Prognostic value of tumour deposit and perineural invasion status in colorectal cancer patients: a SEER-based population study

Evaluating the prognostic significance of tumor deposits in gastric cancer and strategies for their integration into the TNM staging system: a single-center retrospective study

PURPOSE

To propose a new optimal strategy for incorporating tumor deposit (TD) into TNM staging.

METHODS

Totally, 2730 consecutive gastric cancer (GC) patients were included according to the presence and count of TDs between January 2011 and December 2014. Overall survival (OS) was analyzed using Cox regression and propensity score matching (PSM). The relationship between the number of TDs and GC patients' prognosis was analyzed using restricted cubic spline curves and compared with the prognostic value of lymph node metastases (LNMs). Harrell's C-index (C-index) and the Akaike information criterion (AIC) were employed to assess the prognostic performance of different staging systems.

RESULTS

The positive rate of TD was 9.67% (264/2730). The presence of TD was associated with poorer OS before PSM (hazard ratio (HR): 3.31; 95% confidence interval (CI): 2.84, 3.85) and after PSM (HR: 1.62; 95%CI: 1.31, 2.00). The modified TNM staging, equating one TD to four LNMs, achieved superior prognostic performance, surpassing the 8th edition AJCC TNM staging and other modified systems (C-index: 0.751, AIC: 15954.0). In this system, 12.04% (26/216) of TD-positive patients were upstaged from stage II to stage III. These upstaged patients had worse outcomes than the remaining stage II patients (HR: 10.97; 95% CI: 4.55-26.44), while outcomes were similar to those of original stage III patients (HR:1.08; 95%CI: 0.66, 1.78).

CONCLUSION

The presence and increased number of TDs were noted to be associated with GC patients' poor prognosis. Integrating TD count with LNMs could enhance the prognostic accuracy of the TNM staging system.

Aggressive characteristics of tumor deposits in colorectal cancer highlight the need for staging refinement in patients with 0-3 metastatic lymph nodes

Accurate staging is essential for the optimal management of patients with colorectal cancer (CRC). The role of tumor deposits (TDs) in CRC staging has been contentious due to a lack of comprehensive understanding of their clinical and biological traits. In this retrospective study, we analyzed large data from 5718 CRC patients diagnosed between 2011 and 2022, ensuring rigorous data collection and long-term follow-up. Patients with positive TDs displayed aggressive clinical features. The risk factors for TDs varied among patients with different backgrounds of lymph node (LN) involvement, and the numbers of TDs and metastatic LNs showed a significantly positive correlation. TDs significantly impacted CRC prognosis, resulting in unfavorable outcomes irrespective of LN status. To delve into the biological characteristics of TDs, we performed transcriptome sequencing, immunohistochemistry, and Kaplan-Meier analyses on tissue samples from the additional CRC cohort and The Cancer Genome Atlas datasets. TDs exhibited aggressive biological phenotypes that were distinct from primary tumors and metastatic LNs, characterized by elevated signatures of epithelial-mesenchymal transition, angiogenesis, and immune suppression. Cox proportional hazards analysis was then applied to reassess the appropriate role of TDs within the TNM staging system, revealing that the prognostic weightiness of TDs in CRC corresponded to N2a rather than N1 in patients with 0-3 LN metastases. Overall, our comprehensive analysis showed that TDs, with their aggressive clinical and biological characteristics, could optimize the staging of CRC, highlighting the need to refine their role within the TNM staging system.

Predictive Study of Machine Learning-Based Multiparametric MRI Radiomics Nomogram for Perineural Invasion in Rectal Cancer: A Pilot Study

This study aimed to establish and validate the efficacy of a nomogram model, synthesized through the integration of multi-parametric magnetic resonance radiomics and clinical risk factors, for forecasting perineural invasion in rectal cancer. We retrospectively collected data from 108 patients with pathologically confirmed rectal adenocarcinoma who underwent preoperative multiparametric MRI at the First Affiliated Hospital of Bengbu Medical College between April 2019 and August 2023. This dataset was subsequently divided into training and validation sets following a ratio of 7:3. Both univariate and multivariate logistic regression analyses were implemented to identify independent clinical risk factors associated with perineural invasion (PNI) in rectal cancer. We manually delineated the region of interest (ROI) layer-by-layer on T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) sequences and extracted the image features. Five machine learning algorithms were used to construct radiomics model with the features selected by least absolute shrinkage and selection operator (LASSO) method. The optimal radiomics model was then selected and combined with clinical features to formulate a nomogram model. The model performance was evaluated using receiver operating characteristic (ROC) curve analysis, and its clinical value was assessed via decision curve analysis (DCA). Our final selection comprised 10 optimal radiological features and the SVM model showcased superior predictive efficiency and robustness among the five classifiers. The area under the curve (AUC) values of the nomogram model were 0.945 (0.899, 0.991) and 0.846 (0.703, 0.99) for the training and validation sets, respectively. The nomogram model developed in this study exhibited excellent predictive performance in foretelling PNI of rectal cancer, thereby offering valuable guidance for clinical decision-making. The nomogram could predict the perineural invasion status of rectal cancer in early stage.

The prognostic impact of tumor deposits in colorectal cancer: More than just N1c

BACKGROUND

The identification of tumor deposits (TD) currently plays a limited role in staging for colorectal cancer (CRC) aside from N1c lymph node designation. The objective of this study was to determine the prognostic impact, beyond American Joint Committee on Cancer N1c designation, of TDs among patients with primary CRC.

METHODS

Patients who had resected stage I-III primary CRC diagnosed between 2010 and 2019 were identified from the National Cancer Institute's Surveillance, Epidemiology, and End Results database. Cancer-specific survival (CSS) stratified by TD status and lymph node (N) status was calculated using the Kaplan-Meier method and multivariable Cox proportional hazards regression analyses.

RESULTS

In total, 147,783 patients with primary CRC were identified. TDs were present in 15,444 patients (10.5%). The presence of TDs was significantly associated with adverse tumor characteristics, including advanced pathologic stage, nodal status, and metastasis status. The presence of TDs was associated with worse CSS (hazard ratio [HR], 3.12; 95% confidence interval [CI], 3.02-3.22), as it was for each given N category (e.g., N2a and TD-negative [HR, 2.50; 95% CI, 2.37-2.64] vs. N2a and TD-positive [HR, 3.75; 95% CI, 3.49-4.03]). The presence of multiple TDs was also associated with decreased CSS for each given N category compared with a single TD (e.g. N2a with one TD [HR, 3.09; 95% CI, 2.65-3.61] vs. N2a with two or more TDs [HR, 4.32; 95% CI, 3.87-4.82]).

CONCLUSIONS

TDs were identified as an independent predictor of a worse outcome in patients with CRC. The presence of TDs confers distinctly different CSS and provides important prognostic information among patients with CRC and warrants further investigation as a unique variable in future iterations of CRC staging.

Localized Rectal Cancer: Indian Consensus and Guidelines

The rising incidence of colorectal cancer (CRC) in India, particularly the prevalence of rectal cancer over colon cancer (0.7:1), has been a growing concern in recent decades; especially notable is the trend of increasing cases among young CRC patients. Given the diverse treatment approaches for rectal cancer globally and the varying economic capacities of patients in low to middle-income countries (LMICs) like India, it is essential to establish consensus guidelines that are specifically tailored to meet the needs of these patients. To achieve this, a panel comprising 30 eminent rectal cancer experts convened to conduct a comprehensive and impartial evaluation of existing practices and recent advancements in the field. Through meticulous scrutiny of published literature and a consensus-building process that involved voting on pertinent questions, the panel formulated management strategies. These recommendations are the result of a rigorous, evidence-based process and encapsulate the collective wisdom and judgment of leading authorities in the field.

Tumor Deposits as an Adverse Prognostic Indicator in Stage III Colon Cancer: A Multicenter Database Study

Objective

We explored the oncological impact of tumor deposits (TDs) on colon cancer and proposed optimal modifications to the current staging system.

Background

In the existing American Joint Committee on Cancer colon cancer staging system, TDs are incorporated into the N category as N1c. When lymph node metastases (LNMs) are present, their number is considered to determine nodal stages, such as N1a/b or N2a/b, regardless of TDs.

Methods

4212 patients with primary colon cancer who underwent surgical resection in the Seoul Colorectal Group (2010-2020) and 93,057 patients from the Surveillance, Epidemiology, and End Results*Stat database (2000-2017) were included in this study. Patients were classified according to the number of metastatic lymph nodes (LNs) (0/1-3/≥4) and the presence of TDs.

Results

TDs were significantly associated with left colon cancer, a higher T category, and vascular/perineural invasion. Patients with TDs had higher recurrence rates (23.1 vs 7.5%, P < 0.001). The TD-positive patients had notably worse overall survival (OS) and recurrence-free survival rates. The survival outcomes of TD-positive patients without LNM were inferior to those of TD-negative patients with LN1-3 (5-year OS: 78.9 vs 87.8%, P = 0.04). The survival outcomes of TD-positive patients with LN1-3 were similar to those of TD-negative patients with LN ≥4 (5-year OS: 87.0 vs 77.1%, P = 0.11). Survival outcomes obtained using the Surveillance, Epidemiology, and End Results *Stat database yielded consistent results.

Conclusions

TDs were associated with poor prognostic factors and had a significant impact on survival outcomes. The incorporation of tumor deposits into nodal classifications beyond the current N1c criteria may improve the staging system and more accurately reflect the recurrence and survival rates among patients with colon cancer. TD-positive in N1a or N1b could be categorized as N2.

An internally and externally validated nomogram for predicting cancer-specific survival in octogenarians after radical resection for colorectal cancer

AIMS

We aimed to develop an elaborative nomogram that predicts cancer-specific survival (CSS) in American and Chinese octogenarians treated with radical resection for CRC.

METHODS

The patient data of newly diagnosed patients aged 80 years or older who underwent radical resection for CRC from 2010 to 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and then randomly divided into a training cohort and a validation cohort. The patients collected from our hospital were defined as the external validation cohort. Univariate and multivariate Cox regression was used to select independent predictive factors for the construction of a nomogram to predict 1-, 2- and 3-year CSS.

RESULTS

The multivariate Cox regression model identified age, T stage, N stage, perineural invasion, chemotherapy, tumour deposits, carcinoembryonic antigen level, number of lymph node metastases, and number of solid organ metastases as independent predictors of survival. The C-index of the nomogram for 1-, 2- and 3-year CSS was 0.758, 0.762, and 0.727, respectively, demonstrating significant clinical value and substantial reliability compared to the TNM stage. The calibration curve and area under the curve also indicated considerable predictive accuracy. In addition, decision curve analysis demonstrated desirable net benefits in clinical application.

CONCLUSION

We constructed a nomogram for predicting the CSS of individual octogenarian patients with CRC who underwent radical resection. The nomogram performed better than the TNM staging system in this particular population and could guide clinicians in clinical follow-up and individual therapeutic plan formulation.

Radiomics based on T2-weighted and diffusion-weighted MR imaging for preoperative prediction of tumor deposits in rectal cancer

AIM

Preoperative diagnosis of tumor deposits (TDs) in patients with rectal cancer remains a challenge. This study aims to develop and validate a radiomics nomogram based on the combination of T2-weighted (T2WI) and diffusion-weighted MR imaging (DWI) for the preoperative identification of TDs in rectal cancer.

