Survival paradox between stage IIB/C (T4N0) and stage IIIA (T1-2N1) colon cancer

Revisiting the survival paradox between stage IIB/C and IIIA colon cancer

Patients with stage IIB/C (T4a-bN0) colon cancer often exhibit worse survival rates compared to those with stage IIIA (T1-2N1, T1N2a) colon cancer. This study re-evaluates the survival paradox using the latest Surveillance, Epidemiology, and End Results (SEER) data (released on April 17, 2024) to inform potential revisions to the staging criteria. Utilizing SEER data with 8th edition TNM staging criteria, 4692 colon cancer patients diagnosed between 2018 and 2021 were analyzed with chi-square test. Cox regression and Kaplan-Meier survival analysis were employed to assess factors associated with cancer-specific survival (CSS) and overall survival (OS). The 3-year CSS rates for stage IIB and IIC were 73.1% and 70.3%, respectively, whereas stage IIIA had a substantially higher CSS rate of 91% (P < 0.001). Similarly, the OS rates were 64.9% and 63.0% for stage IIB and IIC, respectively, compared to 83.1% for stage IIIA (P < 0.001). Multivariate analyses revealed stage IIIA patients had significantly lower risks of cancer-specific mortality (hazard ratio (HR) = 0.374, 95% CI: 0.296-0.473, P < 0.001) and overall mortality (HR = 0.575, 95% CI: 0.483-0.685, P < 0.001) compared to stage IIB patients. The upcoming 9th edition of the AJCC staging system should address this paradox by integrating advanced diagnostic markers and emphasizing the aggressive biology of T4 tumor, providing more accurate prognostic information and guiding more effective treatment strategies for colon cancer patients.

Developing survival prediction models in colorectal cancer using epigenome-wide DNA methylation data from whole blood

While genome-wide association studies are valuable in identifying CRC survival predictors, the benefit of adding blood DNA methylation (blood-DNAm) to clinical features, including the TNM system, remains unclear. In a multi-site population-based patient cohort study of 2116 CRC patients with baseline blood-DNAm, we analyzed survival predictions using eXtreme Gradient Boosting with a 5-fold nested leave-sites-out cross-validation across four groups: traditional and comprehensive clinical features, blood-DNAm, and their combination. Model performance was assessed using time-dependent ROC curves and calibrations. During a median follow-up of 10.3 years, 1166 patients died. Although blood-DNAm-based predictive signatures achieved moderate performances, predictive signatures based on clinical features outperformed blood-DNAm signatures. The inclusion of blood-DNAm did not improve survival prediction over clinical features. M1 stage, age at blood collection, and N2 stage were the top contributors. Despite some prognostic value, incorporating blood DNA methylation did not enhance survival prediction of CRC patients beyond clinical features.

Construction and validation of a deep learning prognostic model based on digital pathology images of stage III colorectal cancer

BACKGROUND

TNM staging is the main reference standard for prognostic prediction of colorectal cancer (CRC), but the prognosis heterogeneity of patients with the same stage is still large. This study aimed to classify the tumor microenvironment of patients with stage III CRC and quantify the classified tumor tissues based on deep learning to explore the prognostic value of the developed tumor risk signature (TRS).

METHODS

A tissue classification model was developed to identify nine tissues (adipose, background, debris, lymphocytes, mucus, smooth muscle, normal mucosa, stroma, and tumor) in whole-slide images (WSIs) of stage III CRC patients. This model was used to extract tumor tissues from WSIs of 265 stage III CRC patients from The Cancer Genome Atlas and 70 stage III CRC patients from the Sixth Affiliated Hospital of Sun Yat-sen University. We used three different deep learning models for tumor feature extraction and applied a Cox model to establish the TRS. Survival analysis was conducted to explore the prognostic performance of TRS.

RESULTS

The tissue classification model achieved 94.4 % accuracy in identifying nine tissue types. The TRS showed a Harrell's concordance index of 0.736, 0.716, and 0.711 in the internal training, internal validation, and external validation sets. Survival analysis showed that TRS had significant predictive ability (hazard ratio: 3.632, p = 0.03) for prognostic prediction.

