Surgery to the primary tumor is associated with improved survival of patients with metastatic esophageal cancer: propensity score-matched analyses of a large retrospective cohort

A population-based model identifying optimal candidate for primary tumor resection in distant metastatic laryngeal carcinoma

PURPOSE

To developed a model to screen distant metastatic laryngeal carcinoma (DMLC) patients who would benefit from the primary tumor resection.

METHODS

The propensity score matching (PSM) was utilized to avoid disproportionate distributions of the confounding factors. We hypothesized that patients who underwent surgery would benefit from surgery by having a longer median cancer-specific survival (CSS) than patients without surgery. Multivariable Cox model was used to explore the independent factors of CSS and overall survival (OS) among PSM population. We used these factors to construct a nomogram to identify surgery benefit patients. The predictive performance and clinical practicability of the nomogram were determined by area under the curve (AUC), calibration curve, and decision curve.

RESULTS

The CSS and OS for patients who received primary tumor resection were significantly longer than those without resection (median CSS: 19 months vs. 10 months, P = 0.009; median OS: 21 months vs. 10 months, P = 0.001). The nomogram displayed a good degree of discrimination and calibration. The mean AUC of the nomogram was 0.70 (95% confidence interval [CI] 0.66-0.76) through threefold cross-validation.

CONCLUSIONS

A predictive model was established and might be used to screen the optimal candidates for primary tumor surgery in DMLC patients.

Oesophageal cancer metastases: An observational study of a more aggressive approach

BACKGROUND

The prognosis for oesophageal carcinoma is poor, but once distant metastases emerge the prognosis is considered hopeless. There is no consistent protocol for the early identification and aggressive management of metastases.

AIM

To examine the outcome of a policy of active postoperative surveillance with aggressive treatment of confirmed metastases.

METHODS

A prospectively maintained database of 205 patients diagnosed with oesophageal carcinoma between 1998 and 2019 and treated with curative intent was interrogated for patients with metastases, either at diagnosis or on follow-up surveillance and treated for cure. This cohort was compared with incomplete clinical responders to neoadjuvant chemoradiotherapy (nCRT) who subsequently underwent surgery on their primary tumour. Overall survival was estimated using the Kaplan-Meier method, and the log-rank test was used to compare survival differences between groups.

RESULTS

Of 205 patients, 11 (5.4%) had metastases treated for cure (82% male; median age 60 years; 9 adenocarcinoma and 2 squamous cell carcinomas). All had undergone neoadjuvant chemotherapy or chemoradiotherapy, followed by surgery in all but 1 case. Of the 11 patients, 4 had metastatic disease at diagnosis, of whom 3 were successfully downstaged with nCRT before definitive surgery; 2 of these 4 also developed oligometastatic recurrence and were treated with curative intent. Following definitive treatment, 7 had treatment for metachronous oligometastatic disease; 5 of whom underwent metastasectomy (adrenal × 2; lung × 2; liver × 1). The median overall survival was 10.9 years [95% confidence interval (CI): 0.7-21.0 years], which was statistically significantly longer than incomplete clinical responders undergoing surgery on the primary tumour without metastatic intervention [n = 62; median overall survival = 1.9 (95%CI: 1.1-2.7; P = 0.012]. The cumulative proportion surviving 1, 3, and 5 years was 100%, 91%, and 61%, respectively compared to 71%, 36%, and 25% for incomplete clinical responders undergoing surgery on the primary tumour who did not undergo treatment for metastatic disease.

CONCLUSION

Metastatic oesophageal cancer represents a unique challenge, but aggressive treatment can be rewarded with impressive survival data. In view of recent advances in targeted therapies, intensive follow-up may yield a greater number of patients with curative potential and thus improved long-term survival.

Survival after Multimodal Treatment Including Surgery for Metastatic Esophageal Cancer: A Systematic Review

(1) Background: The management of metastatic esophageal cancer is more often limited to palliative chemotherapy. Limited data are available regarding the role of surgery that remains controversial. The aim of this systematic review is to assess the survival outcome of surgically treated metastatic esophageal cancer patients. (2) Methods: The present systematic review is designed using the PRISMA guidelines and has been registered with PROSPERO (CRD42019140306). Two reviewers independently searched and identified studies dealing with surgery for stage IV esophageal cancer in the Medline and Google Scholar databases between January 2008 and December 2019. (3) Results: Seven retrospective nonrandomized studies, totaling 1756 patients with stage IV esophageal cancer who underwent curative surgery, were included. Our analysis demonstrates a three-year overall survival rate of 23% (CI 95% 17–31) among patients undergoing surgery. Because only two comparative studies were identified, data compilation and relative risk evaluation through meta-analysis were not possible. (4) Conclusions: Multimodality treatment, including surgery in curative intent, seems associated with a significant chance of three-year overall survival. A prospective evaluation of this approach and validation of adequate selection criteria are needed.