MATERIALS AND METHODS

A total of 199 patients with rectal cancer who underwent T2WI and DWI were retrospectively enrolled and divided into a training set (n ​= ​159) and a validation set (n ​= ​40). The total incidence of TDs was 37.2 ​% (74/199). Radiomics features were extracted from T2WI and apparent diffusion coefficient (ADC) images. A radiomics nomogram combining Rad-score (T2WI ​+ ​ADC) and clinical factors was subsequently constructed. The area under the receiver operating characteristic curve (AUC) was then calculated to evaluate the models. The nomogram is also compared to three machine learning model constructed based on no-Rad scores.

RESULTS

The Rad-score (T2WI ​+ ​ADC) achieved an AUC of 0.831 in the training and 0.859 in the validation set. The radiomics nomogram (the combined model), incorporating the Rad-score (T2WI ​+ ​ADC), MRI-reported lymph node status (mLN-status), and CA19-9, showed good discrimination of TDs with an AUC of 0.854 for the training and 0.923 for the validation set, which was superior to Random Forests, Support Vector Machines, and Deep Learning models. The combined model for predicting TDs outperformed the other three machine learning models showed an accuracy of 82.5 ​% in the validation set, with sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 66.7 ​%, 92.0 ​%, 83.3 ​%, and 82.1 ​%, respectively.

CONCLUSION

The radiomics nomogram based on Rad-score (T2WI ​+ ​ADC) and clinical factors provides a promising and effective method for the preoperative prediction of TDs in patients with rectal cancer.

MRI-detected tumor deposits in cT3 and cT4 rectal cancer following neoadjuvant chemoradiotherapy

OBJECTIVES

To evaluate the identification of tumor deposits (TDs) and the prognostic significance of an MRI tumor regression grade for TDs in patients with rectal cancer treated with neoadjuvant chemoradiotherapy (nCRT).

METHODS

Ninety-one patients with cT3 or cT4 rectal cancer who underwent surgery following nCRT between August 2014 and June 2020 were retrospectively analyzed. Changes in pre-nCRT MRI-detected TDs (mrTDs) were described as mrTD regression grade. The diagnostic performance of post-nCRT MRI-detected TDs (ymrTDs) was compared with histopathological reference standard. The correlation between ymrTDs, mrTD regression grade, and disease-free survival (DFS) was assessed.

RESULTS

The sensitivity and specificity of ymrTDs were 88.00% and 89.39%, respectively. The area under the receiver operating characteristic curve was 0.887 (95% confidence interval [CI]: 0.803-0.944). The 3-year DFS of patients with positive ymrTDs was significantly lower than of the negative group (44.83% vs 82.73%, p < 0.001). The 3-year DFS was 33.33% for patients with poor regression of mrTDs following nCRT and 55.56% for those with moderate regression, compared to 69.23% in good responders and 83.97% in patients without mrTDs (p < 0.001). On multivariable Cox regression, mrTD regression grade was the only independent MRI factor associated with DFS (p = 0.042).

CONCLUSIONS

Diagnostic performance of ymrTDs was moderate. The mrTD regression grade was independently correlated with DFS, which may have a prognostic implication for treatment and follow-up.

CLINICAL RELEVANCE STATEMENT

Patients with poor regression of MRI-detected tumor deposits may benefit from more aggressive treatments, such as chemoradiation therapy plus induction or consolidation chemotherapy.

KEY POINTS

• MRI provides a preoperative and noninvasive way to visualize tumor deposits (TDs) after neoadjuvant chemoradiotherapy (nCRT). • Post-nCRT MRI-detected TDs are a poor prognostic marker in cT3 and cT4 rectal cancer patients. • The regression of MRI-detected TDs after nCRT is associated with an improved disease-free survival.

Pathological-Features-Modified TNM Staging System Improves Prognostic Accuracy for Rectal Cancer

BACKGROUND

Variations in survival outcomes are observed in the eighth edition of the American Joint Committee on Cancer TNM staging system.

OBJECTIVE

Machine learning ensemble methods were used to develop and evaluate the effectiveness of a pathological-features-modified TNM staging system in predicting survival for patients with rectal cancer by use of commonly reported pathological features, such as histological grade, tumor deposits, and perineural invasion, to improve the prognostic accuracy.

DESIGN

This was a retrospective population-based study.

SETTINGS

Data were assessed from the database of the Surveillance, Epidemiology, and End Results Program.

PATIENTS

The study cohort comprised 14,468 patients with rectal cancer diagnosed between 2010 and 2015. The development cohort included those who underwent surgery as the primary treatment, whereas patients who received neoadjuvant therapy were assigned to the validation cohort.

MAIN OUTCOME MEASURES

The primary outcome measures included cumulative rectal cancer survival, adjusted HRs, and both calibration and discrimination statistics to evaluate model performance and internal validation.

RESULTS

Multivariable Cox regression analysis identified all 3 pathological features as prognostic factors, after which patients were categorized into 4 pathological groups based on the number of pathological features (ie, 0, 1, 2, and 3). Distinct survival differences were observed among the groups, especially with patients with stage III rectal cancer. The proposed pathological-features-modified TNM staging outperformed the TNM staging in both the development and validation cohorts.

LIMITATIONS

Retrospective in design and lack of external validation.

CONCLUSIONS

The proposed pathological-features-modified TNM staging could complement the current TNM staging by improving the accuracy of survival estimation of patients with rectal cancer. See Video Abstract .

EL SISTEMA DE ESTADIFICACIN TNM CON CARACTERSTICAS PATOLGICAS MODIFICADO MEJORA LA PRECISIN DEL PRONSTICO DEL CNCER DE RECTO

ANTECEDENTES:Se observan variaciones en los resultados de supervivencia en el sistema de estadificación TNM del Comité Conjunto Americano del Cáncer 8º ediciónOBJETIVO:Se utilizaron métodos conjuntos de aprendizaje automático para desarrollar y evaluar la eficacia de un sistema de estadificación con características patológicas modificadas de tumores, ganglios y metástasis para predecir la supervivencia de pacientes con cáncer de recto, utilizando algunas características patológicas comúnmente informadas, como el grado histológico, depósitos tumorales e invasión perineural, para mejorar la precisión del pronóstico.DISEÑO:Este fue un estudio retrospectivo de base poblacional.ENTERNO CLINICO:Se recuperaron y evaluaron datos de la base de datos de Vigilancia, Epidemiología y Resultados Finales.PACIENTES:La cohorte del estudio estuvo compuesta por 14,468 pacientes con cáncer de recto diagnosticados entre 2010 y 2015. La cohorte de desarrollo incluyó a aquellos que se sometieron a cirugía como tratamiento primario, mientras que los pacientes que recibieron terapia neoadyuvante fueron asignados a la cohorte de validación.PRINCIPALES MEDIDAS DE RESULTADO:Las medidas de resultado primarias incluyeron supervivencia acumulada del cáncer de recto, índices de riesgo ajustados y estadísticas de calibración y discriminación para evaluar el rendimiento del modelo y la validación interna.RESULTADOS:El análisis de regresión multivariable de Cox identificó las tres características patológicas como factores pronósticos, después de lo cual los pacientes se clasificaron en cuatro grupos patológicos según el número de características patológicas (es decir, 0, 1, 2 y 3). Se observaron distintas diferencias en la supervivencia entre los grupos, especialmente en los pacientes en estadio III. La estadificación propuesta con características patológicas modificadas de tumores-ganglios-metástasis superó a la estadificación TNM tanto en las cohortes de desarrollo como en las de validación.LIMITACIONES:Diseño retrospectivo y falta de validación externa.CONCLUSIONES:La estadificación propuesta con características patológicas modificadas de tumores-ganglios-metástasis podría complementar la estadificación TNM actual al mejorar la precisión de la estimación de supervivencia de los pacientes con cáncer de recto. (Traducción- Dr. Francisco M. Abarca-Rendon ).

The value of machine learning based on CT radiomics in the preoperative identification of peripheral nerve invasion in colorectal cancer: a two-center study

BACKGROUND

We aimed to explore the application value of various machine learning (ML) algorithms based on multicenter CT radiomics in identifying peripheral nerve invasion (PNI) of colorectal cancer (CRC).

METHODS

A total of 268 patients with colorectal cancer who underwent CT examination in two hospitals from January 2016 to December 2022 were considered. Imaging and clinicopathological data were collected through the Picture Archiving and Communication System (PACS). The Feature Explorer software (FAE) was used to identify the peripheral nerve invasion of colorectal patients in center 1, and the best feature selection and classification channels were selected. Finally, the best feature selection and classifier pipeline were verified in center 2.

RESULTS

The six-feature models using RFE feature selection and GP classifier had the highest AUC values, which were 0.610, 0.699, and 0.640, respectively. FAE generated a more concise model based on one feature (wavelet-HLL-glszm-LargeAreaHighGrayLevelEmphasis) and achieved AUC values of 0.614 and 0.663 on the validation and test sets, respectively, using the "one standard error" rule. Using ANOVA feature selection, the GP classifier had the best AUC value in a one-feature model, with AUC values of 0.611, 0.663, and 0.643 on the validation, internal test, and external test sets, respectively. Similarly, when using the "one standard error" rule, the model based on one feature (wave-let-HLL-glszm-LargeAreaHighGrayLevelEmphasis) achieved AUC values of 0.614 and 0.663 on the validation and test sets, respectively.

CONCLUSIONS

Combining artificial intelligence and radiomics features is a promising approach for identifying peripheral nerve invasion in colorectal cancer. This innovative technique holds significant potential for clinical medicine, offering broader application prospects in the field.

CRITICAL RELEVANCE STATEMENT

The multi-channel ML method based on CT radiomics has a simple operation process and can be used to assist in the clinical screening of patients with CRC accompanied by PNI.

KEY POINTS

• Multi-channel ML in the identification of peripheral nerve invasion in CRC. • Multi-channel ML method based on CT-radiomics can detect the PNI of CRC. • Early preoperative identification of PNI in CRC is helpful to improve the formulation of treatment strategies and the prognosis of patients.

Union With Recursive Feature Elimination: A Feature Selection Framework to Improve the Classification Performance of Multicategory Causes of Death in Colorectal Cancer

Despite the use of machine learning tools, it is challenging to properly model cause-specific deaths in colorectal cancer (CRC) patients and choose appropriate treatments. Here, we propose an interesting feature selection framework, namely union with recursive feature elimination (U-RFE), to select the union feature sets that are crucial in CRC progression-specific mortality using The Cancer Genome Atlas (TCGA) dataset. Based on the union feature sets, we compared the performance of 5 classification algorithms, including logistic regression (LR), support vector machines (SVM), random forest (RF), eXtreme gradient boosting (XGBoost), and Stacking, to identify the best model for classifying 4-category deaths. In the first stage of U-RFE, LR, SVM, and RF were used as base estimators to obtain subsets containing the same number of features but not exactly the same specific features. Union analysis of the subsets was then performed to determine the final union feature set, effectively combining the advantages of different algorithms. We found that the U-RFE framework could improve various models' performance. Stacking outperformed LR, SVM, RF, and XGBoost in most scenarios. When the target feature number of the RFE was set to 50 and the union feature set contained 298 deterministic features, the Stacking model achieved F1_weighted, Recall_weighted, Precision_weighted, Accuracy, and Matthews correlation coefficient of 0.851, 0.864, 0.854, 0.864, and 0.717, respectively. The performance of the minority categories was also significantly improved. Therefore, this recursive feature elimination-based approach of feature selection improves performances of classifying CRC deaths using clinical and omics data or those using other data with high feature redundancy and imbalance.

