Proposal of a Nomogram for Predicting Survival in Patients with Siewert Type II Adenocarcinoma of the Esophagogastric Junction After Preoperative Radiation

Prognostic significance of an innovative staging system based on the logarithmic odds of positive lymph nodes for resectable gastroesophageal cancer after neoadjuvant chemoradiation: a population-based study with external validation of data

BACKGROUND

After receiving neoadjuvant chemoradiation, the number of examined lymph nodes in resectable gastroesophageal cancer (GEC) will decrease, this may not accurately determine the N staging. So our study evaluates the clinical significance of a new staging model based on the logarithmic odds of positive lymph nodes (LODDS) in patients with GEC after receiving neoadjuvant chemoradiation.

METHODS

A total of 1 130 patients with pathologically diagnosed GEC who received neoadjuvant chemoradiation from 2004 to 2019 included in the National Cancer Institute Surveillance, Epidemiology, and Results (SEER) database were selected for analysis. Lymph nodes were staged according to the AJCC TNM staging system (eighth edition) and LODDS. Patient prognosis across the two systems were evaluated by the Kaplan-Meier method, differences in node staging were evaluated by the Akaike information criterion and Bayesian information criterion. In addition, 914 patients from our center were externally validated.

RESULTS

Compared to the traditional TNM staging system, the new TLODDSM staging system was comprised of stage I, stage II, stage IIIA, stage IIIB, and stage IVA, and decision curve analysis showed that the new staging system had higher benefits for different decision thresholds than the old staging system. The Akaike information criterion and Bayesian information criterion of the new staging system was lower than those of the old staging system, indicating the sensitivity of the TLODDSM staging system for predicting the prognosis of patients was higher. In addition, stage-IIIB or -IVA patients in the new staging system benefited from adjuvant chemotherapy. The externally validated data from our center supported this conclusion.

CONCLUSIONS

Compared to the TNM staging system, the TLODDSM staging system has significant advantages in predicting prognosis of patients with GEC who have completed neoadjuvant chemoradiation, guiding the adjuvant chemotherapy for patients.

Development of a novel staging classification for Siewert II adenocarcinoma of the esophagogastric junction after neoadjuvant chemotherapy

BACKGROUND

Stage classification for Siewert II adenocarcinoma of the esophagogastric junction (AEG) treated with neoadjuvant chemotherapy (NAC) has not been established.

AIM

To investigate the optimal stage classification for Siewert II AEG with NAC.

METHODS

A nomogram was established based on Cox regression model that analyzed variables associated with overall survival (OS) and disease-specific survival (DSS). The nomogram performance in terms of discrimination and calibration ability was evaluated using the likelihood-ratio test, Akaike information criterion, Harrell concordance index, time-receiver operating characteristic curve, and decision curve analysis.

RESULTS

Data from 725 patients with Siewert type II AEG who underwent neoadjuvant therapy and gastrectomy were obtained from the Surveillance, Epidemiology, and End Results database. Univariate and multivariate analyses revealed that sex, marital status, race, ypT stage, and ypN stage were independent prognostic factors of OS, whereas sex, race, ypT stage, and ypN stage were independent prognostic factors for DSS. These factors were incorporated into the OS and DSS nomograms. Our novel nomogram model performed better in terms of OS and DSS prediction compared to the 8^th American Joint Committee of Cancer pathological staging system for esophageal and gastric cancer. Finally, a user-friendly web application was developed for clinical use.

CONCLUSION

The nomogram established specifically for patients with Siewert type II AEG receiving NAC demonstrated good prognostic performance. Validation using external data is warranted before its widespread clinical application.

Development of a novel staging classification for Siewert II adenocarcinoma of the esophagogastric junction after neoadjuvant chemotherapy

BACKGROUND

Stage classification for Siewert II adenocarcinoma of the esophagogastric junction (AEG) treated with neoadjuvant chemotherapy (NAC) has not been established.