CONCLUSION

The TRS is an independent and significant prognostic factor for PFS of stage III CRC patients and it contributes to risk stratification of patients with different clinical stages.

Multivariable prognostic modelling to improve prediction of colorectal cancer recurrence: the PROSPeCT trial

OBJECTIVE

Improving prognostication to direct personalised therapy remains an unmet need. This study prospectively investigated promising CT, genetic, and immunohistochemical markers to improve the prediction of colorectal cancer recurrence.

MATERIAL AND METHODS

This multicentre trial (ISRCTN 95037515) recruited patients with primary colorectal cancer undergoing CT staging from 13 hospitals. Follow-up identified cancer recurrence and death. A baseline model for cancer recurrence at 3 years was developed from pre-specified clinicopathological variables (age, sex, tumour-node stage, tumour size, location, extramural venous invasion, and treatment). Then, CT perfusion (blood flow, blood volume, transit time and permeability), genetic (RAS, RAF, and DNA mismatch repair), and immunohistochemical markers of angiogenesis and hypoxia (CD105, vascular endothelial growth factor, glucose transporter protein, and hypoxia-inducible factor) were added to assess whether prediction improved over tumour-node staging alone as the main outcome measure.

RESULTS

Three hundred twenty-six of 448 participants formed the final cohort (226 male; mean 66 ± 10 years. 227 (70%) had ≥ T3 stage cancers; 151 (46%) were node-positive; 81 (25%) developed subsequent recurrence. The sensitivity and specificity of staging alone for recurrence were 0.56 [95% CI: 0.44, 0.67] and 0.58 [0.51, 0.64], respectively. The baseline clinicopathologic model improved specificity (0.74 [0.68, 0.79], with equivalent sensitivity of 0.57 [0.45, 0.68] for high vs medium/low-risk participants. The addition of prespecified CT perfusion, genetic, and immunohistochemical markers did not improve prediction over and above the clinicopathologic model (sensitivity, 0.58-0.68; specificity, 0.75-0.76).

CONCLUSION

A multivariable clinicopathological model outperformed staging in identifying patients at high risk of recurrence. Promising CT, genetic, and immunohistochemical markers investigated did not further improve prognostication in rigorous prospective evaluation.

CLINICAL RELEVANCE STATEMENT

A prognostic model based on clinicopathological variables including age, sex, tumour-node stage, size, location, and extramural venous invasion better identifies colorectal cancer patients at high risk of recurrence for neoadjuvant/adjuvant therapy than stage alone.

KEY POINTS

Identification of colorectal cancer patients at high risk of recurrence is an unmet need for treatment personalisation. This model for recurrence, incorporating many patient variables, had higher specificity than staging alone. Continued optimisation of risk stratification schema will help individualise treatment plans and follow-up schedules.

Complete Obstruction, a Real Risk Factor: A Comprehensive Study on Obstruction in Stage IIA Colon Cancer With Propensity Score Matching Analysis

MICROABSTRACT

This study evaluates the prognostic significance of obstructions in stage IIA colon cancer, distinguishing between partial and complete obstructions. It employs a retrospective review of 1914 patients with propensity score matching to analyze oncologic outcomes. Findings reveal complete obstruction as a significant risk factor for poorer outcomes, emphasizing the necessity for further research to refine treatment strategies, particularly regarding the efficacy of adjuvant chemotherapy across obstruction types.

BACKGROUND

This study examined the prognostic impact of obstructions in stage IIA colon cancer. The analysis specifically differentiated partial and complete obstructions, analyzing their distinct influences of both on oncologic outcomes.

MATERIALS AND METHODS

A retrospective review was conducted of stage IIA colon cancer cases with the presence of an obstruction. Patients were stratified by whether it was partial or complete based on the severity of obstruction. Propensity score matching was employed to control for confounders.

RESULTS

Among 1914 consecutive patients diagnosed with stage IIA colon cancer, 758 patients (597 patients with partial obstruction, 161 patients with complete obstruction) exhibited obstruction, while 1156 patients had no obstruction. The median follow-up period was 126 months. Complete obstruction was associated with poorer disease-free survival (Hazard ratio (HR) = 1.785, P < .001) and overall survival (HR = 1.853, P = .001). This trend persisted after propensity score matching, patients with complete obstruction showing a worsened disease-free survival (HR = 1.666, P = .028) and overall survival (HR = 1.732, P = .041). Adjuvant chemotherapy showed improved outcomes overall, but its efficacy varied across obstruction types.