Development and validation of a combined nomogram for predicting perineural invasion status in rectal cancer via computed tomography-based radiomics

AIM

This study aimed to create and validate a clinic-radiomics nomogram based on computed tomography (CT) imaging for predicting preoperative perineural invasion (PNI) of rectal cancer (RC).

MATERIAL AND METHODS

This study enrolled 303 patients with RC who were divided into training (n = 242) and test datasets (n = 61) in an 8:2 ratio with all their clinical outcomes. A total of 3,296 radiomic features were extracted from CT images. Five machine learning (ML) models (logistic regression (LR)/K-nearest neighbor (KNN)/multilayer perceptron (MLP)/support vector machine (SVM)/light gradient boosting machine (LightGBM)) were developed using radiomic features derived from the arterial and venous phase images, and the model with the best diagnostic performance was selected. By combining the radiomics and clinical signatures, a fused nomogram model was constructed.

RESULTS

After using the Mann-Whitney U-test and least absolute shrinkage and selection operator (LASSO) to remove redundant features, the MLP model proved to be the most efficient among the five ML models. The fusion nomogram based on MLP prediction probability further improves the ability to predict the PNI status. The area under the curve (AUC) of the training and test sets was 0.883 and 0.889, respectively, which were higher than those of the clinical (training set, AUC = 0.710; test set, AUC = 0.762) and radiomic models (training set, AUC = 0.840; test set, AUC = 0.834).

CONCLUSIONS

The clinical-radiomics combined nomogram model based on enhanced CT images efficiently predicted the PNI status of patients with RC.

Prognostic Value of Tumor Deposits in Stage III Colorectal Cancer Patients with Different N Stages: A Population-Based, Retrospective, Cohort Study

PURPOSE

Tumor deposits (TDs) seem to be associated with the prognosis of patients with colorectal cancer (CRC). The goal of this study was to investigate the prognostic value of TDs among patients with stage III CRC at different N stages.

METHODS

A retrospective analysis was performed on two independent cohorts of stage III CRC patients from the Surveillance, Epidemiology, and End Results (SEER) database (n = 8232) and the First Affiliated Hospital of Wenzhou Medical University (n = 423). Primary outcomes were overall survival (OS) and cancer-specific survival (CSS).

RESULTS

Of 8232 patients in the SEER cohort, the presence of TDs revealed poorer 5-year OS rates and 5-year CSS rates in all N-stage subgroups. X-tile software identified 5 (5-year OS: P = 0.004; 5-year CSS: P < 0.001) as the optimal cutoff value for TD count in the TD-positive subgroup at the N2 stage. The OS (5-year OS: 62.0% vs. 42.0%, P < 0.001) and CSS (5-year CSS: 66.0% vs. 43.8%, P < 0.001) of patients with five or more TDs were significantly worse than those with one to four TDs in the N2 stage subgroups. Of 423 patients in the Wenzhou cohort, the 3-year OS rate for patients in the positive group was worse than that for patients in the negative group (88.7% vs. 94.3%, P = 0.015).

CONCLUSIONS

TD count should be considered when evaluating the prognosis of patients with the N2 stage. Those with higher TD counts (≥ 5) might have a worse prognosis.

Construction and validation of a prognostic nomogram for predicting cancer-specific survival in patients with intermediate and advanced colon cancer after receiving surgery and chemotherapy

BACKGROUND

Existing predictive models often focus solely on overall survival (OS), neglecting the bias that other causes of death might introduce into survival rate predictions. To date, there is no strict predictive model established for cancer-specific survival (CSS) in patients with intermediate and advanced colon cancer after receiving surgery and chemotherapy.

METHODS

We extracted the data from the Surveillance, Epidemiology, and End Results (SEER) database on patients with stage-III and -IV colon cancer treated with surgery and chemotherapy between 2010 and 2015. The cancer-specific survival (CSS) was assessed using a competitive risk model, and the associated risk factors were identified via univariate and multivariate analyses. A nomogram predicting 1-, 3-, and 5-year CSS was constructed. The c-index, area under the curve (AUC), and calibration curve were adopted to assess the predictive performance of the model. Additionally, the model was externally validated.

RESULTS

A total of 18 risk factors were identified by univariate and multivariate analyses for constructing the nomogram. The AUC values of the nomogram for the 1-, 3-, and 5-year CSS prediction were 0.831, 0.842, and 0.848 in the training set; 0.842, 0.853, and 0.849 in the internal validation set; and 0.815, 0.823, and 0.839 in the external validation set. The C-index were 0.826 (se: 0.001), 0.836 (se: 0.002) and 0.763 (se: 0.013), respectively. Moreover, the calibration curve showed great calibration.

CONCLUSION

The model we have constructed is of great accuracy and reliability, and can help physicians develop treatment and follow-up strategies that are beneficial to the survival of the patients.

Multiple High-Risk Features for Stage II Colon Carcinoma Portends Worse Survival Than Stage III Disease

BACKGROUND

High-risk features in stage II colon cancer worsen survival and serve as an impetus for adjuvant chemotherapy. Limited data exist on the effect of multiple high-risk features on survival.

OBJECTIVE

The study aimed to compare the survival of 0, 1, or multiple high-risk features in stage II to stage III colon cancer.

DESIGN

Patients with stage II and III colon cancer diagnosed between 2010 and 2016 were identified using the Survival, Epidemiology, and End Results database. Patients with stage II colon cancer were then classified according to the presence of 0, 1, or 2 or more of the following high-risk features: pathologic T4, perineural invasion, fewer than 12 lymph nodes assessed, or poor histologic differentiation. Overall survival and cause-specific survival were calculated. Each group was then stratified on the basis of whether chemotherapy was given.

SETTINGS

This study used the Survival, Epidemiology, and End Results database (2010-2016).

PATIENTS

Patients who had stage II or III colon cancer were included.

MAIN OUTCOME MEASURES

The primary outcome measures were 5-year overall survival and cause-specific survival.

RESULTS

A total of 65,831 patients were studied. Of these, 18,056 patients with stage II cancer had 0 high-risk features, 9426 had 1 high-risk feature, and 3503 had 2 or more high-risk features. There were 34,842 patients diagnosed with stage III disease. The 5-year overall survival and cause-specific survival for patients with stage II cancer with 2 or more high-risk features (49.2%, 59.5%) were lower than those without high-risk features (74.9%, 90.7%), with 1 high-risk feature (67.1%, 82.4%), or stage III disease (59.1%, 68.1%; p < 0.05). Although chemotherapy is associated with improved cause-specific survival in stage III disease, it is associated with worse cause-specific survival in patients with stage II disease.

LIMITATIONS

This study being a retrospective database analysis is the main limitation. Also, lymphovascular invasion, margin status, and clinical obstruction or perforation were absent from the dataset.

CONCLUSIONS

Multiple high-risk features in stage II colon cancer predict worse survival than lymph node metastasis. Chemotherapy is associated with adverse cause-specific survival in patients with stage II disease. Further study into this group should focus on the type and duration of adjuvant therapy and biological features of these tumors. See Video Abstract at http://links.lww.com/DCR/B929 .

MLTIPLES CARACTERSTICAS DE ALTO RIESGO PARA EL CARCINOMA DE COLON EN ESTADIO II PRESAGIAN PEOR SUPERVIVENCIA QUE LA ENFERMEDAD EN ESTADIO III

ANTECEDENTES:Las características de alto riesgo en el cáncer de colon en estadio II empeoran la supervivencia y sirven como impulso para la quimioterapia adyuvante. Existen datos limitados sobre el efecto de múltiples características de alto riesgo en la supervivencia.OBJETIVO:Comparar la supervivencia de cero, una o múltiples características de alto riesgo en el cáncer de colon en estadio II con la enfermedad en estadio III.DISEÑO:Los pacientes con cáncer de colon en estadio II y III diagnosticados entre 2010 y 2016 se identificaron mediante la base de datos de supervivencia, epidemiología y resultados finales. Luego, los pacientes en etapa II se clasificaron según la presencia de cero, 1 o 2+ de las siguientes características de alto riesgo: T4 patológico, invasión perineural, menos de 12 ganglios linfáticos evaluados (< 12 ganglios linfáticos) o mala diferenciación histológica. Se calculó la supervivencia observada y específica de la causa. Luego, cada grupo se estratificó en función de si se administró quimioterapia.ESCENARIO:Este estudio utilizó la base de datos de supervivencia, epidemiología y resultados finales, 2010-2016.PACIENTES:Los pacientes tenían cáncer de colon en estadio II o III.PRINCIPALES MEDIDAS DE RESULTADO:La medida principal fue la supervivencia observada a 5 años y la supervivencia por causa específica.RESULTADOS:Se estudiaron un total de 65,831 pacientes. 18,056 pacientes estaban en estadio II sin características de alto riesgo, 9.426 con 1 característica de alto riesgo y 3.503 con 2+ características de alto riesgo. Hubo 34.842 pacientes a los que se les diagnosticó enfermedad en estadio III. La supervivencia observada a los 5 años y la supervivencia específica de la causa para los pacientes con cáncer en estadio II con 2+ características de alto riesgo (49.2 %, 59.5 %) fueron más bajas, en comparación con aquellos sin características de alto riesgo (74.9 %, 90.7 %), con 1 característica de alto riesgo (67.1 %, 82.4 %) o enfermedad en estadio III (59.1 %, 68.1 %) (p < 0.05). Si bien la quimioterapia se asocia con una mejor supervivencia por causa específica en la enfermedad en estadio III, se asocia con una peor supervivencia por causa específica en pacientes con enfermedad en estadio II.LIMITACIONES:Este es un análisis de base de datos retrospectivo. La invasión linfovascular, el estado de los márgenes y la obstrucción o perforación clínicas estaban ausentes en la base de datos.CONCLUSIONES:Múltiples características de alto riesgo en el cáncer de colon en estadio II predicen una peor supervivencia que la metástasis en los ganglios linfáticos. La quimioterapia se asocia con una supervivencia específica de causa adversa en pacientes con enfermedad en estadio II. El estudio adicional de este grupo deberá centrarse en el tipo y la duración de la terapia adyuvante y las características biológicas de estos tumores. Consulte Video Resumen en http://links.lww.com/DCR/B929 . (Traducción-Dr. Jorge Silva Velazco ).

CD51 Intracellular Domain Promotes Cancer Cell Neurotropism through Interacting with Transcription Factor NR4A3 in Colorectal Cancer

The abundant nervous system in intestine provides the basis for perineural invasion (PNI) of colorectal cancer (CRC). PNI is defined as the invasion of the nerves by cancer cells. Although PNI is already known to be an independent prognostic factor in CRC, the molecular mechanism underlying PNI remains obscure. In this study, we first demonstrated that CD51 could promote the neurotropism of tumor cells through cleavage with γ-secretase to generate an intracellular domain (ICD). Mechanistically, ICD of CD51 could bind to the transcription factor NR4A3, and act as a coactivator to promote the expression of downstream effectors, such as NTRK1, NTRK3, and SEMA3E. Pharmacological inhibition of γ-secretase impedes PNI mediated by CD51 in CRC both in vitro and in vivo and may become a potential therapeutic target for PNI in CRC.