AIM

To investigate the optimal stage classification for Siewert II AEG with NAC.

METHODS

A nomogram was established based on Cox regression model that analyzed variables associated with overall survival (OS) and disease-specific survival (DSS). The nomogram performance in terms of discrimination and calibration ability was evaluated using the likelihood-ratio test, Akaike information criterion, Harrell concordance index, time-receiver operating characteristic curve, and decision curve analysis.

RESULTS

Data from 725 patients with Siewert type II AEG who underwent neoadjuvant therapy and gastrectomy were obtained from the Surveillance, Epidemiology, and End Results database. Univariate and multivariate analyses revealed that sex, marital status, race, ypT stage, and ypN stage were independent prognostic factors of OS, whereas sex, race, ypT stage, and ypN stage were independent prognostic factors for DSS. These factors were incorporated into the OS and DSS nomograms. Our novel nomogram model performed better in terms of OS and DSS prediction compared to the 8th American Joint Committee of Cancer pathological staging system for esophageal and gastric cancer. Finally, a user-friendly web application was developed for clinical use.

CONCLUSION

The nomogram established specifically for patients with Siewert type II AEG receiving NAC demonstrated good prognostic performance. Validation using external data is warranted before its widespread clinical application.

Validation of the Memorial Sloan Kettering Gastric Cancer Post-Resection Survival Nomogram: Does It Stand the Test of Time?

BACKGROUND

The Memorial Sloan Kettering Cancer Center (MSK) nomogram combined both gastroesophageal junction (GEJ) and gastric cancer patients and was created in an era from patients who generally did not receive neoadjuvant chemotherapy. We sought to reevaluate the MSK nomogram in the era of multidisciplinary treatment for GEJ and gastric cancer.

STUDY DESIGN

Using data on patients who underwent R0 resection for GEJ or gastric cancer between 2002 and 2016, the C-index of prediction for disease-specific survival (DSS) was compared between the MSK nomogram and the American Joint Committee on Cancer (AJCC) 8th edition staging system after segregating patients by tumor location (GEJ or gastric cancer) and neoadjuvant treatment. A new nomogram was created for the group for which both systems poorly predicted prognosis.

RESULTS

During the study period, 886 patients (645 gastric and 241 GEJ cancer) underwent up-front surgery, and 999 patients (323 gastric and 676 GEJ) received neoadjuvant treatment. Compared with the AJCC staging system, the MSK nomogram demonstrated a comparable C-index in gastric cancer patients undergoing up-front surgery (0.786 vs 0.753) and a better C-index in gastric cancer patients receiving neoadjuvant treatment (0.796 vs 0.698). In GEJ cancer patients receiving neoadjuvant chemotherapy, neither the MSK nomogram nor the AJCC staging system performed well (C-indices 0.647 and 0.646). A new GEJ nomogram was created based on multivariable Cox regression analysis and was validated with a C-index of 0.718.

CONCLUSIONS

The MSK gastric cancer nomogram's predictive accuracy remains high. We developed a new GEJ nomogram that can effectively predict DSS in patients receiving neoadjuvant treatment.

Nomograms for Predicting Disease-Free Survival in Patients With Siewert Type II/III Adenocarcinoma of the Esophagogastric Junction Receiving Neoadjuvant Therapy and Radical Surgery

Objective

This study aimed to develop prognostic prediction models for patients with Siewert type II/III adenocarcinoma of the esophagogastric junction (AEG) who received neoadjuvant therapy (neoadjuvant chemoradiotherapy or neoadjuvant chemotherapy) and radical surgery. A baseline nomogram and a post-operative nomogram were constructed before neoadjuvant therapy and after surgery. The predictive performance of the constructed nomograms was internally validated and compared to the TNM staging system.

