Proposed revision of the 8th edition AJCC clinical staging system for esophageal squamous cell cancer treated with definitive chemo-IMRT based on CT imaging

Optimal Time-to-Surgery Recommendations Based on Primary Tumor Volume Regression for Patients with Resectable Esophageal Cancer after Neoadjuvant Chemoradiotherapy: A Retrospective Study

BACKGROUND

Neoadjuvant chemoradiotherapy (NCRT) has shown promise in improving the prognosis of individuals with locally advanced esophageal squamous cell carcinoma (LA-ESCC). However, the factors influencing tumor response and long-term survival in these patients remain unknown. The optimal timing for surgery after the completion of radiotherapy in LA-ESCC remains controversial. Therefore, this study was designed to identify biomarkers and to determine the optimal post-NCRT time-to-surgery (TTS) for patients with LA-ESCC.

METHODS

This retrospective study included patients with resectable LA-ESCC who underwent NCRT between May 2017 and June 2021. The tumor shrinkage rate was calculated as the difference between the pre- and post-primary gross tumor volume (GTVp) divided by the pre-GTVp. Univariate and multivariate Cox regression analyses and Kaplan-Meier curves were used to calculate overall survival (OS) and progression-free survival (PFS).

RESULTS

We collected data from 248 patients with resectable LA-ESCC who underwent computed tomography (CT) scans before the initiation of treatment. The median follow-up time was 37.7 months. The optimal cutoff of tumor shrinkage was 45%. In the univariate and multivariate analyses, we found a significant association between the tumor shrinkage rate and PFS (p = 0.001). Among the subgroup of patients who responded to treatment, extending the TTS was associated with improved OS (p = 0.037) and PFS (p = 0.028).

CONCLUSIONS

For patients with resectable LA-ESCC, the tumor shrinkage rate is an independent prognostic factor for PFS. Thus, for responders, prolonging TTS is recommended to obtain a better OS.

CT-based radiomics for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis

Objective

We aimed to evaluate the diagnostic effectiveness of computed tomography (CT)-based radiomics for predicting lymph node metastasis (LNM) in patients diagnosed with esophageal cancer (EC).

Methods

The present study conducted a comprehensive search by accessing the following databases: PubMed, Embase, Cochrane Library, and Web of Science, with the aim of identifying relevant studies published until July 10th, 2023. The diagnostic accuracy was summarized using the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC). The researchers utilized Spearman's correlation coefficient for assessing the threshold effect, besides performing meta-regression and subgroup analysis for the exploration of possible heterogeneity sources. The quality assessment was conducted using the Quality Assessment of Diagnostic Accuracy Studies-2 and the Radiomics Quality Score (RQS).

Results

The meta-analysis included six studies conducted from 2018 to 2022, with 483 patients enrolled and LNM rates ranging from 27.2% to 59.4%. The pooled sensitivity, specificity, PLR, NLR, DOR, and AUC, along with their corresponding 95% CI, were 0.73 (0.67, 0.79), 0.76 (0.69, 0.83), 3.1 (2.3, 4.2), 0.35 (0.28, 0.44), 9 (6, 14), and 0.78 (0.74, 0.81), respectively. The results demonstrated the absence of significant heterogeneity in sensitivity, while significant heterogeneity was observed in specificity; no threshold effect was detected. The observed heterogeneity in the specificity was attributed to the sample size and CT-scan phases (P < 0.05). The included studies exhibited suboptimal quality, with RQS ranging from 14 to 16 out of 36. However, most of the enrolled studies exhibited a low-risk bias and minimal concerns relating to applicability.

Conclusion

The present meta-analysis indicated that CT-based radiomics demonstrated a favorable diagnostic performance in predicting LNM in EC. Nevertheless, additional high-quality, large-scale, and multicenter trials are warranted to corroborate these findings.

Systematic Review Registration

Open Science Framework platform at https://osf.io/5zcnd.

Prognostic value of Hematoxylin and eosin staining tumor-infiltrating lymphocytes (H&E-TILs) in patients with esophageal squamous cell carcinoma treated with chemoradiotherapy

BACKGROUND

Tumor-infiltrating lymphocytes (TILs) by routine hematoxylin and eosin staining (H&E-TILs) are a robust prognostic biomarker in various cancers. However, the role of H&E-TILs in esophageal squamous cell carcinoma (ESCC) treated with concurrent chemoradiotherapy (CCRT) has not been reported. The purpose of this study was to assess the prognostic value of H&E-TILs in ESCC treated with CCRT.