Prognostic value of tumor deposits in lymph node-negative gastric cancer: A propensity score matching study

BACKGROUND

The purpose of this study was to assess the prognostic value of TD in lymph node-negative GC.

METHODS

A retrospective study was conducted to collect the clinicopathological data from 1224 patients with lymph node-negative GC. According to their TD status, patients were categorized into TD-positive and TD-negative groups. Patients in both groups underwent a 1:1 propensity score matching analysis. Survival analysis was performed by the Kaplan-Meier method, and the differences between survival curves were measured by log-rank test. The cox proportional hazards model was used for univariate and multivariate analyses.

RESULTS

The TD-negative group had higher 5-year overall survival(OS) rate than TD-positive group(69.4%VS.36.4%,P < 0.05). Further subgroup analysis indicated that patients in the TD-negative group had higher 5-year OS rates than those in the TD-positive group in the T1-2, T3, and T4 subgroups(all with P < 0.05).The OS rates were decreased with the increase of the number of TD.The univariate Cox regression analysis demonstrated that tumor location in antrum, distal gastrectomy, perineural invasion, T4-stage,lymphovascular invasion and the number of TD were all associated with prognosis in patients undergoing curative gastric resection (P < 0.05).The multivariable analysis revealed that the number of TD, perineural invasion, lymphovascular invasion and T4 stage were independently associated with OS.

CONCLUSION

In lymph node-negative GC, TD is an independent risk factor for prognosis, regardless of T-stage, and patients with ≥3 TD have a worse prognosis.

Beyond N staging in colorectal cancer: Current approaches and future perspectives

Traditionally, lymph node metastases (LNM) evaluation is essential to the staging of colon cancer patients according to the TNM (tumor-node-metastasis) system. However, in recent years evidence has accumulated regarding the role of emerging pathological features, which could significantly impact the prognosis of colorectal cancer patients. Lymph Node Ratio (LNR) and Log Odds of Positive Lymph Nodes (LODDS) have been shown to predict patients' prognosis more accurately than traditional nodal staging and it has been suggested that their implementation in existing classification could help stratify further patients with overlapping TNM stage. Tumor deposits (TD) are currently factored within the N1c category of the TNM classification in the absence of lymph node metastases. However, studies have shown that presence of TDs can affect patients' survival regardless of LNM. Moreover, evidence suggest that presence of TDs should not be evaluated as dichotomic but rather as a quantitative variable. Extranodal extension (ENE) has been shown to correlate with presence of other adverse prognostic features and to impact survival of colorectal cancer patients. In this review we will describe current staging systems and prognostic/predictive factors in colorectal cancer and elaborate on available evidence supporting the implementation of LNR/LODDS, TDs and ENE evaluation in existing classification to improve prognosis estimation and patient selection for adjuvant treatment.

The "Classification Pendulum" of Stage I Colorectal Cancer: A National Level Analysis of the Survival Difference Between T1 and T2 Colorectal Cancer

BACKGROUND

The eighth edition of the American Joint Committee on Cancer classifies nonmetastatic, node-negative colorectal cancers invading the submucosa (T1) and muscularis propria (T2) as stage I tumors without additional subclassification.

OBJECTIVE

The aim of the study was to compare survival of T1N0M0 versus T2N0M0 colorectal cancers and to investigate factors associated with decreased survival.

DESIGN

This was an analysis of 2 large population-based data sets.

SETTINGS

The study was conducted analyzing data from the Surveillance Epidemiology and End Result program and the National Cancer Database.

PATIENTS

Adult patients undergoing major resection without additional therapy for stage I colorectal cancer were included.

MAIN OUTCOME MEASURES

Overall and disease-specific survival for T1 versus T2 cancers were measured. Subgroup analyses by tumor location (colon versus rectum) were performed.

RESULTS

A total of 30,228 (36.4% T1 and 63.6% T2) and 41,670 (41.1% T1 and 58.9% T2) patients were identified in the Surveillance Epidemiology and End Result database and the National Cancer Database. The 5-year overall survival rates were 87.1% and 86.2% for patients with T1 versus 82.7% and 80.7% for patients with T2 (p < 0.001) in the Surveillance Epidemiology and End Result database and the National Cancer Database. The 10-year overall survival rates were 71.3% and 66.3% for patients with T1 versus 62.2% and 57.2% for patients with T2 tumors (p < 0.001) in the Surveillance Epidemiology and End Result database and the National Cancer Database. The 5- and 10-year disease-specific survival for colorectal cancer in the Surveillance Epidemiology and End Result database was 97.0% (T1) versus 95.2% (T2) and 94.1% (T1) versus 90.3% (T2). Black race (HR = 1.26 and 1.65 for overall survival and disease-specific survival in the Surveillance Epidemiology and End Result database; HR = 1.20 for overall survival in the National Cancer Database) was associated with worse survival.

LIMITATIONS

The study was limited by intrinsic biases related to large administrative data sets.

CONCLUSIONS

Within stage I colorectal cancer, T2 tumors have decreased overall survival and disease-specific survival as compared with T1 cancers. This survival difference may justify revising the American Joint Committee on Cancer staging system to include the subclassification of stage Ia (T1N0M0) and stage Ib (T2N0M0). See Video Abstract at http://links.lww.com/DCR/B659.

LA CLASIFICACIN PNDULO PARA EL CNCER COLORRECTAL EN ESTADIO I UN ANLISIS A NIVEL NACIONAL DE LA DIFERENCIA DE SOBREVIDA ENTRE EL CNCER COLORRECTAL T Y T

ANTECEDENTES:La octava edición del American Joint Committee on Cancer, clasifica los cánceres colorrectales no metastásicos con ganglios negativos, que invaden la submucosa (T1) y la muscularis propia (T2) como tumores en estadio I sin subclasificación adicional.OBJETIVO:El objetivo del estudio fue comparar la sobrevida de los cánceres colorrectales T1N0M0 versus T2N0M0 e investigar los factores asociados con la disminución de la sobrevida.DISEÑO:Análisis de dos grandes conjuntos de datos poblacionales.MARCO:El estudio se realizó analizando datos del Programa de Epidemiología de Vigilancia y Resultados Finales (SEER) y la Base de Datos Nacional del Cáncer.PACIENTES:Pacientes adultos en los cuales se realizó una resección mayor sin terapia adicional por cáncer colorrectal en estadio I.PRINCIPALES VARIABLES ANALIZADAS:Sobrevida global y específica de la enfermedad para los cánceres T1 versus T2. Se realizó un análisis de subgrupos según la ubicación del tumor (colon versus recto).RESULTADOS:Se incluyeron un total de 30.228 (36,4% T1 y 63,6% T2) y 41.670 (41,1% T1 y 58,9% T2) pacientes en las bases de datos SEER y la Base de Datos Nacional del Cáncer, respectivamente. La sobrevida global a 5 años fue del 87,1% y el 86,2% para los pacientes con T1 frente al 82,7% y el 80,7% de los pacientes con T2 (p < 0,001) en el SEER y la Base de Datos Nacional del Cáncer, respectivamente. La sobrevida global a 10 años fue del 71,3% y el 66,3% para los pacientes con T1 frente al 62,2% y el 57,2% de los pacientes con tumores T2 (p < 0,001) en el SEER y la Base de Datos Nacional del Cáncer, respectivamente. La sobrevida específica de la enfermedad a 5 y 10 años para el cáncer colorrectal en el SEER fue del 97,0% (T1) frente al 95,2% (T2) y del 94,1% (T1) frente al 90,3% (T2), respectivamente. La grupo étnico afroamericano se asoció con una sobrevida menor (Hazard Ratio -HR 1,26 y 1,65 para la sobrevida general y sobrevida específica de la enfermedad-SEER; HR 1,20 para la sobrevida general-Base de de Datos Nacional del Cáncer).LIMITACIONES:Sesgos intrínsecos relacionados con el análisis de grandes conjuntos de datos.CONCLUSIONES:Dentro del cáncer colorrectal en estadio I, los tumores T2 han disminuido la sobrevida general y la sobrevida específica de la enfermedad, en comparación con los cánceres T1. Esta diferencia de sobrevida puede justificar la revisión del sistema de estadificación del American Joint Committee on Cancer para incluir la subclasificación del estadio Ia (T1N0M0) y el estadio Ib (T2N0M0). Consulte Video Resumen en http://links.lww.com/DCR/B659.

Predictive and Prognostic Assessment Models for Tumor Deposit in Colorectal Cancer Patients With No Distant Metastasis

Background

More and more evidence indicated that tumor deposit (TD) was significantly associated with local recurrence, distant metastasis (DM), and poor prognosis for patients with colorectal cancer (CRC). This study aims to explore the main clinical risk factors for the presence of TD in CRC patients with no DM (CRC-NDM) and the prognostic factors for TD-positive patients after surgery.

Methods

The data of patients with CRC-NDM between 2010 and 2017 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. A logistic regression model was used to identify risk factors for TD presence. Fine and Gray’s competing-risk model was performed to analyze prognostic factors for TD-positive CRC-NDM patients. A predictive nomogram was constructed using the multivariate logistic regression model. The concordance index (C-index), the area under the receiver operating characteristic (ROC) curve (AUC), and the calibration were used to evaluate the predictive nomogram. Also, a prognostic nomogram was built based on multivariate competing-risk regression. C-index, the calibration, and decision-curve analysis (DCA) were performed to validate the prognostic model.

Results

The predictive nomogram to predict the presence of TD had a C-index of 0.785 and AUC of 0.787 and 0.782 in the training and validation sets, respectively. From the competing-risk analysis, chemotherapy (subdistribution hazard ratio (SHR) = 0.542, p < 0.001) can significantly reduce CRC-specific death (CCSD). The prognostic nomogram for the outcome prediction in postoperative CRC-NDM patients with TD had a C-index of 0.727. The 5-year survival of CCSD was 17.16%, 36.20%, and 63.19% in low-, medium-, and high-risk subgroups, respectively (Gray’s test, p < 0.001).

Conclusions

We constructed an easily predictive nomogram in identifying the high-risk TD-positive CRC-NDM patients. Besides, a prognostic nomogram was built to help clinicians identify poor-outcome individuals in postoperative CRC-NDM patients with TD. For the high-risk or medium-risk subgroup, additional chemotherapy may be more advantageous for the TD-positive patients rather than radiotherapy.