Materials and Methods

A total of 245 patients diagnosed with Siewert type II/III AEG and treated with neoadjuvant therapy followed by radical surgery at The Fourth Hospital of Hebei Medical University between January 2011 and December 2017 were enrolled. The variables before neoadjuvant therapy were defined as baseline factors, while the variables of baseline factors along with the variables of treatment and postoperative pathology were defined as post-operative factors. To construct the corresponding nomograms, independent predictors of baseline and post-operative factors were identified. The C-index and a time-dependent receiver operating characteristic curve were used to evaluate the model’s discrimination ability. The calibration ability of the model was determined by comparing the probability of predicted free-recurrence to the actual free-recurrence. Decision curve analysis (DCA) was used to determine the clinical usefulness of the nomogram.

Results

Among the baseline factors, age, cT stage, cN stage, Borrmann type, and staging laparoscopy were independent prognostic predictors. In contrast, among the post-operative factors, age, cN stage, staging laparoscopy, ypT stage, clinical response, number of positive lymph nodes, number of negative lymph nodes, laurén classification, and lymphatic, or perineural invasion (VELPI) were independent prognostic predictors. The two nomograms were constructed using the independent predictors of prognosis. The C-indexes for the baseline and post-operative nomograms were 0.690 (95% CI, 0.644-0.736) and 0.817 (95% CI, 0.782-0.853), respectively. The AUCs of the baseline nomogram at 3 and 5 years were both greater than cTNM (73.1 vs 58.8, 76.1 vs 55.7). Similarly, the AUCs of the post-operative nomogram were both greater than ypTNM (85.2 vs 69.1, 88.2 vs 71.3) at 3 and 5 years. The calibration curves indicated that both models had a high degree of calibration ability. By comparing the DCA at 3 and 5 years, we determined that the two nomograms constructed had better clinical utility than the TNM staging system.

Conclusions

The constructed nomograms have a more accurate predictive ability than the eighth edition TNM staging system, which can be useful for treatment selection and follow-up monitoring of patients.

Systematic review and validation of clinical models predicting survival after oesophagectomy for adenocarcinoma

BACKGROUND

Oesophageal adenocarcinoma poses a significant global health burden, yet the staging used to predict survival has limited ability to stratify patients by outcome. This study aimed to identify published clinical models that predict survival in oesophageal adenocarcinoma and to evaluate them using an independent international multicentre dataset.

METHODS

A systematic literature search (title and abstract) using the Ovid Embase and MEDLINE databases (from 1947 to 11 July 2020) was performed. Inclusion criteria were studies that developed or validated a clinical prognostication model to predict either overall or disease-specific survival in patients with oesophageal adenocarcinoma undergoing surgical treatment with curative intent. Published models were validated using an independent dataset of 2450 patients who underwent oesophagectomy for oesophageal adenocarcinoma with curative intent.

RESULTS

Seventeen articles were eligible for inclusion in the study. Eleven models were suitable for testing in the independent validation dataset and nine of these were able to stratify patients successfully into groups with significantly different survival outcomes. Area under the receiver operating characteristic curves for individual survival prediction models ranged from 0.658 to 0.705, suggesting poor-to-fair accuracy.

CONCLUSION

This study highlights the need to concentrate on robust methodologies and improved, independent, validation, to increase the likelihood of clinical adoption of survival predictions models.

The abdominal-transhiatal surgical approach versus the thoracoabdominal surgical approach in Siewert type II adenocarcinoma of the esophagogastric junction: protocol for a multicenter prospective, open, parallel, and randomized controlled trial

Background

To date, Siewert type II adenocarcinoma of the esophagogastric junction (ST-II AEG) can be removed radically utilizing either the abdominal-transhiatal (TH) or the right thoracoabdominal (RTA) approaches. Because of a paucity of high-quality direct evidence, the appropriate surgical approach for ST-II AEG remains debatable. In the present, only several retrospective studies are available, representing ambiguous results. Thus, prospective randomized clinical trials are demanded to compare the survival, oncological outcomes, safety and efficiency and life quality between the TH and RTA approach in patients with resectable AEG of Siewert type II.

