Nomograms for predicting survival in early-onset esophageal cancer

Comparison of postoperative survival between early-onset and late-onset adenocarcinoma of esophagogastric junction: a population-based study

BACKGROUND AND AIM

The prognosis of early-onset adenocarcinoma of esophagogastric junction (AEG) remains unclear. This research aimed at comparing the prognosis between early-onset and late-onset AEGs.

METHODS

We extracted eligible patients with surgically resected, pathologically confirmed, nonmetastatic AEG from the Surveillance, Epidemiology, and End Results database from 2004 to 2015. The cutoff age of early-onset AEG was set at ≤50 years old. Univariate and multivariate Cox analysis as well as competing risk model were adopted for comparing overall survival (OS) and cancer-specific survival (CSS) between early-onset and late-onset AEGs. In addition, multiple imputation and propensity score matching (PSM) were also carried out for sensitivity analysis.

RESULTS

In total, 4610 eligible AEG patients were collected in this study, including 610 early-onset AEGs and 4000 late-onset AEGs. Kaplan-Meier curves revealed significantly better survival in early-onset AEGs than late-onset AEGs. After interpolating missing data by multiple imputation, multivariate Cox regression analysis similarly showed better OS and CSS in early-onset AEGs. By using PSM analysis at a ratio of 1:1, we matched 610 early-onset AEG patients with 610 late-onset AEG patients. After PSM, univariate Cox regression model still revealed favorable prognosis in early-onset AEGs. Similar results were confirmed by performing PSM analysis at a ratio of 1:2 and 1:3. In addition, competing risk model demonstrated significantly lower cancer-specific death in early-onset AEGs compared to late-onset AEGs before and after matching.

CONCLUSION

By applying several effective sensitivity analyses, we reported significantly favorable OS and CSS in early-onset AEGs compared to late-onset AEGs.

Surgery and postoperative radiotherapy affect the prognosis of esophageal cancer: A SEER analysis

The principal treatment modalities for esophageal cancer are radiation, chemotherapy and surgery or a combination of them. In some sense, technological advances have tremendously heightened patients' survival rates. Nevertheless, the debate on the prognostic value of postoperative radiotherapy (PORT) has never ceased. On that account, this study made an effort to probe deep into the effects of PORT and surgery on the prognosis of stage III esophageal cancer. Our study included patients diagnosed with stage III esophageal cancer between 2004 and 2015 through the Surveillance, Epidemiology, and End Results (SEER) program. We performed propensity score matching (PSM) on the basis of whether surgery was carried out and whether PORT conducted. We identified the independent risk factors by multivariate Cox regression and constructed a nomogram model. In this research, we included 3940 patients, and the median follow-up is 14 months: 1932 cases without surgery; 2008 cases with surgery, and 322 cases of them underwent PORT. In the postPSM patient cohort, patients who underwent surgery had a median overall survival rate (OS) of 19.0 (95% confidence interval [CI] 17.2-20.8) and a median cancer-specific survival rate (CSS) of 23.0 (95% CI 20.6-25.3) months, which were remarkably higher than those without surgery (P < .001). The OS（P < .05）and CSS（P < .05）of the patients who underwent PORT were lower than those who did not. Similar results were obtained in the groups of N0 and N1. This study revealed surgery can heighten patients' survival rate, while PORT could not elevate patients' survival rate in stage III esophageal cancer patients.

Influence of adverse effects of neoadjuvant chemoradiotherapy on the prognosis of patients with early-stage esophageal cancer (cT1b-cT2N0M0) based on the SEER database

Objective

To analyze the prognostic impact of neoadjuvant chemoradiotherapy (NCRT) on early-stage (cT1b-cT2N0M0) esophageal cancer (ESCA) and construct a prognostic nomogram for these patients.

Methods

We extracted the clinical data about patients diagnosed with early-stage esophageal cancer from the 2004-2015 period of the Surveillance, Epidemiology, and End Results (SEER) database. We applied the independent risk factors affecting the prognosis of patients with early-stage esophageal cancer obtained after screening by univariate and multifactorial COX regression analyses to establish the nomogram and performed model calibration using bootstrapping resamples. The optimal cut-off point for continuous variables is determined by applying X-tile software. After balancing the confounding factors by propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) method, Kaplan-Meier(K-M) curve, and log-rank test were applied to evaluate the prognostic impact of NCRT on early-stage ESCA patients.