Multimetric feature selection for analyzing multicategory outcomes of colorectal cancer: random forest and multinomial logistic regression models

Colorectal cancer (CRC) is one of the most common cancers worldwide, and a leading cause of cancer deaths. Better classifying multicategory outcomes of CRC with clinical and omic data may help adjust treatment regimens based on individual's risk. Here, we selected the features that were useful for classifying four-category survival outcome of CRC using the clinical and transcriptomic data, or clinical, transcriptomic, microsatellite instability and selected oncogenic-driver data (all data) of TCGA. We also optimized multimetric feature selection to develop the best multinomial logistic regression (MLR) and random forest (RF) models that had the highest accuracy, precision, recall and F1 score, respectively. We identified 2073 differentially expressed genes of the TCGA RNASeq dataset. MLR overall outperformed RF in the multimetric feature selection. In both RF and MLR models, precision, recall and F1 score increased as the feature number increased and peaked at the feature number of 600-1000, while the models' accuracy remained stable. The best model was the MLR one with 825 features based on sum of squared coefficients using all data, and attained the best accuracy of 0.855, F1 of 0.738 and precision of 0.832, which were higher than those using clinical and transcriptomic data. The top-ranked features in the MLR model of the best performance using clinical and transcriptomic data were different from those using all data. However, pathologic staging, HBS1L, TSPYL4, and TP53TG3B were the overlapping top-20 ranked features in the best models using clinical and transcriptomic, or all data. Thus, we developed a multimetric feature-selection based MLR model that outperformed RF models in classifying four-category outcome of CRC patients. Interestingly, adding microsatellite instability and oncogenic-driver data to clinical and transcriptomic data improved models' performances. Precision and recall of tuned algorithms may change significantly as the feature number changes, but accuracy appears not sensitive to these changes.

How Best to Play the Role of Tumor Deposits in Stage III Colon Cancer?

Background

The purpose of this study is to comprehensively evaluate the prognostic role of tumor deposits (TD) in stage III colon cancer.

Methods

24,600 CC patients with III stage colon cancer were collected from the Surveillance, Epidemiology, and End Result (SEER) database and 618 CC patients from the Second Affiliated Hospital of Harbin Medical University. All patients were divided into development, internal, and external validation cohorts. The combination of positive lymph nodes (PLN) and the status or number of TD was defined as modified pN (mpN) and novel pN (npN). The Cox proportional hazard regression model was used to analyze the relationship between cancer-specific survival (CSS) and mpN or npN. CSS stratified by pN, mpN, and npN was analyzed by the Kaplan–Meier curves. The area under the receiver operating characteristic curve (AUC) was used to demonstrate the predictive abilities of the pN, mpN, and npN stages. The validation cohorts were used to validate the results.

Results

The Cox proportional hazard regression model showed that mpN and npN were an independent prognostic factor for CSS. AUC showed that the predictive accuracy of mpN was better than that of the pN stage for 5-year CSS in the development (0.621 vs. 0.609, p < 0.001) and internal validation cohorts (0.618 vs. 0.612, p = 0.016) and the npN was also better than the pN stage for 5-year CSS in the development (0.623 vs. 0.609, p < 0.001) and internal validation cohorts (0.620 vs. 0.612, p = 0.001). However, there was no significant difference between the AUCs of mpN and npN. Moreover, the pN stage for 5-year CSS in the external validation cohort is 0.606 vs. 0.563, p = 0.045.

Conclusions

In stage III CC, mpN and npN may be superior to the pN stage in assessing prognosis, suggesting that the TD information should be included in the pN stage.

Current Perspectives on the Importance of Pathological Features in Prognostication and Guidance of Adjuvant Chemotherapy in Colon Cancer

There is not a clear consensus on which pathological features and biomarkers are important in guiding prognosis and adjuvant therapy in colon cancer. The Pathology in Colon Cancer, Prognosis and Uptake of Adjuvant Therapy (PiCC UP) Australia and New Zealand questionnaire was distributed to colorectal surgeons, medical oncologists and pathologists after institutional board approval. The aim of this study was to understand current specialist attitudes towards pathological features in the prognostication of colon cancer and adjuvant therapy in stage II disease. A 5-scale Likert score was used to assess attitudes towards 23 pathological features for prognosis and 18 features for adjuvant therapy. Data were analysed using a rating scale and graded response model in item response theory (IRT) on STATA (Stata MP, version 15; StataCorp LP). One hundred and sixty-four specialists (45 oncologists, 86 surgeons and 33 pathologists) participated. Based on IRT modelling, the most important pathological features for prognosis in colon cancer were distant metastases, lymph node metastases and liver metastases. Other features seen as important were tumour rupture, involved margin, radial margin, CRM, lymphovascular invasion and grade of differentiation. Size of tumour, location, lymph node ratio and EGFR status were considered less important. The most important features in decision making for adjuvant therapy in stage II colon cancer were tumour rupture, lymphovascular invasion and microsatellite instability. BRAF status, size of tumour, location, tumour budding and tumour infiltrating lymphocytes were factored as lesser importance. Biomarkers such as CDX2, EGFR, KRAS and BRAF status present areas for further research to improve precision oncology. This study provides the most current status on the importance of pathological features in prognostication and recommendations for adjuvant therapy in Australia and New Zealand. Results of this nationwide study may be useful to help in guiding prognosis and adjuvant treatment in colon cancer.

Prognostic Nomogram for Rectal Cancer Patients With Tumor Deposits

Aim

Tumor deposits (TDs) are an aggressive hallmark of rectal cancer, but their prognostic value has not been addressed in current staging systems. This study aimed to construct and validate a prognostic nomogram for rectal cancer patients with TDs.

Methods

A total of 1,388 stage III–IV rectal cancer patients who underwent radical surgical resection from the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively analyzed to identify the clinical value of TDs. TD-positive rectal cancer patients in the SEER database were used as the training set to construct a prognostic model, which was validated by Fujian Cancer Hospital. Three models were constructed to predict the prognosis of rectal cancer patients with TDs, including the least absolute shrinkage and selection operator regression (LASSO, model 1), backward stepwise regression (BSR, model 2), and LASSO followed by BSR (model 3). A nomogram was established among the three models.

Results

In the entire cohort, TD was also identified as an independent risk factor for overall survival (OS), even after adjusting for baseline factors, stage, other risk factors, treatments, and all the included variables in this study (all P < 0.05). Among patients with TDs, model 3 exhibited a higher C-index and area under the curves (AUCs) at 3, 4, and 5 years compared with the American Joint Committee on Cancer staging system both in the training and validation sets (all P < 0.05). The nomogram obtained from model 3 showed good consistency based on the calibration curves and excellent clinical applicability by the decision curve analysis curves. In addition, patients were divided into two subgroups with apparently different OS according to the current nomogram (both P < 0.05), and only patients in the high-risk subgroup were found to benefit from postoperative radiotherapy (P < 0.05).

Conclusion

We identified a novel nomogram that could not only predict the prognosis of rectal cancer patients with TDs but also provide reliable evidence for clinical decision-making.

Tumor Deposits and Perineural Invasion had Comparable Impacts on the Survival of Patients With Non-metastatic Colorectal Adenocarcinoma: A Population-Based Propensity Score Matching and Competing Risk Analysis

BACKGROUND

Both tumor deposits (TD) and perineural invasion (PNI) have been identified as risk factors for poor survival in patients with non-metastatic colorectal adenocarcinoma (CRC). However, the adverse impacts of TD and PNI on the survival of patients with non-metastatic CRC have not been compared.

METHOD

Patients with non-metastatic CRC with known TD and PNI status were selected from the Surveillance, Epidemiology, and End Results (SEER) database. First, bivariate logistic regression analysis was utilized to identify the factors associated with TD and PNI status. Then, patients were divided into four groups, according to TD and PNI status. Propensity score matching (PSM) was performed to balance the baseline covariates. The impact of TD and PNI on survival was assessed by analyzing overall survival (OS) and cancer-specific mortality (CSM) rates. OS was calculated by the Kaplan-Meier method with log-rank analysis. CSM was estimated by competing risk analysis using the Fine and Gray model.

RESULTS

A total of 70 689 patients with CRC met the inclusion and exclusion criteria. The positive rates of TD and PNI were 9.37% and 9.91%, respectively. For TD, the most important risk factor was N stage. With respect to PNI, the most significant factor was T stage. Tumor location, tumor size, differentiation grade, and serum CEA level were also correlated with TD and PNI status. After PSM, 1849 pairs were selected. Patients with TD⁺PNI⁺ status had the worst 5 year CSM and 5 year OS. In addition, the long-term survival outcomes of patients with TD⁺PNI^- and TD^-PNI⁺ status were comparable.

CONCLUSION

The adverse impacts of TD and PNI on the survival of patients with non-metastatic CRC were comparable. CRC patients with both TD and PNI positive had the worst survival outcome.

Pathological Features and Prognostication in Colorectal Cancer

The prognostication of colorectal cancer (CRC) has traditionally relied on staging as defined by the Union for International Cancer Control (UICC) and American Joint Committee on Cancer (AJCC) TNM staging classifications. However, clinically, there appears to be differences in survival patterns independent of stage, suggesting a complex interaction of stage, pathological features, and biomarkers playing a role in guiding prognosis, risk stratification, and guiding neoadjuvant and adjuvant therapies. Histological features such as tumour budding, perineural invasion, apical lymph node involvement, lymph node yield, lymph node ratio, and molecular features such as MSI, KRAS, BRAF, and CDX2 may assist in prognostication and optimising adjuvant treatment. This study provides a comprehensive review of the pathological features and biomarkers that are important in the prognostication and treatment of CRC. We review the importance of pathological features and biomarkers that may be important in colorectal cancer based on the current evidence in the literature.

Combining tumor deposits with the number of lymph node metastases to improve the prognostic accuracy in stage III colon cancer: a post hoc analysis of the CALGB/SWOG 80702 phase III study (Alliance)☆

BACKGROUND

In colon cancer, tumor deposits (TD) are considered in assigning prognosis and staging only in the absence of lymph node metastasis (i.e. stage III pN1c tumors). We aimed to evaluate the prognostic value of the presence and the number of TD in patients with stage III, node-positive colon cancer.

PATIENTS AND METHODS

All participants from the CALGB/SWOG 80702 phase III trial were included in this post hoc analysis. Pathology reports were reviewed for the presence and the number of TD, lymphovascular and perineural invasion. Associations with disease-free survival (DFS) and overall survival (OS) were evaluated by multivariable Cox models adjusting for sex, treatment arm, T-stage, N-stage, lymphovascular invasion, perineural invasion and lymph node ratio.

RESULTS

Overall, 2028 patients were included with 524 (26%) TD-positive and 1504 (74%) TD-negative tumors. Of the TD-positive patients, 80 (15.4%) were node negative (i.e. pN1c), 239 (46.1%) were pN1a/b (<4 positive lymph nodes) and 200 (38.5%) were pN2 (≥4 positive lymph nodes). The presence of TD was associated with poorer DFS [adjusted hazard ratio (aHR) = 1.63, 95% CI 1.33-1.98] and OS (aHR = 1.59, 95% CI 1.24-2.04). The negative effect of TD was observed for both pN1a/b and pN2 groups. Among TD-positive patients, the number of TD had a linear negative effect on DFS and OS. Combining TD and the number of lymph node metastases, 104 of 1470 (7.1%) pN1 patients were re-staged as pN2, with worse outcomes than patients confirmed as pN1 (3-year DFS rate: 65.4% versus 80.5%, P = 0.0003; 5-year OS rate: 87.9% versus 69.1%, P = <0.0001). DFS was not different between patients re-staged as pN2 and those initially staged as pN2 (3-year DFS rate: 65.4% versus 62.3%, P = 0.4895).

CONCLUSION

Combining the number of TD and the number of lymph node metastases improved the prognostication accuracy of tumor-node-metastasis (TNM) staging.

High resolution MRI-based radiomic nomogram in predicting perineural invasion in rectal cancer

BACKGROUND

To establish and validate a high-resolution magnetic resonance imaging (HRMRI)-based radiomic nomogram for prediction of preoperative perineural invasion (PNI) of rectal cancer (RC).