Methods

A prospective, multicenter, open, randomized, and parallel controlled study named S2AEG will be conducted. Three hundred and twelve patients who match the inclusion criteria but not the exclusion criteria will be participating in the trial and randomly divided into the TH (156) and RTA (156) cohorts. The primary efficacy endpoint is the 3-year disease-free survival (DFS) following the operation. The rate of R0-resection, the number and site of lymph nodes infiltrated and dissected, postoperative complications, hospital days and life quality are the second endpoints.

Discussion

This study is the first prospectively randomized controlled trial aiming to compare the surgical outcomes between TH and RTA approaches in patients with resectable ST-II AEG. It is hypothesized that patients in the TH cohort would harvest equivalent oncological results and survival while maintaining acceptable life quality when compared to patients in the RTA cohort. Our findings will provide high-level clinical evidence for clinical decision-making on the appropriate surgical approach for patients with ST-II AEG. Embarked in November 2019, this research will be completed 3 years after the final participant’s enrolment date.

Trial registration

Clinical Trial.gov ID: NCT04910789 May 29, 2021. Name: S2AEG.

Prognostic nomogram for Siewert type II adenocarcinoma of the esophagogastric junction patients with and without neoadjuvant radiotherapy: a retrospective cohort study

OBJECTIVE

To compare the prognostic factors of Siewert type II AEG patients who had received neoadjuvant radiotherapy (nRT) versus those who did not receive nRT. Nomograms for outcome prediction were constructed for the two treatment modalities.

MATERIALS AND METHODS

Data for 1,745 Siewert II type AEG patients who underwent radical surgery between 2010 and 2015 were retrieved from SEER (Surveillance, Epidemiology, and End Results) database. Patients were assigned to neoadjuvant radiotherapy (nRT) and non-neoadjuvant radiotherapy (non-nRT) groups based on treatment modality. Independent prognostic predictors were used to develop nomograms. Concordance index (C-index), receiver operating characteristic (ROC), calibration curves, and decision curve analyses (DCA) were used to determine the performance and prognostic value of the nomograms. The predictive accuracy of nomograms was compared with the prognostic value of the Tumor-Node-Metastasis (TNM) staging system.

RESULTS

The results showed that age, lymph node rate (LNR), and the number of removed lymph nodes (RLN) were independent prognostic factors for CSS in the nRT group. Tumor size, tumor grade, T stage, LNR, and therapy type were independent prognosis factors for CSS in patients in the non-nRT group. The C-indices for the nomograms were 0.652 (95% CI, 0.614-0.690) and 0.663 (95% CI, 0.606-0.720) in the training and validation cohort, respectively, for the nRT group. C-indices for the nomogram in non-nRT group were 0.754 (95% CI, 0.723-0.785) and 0.747 (95% CI, 0.688-0.800) for the training and validation cohorts, respectively. C-indices and ROC curves showed good predictive value compared with the TNM staging system in both groups. C-indices, as well as the AUC values of the nomograms and the TNM staging system for both cohorts in the non-nRT group were higher compared with those in the nRT group. Analysis of the survival calibration curve revealed high consistency between actual versus predicted outcomes determined by the nomograms. Decision curve analyses revealed that the new models had higher prediction value and clinical significance compared with TNM staging system.

CONCLUSION

The established nomograms showed high prognostic value for Siewert type II AEG patients in both nRT and non-nRT groups. In addition, the nomogram and the TNM staging systems showed better prognostic performance for patients in the non-nRT group compared with patients in the nRT group.

Development and validation of a survival nomogram for patients with Siewert type II/III adenocarcinoma of the esophagogastric junction based on real-world data

Background

The clinical staging systems for adenocarcinoma of the esophagogastric junction (AEG) are controversial. We aimed to propose a prognostic nomogram based on real-world data for predicting survival of Siewert type II/III AEG patients after surgery.

