Conditional Survival of Patients with Limited-Stage Small Cell Lung Cancer After Surgery: A National Real-World Cohort Study.

BACKGROUND: The prognosis of limited-stage small cell lung cancer (LS-SCLC) after surgery usually is estimated at diagnosis, but how the prognosis actually evolves over time for patients who survived for a predefined time is unknown. METHODS: Data on patients with a diagnosis of LS-SCLC after surgery between 2004 and 2015 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. The 5-year conditional cancer-specific survival (CCSS) and conditional overall survival (COS) were calculated. RESULTS: This study analyzed 997 patients (555 women, 55.7%) with a median age, of 67 years (interquartile range [IQR], 60-73 years). The 5-year CCSS and COS increased from 44.7% and 38.3%, respectively, at diagnosis to 83.7% and 67.9% at 5 years after diagnosis. Although there were large differences with different stages (stages I, II, and III) at diagnosis (respectively 59.5%, 28.4%; 28.1% for CCSS and 50.6%, 24.8%, and 23.6% for COS), the gap decreased with time, and the rates were similar after 5 years (respectively 85.0%, 80.3%, and 79.4% for CCSS; 65.6%, 56.9%, and 61.3% for COS). The 5-year conditional survival for the patients who received lobectomy was better than for those who received sublobectomy or pneumonectomy. Multivariable analyses showed that only age and resection type were independent predictors for CCSS and COS, respectively, throughout the period. CONCLUSION: Conditional survival estimates for LS-SCLC generally increased over time, with the most significant improvement in patients with advanced stage of disease. Resection type and old age represented extremely important determinants of prognosis after a lengthy event-free follow-up period.

The association between histological subtypes and lymph node metastasis and prognosis in early esophageal cancer: a population-based study.

BACKGROUND: There is still a lack of high-level clinical evidence and uniform conclusions on whether there are differences in lymph node metastasis (LNM) and prognosis between early esophageal adenocarcinoma (EAC) and squamous cell carcinoma (ESCC). METHODS: Patients with surgically resected, histologically diagnosed, pT1 EAC or ESCC in the Surveillance, Epidemiology and End Results registries database from 2004 to 2015 were included. Multivariable logistic regression, Cox regression, multivariate competing risk model, and propensity score matching were used to analyze association the histology and LNM or prognosis. RESULTS: A total of 570 early esophageal cancer patients were included. The LNM rates were 13.8% and 15.1% for EAC and ESCC ( P  = 0.757), respectively. Multivariate logistic regression analysis showed no significant association between histological type and LNM (odds ratio [OR], 1.209; 95% CI, 0.538-2.715; P  = 0.646). Moreover, the prognosis of early EAC and ESCC was shown to be comparable in both multivariate Cox regression (hazard ratio [HR], 1.483; 95% CI, 0.699-3.150; P  = 0.305) and the multivariate competing risk model (subdistribution HR, 1.451; 95% CI, 0.628-3.354; P  = 0.383). After propensity score matching, there were no significant differences between early EAC and ESCC in terms of LNM (10.6% vs.18.2%, P  = 0.215), 5-year CSS (89.8% [95% CI, 81.0%-98.6%] vs. 79.1% [95% CI, 67.9%-90.3%], P  = 0.102) and 5-year cumulative incidence of CSS (10.2% [95% CI, 1.4%-19.0%] vs. 79.1% [95% CI, 9.7%-32.1%], P  = 0.124). CONCLUSION: The risk of LNM and prognosis of early ESCC and EAC are comparable, so the treatment choice for early esophageal cancer does not depend on the histologic type.

Construction and validation of a risk-scoring model to predict lymph node metastasis in T1b-T2 esophageal cancer.

BACKGROUND: Lymph node status is an important factor in determining preoperative treatment strategies for stage T1b-T2 esophageal cancer (EC). Thus, the aim of this study was to investigate the risk factors for lymph node metastasis (LNM) in T1b-T2 EC and to establish and validate a risk-scoring model to guide the selection of optimal treatment options. METHODS: Patients who underwent upfront surgery for pT1b-T2 EC between January 2016 and December 2022 were analyzed. On the basis of the independent risk factors determined by multivariate logistic regression analysis, a risk-scoring model for the prediction of LNM was constructed and then validated. The area under the receiver operating characteristic curve (AUC) was used to assess the discriminant ability of the model. RESULTS: The incidence of LNM was 33.5% (214/638) in our cohort, 33.4% (169/506) in the primary cohort and 34.1% (45/132) in the validation cohort. Multivariate analysis confirmed that primary site, tumor grade, tumor size, depth, and lymphovascular invasion were independent risk factors for LNM (all P < 0.05), and patients were grouped based on these factors. A 7-point risk-scoring model based on these variables had good predictive accuracy in both the primary cohort (AUC, 0.749; 95% confidence interval 0.709-0.786) and the validation cohort (AUC, 0.738; 95% confidence interval 0.655-0.811). CONCLUSION: A novel risk-scoring model for lymph node metastasis was established to guide the optimal treatment of patients with T1b-T2 EC.