METHODS

Our retrospective study included 140 subjects with RC (99 in the training cohort and 41 in the validation cohort) who underwent a preoperative HRMRI scan between December 2016 and December 2019. All subjects underwent radical surgery, and then PNI status was evaluated by a qualified pathologist. A total of 396 radiomic features were extracted from oblique axial T2 weighted images, and optimal features were selected to construct a radiomic signature. A combined nomogram was established by incorporating the radiomic signature, HRMRI findings, and clinical risk factors selected by using multivariable logistic regression.

RESULTS

The predictive nomogram of PNI included a radiomic signature, and MRI-reported tumor stage (mT-stage). Clinical risk factors failed to increase the predictive value. Favorable discrimination was achieved between PNI-positive and PNI-negative groups using the radiomic nomogram. The area under the curve (AUC) was 0.81 (95% confidence interval [CI], 0.71-0.91) in the training cohort and 0.75 (95% CI, 0.58-0.92) in the validation cohort. Moreover, our result highlighted that the radiomic nomogram was clinically beneficial, as evidenced by a decision curve analysis.

CONCLUSIONS

HRMRI-based radiomic nomogram could be helpful in the prediction of preoperative PNI in RC patients.

Performance and efficiency of machine learning algorithms for analyzing rectangular biomedical data

Most biomedical datasets, including those of 'omics, population studies, and surveys, are rectangular in shape and have few missing data. Recently, their sample sizes have grown significantly. Rigorous analyses on these large datasets demand considerably more efficient and more accurate algorithms. Machine learning (ML) algorithms have been used to classify outcomes in biomedical datasets, including random forests (RF), decision tree (DT), artificial neural networks (ANN), and support vector machine (SVM). However, their performance and efficiency in classifying multi-category outcomes of rectangular data are poorly understood. Therefore, we compared these metrics among the 4 ML algorithms. As an example, we created a large rectangular dataset using the female breast cancers in the surveillance, epidemiology, and end results-18 database, which were diagnosed in 2004 and followed up until December 2016. The outcome was the five-category cause of death, namely alive, non-breast cancer, breast cancer, cardiovascular disease, and other cause. We analyzed the 54 dichotomized features from ~45,000 patients using MatLab (version 2018a) and the tenfold cross-validation approach. The accuracy in classifying five-category cause of death with DT, RF, ANN, and SVM was 69.21%, 70.23%, 70.16%, and 69.06%, respectively, which was higher than the accuracy of 68.12% with multinomial logistic regression. Based on the features' information entropy, we optimized dimension reduction (i.e., reduce the number of features in models). We found 32 or more features were required to maintain similar accuracy, while the running time decreased from 55.57 s for 54 features to 25.99 s for 32 features in RF, from 12.92 s to 10.48 s in ANN, and from 175.50 s to 67.81 s in SVM. In summary, we here show that RF, DT, ANN, and SVM had similar accuracy for classifying multi-category outcomes in this large rectangular dataset. Dimension reduction based on information gain will increase the model's efficiency while maintaining classification accuracy.

N1c colon cancer and the use of adjuvant chemotherapy: a current audit of the National Cancer Database

AIM

Colorectal cancer staging has evolved to define N1c as the presence of tumour deposits without concurrent positive lymph nodes. Work to date reports poor prognosis in N1c colon cancer, with Stage III categorization and adjuvant chemotherapy (AC) recommended. No study has yet evaluated the prevalence, treatment compliance or treatment-related outcomes on a national scale. We aimed to evaluate the prevalence of N1c colon cancer, use, outcomes and factors associated with AC in the USA.

METHOD

The National Cancer Database was reviewed for N1cM0 colon adenocarcinomas that underwent resection from 2010 to 2016. Cases were stratified into 'AC' or 'no AC' cohorts. The Kaplan-Meier method was used to estimate overall survival (OS) and compare the AC and no AC cohorts using the log-rank test. Multivariable logistic regression identified factors associated with AC. The main outcome measures were the prevalence and factors associated with AC use and its impact in N1c disease.

RESULTS

Of the 5684 (1.59% of 357 752) colon adenocarcinomas that were N1c, 55% (n = 3071) received AC. AC significantly improved 1-, 3- and 5-year OS compared with no AC (96.2%, 80%, 67.4% and 72.9%, 48.5%, 33.8%, respectively; P < 0.001). Compared with the no AC group, AC patients were younger, had less comorbidity, were of the male gender and received minimally invasive surgery at an academic treatment centre (all P < 0.05). Socioeconomic and procedural factors significantly impacted the use of AC.

CONCLUSION

In the USA, AC is underutilized in N1c colon cancer despite significantly improved OS. Socioeconomic and procedural factors associated with AC were identified, highlighting disparities in AC use and opportunities to improve oncological outcomes and survival.

A Modified Pathological N Stage Including Status of Tumor Deposits in Colorectal Cancer With Nodal Metastasis

Background

The American Joint Committee on Cancer 8th classification states that colorectal cancer (CRC) is classified as N1c stage when regional lymph nodes (LNs) are negative and tumor deposits (TDs) are positive. However, how to classify TDs when regional LNs are positive remains unclear. The current study aimed to investigate the possibility of combining positive LNs and positive TDs to develop a modified pathological N (mpN) stage for CRC.

Methods

We retrospectively analyzed 9,198 patients with stage III CRC from the Surveillance, Epidemiology, and End Results program who underwent surgery (6,440 in the training cohort and 2,758 the validation cohort). The combination of positive LNs and TD status was defined as mpN stage. Overall survival (OS) according to mpN and pathological N (pN) stages was analyzed by the Kaplan–Meier method. The area under the curves (AUCs) and Akaike’s information criterion (AIC) were applied to assess the predictive discrimination abilities and goodness-of-fit of the model. The clinical benefits were measured using decision curve analyses. The validation cohort was used to validate the results.

Results

AUC analysis showed that the prognostic discrimination of mpN stage (AUC = 0.628, 95% confidence interval (CI), 0.616–0.640) was better than that of pN stage (AUC = 0.618, 95% CI, 0.606–0.630, p = 0.006) for OS. The AIC demonstrated that mpN stage (AIC = 30,217) also showed superior model-fitting compared with pN stage (AIC = 30,257) and decision curve analyses revealed that mpN stage had better clinical benefits than pN stage. Similar results were found in the validation cohort.

Conclusions

Among patients with CRC and LN metastasis, mpN stage might be superior to pN stage for assessing prognosis and survival, suggesting that TD status should be included in the pN stage.

Predictive and Prognostic Factors of Synchronous Colorectal Lung-Limited Metastasis

Aim

This study is aimed at investigating predictive and prognostic factors of synchronous colorectal lung-limited metastasis (SCLLM) based on The Surveillance, Epidemiology, and End Results (SEER) database.

Methods

A multivariate logistic regression model was constructed to identify independent predictors of SCLLM. A multivariate Cox proportional hazards regression model was used to distinguish independent prognostic factors.

Results

This study enrolled 168,007 colorectal cancer (CRC) patients without metastatic diseases and 1,298 cases with SCLLM. Eight features, involving race, tumor location, pathological grade, histological type, T stage, N stage, and tumor size as well as CEA, could be used as the independent predictors. As the nomogram shown, the T4 stage contributed the most to SCLLM, followed by the N2 stage, elevated CEA, and rectal cancer. A multivariate regression analysis discriminated 9 independent prognostic factors, including age, race, marital status, pathological grade, T stage, colectomy/proctectomy, chemotherapy, CEA, and TD. The prognostic nomogram illustrated that nonresection/NOS played as the poorest prognostic factor, followed by nonchemotherapy, ≥75-year old and T4 stage. The cumulative survival curves revealed the influence of each prognostic factor on survival after controlling the other variables.

Conclusions

This study identified independent predictors and prognostic factors for SCLLM based on a large database of the United States. The predictors and prognostic factors can provide supporting evidence for the prevention and treatment of SCLLM.

The Role of Tumor Deposits in Predicting the Efficacy of Chemotherapy in Stage III Colon Cancer

Purpose

To evaluate the role of tumor deposits (TDs) in predicting the efficacy of chemotherapy in stage III colon cancer.

Methods

Using the SEER^∗Stat software Version 8.3.6, we started with a national cohort of colon cancer cases diagnosed between 2004 and 2016. We used the χ² (Chi-square) test to compare differences between different categorical variables according to the number of TDs. The Cox proportional hazards regression model was used to determine the independent association of different clinical and pathological variables with CSS, which were adjusted for other significant prognostic factors.

Results

We have identified 29,017 patients diagnosed with stage III colon cancer from the SEER database. The results of multivariate analyses showed that patients with the receipt of chemotherapy had 54.7% decreased risk of cancer-specific mortality compared with those not (HR = 0.453, 95% CI = 0.425-0.483, P < 0.0001) in the no-TD group; In the 1-2-TD group, patients with the receipt of chemotherapy had 56.8% decreased risk of cancer-specific mortality compared with those not (HR = 0.432, 95% CI = 0.364-0.512, P < 0.0001); In the ≥3-TD group, patients with the receipt of chemotherapy had 51.8% decreased risk of cancer-specific mortality compared with those not (HR = 0.482, 95% CI = 0.389-0.597, P < 0.0001).

Conclusions

Our study demonstrated that the presence of TDs was associated with a dismal prognosis and high number of TDs would also contribute to the worse survival of colon cancer. High number of TDs did not affect the survival benefit of chemotherapy in stage III colon cancer.

Diagnosis and prognostic significance of extramural venous invasion in neuroendocrine tumors of the small intestine

Extramural venous invasion (EMVI) is an established independent prognostic factor in colorectal carcinoma where it is linked to hematogenous spread (i.e., liver metastases), influencing the decision for adjuvant chemotherapy. However, its prognostic significance in small intestinal neuroendocrine tumors (NETs) has not been studied, nor is it routinely assessed or reported. We reviewed primary small bowel NETs (14 jejunum, 82 ileum, 8 not specified) from 104 patients (52 women; median age 60.5, range: 24-84). EMVI was identified in 58 cases (55.8%), including in 13 of 21 equivocal cases using an elastin stain. In univariate analysis, EMVI was associated with lymphovascular and perineural invasion, tumor stage, and lymph node and distant metastases, whereas in multivariate analysis, only distant metastases remained significant (p < 0.001). Liver metastases were present in 55 cases (52.9%) and were significantly associated in univariate analysis with lymphovascular and perineural invasion, tumor stage, lymph node metastases, and EMVI, whereas in multivariate analysis, only EMVI remained significant (p < 0.001; odds ratio (OR) = 59.42). Eight patients developed metachronous liver metastases during follow-up (mean 22.9 ± 22.0 months, range: 4.7-73.2) and all (100%) were positive for EMVI. In contrast, of 49 patients who never developed liver metastases over significantly longer follow-up (mean 71.0 ± 32.4 months, range: 6.6-150.4; p < 0.001), only 7 (14.3%) had EMVI (p < 0.001). In Kaplan-Meier analysis, 8 of 15 patients with EMVI (53.3%) developed metachronous liver metastases, compared with 0 of 42 patients without EMVI (p < 0.001). In contrast, nonhepatic distant metastases, seen in 26 (25.0%) patients, were not associated with EMVI in multivariate or Kaplan-Meier analyses. Our data demonstrate that EMVI is common in small bowel NETs and strongly correlates with development of liver metastases. Therefore, its evaluation is critical and should be assessed in combination with adjuvant techniques such as elastin staining, if necessary. Moreover, inclusion of EMVI in pathology reporting guidelines should be considered.

A Modified Tumor-Node-Metastasis Classification for Stage III Colorectal Cancers Based on Treating Tumor Deposits as Positive Lymph Nodes

Background: The tumor-node-metastasis classification of the American Joint Committee on Cancer classified tumor deposits (TDs) in patients with colorectal cancer (CRC) without lymph node (LN) metastasis as N1c, but the classification of TDs in patients with LN metastases remains controversial. This study investigated the probability of regarding TDs as positive LNs (pLNs) in pN stage and estimated its prognostic ability in CRC. Methods: We used the Surveillance, Epidemiology, and End Results program to analyze CRC patients who underwent surgical therapy (14,906 training cohort, 6,384 validation cohort). A modified pN stage (mpN) was identified using the number of pLNs plus TDs. Overall survival (OS) was analyzed using the Kaplan-Meier survival curves, and significant prognostic factors were identified by univariate and multivariate analyses. Prognostic ability was estimated using the area under the curve (AUC), calibration curve, and the Akaike's information criterion (AIC). Clinical benefit was measured by the decision curve analyses (DCA). The results were validated using the validation cohort. Results: Both the pN and mpN stages were independent prognostic factors in CRC according to univariate and multivariate analyses. The AUC analysis showed that the mpN stage had better prognostic discrimination for OS than the pN stage (0.612 vs. 0.605, P < 0.001). The AIC demonstrated that the mpN stage also showed superior model-fitting compared with the pN stage (49,756 vs. 49,841). The DCA further revealed that the mpN stage had better clinical benefits than the pN stage. The validation cohort showed similar findings. Conclusions: We concluded that counting TDs as pLNs may be superior to the pN stage when assessing the prognosis of CRC patients.

Association of KRAS mutation with tumor deposit status and overall survival of colorectal cancer

PURPOSE

To examine associations of KRAS mutation with tumor deposit status and overall survival in colorectal cancer (CRC) patients.

METHODS

This retrospective cohort study included patients with incidental CRC diagnosed during 2010-2014 and recorded statuses of KRAS and tumor deposit in the National Cancer Database of the USA. Multivariable logistic regression and time-varying Cox regression analyses were used.

RESULTS

We included 45,761 CRC patients with KRAS status (24,027 [52.5%] men, 24,240 [53.0%] < 65 years old, 17,338 [37.9%] with KRAS mutation). Adjusted for microsatellite instability, age, pathologic stage and tumor grade, KRAS mutation (versus wild type) was associated with tumor deposit presence (odds ratio = 1.11, 95% CI 1.02-1.20). KRAS mutation was also linked to worse overall survival of CRC patients regardless of tumor deposit status (adjusted Hazard ratio [HR] = 1.20, 95% CI 1.07-1.33 for CRC with tumor deposits, and adjusted HR = 1.24, 95% CI 1.14-1.35 or CRC without) or tumor stage (adjusted HR = 1.32, 95% CI 1.14-1.54 for early-stage and adjusted HR = 1.18, 95% CI 1.10-1.27 for late-stage). Microsatellite instability was associated with better overall survival in CRC without tumor deposit (adjusted HR = 0.89, 95% CI 0.79-0.99), but not in CRC with tumor deposit (adjusted HR = 1.12, 95% CI 0.97-1.30).

CONCLUSION

KRAS mutation is independently associated with tumor deposit presence and a worse overall survival in CRC patients.

Tumor Deposits in Stage III Colon Cancer: Correlation With Other Histopathologic Variables, Prognostic Value, and Risk Stratification-Time to Consider "N2c"

Objectives:

National Comprehensive Cancer Network (NCCN) guidelines for stage III colon cancer define low-risk versus high-risk patients based on T (1 to 3 vs. 4) and N (1 vs. 2) status, with some variations in treatment. This study analyzes the impact of tumor deposits (TDs), T and N status, poor differentiation (PD), perineural invasion (PNI), and lymphovascular invasion (LVI) on survival.

Materials and Methods:

A retrospective analysis (2010-2015) of the National Cancer Database of stage III colon cancer patients treated with both surgery and chemotherapy was conducted. Data was extracted on sex, race, age at diagnosis, Charlson-Deyo Score, histopathologic variables, and survival rates. Statistical analysis used the test of proportions, log-rank test for Kaplan-Meier curves, and Cox proportional hazard models.

Results:

For the 42,901 patients analyzed, 5-year survival rates were similar for LN⁺TD⁻ (59.8%) and LN⁻TD⁺ (58.2%), but significantly worse for LN⁺TD⁺ (41.5%) (P<0.001). The presence of LN⁺TD⁺ was more often associated with T4 (36.9%), N2 (55.1%), PD⁺ (37.4%), PNI⁺ (34.5%), and LVI⁺ (69.1%), than LN⁺TD⁻ or LN⁻TD⁺ (P<0.001). The hazard ratios for each variable were: TD: 1.34; T4: 1.71; N2: 1.44; PD⁺: 1.37; PNI: 1.11; LVI⁺: 1.18. LN⁻ patients with ≥3 TD⁺ (N1c) had worse overall survival than those with 1 to 2 TD⁺ (P<0.01), but similar to ≥4 LN⁺TD⁻ (N2) and 1 to 3 LN⁺TD⁺ (N1a-b). In our model, 5-year survival ranged from 23.4% for high-risk to 78.1% for low-risk patients (P<0.001).

Conclusion:

This National Cancer Database (NCDB) analysis offers greater risk stratification and may prompt consideration of changes in American Joint Committee on Cancer (AJCC) classification (N2c, in addition to N1c) to reflect the different prognosis and guide management, as well as survivorship strategies, for TD⁺ stage III colon cancer patients.

The Prognostic Significance of Tumor Deposit Count for Colorectal Cancer Patients after Radical Surgery

BACKGROUND

The prognostic value of tumor deposit (TD) count in colorectal cancer (CRC) patients has been rarely evaluated. This study is aimed at exploring the prognostic value of TD count and finding out the optimal cutoff point of TD count to differentiate the prognoses of TD-positive CRC patients.

METHOD

Patients diagnosed with CRC from Surveillance, Epidemiology, and End Results (SEER) database from January 1, 2010, to December 31, 2012, were analyzed. X-tile program was used to identify the optimal cutoff point of TD count in training cohort, and a validation cohort was used to test this cutoff point after propensity score matching (PSM). Univariate and multivariate Cox proportional hazard models were used to assess the risk factors of survival.

RESULTS

X-tile plots identified 3 (P < 0.001) as the optimal cutoff point of TD count to divide the patients of training cohort into high and low risk subsets in terms of disease-specific survival (DSS). This cutoff point was validated in validation cohort before and after PSM (P < 0.001, P = 0.002). More TD count, which was defined as more than 3, was validated as an independent risk prognostic factor in univariate and multivariate analysis (P < 0.001).

CONCLUSION

More TD count (TD count ≥ 4) was significantly associated with poor disease-specific survival in CRC patients.

A competing-risk nomogram to predict cause-specific death in elderly patients with colorectal cancer after surgery (especially for colon cancer)

Background

Clinically, when the diagnosis of colorectal cancer is clear, patients are more concerned about their own prognosis survival. Special population with high risk of accidental death, such as elderly patients, is more likely to die due to causes other than tumors. The main purpose of this study is to construct a prediction model of cause-specific death (CSD) in elderly patients using competing-risk approach, so as to help clinicians to predict the probability of CSD in elderly patients with colorectal cancer.

Methods

The data were extracted from Surveillance, Epidemiology, and End Results (SEER) database to include ≥ 65-year-old patients with colorectal cancer who had undergone surgical treatment from 2010 to 2016. Using competing-risk methodology, the cumulative incidence function (CIF) of CSD was calculated to select the predictors among 13 variables, and the selected variables were subsequently refined and used for the construction of the proportional subdistribution hazard model. The model was presented in the form of nomogram, and the performance of nomogram was bootstrap validated internally and externally using the concordance index (C-index).

Results

Dataset of 19,789 patients who met the inclusion criteria were eventually selected for analysis. The five-year cumulative incidence of CSD was 31.405% (95% confidence interval [CI] 31.402–31.408%). The identified clinically relevant variables in nomogram included marital status, pathological grade, AJCC TNM stage, CEA, perineural invasion, and chemotherapy. The nomogram was shown to have good discrimination after internal validation with a C-index of 0.801 (95% CI 0.795–0.807) as well as external validation with a C-index of 0.759 (95% CI 0.716–0.802). Both the internal and external validation calibration curve indicated good concordance between the predicted and actual outcomes.

Conclusion

Using the large sample database and competing-risk analysis, a postoperative prediction model for elderly patients with colorectal cancer was established with satisfactory accuracy. The individualized estimates of CSD outcome for the elderly patients were realized.

Reconsidering the prognostic significance of tumour deposit count in the TNM staging system for colorectal cancer

Although the occurrence of tumour deposits (TDs) without metastatic lymph nodes (mLNs) is classified as "N1c" in the 8th TNM staging system for colorectal cancer (CRC), the prognostic significance of the TD count is still controversial. A total of 39155 CRC patients were collected from the Surveillance, Epidemiology, and End Results (SEER) database. The potential associations between baseline characteristics and TD status were evaluated using the χ2 test. Cancer-specific survival (CSS) rates were calculated by using the Kaplan-Meier method, and CSS comparisons were performed by using the log-rank test. The results showed that TD count was an important prognostic factor and that the number of TDs was negatively correlated with the prognosis of CRC patients. We found that the prognostic value of one TD is equivalent to that of two mLNs based on the comparison of CSS rates. Accordingly, we proposed a novel N staging system by integrating the TD count into the N category with the ratio of TDs to mLNs being 1:2. There were no prognostic differences in patients with or without TDs in each novel N category. Weighing one TD as two mLNs in this novel TNM staging system is superior to the "N1c" classification in the 8th TNM staging system in evaluating the prognosis of CRC patients.

Prognosis of synchronous colorectal carcinoma compared to solitary colorectal carcinoma: a matched pair analysis

BACKGROUND

Synchronous colorectal carcinoma (CRC) is a specific and rare type of colorectal malignancy. The data on the impact of synchronous CRC are controversial. This study aimed to compare the characteristics and prognosis between synchronous CRC and solitary CRC.

PATIENTS AND METHODS

252 patients who underwent surgery between October 2009 and June 2013 with synchronous CRC (n = 126) or solitary CRC (n = 126) were included. The patients were matched according to age, sex, American Society of Anesthesiologists score, BMI, cancer grade, tumor location, and tumor stage. The short-term outcomes included the length of hospital stay, complications, and 30-day mortality. Long-term endpoints were overall survival (OS), disease-free survival (DFS), and cancer-specific survival (CSS).

RESULTS

The median follow-up duration for all patients were 42.5 months. The incidence of synchronous CRC was high than in older and male patients as well as in mucinous adenocarcinoma containing signet-ring cell carcinoma, tumor deposit, and polypus. The length of hospital stay after surgery was longer for synchronous CRC than solitary CRC (median: 10 vs. 4 days, P = 0.033). In multivariate analysis, synchronous CRC was an independent prognostic factor associated with poor OS (hazard ratio: 2.355, 95% confidence interval: 1.322-4.195, P = 0.004), DFS (hazard ratio: 2.079, 95% confidence interval: 1.261-3.429, P = 0.004), and CSS (hazard ratio: 2.429, 95% confidence interval: 1.313-4.493, P = 0.005).