Methods

A total of 396 patients with Siewert type II/III AEG diagnosed and treated at the Center for Gastrointestinal Surgery, the First Affiliated Hospital, Sun Yat-sen University, from June 2009 to June 2017 were enrolled. The original data of 29 variables were exported from the electronic medical records system. The nomogram was established based on multivariate Cox regression coefficients, and its performance was measured using Harrell’s concordance index (C-index), receiver operating characteristic (ROC) curve analysis and calibration curve.

Results

A nomogram was constructed based on nine variables. The C-index for overall survival (OS) prediction was 0.76 (95% CI, 0.72 to 0.80) in the training cohort, in the validation-1 cohort was 0.79 (95% CI, 0.72 to 0.86), and 0.73 (95% CI, 0.67 to 0.80) in the validation-2 cohort. Time-dependent ROC curves and calibration curves in all three cohorts showed good prognostic predictive accuracy. We further proved the superiority of the nomogram in predictive accuracy for OS to pathological TNM (pTNM) staging system and other independent prognostic factors. Kaplan-Meier survival curves demonstrated the pTNM stage, grade of differentiation, positive lymph node, log odds of positive lymph node and organ invasion were prognostic factors with good discriminative ability.

Conclusion

The established nomogram demonstrated a more precise prognostic prediction for patients with Siewert type II/III AEG.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08249-x.

Prognostic Nomogram for Postoperative Patients With Gastroesophageal Junction Cancer of No Distant Metastasis

Background

Gastroesophageal junction (GEJ) was one of the most common malignant tumors. However, the value of clinicopathological features in predicting the prognosis of postoperative patients with GEJ cancer and without distant metastasis was still unclear.

Methods

The 3425 GEJ patients diagnosed and underwent surgical resection without distant metastasis in the Surveillance, Epidemiology and End Results (SEER) database from 2010 to 2015 were enrolled,and they were randomly divided into training and validation cohorts with 7:3 ratio. Univariate and multivariate Cox regression analysis were used to determine the predictive factors that constituted the nomogram. The predictive accuracy and discriminability of Nomogram were determined by the area under the curve (AUC), C index, and calibration curve, and the influence of various factors on prognosis was explored.

Results

2,400 patients were designed as training cohort and 1025 patients were designed as validation cohort. The percentages of the distribution of demographic and clinicopathological characteristics in the training and validation cohorts tended to be the same. In the training cohort, multivariate Cox regression analysis revealed that the age, tumor grade, T stage and N stage were independent prognostic risk factors for patients with GEJ cancer without distant metastasis. The C index of nomogram model was 0.667. The AUC of the receiver operating characteristic (ROC) analysis for 3- and 5-year overall survival (OS) were 0.704 and 0.71, respectively. The calibration curve of 3- and 5-year OS after operation showed that there was the best consistency between nomogram prediction and actual observation. In the validation cohort, the C index of nomogram model, the AUC of 3- and 5-year OS, and the calibration curve were similar to the training cohort.

Conclusions

Nomogram could evaluate the prognosis of patients with GEJ cancer who underwent surgical resection without distant metastasis.

A nomogram-based immune-serum scoring system predicts overall survival in patients with lung adenocarcinoma

OBJECTIVE

The immunoscore, which is used to quantify immune infiltrates, has greater relative prognostic value than tumor, node, and metastasis (TNM) stage and might serve as a new system for classification of colorectal cancer. However, a comparable immunoscore for predicting lung adenocarcinoma (LUAD) prognosis is currently lacking.

METHODS

We analyzed the expression of 18 immune features by immunohistochemistry in 171 specimens. The relationship of immune marker expression and clinicopathologic factors to the overall survival (OS) was analyzed with the Kaplan-Meier method. A nomogram was developed by using the optimal features selected by least absolute shrinkage and selection operator (LASSO) regression in the training cohort (n = 111) and evaluated in the validation cohort (n = 60).

