marital status, tumor site, AJCC stage, surgery, radiation and chemotherapy. Compared to AJCC stage, the novel nomogram exhibited better performance: C-index (training group: 0.789 vs. 0.730, validation group: 0.791 vs. 0.733), the areas under the receiver operating characteristic curve of the training set (1-year AUC: 0.846 vs. 0.791, 3-year AUC: 0.860 vs. 0.801, 5-year AUC: 0.859 vs. 0.794) and the validation set (1-year AUC: 0.846 vs. 0.793, 3-year AUC: 0.863 vs. 0.806, 5-year AUC: 0.866 vs. 0.801), and the 1-, 3- and 5-year calibration plots. Additionally, the NRI and IDI and 1-, 3- and 5-year DCA curves all confirmed that the nomogram was a great prognosis tool. Conclusions We constructed a novel nomogram that could be practical and helpful for precise evaluation of elderly SCC patient prognosis, thus helping clinicians in determining the appropriate therapy strategies for individual SCC patients.

scholarly journals A nomogram model to predict death rate among non-small cell lung cancer (NSCLC) patients with surgery in Surveillance, Epidemiology, and End Results (SEER) database

2020 ◽  
Author(s):  
Bo Jia ◽  
Qiwen Zheng ◽  
Jingjing Wang ◽  
Hongyan Sun ◽  
Jun Zhao ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lymph Node ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Death Rate ◽  
Prognostic Model ◽  
Small Cell ◽  
Seer Database ◽  
Small Cell Lung ◽  
Nsclc Patients

Abstract Background This study aimed to establish a novel nomogram prognostic model to predict death probability for non-small cell lung cancer (NSCLC) patients who received surgery. Methods We collected data from the Surveillance, Epidemiology, and End Results (SEER) database of the National Cancer Institute in the United States. A nomogram prognostic model was constructed to predict mortality of NSCLC patients who received surgery. Results A total of 44,880 NSCLC patients who received surgery from 2004 to 2014 were included in this study. Gender, race, tumor anatomic sites, histologic subtype, tumor differentiation, clinical stage, tumor size, tumor extent, lymph node stage, examined lymph node, positive lymph node, type of surgery showed significant associations with lung cancer related death rate (P<0.001). Patients who received chemotherapy and radiotherapy had significant higher lung cancer related death rate but were associated with significant lower non-cancer related mortality (P<0.001). A nomogram model was established based on multivariate models of training data set. In the validation cohort, the unadjusted C-index was 0.73 (95% CI, 0.72-0.74), 0.71 (95% CI, 0.66-0.75) and 0.69 (95% CI, 0.68-0.70) for lung cancer related death, other cancer related death and non-cancer related death. Conclusions A prognostic nomogram model was constructed to predict death rate for NSCLC patients who received surgery. This novel prognostic model may be helpful for physicians to develop the most appropriate treatment strategies for resected NSCLC patients. Parts of these results were presented at the 2018 American Society of Clinical Oncology Annual Meeting (Abstract #8525)

scholarly journals Surgery Plus Chemotherapy Versus Surgery Alone for Limited-Stage Small-Cell Lung Cancer: A Population-Based Survival Outcome Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Pingting Ye ◽  
Zhuolin Guo ◽  
Yanfei Zhang ◽  
Chunyan Dong ◽  
Ming Li
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Survival Outcome ◽  
Small Cell ◽  
Stage I ◽  
Seer Database ◽  
Chemotherapy Treatment ◽  
Small Cell Lung ◽  
Ajcc Stage

IntroductionFor patients with limited-stage small-cell lung cancer (LS-SCLC), effective treatment methods still remain a clinical challenge. The aim of this study is to evaluate the survival outcome of surgery plus chemotherapy vs. surgery alone in patients with LS-SCLC.MethodsLS-SCLC patients selected from the Surveillance, Epidemiology and End Results (SEER) database diagnosed between January 1, 2004, and December 31, 2015. Comparison of overall survival (OS) and cancer-specific survival (CSS) between two groups performed propensity score matching (PSM), inverse probability of treatment weight (IPTW), and overlap weighting analysis.ResultsOf the 477 LS-SCLC patients identified from the SEER database between 2004 and 2015, 262 (54.9%) received surgery-plus-chemotherapy treatment and the others received surgery-alone treatment. Univariate and multivariate analyses showed that treatment option (P&lt; 0.001), tumor location (P= 0.02) and AJCC stage (P&lt; 0.001) were independent prognostic predictors of OS in LS-SCLC patients. Median OS was 35 months in surgery-plus-chemotherapy group vs. 23 months in surgery-alone group. Survival analysis showed that surgery plus chemotherapy offered significantly improved OS as compared with surgery-alone treatment before and after IPTW, PSM and overlap weighting method (all P&lt; 0.05). According to AJCC stage stratification, OS of the unmatched patients with stage I (P= 0.049) and II (P= 0.001) SCLC who received surgery-plus-chemotherapy treatment was significantly better than that of surgery-alone patients.ConclusionsThis cohort study showed that surgery plus chemotherapy was associated with longer survival time than surgery alone in LS-SCLC patients, especially in those with stage I and II SCLC. Further prospective studies are required to confirm our conclusions.

scholarly journals Development and validation of nomograms for predicting survival of elderly patients with stage I small-cell lung cancer

2021 ◽  
Author(s):  
Yaji Yang ◽  
Shusen Sun ◽  
Yuwei Wang ◽  
Feng Xiong ◽  
Yin Xiao ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Multivariate Analysis ◽  
Elderly Patients ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Stage I ◽  
Small Cell Lung ◽  
Predictive Tool ◽  
Ajcc Stage

There is a lack of predictive models to determine the prognosis of elderly patients diagnosed with stage I small-cell lung cancer (SCLC). The purpose of this study was to establish a useful nomogram to predict cancer-specific survival (CSS) in this patient population. Based on the Surveillance, Epidemiology, and End Results registry database, patients aged ≥ 65 years with pathological American Joint Committee on Cancer (AJCC) stage I SCLC from 2004 to 2014 were identified. The CSS was evaluated by the Kaplan-Meier method. Patients were randomly split into training and validation sets. In the training cohort, univariate analysis and multivariate analysis using the Cox regression identified risk factors that affected CSS. The results were utilized to construct a nomogram for the prediction of the 1-, 3-, and 5-year CSS rates of elderly patients with stage I SCLC. The effectiveness of the nomogram was validated internally and externally by the bootstrap method. The clinical practicability and accuracy of the nomogram were evaluated by the concordance index (C-index), calibration curve, receiver operating characteristic curve, and decision curve analysis. In total, we extracted 1,623 elderly patients with stage I SCLC. The median CSS was 34 months, and the 5-year CSS was 41%. Multivariate analysis revealed that histologic type, tumor size, age, and AJCC stage were significant predictors of CSS. A nomogram was constructed according to the results of multivariate Cox analysis. The C-indices of the nomogram for training and validation sets were 0.68 and 0.62, indicating that the nomogram demonstrated a favorable level of discrimination. The calibration curves exhibited satisfactory agreement between the actual observation and nomogram prediction. The net benefit of the nomogram was better than the AJCC TNM staging. We constructed a practical nomogram to predict the CSS of elderly patients with stage I SCLC. The predictive tool is helpful for patients counseling and treatment decision-making.

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