Dataset Information

A nomogram to predict prognosis in patients undergoing sublobar resection for stage IA non-small-cell lung cancer.

ABSTRACT:

Introduction

This study aimed to develop a practical nomogram to predict prognosis in patients who are undergoing sublobar resection for stage IA non-small-cell lung cancer (NSCLC). Data from Surveillance, Epidemiology, and End Results (SEER) databases were used to construct the nomogram.

Methods

Data from patients undergoing sublobar resection for stage IA NSCLC diagnosed between 2004 and 2014 were extracted from the SEER database. Factors that may predict the outcome were identified using the Kaplan-Meier method and the Cox proportional-hazards model. A nomogram was constructed to predict the 3- and 5-year overall survival (OS) and lung cancer-specific survival (LCSS) rates of these patients. The predictive accuracy of the nomogram was measured using the concordance index (C-index) and calibration curve.

Results

A total of 4,866 patients were selected for this study. Using univariate and multivariate analyses, eight independent prognostic factors associated with OS were identified, including sex (P<0.001), age (P<0.001), race (P=0.043), marital status (P=0.009), pathology (P=0.004), differentiation (P<0.001), tumor size (P<0.001), and surgery (P=0.001), and five independent prognostic factors associated with LCSS were also identified, including sex (P<0.001), age (P<0.001), differentiation (P<0.001), tumor size (P<0.001), and surgery (P=0.011). A nomogram was established based on these results and validated using the internal bootstrap resampling method. The C-index of the established nomogram for OS and LCSS was 0.649 (95% CI: 0.635-0.663) and 0.640 (95% CI: 0.622-0.658), respectively. The calibration curves for probability of 3-, and 5-year OS and LCSS rates demonstrated good agreement between the nomogram prediction and actual observation.

Conclusion

This innovative nomogram delivered a relatively accurate individual prognostic prediction for patients undergoing sublobar resection for stage IA NSCLC.

SUBMITTER: Yang H

PROVIDER: S-EPMC6284539 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A nomogram to predict prognosis in patients undergoing sublobar resection for stage IA non-small-cell lung cancer.

Yang Heli H Li Xiangdong X Shi Jialun J Fu Hao H Yang Hao H Liang Zhen Z Xiong Hongchao H Wang Hui H

Cancer management and research 20181204

<h4>Introduction</h4>This study aimed to develop a practical nomogram to predict prognosis in patients who are undergoing sublobar resection for stage IA non-small-cell lung cancer (NSCLC). Data from Surveillance, Epidemiology, and End Results (SEER) databases were used to construct the nomogram.<h4>Methods</h4>Data from patients undergoing sublobar resection for stage IA NSCLC diagnosed between 2004 and 2014 were extracted from the SEER database. Factors that may predict the outcome were identi ...[more]

PMID: 30584357

Similar Datasets

Project description:BackgroundThe increased detection of small-sized peripheral non-small-cell lung cancer (NSCLC) has renewed interest in sublobar resection in lieu of lobectomy.MethodsWe conducted a multicenter, noninferiority, phase 3 trial in which patients with NSCLC clinically staged as T1aN0 (tumor size, ≤2 cm) were randomly assigned to undergo sublobar resection or lobar resection after intraoperative confirmation of node-negative disease. The primary end point was disease-free survival, defined as the time between randomization and disease recurrence or death from any cause. Secondary end points were overall survival, locoregional and systemic recurrence, and pulmonary functions.ResultsFrom June 2007 through March 2017, a total of 697 patients were assigned to undergo sublobar resection (340 patients) or lobar resection (357 patients). After a median follow-up of 7 years, sublobar resection was noninferior to lobar resection for disease-free survival (hazard ratio for disease recurrence or death, 1.01; 90% confidence interval [CI], 0.83 to 1.24). In addition, overall survival after sublobar resection was similar to that after lobar resection (hazard ratio for death, 0.95; 95% CI, 0.72 to 1.26). The 5-year disease-free survival was 63.6% (95% CI, 57.9 to 68.8) after sublobar resection and 64.1% (95% CI, 58.5 to 69.0) after lobar resection. The 5-year overall survival was 80.3% (95% CI, 75.5 to 84.3) after sublobar resection and 78.9% (95% CI, 74.1 to 82.9) after lobar resection. No substantial difference was seen between the two groups in the incidence of locoregional or distant recurrence. At 6 months postoperatively, a between-group difference of 2 percentage points was measured in the median percentage of predicted forced expiratory volume in 1 second, favoring the sublobar-resection group.ConclusionsIn patients with peripheral NSCLC with a tumor size of 2 cm or less and pathologically confirmed node-negative disease in the hilar and mediastinal lymph nodes, sublobar resection was not inferior to lobectomy with respect to disease-free survival. Overall survival was similar with the two procedures. (Funded by the National Cancer Institute and others; CALGB 140503 ClinicalTrials.gov number, NCT00499330.).