A machine learning model predicting candidates for surgical treatment modality in patients with distant metastatic esophageal adenocarcinoma: A propensity score-matched analysis

Objective

To explore the role of surgical treatment modality on prognosis of metastatic esophageal adenocarcinoma (mEAC), as well as to construct a machine learning model to predict suitable candidates.

Method

All mEAC patients pathologically diagnosed between January 2010 and December 2018 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. A 1:4 propensity score-matched analysis and a multivariate Cox analysis were performed to verify the prognostic value of surgical treatment modality. To identify suitable candidates, a machine learning model, classification and regression tree (CART), was constructed, and its predictive performance was evaluated by the area under receiver operating characteristic curve (AUC).

Results

Of 4520 mEAC patients, 2901 (64.2%) were aged over 60 years and 4012 (88.8%) were males. There were 411 (9.1%) patients receiving surgical treatment modality. In the propensity score-matched analysis, surgical treatment modality was significantly associated with a decreased risk of death (HR: 0.47, 95% CI: 0.40-0.55); surgical patients had almost twice as much median survival time (MST) as those without resection (MST with 95% CI: 23 [17-27] months vs. 11 [11-12] months, P <0.0001). The similar association was also observed in the multivariate Cox analysis (HR: 0.47, 95% CI: 0.41-0.53). Then, a CART was constructed to identify suitable candidates for surgical treatment modality, with a relatively good discrimination ability (AUC with 95% CI: 0.710 [0.648-0.771]).

Conclusion

Surgical treatment modality may be a promising strategy to prolong survival of mEAC patients. The CART in our study could serve as a useful tool to predict suitable candidates for surgical treatment modality. Further creditable studies are warranted to confirm our findings.

The Effect of the Appropriate Timing of Radiotherapy on Survival Benefit in Patients with Metastatic Esophageal Cancer Who Have Undergone Resection of Primary Site: A SEER Database Analysis

Background

Metastatic esophageal cancer (MEC) is an advanced stage of esophageal cancer. However, still, resection of primary site and radiotherapy are considered treatment modalities to treat patients with MEC. Hence, this study is aimed at exploring the effect of the appropriate timing of radiotherapy on the survival benefit of these patients by comparing cancer-specific survival (CSS).

Method

The patient information was obtained from the National Surveillance Epidemiology and End Results (SEER) database between the years 2004 and 2017. We used the SEER∗ STAT (V8.3.9.2) software to search and download data. Patients treated with pre- and postoperative radiotherapy were divided into two groups. The propensity score matching (PSM) analysis was performed to increase the comparability of data within two groups. We used the Kaplan-Meier method to analyze and compare the CSS between the two groups. The Cox risk model was used to analyze variables affecting patient survival.

Results

A total of 599 patients with MEC who experienced resection of the primary site and radiotherapy were recruited. 144 pairings formed through PSM. The 5-year CSS was 23.0% and 11.7% for patients who have undergone pre- and postoperative radiotherapy, respectively. Patients who have undergone preoperative radiotherapy showed better CSS than those who received postoperative radiotherapy (P < 0.001). The multivariate Cox analysis of the entire cohort showed that age > 60 years at the time of diagnosis (HR = 1.481, 95% CI: 1.1341-1.934, and P = 0.04) and other histological types of esophageal cancer (HR = 1.581, 95% CI: 1.067-2.341, and P = 0.022) increased the risk of cancer-related death. Inversely, marriage (HR = 0.696, 95% CI: 0.514-0.942, and P = 0.019) and preoperative radiotherapy (HR = 0.664, 95% CI: 0.517-0.853, and P < 0.001) reduced the risk of death from cancer.

Conclusions

For patients with MEC, preoperative radiotherapy might have a significant effect on the survival benefit over those who receive postoperative radiotherapy.

Models for Predicting Early Death in Patients With Stage IV Esophageal Cancer: A Surveillance, Epidemiology, and End Results-Based Cohort Study

Background

Despite enormous progress in the stage IV esophageal cancer (EC) treatment, some patients experience early death after diagnosis. This study aimed to identify the early death risk factors and construct models for predicting early death in stage IV EC patients.

