Unresected small lymph node assessment predicts prognosis for patients with pT3N0M0 thoracic esophageal squamous cell carcinoma

Effect of different surgical approaches on the prognosis of patients with postoperative radiotherapy for stage IIB-IVA esophageal squamous cancer

Objective

To investigate the effect and clinical significance of different thoracic surgical approaches for patients with stage IIB–IVA esophageal squamous cell carcinoma on the survival and prognosis of postoperative radiotherapy patients.

Methods

One hundred thirty-two patients with stage IIB–IVA esophageal squamous cancer who received radiotherapy after surgery were screened for baseline characteristics and survival analysis. The Kaplan-Meier method was used to draw the survival curve for the follow-up data, and the log-rank test was used to compare the difference in survival rate between the two groups. The Cox regression model was used for multivariate survival analysis.

Result

For stage IIB–IVA esophageal squamous cell carcinoma, the results of multivariate analysis showed that different surgical methods and clinical staging were independent factors affecting the survival and prognosis of patients after radiotherapy. The 1-, 3-, and 5-year survival rates of patients with advanced esophageal cancer through the left chest approach were 84.2%, 61.4%, and 36.8% respectively. The 1-, 3-, and 5-year survival rates of patients with advanced esophageal cancer through the right chest approach were 73.3%, 40.0%, and 21.3% respectively. There was no significant difference in the 1-year survival rate (P = 0.135) between the two surgical procedures. The 3-year survival rate (P < 0.05) and the 5-year survival rate (P < 0.05) were significantly different.

Conclusion

For patients with stage IIB–IVA esophageal squamous cell carcinoma undergoing radiotherapy after surgery, the long-term survival prognosis of patients after the left thoracic approach is significantly higher than that of the right thoracic approach.

Sex differences in cancer-specific survival for locally advanced esophageal cancer after neoadjuvant chemoradiotherapy: A population-based analysis

Objective

Neoadjuvant chemoradiotherapy (nCRT) is the recommended standard treatment for locally advanced esophageal cancer (LA-EC). This study aimed to determine whether sex makes a difference in cancer-specific survival (CSS) and construct a novel nomogram model to predict CSS for LA-EC after nCRT based on the SEER database.

Methods

Patients coded by 04–15 were identified from the SEER database. Patients with systemic treatment and radiotherapy before surgery were defined as nCRT. We further divided this population into a training group and a verification group at a ratio of 7:3. Univariate and multivariate cox analyses were applied to determine the prognostic risk factors based on the training cohort, and then the Nomogram model was established. The area under the curve (AUC) was used to evaluate the predictive ability of the model. We used the calibration curve to evaluate the consistency between the predicted status and actual status and decision curve analysis (DCA) to evaluate the clinical value. We used X-tile software to determine the best cut-off value of nomogram scores and divided the population into low-risk, medium-risk, and high-risk groups, and Kaplan-Meier analysis was applied to compare the CSS.

Results

A total of 2096 LA-EC patients were included for further analysis, with 1,540 in the training cohort and 656 in the validation group. Male (HR: 1.29, 95% CI, 1.04 −1.58), T stage, N stage, and M stage were identified as independent risk factors of CSS based on the training cohort. A Nomogram model was constructed to predict the 3-, 5- and 7-years CSS. ROC curve and AUC confirmed that this nomogram has median discrimination ability. The calibration curve showed good agreement between predicted status and actual status. The DCA curves confirmed the clinical value. Kaplan-Meier analysis indicated that patients in the high-risk subgroup had poorer CSS in both the training cohort and validation cohort (P < 0.001).

Conclusion

Male patients had poorer CSS in LA-EC patients after nCRT. A nomogram model composed of sex, T stage, N stage, and M stage was constructed to identify the high-risk population and provide a personalized follow-up plan.

Prognostic Nomogram for Predicting Long-Term Overall Survival of Esophageal Cancer Patients Receiving Neoadjuvant Chemoradiotherapy Plus Surgery: A Population-Based Study

Objective

Neoadjuvant chemoradiotherapy (nCRT) plays an important role in patients with locally advanced esophageal cancer (EC). We aim to determine the prognostic risk factors and establish a reliable nomogram to predict overall survival (OS) based on SEER population.

Methods

Patients with EC coded by 04–15 in the SEER database were included. The data were divided into training group and verification group (7:3). The Cox proportional-risk model was evaluated by using the working characteristic curve (receiver operating characteristic curve, ROC) and the area under the curve (AUC), and a nomogram was constructed. The calibration curve was used to measure the consistency between the predicted and the actual results. Decision curve analysis (DCA) was used to evaluate its clinical value. The best cut-off value of nomogram score in OS was determined by using X-tile software, and the patients were divided into low-risk, medium-risk, and high-risk groups.

Results

A total of 2,209 EC patients who underwent nCRT were included in further analysis, including 1,549 in the training cohort and 660 in the validation group. By Cox analysis, sex, marital status, T stage, N stage, M stage, and pathological grade were identified as risk factors. A nomogram survival prediction model was established to predict the 36-, 60-, and 84-month survival. The ROC curve and AUC showed that the model had good discrimination ability. The correction curve was in good agreement with the prediction results. DCA further proved the effective clinical value of the nomogram model. The results of X-tile analysis showed that the long-term prognosis of patients in the low-risk subgroup was better in the training cohort and the validation cohort (p &lt; 0.001).

Conclusion

This study established an easy-to-use nomogram risk prediction model consisting of independent prognostic factors in EC patients receiving nCRT, helping to stratify risk, identify high-risk patients, and provide personalized treatment options.