CONCLUSION

Differentiating between complete and partial obstructions in stage IIA colon cancer is an important clinical distinction, as our findings suggest that complete obstruction is a significant risk factor for poorer oncologic outcomes. While adjuvant chemotherapy generally improves prognosis in stage IIA colon cancer, the correlation of obstruction type with its efficacy remains uncertain, necessitating further research to refine treatment strategies.

Predicting 5-year recurrence risk in colorectal cancer: development and validation of a histology-based deep learning approach

BACKGROUND

Accurate estimation of the long-term risk of recurrence in patients with non-metastatic colorectal cancer (CRC) is crucial for clinical management. Histology-based deep learning is expected to provide more abundant information for risk stratification.

METHODS

We developed and validated a weakly supervised deep-learning model for predicting 5-year relapse-free survival (RFS) to stratify patients with different risks based on histological images from three hospitals of 614 cases with non-metastatic CRC. A deep prognostic factor (DL-RRS) was established to stratify patients into high and low-risk group. The areas under the curve (AUCs) were calculated to evaluate the performances of models.

RESULTS

Our proposed model achieves the AUCs of 0.833 (95% CI: 0.736-0.905) and 0.715 (95% CI: 0.647-0.776) on validation cohort and external test cohort, respectively. The 5-year RFS rate was 45.7% for high DL-RRS patients, and 82.5% for low DL-RRS patients respectively in the external test cohort (HR: 3.89, 95% CI: 2.51-6.03, P < 0.001). Adjuvant chemotherapy was associated with improved RFS in Stage II patients with high DL-RRS (HR: 0.15, 95% CI: 0.06-0.38, P < 0.001).

CONCLUSIONS

DL-RRS has a good predictive performance of 5-year recurrence risk in CRC, and will better serve the clinical decision-making.

Machine-Learning Algorithms Using Systemic Inflammatory Markers to Predict the Oncologic Outcomes of Colorectal Cancer After Surgery

BACKGROUND

This study aimed to investigate the clinical significance of machine-learning (ML) algorithms based on serum inflammatory markers to predict survival outcomes for patients with colorectal cancer (CRC).

METHODS

The study included 941 patients with stages I to III CRC. Based on random forest algorithms using 15 compositions of inflammatory markers, four different prediction scores (DFS score-1, DFS score-2, DFS score-3, and DFS score-4) were developed for the Yonsei cohort (training set, n = 803) and tested in the Ulsan cohort (test set, n = 138). The Cox proportional hazards model was used to determine correlation between prediction scores and disease-free survival (DFS). Harrell's concordance index (C-index) was used to compare the predictive ability of prediction scores for each composition.

RESULTS

The multivariable analysis showed the DFS score-4 to be an independent prognostic factor after adjustment for clinicopathologic factors in both the training and test sets (hazard ratio [HR], 8.98; 95% confidence interval [CI] 6.7-12.04; P < 0.001 for the training set and HR, 2.55; 95% CI 1.1-5.89; P = 0.028 for the test set]. With regard to DFS, the highest C-index among single compositions was observed in the lymphocyte-to-C-reactive protein ratio (LCR) (0.659; 95% CI 0.656-0.662), and the C-index of DFS score-4 (0.727; 95% CI 0.724-0.729) was significantly higher than that of LCR in the test set. The C-index of DFS score-3 (0.725; 95% CI 0.723-0.728) was similar to that of DFS score-4, but higher than that of DFS score-2 (0.680; 95% CI 0.676-0.683).

CONCLUSIONS

The ML-based approaches showed prognostic utility in predicting DFS. They could enhance clinical use of inflammatory markers in patients with CRC.