Project description:The incidence of early-stage non-small cell lung cancer (NSCLC) among the elderly is expected to rise dramatically owing to demographic trends and increased computed tomographic screening. However, to our knowledge, no modern trials have compared the most common treatments for NSCLC.To determine clinical characteristics and survival outcomes associated with the 3 most commonly used definitive therapies for early-stage NSCLC in the elderly.The Surveillance, Epidemiology, and End Results database linked to Medicare was used to determine the baseline characteristics and outcomes of 9093 patients with early-stage, node-negative NSCLC who underwent definitive treatment consisting of lobectomy, sublobar resection, or stereotactic ablative radiotherapy (SABR) from January 1, 2003, through December 31, 2009.Overall and lung cancer-specific survival were compared using Medicare claims through December 31, 2012. We used proportional hazards regression and propensity score matching to adjust outcomes for key patient, tumor, and practice environment factors.The median age was 75 years, and treatment distribution was 79.3% for lobectomy, 16.5% for sublobar resection, and 4.2% for SABR. Unadjusted 90-day mortality was highest for lobectomy (4.0%) followed by sublobar resection (3.7%; P = .79) and SABR (1.3%; P = .008). At 3 years, unadjusted mortality was lowest for lobectomy (25.0%), followed by sublobar resection (35.3%; P < .001) and SABR (45.1%; P < .001). Proportional hazards regression demonstrated that sublobar resection was associated with worse overall survival (adjusted hazard ratio [AHR], 1.32 [95% CI, 1.20-1.44]; P < .001) and lung cancer-specific survival (AHR, 1.50 [95% CI, 1.29-1.75]; P < .001) compared with lobectomy. Propensity score-matching analysis reiterated these findings for overall survival (AHR, 1.36 [95% CI, 1.17-1.58]; P < .001) and lung cancer-specific survival (AHR, 1.46 [95% CI, 1.13-1.90]; P = .004). In proportional hazards regression, SABR was associated with better overall survival than lobectomy in the first 6 months after diagnosis (AHR, 0.45 [95% CI, 0.27-0.75]; P < .001) but worse survival thereafter (AHR, 1.66 [95% CI, 1.39-1.99]; P < .001). Propensity score-matching analysis of well-matched SABR and lobectomy cohorts demonstrated similar overall survival in both groups (AHR, 1.01 [95% CI, 0.74-1.38]; P = .94).Lobectomy was associated with better outcomes than sublobar resection in elderly patients with early-stage NSCLC. Propensity score matching suggests that SABR may be a good option among patients with very advanced age and multiple comorbidities.

Project description:BackgroundThymomas and thymic carcinoma are thymic epithelial tumors (TETs) of the anterior mediastinum. On the basis of The AJCC 8th Edition of TNM classification, no prognostic prediction model has been established for TETs patients undergoing surgical resection. In this study, based on data from Qilu Hospital of Shandong University, we identified prognostic factors and developed a nomogram to predict the prognosis for TETs patients undergoing extended thymectomy.MethodsPatients with TETs who underwent thymectomy between 2010 and 2020 were consecutively enrolled. An analysis of multivariate Cox regression and stepwise regression using the Akaike information criterion (AIC) was conducted to identify prognostic factors, and a nomogram for TETs was derived from the results of these analyses. The model was validated internally with the Kaplan-Meier curves, ROC curves and calibration curves.ResultsThere were 350 patients with TETs enrolled in the study, and they were divided into a training group (245,0.7) and a validation group (105,0.3). Age, histological type, tumor size, myasthenia gravis, and TNM stage were independent prognostic factors for CSS. The Kaplan-Meier curves showed a significant difference between high nomorisk group and low nomorisk group. A nomogram for CSS was formulated based on the independent prognostic factors and exhibited good discriminative ability as a means of predicting cause-specific mortality, as evidenced by the area under the ROC curves (AUCs) of 3-year, 5-year, and 10-year being 0.946, 0.949, and 0.937, respectively. The calibration curves further revealed excellent consistency between the predicted and actual mortality when using this nomogram.ConclusionThere are several prognostic factors for TETs. Based on TNM stage and other prognostic factors, the nomogram accurately predicted the 3-, 5-, and 10-year mortality rates of patients with TETs in this study. The nomogram could be used to stratify risk and optimize therapy for individual patients.

Project description:BackgroundTo investigate the differences in survival between lobectomy and sub-lobar resection for elderly stage I non-small-cell lung cancer (NSCLC) patients using the Surveillance, Epidemiology, and End Results (SEER) registry.MethodThe data of stage IA elderly NSCLC patients (≥ 70 years) with tumors less than or equal to 3 cm in diameter were extracted. Propensity-matched analysis was used. Lung cancer-specific survival (LCSS) was compared among the patients after lobectomy and sub-lobar resection. The proportional hazards model was applied to identify multiple prognostic factors.ResultsA total of 3,504 patients met criteria after propensity score matching (PSM). Although the LCSS was better for lobectomy than for sub-lobar resection in patients with tumors ≤ 3 cm before PSM (p < 0.001), no significant difference in the LCSS was identified between the two treatment groups after PSM (p = 0.191). Multivariate Cox regression showed the elder age, male gender, squamous cell carcinoma (SQC) histology type, poor/undifferentiated grade and a large tumor size were associated with poor LCSS. The subgroup analysis of tumor sizes, histologic types and lymph nodes (LNs) dissection, there were also no significant difference for LCSS between lobectomy and sub-lobar resection. The sub-lobar resection was further divided into segmentectomy or wedge resection, and it demonstrated that no significant differences in LCSS were identified among the treatment subgroups either. Multivariate Cox regression analysis showed that the elder age, poor/undifferentiated grade and a large tumor size were a statistically significant independent factor associated with survival.ConclusionIn terms of LCSS, lobectomy has no significant advantage over sub-lobar resection in elderly patients with stage IA NSCLC if lymph node assessment is performed adequately. The present data may contribute to develop a more suitable surgical treatment strategy for the stage IA elderly NSCLC patients.

Dataset Information

A nomogram to predict prognosis in patients undergoing sublobar resection for stage IA non-small-cell lung cancer.

Introduction

Methods

Results

Conclusion

Publications

A nomogram to predict prognosis in patients undergoing sublobar resection for stage IA non-small-cell lung cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets