scholarly journals Development and Validation of a Nomogram Prognostic Model for Resected Limited-Stage Small Cell Lung Cancer Patients

2021 ◽  
Author(s):  
Qingpeng Zeng ◽  
Jiagen Li ◽  
Fengwei Tan ◽  
Nan Sun ◽  
Yousheng Mao ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Prognostic Factors ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Calibration Curve ◽  
Validation Cohort ◽  
Small Cell ◽  
Small Cell Lung ◽  
Training Cohort ◽  
Limited Stage

Abstract Background In this study, we developed and validated nomograms for predicting the survival in surgically resected limited-stage small cell lung cancer (SCLC) patients. Methods The SCLC patients extracted from the Surveillance, Epidemiology, and End Results database between 2000 and 2014 were reviewed. Significant prognostic factors were identified and integrated to develop the nomogram using multivariable Cox regression. The model was then validated internally by bootstrap resampling, and externally using an independent SCLC cohort diagnosed between 2000 and 2015 at our institution. The prognostic performance was measured by the concordance index (C-index) and calibration curve. Results A total of 1006 resected limited-stage SCLC patients were included in the training cohort. Overall, 444 cases from our institution constituted the validation cohort. Seven prognostic factors were identified and entered into the nomogram construction. The C-indexes of this model in the training cohort were 0.723, 0.722, and 0.746 for predicting 1-, 3-, and 5-year overall survival (OS), respectively, and 0.816, 0.710, and 0.693, respectively, in the validation cohort. The calibration curve showed optimal agreement between nomogram-predicted survival and actual observed survival. Additionally, significant distinctions in survival curves between different risk groups stratified by prognostic scores were also observed. The proposed nomogram was then deployed into a website server for convenient application. Conclusions We developed and validated novel nomograms for individual prediction of survival for resected limited-stage SCLC patients. These models perform better than the previously widely used staging system and may offer clinicians instructions for strategy making and the design of clinical trials.

Outcome of patients with small-cell lung cancer: effect of changes in staging procedures and imaging technology on prognostic factors over 14 years.

1990 ◽  
Vol 8 (6) ◽  
pp. 1042-1049 ◽  
Author(s):  
M P Dearing ◽  
S M Steinberg ◽  
R Phelps ◽  
M J Anderson ◽  
J L Mulshine ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Prognostic Factors ◽  
Brain Metastases ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Cox Proportional Hazards ◽  
Small Cell ◽  
Small Cell Lung ◽  
Limited Stage ◽  
The Impact

In a study of 411 patients with small-cell lung cancer (SCLC) entered on therapeutic clinical trials between 1973 and 1987, we analyzed whether changes in the prognostic importance of pretreatment factors had occurred during the 14-year time period. After adjusting for other prognostic factors, brain involvement was associated with shorter survival in patients treated before December 1979 (P = .024) but not in patients treated thereafter (P = .54). The patients diagnosed before 1979 had brain metastases documented by radionuclide scan while computed cranial tomography (CCT) was more commonly used after 1979. Patients who had brain metastases diagnosed by radionuclide scan lived a shorter period of time than patients who had the diagnosis made by the more sensitive CCT scan (P = .031). In contrast, Cox proportional hazards modeling showed that liver metastases in patients were associated with shorter survival in patients treated after 1979 (P = .0007) but not in patients treated before then (P = .30). A larger proportion of patients had a routine liver biopsy before 1979 than after 1979 when more patients had the liver staged with less sensitive imaging studies and biochemical parameters. Patients with SCLC whose cancer was confined to the thorax but had medical or anatomic contraindications to intensive chest radiotherapy had similar survival compared with patients with limited-stage SCLC who were treated with combination chemotherapy alone (P = .68). From these data we conclude: (1) the sensitivity of the staging procedures used can affect the impact on survival of cancer involvement of a given site; and (2) patients with cancer confined to their chest with medical or anatomic contraindications to chest radiotherapy do not have a shorter survival than patients with limited-stage disease treated with chemotherapy alone.

scholarly journals Prognostic Value of Germline Copy Number Variants and Environmental Exposures in Non-small Cell Lung Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Shizhen Chen ◽  
Liming Lu ◽  
Jianfeng Xian ◽  
Changhong Shi ◽  
Jinbin Chen ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Copy Number ◽  
Chinese Population ◽  
Validation Cohort ◽  
Small Cell ◽  
Polygenic Risk Score ◽  
Small Cell Lung ◽  
Training Cohort