Advantage of log odds of positive lymph nodes in prognostic evaluation of patients with early-onset colon cancer

BACKGROUND

Colon cancer (CC) is one of the most common cancers of the digestive tract, the third most common cancer worldwide, and the second most common cause of cancer-related deaths. Previous studies have demonstrated a higher risk of lymph node metastasis (LNM) in young patients with CC. It might be reasonable to treat patients with early-onset locally advanced CC with extended lymph node dissection. However, few studies have focused on early-onset CC (ECC) patients with LNM. At present, the methods of predicting and evaluating the prognosis of ECC patients with LNM are controversial.

AIM

To compare the prognostic values of four lymph node staging indices and establish the best nomogram for patients with ECC.

METHODS

From the data of patients with CC obtained from the Surveillance, Epidemiology, and End Results (SEER) database, data of young patients with ECC (≤ 50 years old) was screened. Patients with unknown data were excluded from the study, while the remaining patients were included. The patients were randomly divided into a training group (train) and a testing group (test) in the ratio of 7:3, while building the model. The model was constructed by the training group and verified by the testing group. Using multiple Cox regression models to compare the prediction efficiency of LNM indicators, nomograms were built based on the best model selected for overall survival (OS) and cause-specific survival (CSS). In the two groups, the performance of the nomogram was evaluated by constructing a calibration plot, time-dependent area under the curve (AUC), and decision curve analysis. Finally, the patients were grouped based on the risk score predicted by the prognosis model, and the survival curve was constructed after comparing the survival status of the high and low-risk groups.

RESULTS

Records of 26922 ECC patients were screened from the SEER database. N classification, positive lymph nodes (PLN), lymph node ratio (LNR) and log odds of PLN (LODDS) were considered to be independent predictors of OS and CSS. In addition, independent risk factors for OS included gender, race, marital status, primary site, histology, grade, T, and M classification, while the independent prognostic factors for CSS included race, marital status, primary site, grade, T, and M classification. The prediction model including LODDS is composed of minimal Akaike information criterion, maximal concordance indexes, and AUCs. Factors including gender, race, marital status, primary site, histology, grade, T, M classification, and LODDS were integrated into the OS nomogram, while race, marital status, primary site, grade, T, M classification, and LODDS were included into the CSS nomogram. The nomogram representing both cohorts had been successfully verified in terms of prediction accuracy and clinical practicability.

CONCLUSION

LODDS is superior to N-stage, PLN, and LNR of ECC. The nomogram containing LODDS might be helpful in tumor evaluation and clinical decision-making, since it provides an appropriate prediction of ECC.

Histopathology and levels of proteins in plasma associate with survival after colorectal cancer diagnosis

BACKGROUND

The TNM system is used to assess prognosis after colorectal cancer (CRC) diagnosis. Other prognostic factors reported include histopathological assessments of the tumour, tumour mutations and proteins in the blood. As some of these factors are strongly correlated, it is important to evaluate the independent effects they may have on survival.

METHODS

Tumour samples from 2162 CRC patients were visually assessed for amount of tumour stroma, severity of lymphocytic infiltrate at the tumour margins and the presence of lymphoid follicles. Somatic mutations in the tumour were assessed for 2134 individuals. Pre-surgical levels of 4963 plasma proteins were measured in 128 individuals. The associations between these features and prognosis were inspected by a Cox Proportional Hazards Model (CPH).

RESULTS

Levels of stroma, lymphocytic infiltration and presence of lymphoid follicles all associate with prognosis, along with high tumour mutation burden, high microsatellite instability and TP53 and BRAF mutations. The somatic mutations are correlated with the histopathology and none of the somatic mutations associate with survival in a multivariate analysis. Amount of stroma and lymphocytic infiltration associate with local invasion of tumours. Elevated levels of two plasma proteins, CA-125 and PPP1R1A, associate with a worse prognosis.

CONCLUSIONS

Tumour stroma and lymphocytic infiltration variables are strongly associated with prognosis of CRC and capture the prognostic effects of tumour mutation status. CA-125 and PPP1R1A may be useful prognostic biomarkers in CRC.