METHODS

The clinical data of 160 patients with ESCC treated with CCRT in our center between Jan. 2014 and Dec. 2021 were collected and retrospectively reviewed, and propensity score matching (PSM) analyses were performed. The H&E-TILs sections before CCRT were reassessed by two experienced pathologists independently. The H&E-TILs sections were classified into a positive group (+, > 10%) and a negative group (-, ≤ 10%) using 10% as the cutoff. The effects of H&E-TILs on overall survival (OS), progression-free survival (PFS), distant metastasis-free survival (DMFS), and locoregional recurrence-free survival (LRFS) were explored using the Kaplan‒Meier method, and the log-rank test was used to test the differences. Multivariable analysis was performed using the Cox proportion hazards model.

RESULTS

The short-term response to CCRT and the OS (P < 0.001), DMFS (P = 0.001), and LRFS (P < 0.001) rates were significantly different between the H&E-TILs (+) and H&E-TILs (-) groups. Subgroup analysis showed that H&E-TILs(+) with CR + PR group had a longer survival than H&E-TILs(-) with CR + PR, H&E-TILs(+) with SD + PD and H&E-TILs(-) with SD + PD group, respectively(P < 0.001). Furthermore, based on TCGA data, patients in the high TILs group had a better prognosis than those in the low TILs group. Multivariate analyses indicated that H&E-TILs and the short-term response to CCRT were the only two independent factors affecting OS, PFS, DMFS, and LRFS simultaneously, and H&E-TILs expression was associated with an even better prognosis for those patients with CR + PR.

CONCLUSIONS

H&E-TILs may be an effective and beneficial prognostic biomarker for ESCC patients treated with CCRT. Patients with H&E-TILs (+) with PR + CR would achieve excellent survival. Further prospective studies are required to validate the conclusions.

Development of a prognostic nomogram and risk stratification system for upper thoracic esophageal squamous cell carcinoma

Background

The study aimed to develop a nomogram model to predict overall survival (OS) and construct a risk stratification system of upper thoracic esophageal squamous cell carcinoma (ESCC).

Methods

Newly diagnosed 568 patients with upper ESCC at Fujian Medical University Cancer Hospital were taken as a training cohort, and additional 155 patients with upper ESCC from Sichuan Cancer Hospital Institute were used as a validation cohort. A nomogram was established using Cox proportional hazard regression to identify prognostic factors for OS. The predictive power of nomogram model was evaluated by using 4 indices: concordance statistics (C-index), time-dependent ROC (ROCt) curve, net reclassification index (NRI) and integrated discrimination improvement (IDI).

Results

In this study, multivariate analysis revealed that gender, clinical T stage, clinical N stage and primary gross tumor volume were independent prognostic factors for OS in the training cohort. The nomogram based on these factors presented favorable prognostic efficacy in the both training and validation cohorts, with concordance statistics (C-index) of 0.622, 0.713, and area under the curve (AUC) value of 0.709, 0.739, respectively, which appeared superior to those of the American Joint Committee on Cancer (AJCC) staging system. Additionally, net reclassification index (NRI) and integrated discrimination improvement (IDI) of the nomogram presented better discrimination ability to predict survival than those of AJCC staging. Furthermore, decision curve analysis (DCA) of the nomogram exhibited greater clinical performance than that of AJCC staging. Finally, the nomogram fairly distinguished the OS rates among low, moderate, and high risk groups, whereas the OS curves of clinical stage could not be well separated among clinical AJCC stage.

Conclusion

We built an effective nomogram model for predicting OS of upper ESCC, which may improve clinicians' abilities to predict individualized survival and facilitate to further stratify the management of patients at risk.

Influence of age as a continuous variable on survival outcomes and treatment options in patients with upper thoracic esophageal carcinoma

Background: This retrospective review of patients with upper thoracic esophageal squamous cell carcinoma (ESCC) analyzed the prognostic value of age, as a continuous variable, and offered insight into treatment options. Methods: 568 upper ESCC patients underwent radical therapy between 2004 and 2016. Age as a continuous variable was entered into the Cox regression model with penalized spline (P-spline) analysis to investigate a correlation between age and survival outcomes. Results: Before adjustment, P-spline regression revealed U-shaped survival curves. Sixty years was the optimal cut-off age for differences in overall and progression-free survival (OS, PFS). The cohort was divided into age groups ≤ 50, 51-69, and ≥ 70 years. Multivariate analyses showed no significant differences in either PFS or OS for patients aged ≤ 50 and 51-69 years. After adjusting for covariates, P-spline regression showed that the risk of mortality and disease progression increased with age, and ≥ 70 years was an unfavorable independent prognostic factor. For age ≥ 70 years, the OS and PFS associated with non-surgery was comparable to that of surgery. For patients younger, the OS and PFS of patients given surgery was significantly better than that of patients given non-surgery. Conclusion: Age was an independent prognostic factor for upper ESCC. Patients ≥ 70 years achieved no significant survival benefit from surgery, but for those younger than 70 years surgery was the preferred treatment option.

The Prognostic Significance of Nomogram-Based Pretreatment Inflammatory Indicators in Patients With Esophageal Squamous Cell Carcinoma Receiving Intensity-Modulated Radiotherapy

BACKGROUND

At present, there is no objective prognostic index available for patients with esophageal squamous cell carcinoma (ESCC) who underwent intensity-modulated radiotherapy (IMRT). This study is to develop a nomogram based on hematologic inflammatory indices for ESCC patients treated with IMRT.

METHODS

581 patients with ESCC receiving definitive IMRT were enrolled in our retrospective study. Of which, 434 patients with treatment-naïve ESCC in Fujian Cancer Hospital were defined as the training cohort. Additional 147 newly diagnosed ESCC patients were used as the validation cohort. Independent predictors of overall survival (OS) were employed to establish a nomogram model. The predictive ability was evaluated by time-dependent receiver operating characteristic curves, the concordance index (C-index), net reclassification index (NRI), and integrated discrimination improvement (IDI). Decision curve analysis (DCA) was performed to assess the clinical benefits of the nomogram model. The entire series was divided into 3 risk subgroups stratified by the total nomogram scores.

RESULTS

Clinical TNM staging, primary gross tumor volume, chemotherapy, neutrophil-to-lymphocyte ratio and platelet lymphocyte ratio were independent predictors of OS. Nomogram was developed incorporating these factors. Compared with the 8th American Joint Committee on Cancer (AJCC) staging, the C-index for 5-year OS (.627 and .629) and the AUC value of 5-year OS (.706 and .719) in the training and validation cohorts (respectively) were superior. Furthermore, the nomogram model presented higher NRI and IDI. DCA also demonstrated that the nomogram model provided greater clinical benefit. Finally, patients with <84.8, 84.8-151.4, and >151.4 points were categorized into low-risk, intermediate-risk, and high-risk groups. Their 5-year OS rates were 44.0%, 23.6%, and 8.9%, respectively. The C-index was .625, which was higher than the 8^th AJCC staging.

CONCLUSIONS

We have developed a nomogram model that enables risk-stratification of patients with ESCC receiving definitive IMRT. Our findings may serve as a reference for personalized treatment.

Prognostic values of the gross volume of metastatic lymph nodes in patients with esophageal squamous cell carcinoma treated with definitive concurrent chemoradiotherapy

Purpose

We aim to explore whether the gross volume of metastatic lymph nodes (GTVnd) and the gross volume of primary tumor (GTVp) could be prognostic factors for esophageal squamous cell carcinoma (ESCC) patients treated with definitive concurrent chemoradiotherapy (dCCRT).

Methods

We retrospectively analyzed 252 ESCC patients treated with dCCRT in the era of intensity-modulated radiation therapy (IMRT) at our institution. The cut-off value for the GTVnd derived from the restricted cubic splines (RCS) was determined. Univariate and multivariate Cox proportional hazard models were performed to determine the association between GTVnd and prognosis. we performed recursive partitioning analysis (RPA) method using GTVnd to develop a new risk stratification (TGTVndM). Moreover, the linear trend χ2, likelihood ratio χ2, and akaike information criterion (AIC) were used to determine the prognostic value between the TNM and TGTVndM staging systems.

Results

The five-year overall survival (OS) rate was 30.6%, with a median follow-up of 38 months. The cut-off value of GTVnd determined by the RCS was 4.35 cm3. GTVnd≥4.35 cm3 was an independent and significant negative prognostic factor for OS (HR=1.949, P&lt;0.001), progression free survival (PFS) (HR=1.425, P=0.048), and distance metastasis free survival (DMFS) (HR=2.548, P=0.001). In multivariable analysis, gender, clinical T stage, and GTVnd were independently associated with OS. RPA segregated patients into 3 prognostic groups: high risk (T1-4 GTVnd≥4.35, n=126, III stage), intermediate risk (T4 GTVnd&lt;4.35,n=38,II stage), and low risk(T1-3GTVnd&lt;4.35, n=88, I stage). The 5-year OS(P&lt;0.001), PFS (P=0.002), and DMFS (P=0.001) were significantly worse in high-risk group in comparison with the intermediate and low risk groups. Compared with the TNM staging system, the clinical T stage combined with GTVnd (TGTVndM) had a higher linear trend χ2 (26.38 versus 25.77), higher likelihood ratio χ2 (24.39 versus 20.69), and lower AIC (1255.07 versus 1260.06).

Conclusions

GTVnd may serve as a good prognostic factor in predicting distant metastasis and death for ESCC patients treated with dCCRT. The TGTVndM staging system demonstrated superior accuracy for predicting OS and could serve as a more effective prognostic guidance for unresectable ESCC patients.

Radiomics Analysis of Lymph Nodes with Esophageal Squamous Cell Carcinoma Based on Deep Learning

Purpose

To assess the role of multiple radiomic features of lymph nodes in the preoperative prediction of lymph node metastasis (LNM) in patients with esophageal squamous cell carcinoma (ESCC).

Methods

Three hundred eight patients with pathologically confirmed ESCC were retrospectively enrolled (training cohort, n = 216; test cohort, n = 92). We extracted 207 handcrafted radiomic features and 1000 deep radiomic features of lymph nodes from their computed tomography (CT) images. The t-test and least absolute shrinkage and selection operator (LASSO) were used to reduce the dimensions and select key features. Handcrafted radiomics, deep radiomics, and clinical features were combined to construct models. Models I (handcrafted radiomic features), II (Model I plus deep radiomic features), and III (Model II plus clinical features) were built using three machine learning methods: support vector machine (SVM), adaptive boosting (AdaBoost), and random forest (RF). The best model was compared with the results of two radiologists, and its performance was evaluated in terms of sensitivity, specificity, accuracy, area under the curve (AUC), and receiver operating characteristic (ROC) curve analysis.

Results

No significant differences were observed between cohorts. Ten handcrafted and 12 deep radiomic features were selected from the extracted features (p < 0.05). Model III could discriminate between patients with and without LNM better than the diagnostic results of the two radiologists.

Conclusion

The combination of handcrafted radiomic features, deep radiomic features, and clinical features could be used clinically to assess lymph node status in patients with ESCC.

The novel pretreatment immune prognostic index discriminates survival outcomes in locally advanced non-operative esophageal squamous cell carcinoma patients treated with definitive chemoradiotherapy: a 6-year retrospective study

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dNLR and LDH were correlated with OS and PFS in locally advanced ESCC patients received dCRT.

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The EIPI, a novel inflammatory-based and immune-related prognostic score, was an independent prognostic indicator in locally advanced ESCC.

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The risk stratification of EIPI can help set individualized treatment strategies and intensities for different subgroups of ESCC patients.

Objective

We aimed to construct risk stratification to help set individualized treatment strategies and intensities for different subgroups of patients.

Methods

The Esophagus Immune Prognostic Index (EIPI) scores were constructed according to the levels of derived neutrophil-to-lymphocyte ratio (dNLR) and lactate dehydrogenase (LDH) before treatment, and the patients were divided into low-, medium-, and high-risk groups. Finally, restricted cubic splines (RCS) were used to explore the relationship between dNLR, LDH, and survival outcomes.

Results

The median follow-up period of overall survival (OS) and progression-free survival (PFS) were 25.2 and 17.6 months, respectively. Multivariate Cox regression analysis showed dNLR were the independent prognostic factors that were associated with OS and PFS. The 3-year OS and PFS rates in the low-, medium-, and high-risk groups were 44.4% and 38.2%, 26.1% and 23.6%, and 10.5% and 5.3%, respectively. Patients who received chemotherapy had better OS and PFS than those who did not receive chemotherapy in low-risk and medium/high-risk groups (all p < 0.05). Besides, the results also revealed significant differences for patients with clinical T, N, and TNM stage groups of the OS and PFS in different risk groups. Finally, RCS analysis indicated a nonlinear relationship between the dNLR, LDH, and survival for esophageal squamous cell carcinoma (ESCC) patients. The death hazard ratios of dNLR and LDH sharply increased at 1.97 and 191, respectively.

Conclusions

In summary, the EIPI, a novel inflammatory-based and immune-related prognostic score, is an independent prognostic indicator in locally advanced ESCC patients undergoing definitive chemoradiotherapy (dCRT).

Esophageal wall thickness on CT scans: can it predict the T stage of primary thoracic esophageal squamous cell carcinoma?

BACKGROUND

CT is the most commonly used method to stage esophageal cancer (EC). However, the reported CT T-staging criteria for EC are controversial.

PURPOSE

To determine and validate the optimal esophageal wall thickness (EWT) threshold on CT to distinguish lesions with different T stages in esophageal squamous cell carcinoma (ESCC) patients.

METHODS

One thousand, one hundred-two consecutive patients with histopathologically confirmed ESCC between July 2014 and April 2020 were retrospectively reviewed. All patients underwent a preoperative CT examination and surgical treatment. The maximal EWT of the lesions on CT was measured. Patients were divided into pT1, pT2, pT3 and pT4 subgroups according to the pathologic stage. We employed the support vector machine, where linear kernels were leveraged to determine the optimal threshold to classify samples with different T stages. 90% of samples from each subgroup were randomly selected as the training set, while the remainder comprised the testing set.

RESULTS

The mean EWTs of the pT1, pT2, pT3 and pT4 subgroups were 4.9 ± 2.6 mm, 8.1 ± 2.3 mm, 12.4 ± 3.6 mm, and 18.6 ± 4.4 mm, respectively. Differences in the EWT between the four subgroups or between adjacent subgroups were significant (p < 0.001), and esophageal wall became thicker with increasing pT stage. We utilized MATLAB 2020a to implement the SVM model and ran the code 10 times. The accuracy of the model was 60.29 ± 2.33%. The thresholds between samples from pT1/pT2, pT2/pT3 and pT3/pT4 lesions were 5.5 ± 0.3 mm, 10.8 ± 0.8 mm and 15.9 ± 0.5 mm, respectively.

CONCLUSIONS

Possibility of predicting T stage of ESCC by EWT on CT scans was limited to 60% by model examination with large sample size.

Can Lymphovascular Invasion be Predicted by Preoperative Contrast-Enhanced CT in Esophageal Squamous Cell Carcinoma?

Objective: To explore whether preoperative contrast-enhanced computed tomogrpahy (CT) can predict lymphovascular invasion (LVI) in esophageal squamous cell carcinoma (ESCC), and provide a reliable reference for the formulation of clinical individualized treatment plans. Methods: This retrospective study enrolled 228 patients with surgically resected and pathologically confirmed ESCC, including 36 patients with LVI and 192 patients without LVI. All patients underwent contrast-enhanced CT (CECT) scan within 2 weeks before the operation. Tumor size (including tumor length and maximum tumor thickness), tumor-to-normal wall enhancement ratio (TNR), and gross tumor volume (GTV) were obtained. All clinical features and CECT-derived parameters associated with LVI were analyzed by univariate and multivariate analysis. The independent predictors for LVI were identified, and their combination was built by multivariate logistic regression analysis, using the significant variables from the univariate analysis as inputs. Results: Univariate analysis of clinical features and CECT-derived parameters revealed that age, TNR, and clinical N stage (cN stage) were significantly associated with LVI. The multivariable analysis results demonstrated that age (odds ratio [OR]: 5.32, 95% confidence interval [CI]: 2.224-12.743, P<.001), TNR (OR: 5.399, 95% CI: 1.609-18.110, P  =  .006), and cN stage (cN1: OR: 2.874, 95% CI: 1.182-6.989, P  =  .02; cN2: OR: 6.876, 95% CI: 2.222-21.227) were identified to be independent predictors for LVI. The combination of age, TNR, and cN stage achieved a relatively higher area under the curve (AUC) (0.798), accuracy (ACC) (65.4%), sensitivity (SEN) (69.4%), specificity (SPE) (79.7%), positive predictive value (PPV) (77.4%), and negative predictive value (NPV) (71.6%). Conclusions: The combination of clinical features and CECT-derived parameters may be effective in predicting LVI status preoperatively in ESCC.

Primary gross tumor volume is prognostic and suggests treatment in upper esophageal cancer

Background

To aid clinicians strategizing treatment for upper esophageal squamous cell carcinoma (ESCC), this retrospective study investigated associations between primary gross tumor volume (GTVp) and prognosis in patients given surgical resection, radiotherapy, or both resection and radiotherapy.

Methods

The population comprised 568 patients with upper ESCC given definitive treatment, including 238, 216, and 114 who underwent surgery, radiotherapy, or combined radiotherapy and surgery. GTVp as a continuous variable was entered into the multivariate Cox model using penalized splines (P-splines) to determine the optimal cutoff value. Propensity score matching (PSM) was used to adjust imbalanced characteristics among the treatment groups.

Results

P-spline regression revealed a dependence of patient outcomes on GTVp, with 30 cm³ being an optimal cut-off for differences in overall and progression-free survival (OS, PFS). GTVp ≥30 cm³ was a negative independent prognostic factor for OS and PFS. PSM analyses confirmed the prognostic value of GTVp. For GTVp < 30 cm³, no significant survival differences were observed among the 3 treatments. For GTVp ≥30 cm³, the worst 5-year OS rate was experienced by those given surgery. The 5-year PFS rate of patients given combined radiotherapy and surgery was significantly better than that of patients given radiotherapy. The surgical complications of patients given the combined treatment were comparable to those who received surgery, but radiation side effects were significantly lower.

Conclusion

GTVp is prognostic for OS and PFS in upper ESCC. For patients with GTVp ≥30 cm³, radiotherapy plus surgery was more effective than either treatment alone.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08838-w.

Tumor size measured by multidetector CT in resectable colon cancer: correlation with regional lymph node metastasis and N stage

Background

Lymph node metastasis (LNM) is a risk factor for poor long-term outcomes and a prognostic factor for disease-free survival in colon cancer. Preoperative lymph node status evaluation remains a challenge. The purpose of this study is to determine whether tumor size measured by multidetector computed tomography (MDCT) could be used to predict LNM and N stage in colon cancer.

Material and methods

One hundred six patients with colon cancer who underwent radical surgery within 1 week of MDCT scan were enrolled. Tumor size including tumor length (Tlen), tumor maximum diameter (Tdia), tumor maximum cross-sectional area (Tare), and tumor volume (Tvol) were measured to be correlated with pathologic LNM and N stage using univariate logistic regression analysis, multivariate logistic analysis, and receiver operating characteristic (ROC) curve analysis.

Results

The inter- and intraobserver reproducibility of Tlen (intraclass correlation coefficient [ICC] = 0.94, 0.95, respectively), Tdia (ICC = 0.81, 0.93, respectively), Tare (ICC = 0.97, 0.91, respectively), and Tvol (ICC = 0.99, 0.99, respectively) parameters measurement are excellent. Univariate logistic regression analysis showed that there were significant differences in Tlen, Tdia, Tare, and Tvol between positive and negative LNM (p < 0.001, 0.001, < 0.001, < 0.001, respectively). Multivariate logistic regression analysis revealed that Tvol was independent risk factor for predicting LNM (odds ratio, 1.082; 95% confidence interval for odds ratio, 1.039, 1.127, p<0.001). Tlen, Tdia, Tare, and Tvol could distinguish N0 from N1 stage (p < 0.001, 0.041, < 0.001, < 0.001, respectively), N0 from N2 (all p < 0.001), N0 from N1-2 (p < 0.001, 0.001, < 0.001, < 0.001, respectively), and N0-1 from N2 (p < 0.001, 0.001, < 0.001, < 0.001, respectively). The area under the ROC curve (AUC) was higher for Tvol than that of Tlen, Tdia, and Tare in identifying LNM (AUC = 0.83, 0.82, 0.69, 0.79), and distinguishing N0 from N1 stage (AUC = 0.79, 0.78, 0.63, 0.74), N0 from N2 stage (AUC = 0.92, 0.89, 0.80, 0.89, respectively), and N0-1 from N2 stage (AUC = 0.84, 0.79, 0.76, 0.83, respectively).