Germline copy number variant (gCNV) has been studied as a genetic determinant for prognosis of several types of cancer, but little is known about how it affects non-small cell lung cancer (NSCLC) prognosis. We aimed to develop a prognostic nomogram for NSCLC based on gCNVs. Promising gCNVs that are associated with overall survival (OS) of NSCLC were sorted by analyzing the TCGA data and were validated in a small Chinese population. Then the successfully verified gCNVs were determined in a training cohort (n = 570) to develop a prognostic nomogram, and in a validation cohort (n = 465) to validate the nomogram. Thirty-five OS-related gCNVs were sorted and were reduced to 15 predictors by the Lasso regression analysis. Of them, only CNVR395.1 and CNVR2239.1 were confirmed to be associated with OS of NSCLC in the Chinese population. High polygenic risk score (PRS), which was calculated by the hazard effects of CNVR395.1 and CNVR2239.1, exerted a significantly higher death rate in the training cohort (HR = 1.41, 95%CI: 1.16–1.74) and validation cohort (HR = 1.42, 95%CI: 1.13–1.77) than low PRS. The nomogram incorporating PRS and surrounding factors, achieved admissible concordance indexes of 0.678 (95%CI: 0.664–0.693) and 0.686 (95%CI: 0.670–0.702) in predicting OS in the training and validation cohorts, respectively, and had well-fitted calibration curves. Moreover, an interaction between PRS and asbestos exposure was observed on affecting OS (Pinteraction = 0.042). Our analysis developed a nomogram that achieved an admissible prediction of NSCLC survival, which would be beneficial to the personalized intervention of NSCLC.

Limited Stage Small Cell Lung Cancer: Analysis of Clinical Prognostic Factors

1987 ◽  
Vol 80 (12) ◽  
pp. 1518-1522 ◽  
Author(s):  
JOHN D. HAINSWORTH ◽  
DAVID H. JOHNSON ◽  
ROBERT V. FARESE ◽  
JODY W. MACEY ◽  
WILLIAM K. VAUGHN ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Prognostic Factors ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung ◽  
Limited Stage

scholarly journals CT-Based Sarcopenic Nomogram for Predicting Progressive Disease in Advanced Non-Small-Cell Lung Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Xiaoping Yi ◽  
Qiurong Chen ◽  
Jingying Yang ◽  
Dengke Jiang ◽  
Liping Zhu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Progressive Disease ◽  
Validation Cohort ◽  
Small Cell ◽  
Small Cell Lung ◽  
Skeletal Muscle Index ◽  
Training Cohort ◽  
Platinum Based Chemotherapy

BackgroundIt is prudent to identify the risk for progressive disease (PD) in patients with non-small-cell lung cancer (NSCLC) who undergo platinum-based chemotherapy. The present study aimed to develop a CT imaging-based sarcopenic nomogram for predicting the risk of PD prior to chemotherapy treatment.MethodsWe retrospectively enrolled patients with NSCLC who underwent platinum-based chemotherapy. Imaging-based body composition parameters such as skeletal muscle index (SMI) for assessment of sarcopenia were obtained from pre-chemotherapy chest CT images at the level of the eleventh thoracic vertebral body (T11). Sarcopenic nomogram was constructed using multivariate logistic regression and performance of the nomogram was evaluated by discrimination, calibration curve, and decision curve.ResultsSixty (14.7%) of the 408 patients in the study cohort developed PD during chemotherapy. The prediction nomogram for developing PD achieved a moderate efficiency with an area under the curve (AUC) of 0.75 (95% CI: 0.69-0.80) for the training cohort, and 0.76 (95%CI: 0.68-0.84) for the validation cohort, as well as a good performance of consistence (bootstrap for training cohort: 0.75 ± 0.02; validation cohort: 0.74 ± 0.06). Favorable clinical application was observed in the decision curve analysis.ConclusionOur CT-based sarcopenic nomogram showed the potential for an individualized prediction of progression for patients with NSCLC receiving platinum-based chemotherapy.

scholarly journals Survival and prognostic factors in limited stage small cell lung cancer: A retrospective study from northeast Turkey

2016 ◽  
Vol 12 (1) ◽  
pp. 238
Author(s):  
Özlem Aynaci ◽  
Emine Canyilmaz ◽  
Lasif Serdar ◽  
Mustafa Kandaz ◽  
Zümrüt Bahat ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Prognostic Factors ◽  
Retrospective Study ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung ◽  
Limited Stage

scholarly journals Clinical impact of post-progression survival on overall survival in patients with limited-stage disease small cell lung cancer after first-line chemoradiotherapy

2015 ◽  
Vol 49 (4) ◽  
pp. 409-415 ◽  
Author(s):  
Norimitsu Kasahara ◽  
Hisao Imai ◽  
Kyoichi Kaira ◽  
Keita Mori ◽  
Kazushige Wakuda ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Overall Survival ◽  
Prognostic Factors ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung ◽  
First Line ◽  
Limited Stage ◽  
Stage Disease