Identification of a ferroptosis-related gene signature predicting recurrence in stage II/III colorectal cancer based on machine learning algorithms

Background: Colorectal cancer (CRC) is one of the most prevalent cancer types globally. A survival paradox exists due to the inherent heterogeneity in stage II/III CRC tumor biology. Ferroptosis is closely related to the progression of tumors, and ferroptosis-related genes can be used as a novel biomarker in predicting cancer prognosis. Methods: Ferroptosis-related genes were retrieved from the FerrDb and KEGG databases. A total of 1,397 samples were enrolled in our study from nine independent datasets, four of which were integrated as the training dataset to train and construct the model, and validated in the remaining datasets. We developed a machine learning framework with 83 combinations of 10 algorithms based on 10-fold cross-validation (CV) or bootstrap resampling algorithm to identify the most robust and stable model. C-indice and ROC analysis were performed to gauge its predictive accuracy and discrimination capabilities. Survival analysis was conducted followed by univariate and multivariate Cox regression analyses to evaluate the performance of identified signature. Results: The ferroptosis-related gene (FRG) signature was identified by the combination of Lasso and plsRcox and composed of 23 genes. The FRG signature presented better performance than common clinicopathological features (e.g., age and stage), molecular characteristics (e.g., BRAF mutation and microsatellite instability) and several published signatures in predicting the prognosis of the CRC. The signature was further stratified into a high-risk group and low-risk subgroup, where a high FRG signature indicated poor prognosis among all collected datasets. Sensitivity analysis showed the FRG signature remained a significant prognostic factor. Finally, we have developed a nomogram and a decision tree to enhance prognosis evaluation. Conclusion: The FRG signature enabled the accurate selection of high-risk stage II/III CRC population and helped optimize precision treatment to improve their clinical outcomes.

Is the prognosis of T1-2N1 colon cancer the same as that of T1-2N0 colon cancer after curative surgery?

Objectives: The prognoses of T1-2N0 and T1-2N1 colon cancer after curative surgery remain unclear. This study compared the prognoses of patients with T1-2N0 and T1-2N1 colon cancer after curative surgery.Materials and methods: We retrospectively evaluated 307 consecutive patients with T1-2N0/1 colon cancer who underwent radical surgery at our hospital between January 2010 and December 2016. There were 266 patients with T1-2N0 colon cancer and 41 patients with T1-2N1 colon cancer. After excluding patients with <12 retrieved lymph nodes, 179 patients with T1-2N0 and 32 with T1-2N1 colon cancer were included in the cohort.Results: Overall survival and disease-free survival did not differ between the T1-2N0 and T1-2N1 groups (p = 0.498 and p = 0.681, respectively). Overall survival and disease-free survival were not significantly different between the T1-2N1 + no chemotherapy and T1-2N1 + chemotherapy groups (p = 0.740 and p = 0.765, respectively). Additionally, overall survival and disease-free survival did not differ between the T1-2N0, T1-2N1 + no chemotherapy, and T1-2N1 + chemotherapy groups (p = 0.757 and p = 0.877, respectively), even after excluding patients with <12 retrieved lymph nodes.Conclusions: T1-2N1 has a prognosis as good as that of T1-2N0 colon cancer after curative surgery. Moreover, further research is needed to investigate the efficacy of adjuvant FOLFOX chemotherapy in T1-2N1.

Evaluation of ctDNA in the Prediction of Response to Neoadjuvant Therapy and Prognosis in Locally Advanced Rectal Cancer Patients: A Prospective Study

“Watch and wait” is becoming a common treatment option for patients with locally advanced rectal cancer (LARC) submitted to neoadjuvant treatment. However, currently, no clinical modality has an acceptable accuracy for predicting pathological complete response (pCR). The aim of this study was to assess the clinical utility of circulating tumor DNA (ctDNA) in predicting the response and prognosis in these patients. We prospectively enrolled a cohort of three Iberian centers between January 2020 and December 2021 and performed an analysis on the association of ctDNA with the main response outcomes and disease-free survival (DFS). The rate of pCR in the total sample was 15.3%. A total of 24 plasma samples from 18 patients were analyzed by next-generation sequencing. At baseline, mutations were detected in 38.9%, with the most common being TP53 and KRAS. Combination of either positive magnetic resonance imaging (MRI) extramural venous invasion (mrEMVI) and ctDNA increased the risk of poor response (p = 0.021). Also, patients with two mutations vs. those with fewer than two mutations had a worse DFS (p = 0.005). Although these results should be read carefully due to sample size, this study suggests that baseline ctDNA combined with mrEMVI could potentially help to predict the response and baseline ctDNA number of mutations might allow the discrimination of groups with different DFS. Further studies are needed to clarify the role of ctDNA as an independent tool in the selection and management of LARC patients.