Conclusion

Tumor size was correlated with regional LNM in resectable colon cancer. In particularly, Tvol showed the most potential for noninvasive preoperative prediction of regional LNM and N stage.

Contrast-Enhanced CT-Based Radiomics Analysis in Predicting Lymphovascular Invasion in Esophageal Squamous Cell Carcinoma

Objectives

To develop a radiomics model based on contrast-enhanced CT (CECT) to predict the lymphovascular invasion (LVI) in esophageal squamous cell carcinoma (ESCC) and provide decision-making support for clinicians.

Patients and Methods

This retrospective study enrolled 334 patients with surgically resected and pathologically confirmed ESCC, including 96 patients with LVI and 238 patients without LVI. All enrolled patients were randomly divided into a training cohort and a testing cohort at a ratio of 7:3, with the training cohort containing 234 patients (68 patients with LVI and 166 without LVI) and the testing cohort containing 100 patients (28 patients with LVI and 72 without LVI). All patients underwent preoperative CECT scans within 2 weeks before operation. Quantitative radiomics features were extracted from CECT images, and the least absolute shrinkage and selection operator (LASSO) method was applied to select radiomics features. Logistic regression (Logistic), support vector machine (SVM), and decision tree (Tree) methods were separately used to establish radiomics models to predict the LVI status in ESCC, and the best model was selected to calculate Radscore, which combined with two clinical CT predictors to build a combined model. The clinical model was also developed by using logistic regression. The receiver characteristic curve (ROC) and decision curve (DCA) analysis were used to evaluate the model performance in predicting the LVI status in ESCC.

Results

In the radiomics model, Sphericity and gray-level non-uniformity (GLNU) were the most significant radiomics features for predicting LVI. In the clinical model, the maximum tumor thickness based on CECT (cThick) in patients with LVI was significantly greater than that in patients without LVI (P<0.001). Patients with LVI had higher clinical N stage based on CECT (cN stage) than patients without LVI (P<0.001). The ROC analysis showed that both the radiomics model (AUC values were 0.847 and 0.826 in the training and testing cohort, respectively) and the combined model (0.876 and 0.867, respectively) performed better than the clinical model (0.775 and 0.798, respectively), with the combined model exhibiting the best performance.

Conclusions

The combined model incorporating radiomics features and clinical CT predictors may potentially predict the LVI status in ESCC and provide support for clinical treatment decisions.

Radiation dose escalation can improve local disease control and survival among esophageal cancer patients with large primary tumor volume receiving definitive chemoradiotherapy

BACKGROUND

This study aimed to investigate the correlation between primary tumor volume and cancer failure patterns in esophageal squamous cell carcinoma (ESCC) treated with definitive concurrent chemoradiotherapy (CCRT) and examine whether increasing radiation dose can improve the outcome.

METHODS

We retrospectively reviewed 124 patients with stage III ESCC treated by definitive CCRT. The primary tumor volume calculated from the radiotherapy planning computed tomography scans was correlated to treatment response, time to disease progression, and overall survival. We further analyzed whether a higher radiation dose correlated with better disease control and patient survival.

RESULTS

Patients with poor CCRT response had a larger primary tumor volume than those with good response (97.9 vs 64.3 cm3, P = 0.032). The optimal cutoff value to predict CCRT response was 55.3 cm3. Large primary tumor volume (≥ 55.3 cm3) correlated with shorter time to tumor progression in the esophagus (13.6 vs 48.6 months, P = 0.033) compared with small tumor volume (< 55.3 cm3). For the large esophageal tumors (≥ 55.3 cm3), radiation dose > 60 gray significantly prolonged the time to tumor progression in esophagus (20.3 vs 10.1 months, P = 0.036) and overall survival (12.2 vs 8.0 months, P = 0.030), compared with dose ≤ 60 gray. In contrast, higher radiation dose did not benefit local disease control or overall survival in the small esophageal tumors (< 55.3 cm3).