Methods

Stage IV EC patients diagnosed between 2010 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were selected. Early death was defined as death within 3 months of diagnosis, with or without therapy. Early death risk factors were identified using logistic regression analyses and further used to construct predictive models. The concordance index (C-index), calibration curves, and decision curve analyses (DCA) were used to assess model performance.

Results

Out of 4411 patients enrolled, 1779 died within 3 months. Histologic grade, therapy, the status of the bone, liver, brain and lung metastasis, marriage, and insurance were independent factors for early death in stage IV EC patients. Histologic grade and the status of the bone and liver metastases were independent factors for early death in both chemoradiotherapy and untreated groups. Based on these variables, predictive models were constructed. The C-index was .613 (95% confidence interval (CI), [.573–.653]) and .635 (95% CI, [.596–.674]) in the chemoradiotherapy and untreated groups, respectively, while calibration curves and DCA showed moderate performance.

Conclusions

More than 40% of stage IV EC patients suffered from an early death. The models could help clinicians discriminate between low and high risks of early death and strategize individually-tailed therapeutic interventions in stage IV EC patients.

A population-based predictive model predicting candidate for primary tumor surgery in patients with metastatic esophageal cancer

Background

The survival benefit of primary tumor surgery for metastatic esophageal cancer (mEC) patients has been observed, but methods for discriminating which individual patients would benefit from surgery have been poorly defined. Herein, a predictive model was developed to test the hypothesis that only certain metastatic patients would gain a survival benefit from primary tumor surgery.

Methods

Clinical data for patients with mEC were extracted from the Surveillance, Epidemiology and End Results (SEER) database [2004-2016] and then divided into surgery and no-surgery groups according to whether surgery was performed on the primary tumor. Propensity-score-matching (PSM) was performed to balance the confounding factors. We hypothesized that the patients who had undergone surgery and lived longer than the median cancer-specific-survival (CSS) of the no-surgery group could benefit from surgery. We constructed a nomogram to predict surgery benefit potential based on multivariable logistic-regression analysis using preoperative factors. The predictive performance of the nomogram was evaluated by the area under the receiver operating characteristic (AUC) and calibration curves. The clinical application value of the nomogram was estimated with decision curve analysis (DCA).

Results

A total of 5,250 eligible patients with mEC were identified, and 9.4% [492] received primary tumor surgery. After PSM, CSS for the surgery group was significantly longer [median: 19 vs. 9 months; hazard ratio (HR) 0.52, P<0.001] compared with the no-surgery group. Among the surgery group, 69.3% [327] survived >9 months (surgery-beneficial group). The prediction nomogram showed good discrimination both in training and validation sets (AUC: 0.72 and 0.70, respectively), and the calibration curves indicated a good consistency. DCA demonstrated that the nomogram was clinically useful. According to this nomogram, surgery patients were classified into two groups: no-benefit-candidate and benefit-candidate. The benefit-candidate group was associated with longer survival than the no-benefit-candidate group (median CSS: 19 vs. 6.5 months, P<0.001). Additionally, there was no difference in survival between the no-benefit-candidate and no-surgery groups (median CSS: 6.5 vs. 9 months, P=0.070).

Conclusions

A predictive model was created for the selection of candidates for surgical treatment among mEC patients. This predictive model might be used to select patients who may benefit from primary tumor surgery.

The primary tumor resection in patients with distant metastatic laryngeal carcinoma

BACKGROUND

The role of primary tumor resection in patients with distant metastatic laryngeal carcinoma (DMLC) has not been clarified completely. Thus, we used propensity score matching (PSM) and survival analysis to address this issue.

METHODS

The PSM was utilized to avoid selection bias and disproportionate distributions of the confounding factors. Kaplan-Meier estimates and Cox proportional hazard analysis were utilized to evaluate overall survival (OS) and cancer-specific survival (CSS).

RESULTS

From the Surveillance, Epidemiology, and End Results Program database, a cohort of 480 patients with DMLC were included. After PSM, the OS and CSS for patients who underwent resection were significantly longer than those without resection (median OS: 19 months vs. 8 months, P < 0.001; median CSS: 19 months vs. 9 months, P = 0.002). Tumor resection significantly prolonged survival of DMLC patients with appropriate demographic and clinical characteristics. In the multivariate analysis, age at diagnosis, race, pathologic subtype, and marital status were found significantly affecting both OS and CSS of patients who underwent surgical resection. Predictive nomograms were developed to help distinguish patients with early mortality potential after surgical resection.

CONCLUSIONS

This study is the first one using PSM to assess the role played by surgical resection in DMLC and evaluate the prognostic factor of resected patients. Premised on well controlled postoperative complications, resection could significantly prolong OS and CSS of certain patients.