Integrated analysis identifies oxidative stress-related lncRNAs associated with progression and prognosis in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is one of the most common cancers in the world. Oxidative stress reactions have been reportedly associated with oncogenesis and tumor progression. By analyzing mRNA expression data and clinical information from The Cancer Genome Atlas (TCGA), we aimed to construct an oxidative stress-related long noncoding RNA (lncRNA) risk model and identify oxidative stress-related biomarkers to improve the prognosis and treatment of CRC.

RESULTS

Differentially expressed oxidative stress-related genes (DEOSGs) and oxidative stress-related lncRNAs were identified by using bioinformatics tools. An oxidative stress-related lncRNA risk model was constructed based on 9 lncRNAs (AC034213.1, AC008124.1, LINC01836, USP30-AS1, AP003555.1, AC083906.3, AC008494.3, AC009549.1, and AP006621.3) by least absolute shrinkage and selection operator (LASSO) analysis. The patients were then divided into high- and low-risk groups based on the median risk score. The high-risk group had a significantly worse overall survival (OS) (p < 0.001). Receiver operating characteristic (ROC) and calibration curves displayed the favorable predictive performance of the risk model. The nomogram successfully quantified the contribution of each metric to survival, and the concordance index and calibration plots demonstrated its excellent predictive capacity. Notably, different risk subgroups showed significant differences in terms of their metabolic activity, mutation landscape, immune microenvironment and drug sensitivity. Specifically, differences in the immune microenvironment implied that CRC patients in certain subgroups might be more responsive to immune checkpoint inhibitors.

CONCLUSIONS

Oxidative stress-related lncRNAs can predict the prognosis of CRC patients, which provides new insight for future immunotherapies based on potential oxidative stress targets.

Combining prognostic nutritional index (PNI) and controlling nutritional status (CONUT) score as a valuable prognostic factor for overall survival in patients with stage I-III colorectal cancer

Background and aims

This study compared the prognostic significance of various nutritional and inflammatory indicators such as neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio and platelet-to-lymphocyte ratio, prognostic nutritional index, and controlling nutritional status score. In addition, we aimed to establish a more accurate prognostic indicator.

Methods

We retrospectively evaluated 1112 patients with stage I-III colorectal cancer between January 2004 and April 2014. The controlling nutritional status scores were classified as low (0-1), intermediate (2-4), and high (5-12) scores. The cut-off values for prognostic nutritional index and inflammatory markers were calculated using the X-tile program. P-CONUT, a combination of prognostic nutritional index and the controlling nutritional status score, was suggested. The integrated areas under the curve were then compared.

Results

The multivariable analysis showed that prognostic nutritional index was an independent prognostic factor for overall survival, whereas the controlling nutritional status score, neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, and platelet-to-lymphocyte ratio were not. The patients were divided into three P-CONUT groups as follows: G1, controlling nutritional status (0-4) and high prognostic nutritional index; G2, controlling nutritional status (0-4) and low prognostic nutritional index; and G3, controlling nutritional status (5-12) and low prognostic nutritional index. There were significant survival differences between the P-CONUT groups (5-year overall survival of G1, G2, and G3 were 91.7%, 81.2%, and 64.1%, respectively; p < 0.0001). The integrated areas under the curve of P-CONUT (0.610, CI: 0.578-0.642) was superior to those of the controlling nutritional status score alone (bootstrap integrated areas under the curve mean difference=0.050; 95% CI=0.022-0.079) and prognostic nutritional index alone (bootstrap integrated areas under the curve mean difference=0.012; 95% CI=0.001-0.025).

Conclusion

Prognostic effect of P-CONUT may be better than inflammatory markers such as neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio and platelet-to-lymphocyte ratio. Thus, it could be used as a reliable nutritional risk stratification tool in patients with colorectal cancer.