Abstract Background. The effects of first-line chemoradiotherapy on overall survival (OS) may be confounded by subsequent lines of therapy in patients with limited-stage disease small cell lung cancer (LD-SCLC). Therefore, we aimed to determine the relationships between progression-free survival (PFS), post-progression survival (PPS) and OS after first-line chemoradiotherapy in LD-SCLC patients. Patients and methods. We retrospectively analyzed 71 LD-SCLC patients with performance status (PS) 0-2 who received first-line chemoradiotherapy and had disease recurrence between September 2002 and March 2013 at Shizuoka Cancer Center (Shizuoka, Japan). We determined the correlation between PFS and OS and between PPS and OS at the individual level. In addition, we performed univariate and multivariate analyses to identify significant prognostic factors of PPS. Results. OS is more strongly correlated with PPS (Spearman’s r = 0.86, R2 = 0.72, p < 0.05) than PFS (Spearman’s r = 0.46, R2 = 0.38, p < 0.05). In addition, the response to second-line treatments, the presence of distant metastases at recurrence and the number of additional regimens after first-line chemoradiotherapy were significant independent prognostic factors for PPS. Conclusions. PPS has more impact on OS than PFS in recurrent LD-SCLC patients with good PS at beginning of the treatment. Moreover, treatments administered after first-line chemoradiotherapy may affect their OS. However, larger multicenter studies are needed to validate these findings.

scholarly journals A risk score-matched model analysis of 4,452 patients with small cell lung cancer: who will benefit from operative treatment

2020 ◽  
Author(s):  
Shuzhen Tan ◽  
Ying Kong ◽  
Shuilong Leng ◽  
Xiao Zhu
Keyword(s):  
Lung Cancer ◽  
Prognostic Factors ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Cox Regression ◽  
Small Cell ◽  
Risk Scores ◽  
Small Cell Lung ◽  
Training Cohort ◽  
Calibration Algorithm

Abstract Purpose: Small-cell lung cancer (SCLC) is difficult to cure. In this study, the SEER database was used to construct a model and explore the potential prognostic factors of SCLC patients. Methods: The data were sorted out and randomly divided into training cohort and verification cohort. Univariate and multivariate Cox regression were used in the training cohort to analyze the independent prognostic factors, then they be incorporated into the Nomogram model. Using the C-index, calibration algorithm and ROC in conjunction with the risk scores, the model was verified with the verification cohort. Finally, the overall survivals of those factors were evaluated in the total cases.Results: In the training cohort, we found that age, race, sex, total stage and extension were independent factors which were included in the Nomogram model. C-index(s) that obtained from the training and verification cohorts showed that the model has predictive power. Moreover, the calibration curves and AUC results proved that the model is of great consistency not only in the training cohort but also in the verification cohort. Finally, significant differences in survival were observed among the above-mentioned factors and the overall survivals decreased over time.Conclusions: Age, race, sex, total stage and extension degree are independent risk factors for overall survival of patients. The Nomogram model can better predict the 1-year, 3-year and 5-year survival probabilities, providing accurate reference for clinical individualized treatment.

A nomogram model assessing prognostic factors in patients with chemo/radiotherapy of small-cell lung cancer

2020 ◽  
Author(s):  
Shuzhen Tan ◽  
Yongmei Huang ◽  
Ying Kong ◽  
Ming Zhang ◽  
Shuilong Leng ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Prognostic Factors ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Cox Regression ◽  
Small Cell ◽  
Risk Scores ◽  
Small Cell Lung ◽  
Training Cohort ◽  
Calibration Algorithm

Abstract Background: Small-cell lung cancer (SCLC) is difficult to cure. In this study, the SEER database was used to construct a nomogram model and explore the potential prognostic factors of SCLC patients who treated with chemo/radiotherapy. Methods: The data were sorted out and randomly divided into training cohort and verification cohort. Univariate and multivariate Cox regression were used in the training cohort to analyze the independent prognostic factors, then they be incorporated into the Nomogram model. Using the C-index, calibration algorithm and ROC in conjunction with the risk scores, the model was verified with the verification cohort. Finally, the overall survivals of those factors were evaluated in the total cases.Results: In the training cohort, we found that age, race, sex, total stage and extension were independent factors which were included in the nomogram model. C-index(s) that obtained from the training and verification cohorts showed that the model has predictive power. Moreover, the calibration curves and AUC results proved that the model is of great consistency not only in the training cohort but also in the verification cohort. Finally, significant differences in survival were observed among the above-mentioned factors and the overall survivals decreased over time.Conclusions: Age, race, sex, total stage and extension degree are independent factors for overall survival of patients. The nomogram model can better predict the 1-year, 3-year and 5-year survival probabilities, providing accurate reference for clinical individualized treatment.

Sign in / Sign up

Export Citation Format

Share Document