CONCLUSION

The clinical and pathological features exhibit differences between synchronous CRC and solitary CRC and the prognosis of patients with synchronous CRC was poorer than those with solitary CRC.

The unique prognostic characteristics of tumor deposits in colorectal cancer patients

Background

Both AJCC 7th and 8th TNM systems have included tumor deposits (TDs) in nodal staging when lymph nodes metastases (LNMs) are negative in colorectal cancer (CRC). However, the prognostic role of TDs has not been determined in the presence of positive LNMs.

Methods

Two independent large-scale cohorts of CRC patients from the Surveillance Epidemiology and End Results (SEER) database (n=69,178) [2010-2013] and Fudan University Shanghai Cancer Center (FUSCC) (n=3,137) [2010-2014] were retrospectively analyzed. Kaplan-Meier method was used to estimate survival curves and univariate and multivariate analyses were performed by Cox proportional hazard model.

Results

TDs were observed in 12.3% (n=8,480) and 14.8% (n=463) of patients in the SEER and FUSCC cohorts, respectively. Multivariate analysis suggested TDs were an independent adverse prognostic factors for overall survival (OS) (P<0.001). Remarkably, both cohorts showed the presence of TDs was significantly associated with OS, but not was the number of TDs (P=0.982 and P=0.252 for the SEER and FUSCC cohorts, respectively). In the presence of LNMs, positive TDs were associated with a shorter OS [hazard ratio (HR): 2.69, 95.0% confidence interval (CI): 2.597-2.778; P<0.001]. Further analysis combining TDs with LNMs demonstrated that the prognosis of patients with N1TD (N1 with positive TDs) was same as the N2 patients, and N2TD (N2 with positive TDs) patients had much worse prognosis than N2 (P<0.001).

Conclusions

Our results have shown the unique features of TDs in patients with CRC, different from LNMs. In the presence of LNMs, TDs should also be considered in TMN system.

Prognostic value of N1c in colorectal cancer: a large population-based study using propensity score matching

PURPOSE

We conducted this large population-based study to investigate the prognostic significance of N1c.

METHODS

Patients diagnosed with colorectal cancer from the surveillance, epidemiology, and end results (SEER) database between January 1, 2010, and December 31, 2010, were included in the sample. The primary outcome of interest used in our study was cause-specific survival (CSS). Cox proportional hazards models and Kaplan-Meier methods were used to evaluate the prognostic value of N1c. Propensity score matching (PSM) was implemented to reduce the possibility of selection bias using a logistic regression model.

RESULTS

A total of 19,991 patients diagnosed with colorectal cancer were identified from the SEER database. The median follow-up time of the whole cohort was 60 months (0-71 months). Multivariate Cox analysis showed that N1c was associated with significantly higher risk of colorectal cancer-specific mortality compared with N0 (HR = 1.962, 95%CI = 1.642 to 2.343, P < 0.001) and N1a (HR = 0.818, 95%CI = 0.678 to 0.987, P = 0.036); N1c was associated with significantly lower risk of colorectal cancer-specific mortality compared with N2a (HR = 1.296, 95%CI = 1.081 to 1.554, P = 0.005) and N2b (HR = 1.663, 95%CI = 1.391 to 1.989, P < 0.001). Yet the CSS difference between N1b and N1c did not achieve statistical difference (HR = 1.089, 95%CI = 0.909 to 1.304, P = 0.354).

CONCLUSIONS

The large population-based and propensity score-matched study with long follow-up time provides the first evidence that CSS difference between N1b and N1c does not achieve a statistical difference.

Tumor deposit is an independent prognostic indicator in patients who underwent radical resection for colorectal cancer

Background: Tumor deposits are one of the promising factors among the different edition of Tumor, Node, Metastasis classification. Despite improvement in the treatment of various types of metastatic disease the source and prognostic significance of tumor deposits in staging has not been deliberating the agreeable opinion. We investigated the possibility of tumor deposit as independent prognostic factor and evaluating its prognostic value in colorectal carcinoma patients. Methods: Author studied 313 colorectal cancer patients clinocopathological data and outcome who underwent radical resection. Data between 2011-2015 were retrospectively collected from Shanghai East Hospital, affiliated with Tongji University data information centre. The analysis was used to calculate 2 years disease free survival(DFS) and relation of tumor deposit with number of lymph node positive. Cox-regression analysis was performed to assess the prognostic factor. Results: Out of 313 colorectal patients included in the study, tumor deposits were detected in 17%. Tumor deposits (TDs) are relevantly associated with significant poor outcomes. The tumor deposit were significantly correlated with T-stage(P=<0.001), N-stage(P=<0.001), PLNC(P=<0.001), venous invasion(P=<0.001), TNM staging(P=<0.001), CEA(P=0.021) and CA19-9(P=0.042) of primary tumor. The Kaplan-Meier analysis revealed that disease-free survival of CRC patients with positive tumor deposit were significantly poorer that those with negative tumor deposit cohort(P=<0.001) And with multivariate analysis in different model, we found that positive tumor deposit were significantly associated with shorter DSF which is totally independent with lymph node status (P=0.001 and P=0.023 respectively). Subgroup analysis found that of 179 CRC patients with negative lymph node status, the DFS of patients with positive tumor deposit were significantly shorter that those with negative tumor deposit(P=,0.001). Of 134patients with positive lymph node status, the DFS of patients shows similar result. (P=<0.001). Conclusion: We have shown that TDs are not equal to lymph node metastasis with respect to biology and outcome. Tumor deposits are an independent adverse prognostic factor in CRC patient who have undergone radical resection.

Prognostic value and characteristics of N1c colorectal cancer

AIM

The presence of tumour deposits (TDs) in colorectal cancer (CRC) is associated with poor prognosis. The seventh edition of TNM subclassified a new nodal stage, N1c, characterized by the presence of TDs without any concurrent positive lymph node (LN). It is not clear if the N1c category is or is not equal to LN metastasis. We aimed to examine the prevalence, characteristics and prognostic significance of this new subcategory.

METHOD

Consecutive patients who underwent surgery for CRC in two centres (2011-2014) were analysed. N1 cM0 patients were matched against non-N1 cM0 (N0, N1a and N1b) patients for 3-year overall survival (OS) and disease-free survival (DFS).

RESULTS

We identified 1122 patients with 648 (57.8%) colonic cancers. In 57 patients (5.1%), N1c status was associated with rectal cancers [rectum = 33/57 (57.9%) vs colon = 24/57 (42.1%); P = 0.029], a higher pathological tumour stage [pT3-T4 N1c = 55/843 (6.5% vspT3-T4 non-N1c = 2/279 (0.7%); P < 0.0001] and vascular emboli [n = 35 (61.4%) vs n = 552 (51.8%); P = 0.0305]. Synchronous metastasis was observed in 23 cases (40%). After a mean follow-up of 31 months, 3-year OS for M0 patients, was 89.4%, 89.1%, 86.6% and 81.8% for N0, N1a, N1b and N1c tumours, respectively. DFS was significantly worse for N1c than for N0 (P = 0.0169), with N1c status having a significant effect on DFS in colonic cancers (P = 0.014). The presence of more than one TD was associated with a significantly worse DFS (P = 0.021).

CONCLUSION

Our results indicate that N1c CRC patients should be included among high-risk patients for whom it is widely accepted that adjuvant chemotherapy should be considered.

Newly recognized extratumoral features of colorectal cancer challenge the current tumor-node-metastasis staging system

One of the most common malignant tumors in humans, colorectal cancer has been extensively studied during the past few decades. Staging colorectal cancer allows clinicians to obtain precise prognostic information and apply specific treatment procedures. Apart from remote metastases, the depth of tumor infiltration and lymph node involvement have traditionally been recognized as the most important factors predicting outcome. Variations in the molecular signature of colorectal cancer have also revealed differences in phenotypic aggressiveness and therapeutic response rates. This article presents a review of the extratumoral environment in colorectal surgery.

Beyond T, N and M: The impact of tumor deposits on the staging and treatment of colorectal and gastric carcinoma

This review aims to describe the results of the most recent studies on the prognostic value of TDs and highlight the impact of TDs on the staging and treatment of colorectal and gastric carcinoma. For colorectal carcinoma TDs have an adverse prognostic effect that is at least similar to that of positive regional lymph nodes. However, support is growing in favor of including of TDs in the M category, rather than the N or T categories of the TNM classification. Moreover, TDs seem to have an adverse effect on outcomes not only in patients without lymph node involvement but also in patients with nodal involvement. Although the prognostic impact of TDs in gastric cancer appears to be undeniable, the actual prognostic determinants of TDs, particularly in relation to the number, size and histological types, remain to be established. Although the 7th and 8th Edition of the TNM classification of colorectal and gastric carcinoma includes TDs in the N category, no current procedures or methods to assess preoperative or intraoperative N-status allow TD detection. After neoadjuvant treatment for advanced rectal carcinoma, the presence of TDs may indicate incomplete eradication of the main tumor and not discontinuous tumor foci. TDs have an undeniable prognostic impact but no algorithm of staging and strategy of treatment has been conformed to this prognostic factor to overcome the classical T,N, and M prognostic categories. Staging and treatment of colorectal and gastric cancers should be reconsidered in light of the emerging prognostic value of TDs.

A modified TNM staging system for non-metastatic colorectal cancer based on nomogram analysis of SEER database

Background

To revise the American Joint Committee on Cancer TNM staging system for colorectal cancer (CRC) based on a nomogram analysis of Surveillance, Epidemiology, and End Results (SEER) database, and to prove the rationality of enhancing T stage’s weighting in our previously proposed T-plus staging system.

Methods

Total 115,377 non-metastatic CRC patients from SEER were randomly grouped as training and testing set by ratio 1:1. The Nomo-staging system was established via three nomograms based on 1-year, 2-year and 3-year disease specific survival (DSS) Logistic regression analysis of the training set. The predictive value of Nomo-staging system for the testing set was evaluated by concordance index (c-index), likelihood ratio (L.R.) and Akaike information criteria (AIC) for 1-year, 2-year, 3-year overall survival (OS) and DSS. Kaplan–Meier survival curve was used to valuate discrimination and gradient monotonicity. And an external validation was performed on database from the Second Affiliated Hospital of Zhejiang University (SAHZU).

Results

Patients with T1-2 N1 and T1N2a were classified into stage II while T4 N0 patients were classified into stage III in Nomo-staging system. Kaplan–Meier survival curves of OS and DSS in testing set showed Nomo-staging system performed better in discrimination and gradient monotonicity, and the external validation in SAHZU database also showed distinctly better discrimination. The Nomo-staging system showed higher value in L.R. and c-index, and lower value in AIC when predicting OS and DSS in testing set.

Conclusion

The Nomo-staging system showed better performance in prognosis prediction and the weight of lymph nodes status in prognosis prediction should be cautiously reconsidered.

Electronic supplementary material

The online version of this article (10.1186/s12885-017-3796-1) contains supplementary material, which is available to authorized users.