RESULTS

The indicators integrated in the nomogram were TNM stage, neuron-specific enolase, carcino-embryonic antigen, CD8center of tumor (CT), CD8invasive margin (IM), FoxP3CT, and CD45ROCT. The calibration curve showed prominent agreement between the observed 2- and 5-year OS and that predicted by the nomogram. To simplify the nomogram, we developed a new immune-serum scoring system (I-SSS) based on the points awarded for each factor in the nomogram. Our I-SSS was able to stratify same-stage patients into different risk subgroups. The combination of I-SSS and TNM stage had better prognostic value than the TNM stage alone.

CONCLUSIONS

Our new I-SSS can accurately and individually predict LUAD prognosis and may be used to supplement prognostication based on the TNM stage.

Development and validation of a nomogram to predict the prognosis of patients with gastric cardia cancer

Our goal was to develop a prognostic nomogram to predict overall survival (OS) and cancer-specific survival (CSS) in patients with gastric cardia cancer (GCC). Patients diagnosed with GCC from 2004 to 2015 were screened from the surveillance, epidemiology, and end results (SEER) database. A nomogram was developed based on the variables associated with OS and CSS using multivariate Cox analysis regression models, which predicted 3- and 5-year OS and CSS. The predictive performance of the nomogram was evaluated using the consistency index (C-index), calibration curve and decision curve analysis (DCA), and the nomogram was calibrated for 3- and 5-year OS and CSS. A total of 7,332 GCC patients were identified and randomized into a training cohort (5,231, 70%) and a validation cohort (2,200, 30%). Multivariate Cox regression analysis showed that marital status, race, SEER stage, grade, T stage, N stage, M stage, tumor size, and surgery were independent risk factors for OS and CSS in GCC patients. Based on the multivariate Cox regression results, we constructed prognostic nomograms of OS and CSS. In the training cohort, the C-index for the OS nomogram was 0.714 (95% CI = 0.705–0.723), and the C-index for the CSS nomogram was 0.759 (95% CI = 0.746–0.772). In the validation cohort, the C-index for the OS nomogram was 0.734 (95% CI = 0.721–0.747), while the C-index for the CSS nomogram was 0.780 (95% CI = 0.759–0.801). Our nomogram has better prediction than the nomogram based on TNM stage. In addition, in the training and external validation cohorts, the calibration curves of the nomogram showed good consistency between the predicted and actual 3- and 5-year OS and CSS rates. The nomogram can effectively predict OS and CSS in GCC patients, which may help clinicians personalize prognostic assessments and clinical decisions.

Survival nomogram for patients with metastatic siewert type II adenocarcinoma of the esophagogastric junction: a population-based study

BACKGROUND

The aim of this study was to construct a nomogram to predict the survival of patients with metastatic Siewert Type II adenocarcinomas of the esophagogastric junction (AEG).

METHODS

Patients were identified using the Surveillance, Epidemiology, and End Results (SEER) database. Cox regression analysis was performed to assess the prognostic factors. A nomogram comprising independent prognostic factors was established and evaluated using C-indexes, calibration curves, and decision curve analyses.

RESULTS

In total 1616 eligible patients were enrolled. Race, age, bone metastasis, liver metastasis, lung metastasis, other metastasis sites, and distant lymph nodes metastasis were independent prognostic factors and were integrated to construct the nomogram. The nomogram had a C-index of 0.590 (95% CI: 0.569-0.611) in the training cohort and 0.569 (95% CI: 0.532-0.606) in the validation cohort. The calibration plots for the probabilities of 6-month and 1-year overall survival demonstrated there was an optimum between nomogram prediction and actual observation.

CONCLUSION

We developed and validated a nomogram to predict individual prognosis for patients with metastatic Siewert Type II AEG, and the risk stratification system based on the nomogram could effectively stratify the patients into two risk subgroups, which can help clinicians accurately predict mortality risk and recommend personalized treatment modalities.