CONCLUSION

Large primary tumor volume correlates with poor local control and overall survival in ESCC treated with definitive CCRT. Radiation dose > 60 gray can improve the outcomes in patients with large primary tumor. Further prospective dose escalation trials are warranted.

Prognostic Significance of Baseline Neutrophil Count and Lactate Dehydrogenase Level in Patients With Esophageal Squamous Cell Cancer Treated With Radiotherapy

Background: This present study aimed to explore the prognostic value of pretreatment neutrophil and lactate dehydrogenase (LDH) and to develop a prognostic risk scoring model to predict prognosis in esophageal squamous cell cancer (ESCC) patients treated with definitive radiotherapy.

Methods: Retrospectively collected data of patients who received definitive radiotherapy for ESCC at Shantou Central Hospital between January 2009 and December 2015 were included for the analysis. The association between the level of LDH and neutrophil and clinicopathological characteristics were analyzed. We performed univariate and multivariate analyses to identify the prognostic predictors for patients with ESCC. Based on the results, we also developed a prognostic risk scoring model and assessed its predictive ability in the subgroups.

Results: A total of 567 patients who received definitive radiotherapy for ESCC were included in the present study. The optimal cutoff values were 4.5 × 10⁹/L, 3.25, and 220 U/L for neutrophil, neutrophil-to-lymphocyte ratio (NLR), and LDH, respectively. A high level of LDH was significantly associated with advanced N stage (p = 0.031), and neutrophil count was significantly associated with gender (p = 0.001), T stage (p < 0.001), N stage (p = 0.019), clinical stage (p < 0.001), and NLR (p < 0.001). Multivariate survival analysis identified gender (p = 0.006), T stage (p < 0.001), N stage (p = 0.008), treatment modality (p < 0.001), LDH level (p = 0.012), and neutrophil count (p = 0.038) as independent prognostic factors for overall survival. Furthermore, a new prognostic risk scoring (PRS) model based on six prognostic factors was developed, in which the patients were divided into three groups with distinct prognosis (χ2 = 67.94, p < 0.0001).

Conclusions: Elevated baseline LDH level and neutrophil count predicted poor prognosis for ESCC patients treated with definitive radiotherapy. A PRS model comprised of LDH, neutrophil count, and other prognostic factors would help identify the patients who would benefit the most from definitive radiotherapy.

Does chemoradiotherapy benefit elderly patients with esophageal squamous cell cancer? A propensity-score matched analysis on multicenter data (3JECROG R-03A)

Background

The aim of the present study was to assess the efficacy of concurrent chemoradiotherapy (CRT) or radiotherapy alone (RT-alone) in elderly patients with esophageal squamous cell carcinoma (ESCC).

Methods

The clinical data of patients with ESCC treated with RT-alone or CRT were collected and retrospectively reviewed. The 1-, 3- and 5-year overall survival (OS) rates and the clinical characteristics correlated with survival were analyzed statistically. Propensity score matching (PSM) analyses were used to compensate for differences in baseline characteristics between the CRT and RT-alone groups to confirm the survival difference.

Results

A total of 729 patients fulfilling the inclusion criteria were reviewed. Diabetes, primary tumor volume (pTV), primary tumor location (pTLo), clinical T stage,(cT) clinical N stage (cN), clinical M stage (cM) and short-term response to RT were independent factors influencing OS (P = 0.002–0.044). The 5-year OS rate was 26.6, 26.0 and 30.1% in the whole cohort, RT-alone and CRT groups, respectively. The survival difference between RT alone and CRT was not significant before or following PSM. Compared with the corresponding subgroups treated with RT alone, CRT significantly benefited patients with diabetes (P = 0.003), cT4 (P = 0.030) and cN0 (P = 0.049), whereas no benefit was identified between CRT and RT alone in the other subgroups, including cT1–3, cN1, cM, pTLo, pTV, age and gender.

Conclusions

CRT with the current chemotherapy regimens may not improve the survival of elderly ESCC patients compared to RT-alone, except in patients with cT4 stage, cN0 stage or diabetes. However, due to the limitation of the retrospective nature of the current study, further clinical trials are required for confirmation.