Results

Among patients who met the inclusion criteria, patients in the NCRT plus esophagectomy (ES) group had a poorer prognosis for overall survival (OS) and esophageal cancer-specific survival (ECSS) than patients in the ES alone group (p < 0.05), especially in patients who survived longer than 1 year. After PSM, patients in the NCRT + ES group had poorer ECSS than patients in the ES alone group, especially after 6 months, while OS was not significantly different between the two groups. IPTW analysis showed that, prior to 6 months patients in the NCRT + ES group had a better prognosis than patients in the ES group, regardless of OS or ECSS, whereas after 6 months, patients in the NCRT + ES group had a poorer prognosis. Based on multivariate COX analysis, we established a prognostic nomogram which showed areas under the ROC curve (AUC) for 3-, 5-, and 10-year OS 0.707, 0.712, and 0.706, respectively, with the calibration curves showing that the nomogram was well calibrated.

Conclusions

Patients with early-stage ESCA (cT1b-cT2) did not benefit from NCRT, and we established a prognostic nomogram to provide clinical decision aid for the treatment of patients with early-stage ESCA.

The Evaluation of a SEER-Based Nomogram in Predicting the Survival of Patients Treated with Neoadjuvant Therapy Followed by Esophagectomy

Background

A novel nomogram based on the Surveillance, Epidemiology, and End Results (SEER) database has been developed to predict the survival of patients with esophageal carcinoma who received neoadjuvant therapy followed by surgery. We aimed to evaluate the accuracy and value of the nomogram with an external validation cohort.

Methods

A total of 2,224 patients in SEER database were divided into the training cohort (n = 1556) and the internal validation cohort (n = 668), while 77 patients in our institute were enrolled in the external validation cohort. A Cox proportional hazards regression model was used to develop a nomogram based on the training cohort, while the C-indexes, the calibration curves, receiver operating characteristics curve (ROC), and Kaplan-Meier survival curve were applied in the internal and external validation cohort.

Results

Five independent risk factors were identified and integrated into the nomogram (C-index = 0.645, 95%CI 0.627–0.663). The nomogram exhibited good prognostic value in the internal validation cohort (C-index = 0.648 95%CI 0.622–0.674). However, the C-index, calibration plot, receiver operating characteristics curve (ROC) analysis, Kaplan-Meier survival curve of the nomogram in the external validation cohort were not as good as the training and internal validation cohort (C-index = 0.584 95%CI 0.445–0.723). Further analysis demonstrated that the resection margin involvement (R0, R1, or R2 resection) was an independent risk factor for the patients, which was not included in the SEER cohort.

Conclusions

the nomogram based on the SEER database fails to accurately predict the prognosis of the patients in the external validation cohort, which can be caused by the absence of essential information from the SEER database.

Prediction of overall survival in patients with Stage I esophageal cancer: A novel web-based calculator

BACKGROUND AND AIMS

In this study, we aimed to develop a convenient web-based calculator to predict the overall survival (OS) of patients with Stage I esophageal cancer (EC).

METHODS

Data of 1664 patients, between 2004 and 2015, were extracted from the Surveillance, Epidemiology, and End Results database. Least absolute shrinkage and selection operator regression was employed to sift variables; subsequently, Cox proportional hazards regression model was built. We applied the enhanced bootstrap validation to appraise the discrimination and calibration of the model. Clinical benefit was measured using decision curve analysis (DCA). Thereafter, a web-based calculator based on the model, which could be used to predict the 1-, 3-, and 5-year OS rates, was developed.

RESULTS

Race, age, histologic type, grade, N stage, and therapeutic methods were selected. C-indices of the prediction model in the training and validation groups were 0.726 (95% confidence interval [CI], 0.679-0.773) and 0.724 (95% CI, 0.679-0.769), respectively. Calibration curves showed good agreement between the groups. The DCA demonstrated that the prediction model is clinically useful.

CONCLUSIONS

The prediction model we developed showed a good performance in calculating the OS rates in patients with Stage I EC. The web-based calculator is available at https://championship.shinyapps.io/dynnomapp/.