The impact of adjuvant oxaliplatin and tumor sidedness on the overall survival of stage IIB colon cancer patients: a multicentre study

The aim of this multicentre retrospective study was to compare the efficacy of adjuvant chemotherapy regimens both with and without oxaliplatin and tumor sidedness in stage IIB (pT4aN0) colon cancer patients. This study included patients with stage IIB colon cancer who underwent curative surgery and received adjuvant chemotherapy. The patients were divided into two groups (one with and one without oxaliplatin) to compare the overall survival (OS) in right- and left-sided tumors. The study population included 298 patients with stage IIB colon cancer (median age: 57) of whom 69.1% were male. Forty-four per cent of these patients (n = 131) were diagnosed with right-sided colon cancer. The median follow-up duration was 35.9 months. In the entire population, a median OS was not reached, and the five-year OS was 83%. The median disease-free survival (DFS) was 12 months. There was no significant difference in terms of the five-year OS between right- (82%) and left-sided (84%) colon tumors (p = 0.67). In addition, the five-year OS of patients treated with and without oxaliplatin were 76% and 89%, respectively, and there was no statistically significant difference (p = 0.23). The five-year OS of the patients treated with and without oxaliplatin were 83% and 96.5%, respectively, (p = 0.8) in right-sided colon tumors, while it was 75% and 93% (p = 0.06), respectively, in left-sided colon tumors. Tumor sidedness and the addition of oxaliplatin to adjuvant chemotherapy were not found to be associated with the OS in stage IIB colon cancer patients in our study. Further large prospective studies that also include MSI, RAS and BRAF status data are warranted in colon cancer patients.

Benefit of Uracil-Tegafur Used as a Postoperative Adjuvant Chemotherapy for Stage IIA Colon Cancer

Background and Objectives: Postoperative adjuvant therapy with uracil and tegafur (UFT) is often used for stage II colon cancer in Japan, but a limited number of studies have investigated the effects of UFT in these patients. Materials and Methods: We conducted a population-based cohort study in patients with resected stage II colon cancer comparing the outcomes after postoperative adjuvant chemotherapy with UFT with an observation-only group. The data were collected from the Taiwan National Health Insurance Research Database from 2000 to 2015. The outcomes of the study were disease-free survival (DFS) and overall survival (OS). The hazard ratios (HRs) were calculated using multivariate Cox proportional hazard regression models. Results: No differences in the DFS and OS were detected between the UFT (1137 patients) and observation (2779 patients) cohorts (DFS: adjusted HR 0.702; 95% confidence interval (CI) 0.489-1.024; p = 0.074) (OS: adjusted HR 0.894; 95% CI 0.542-1.186; p = 0.477). In the subgroup analyses of the different substages, UFT prolonged DFS in patients with stage IIA colon cancer (adjusted HR 0.652; 95% CI 0.352-0.951; p = 0.001) compared with DFS in the observation cohort, but no differences in the OS were detected (adjusted HR 0.734; 95% CI 0.475-1.093; p = 0.503). Conclusions: Our results show that DFS improved significantly in patients with stage IIA colon cancer receiving UFT as a postoperative adjuvant chemotherapy compared with DFS in the observation group.

Prognostic value of elastic lamina staining in patients with stage III colon cancer

OBJECTIVE

The objectives of this study were to analyze the difference between the preoperative radiological and postoperative pathological stages of colorectal cancer (CRC) and explore the feasibility of elastic lamina invasion (ELI) as a prognostic marker for patients with stage III colon cancer.

METHODS

A total of 105 consecutive patients underwent radical surgery (R0 resection) for stage III colon cancer at the Cancer Hospital of China Medical University between January 2015 and December 2017. Clinicopathological features, including radiological stage and elastic lamina staining, were analyzed for prognostic significance in stage III colon cancer.

RESULTS

A total of 105 patients with stage III colon cancer who met the criteria and had complete data available were included. The median follow-up period of survivors was 41 months. During the follow-up period, 33 (31.4%) patients experienced recurrence after radical resection, and the 3-year disease-free survival (DFS) rate was 64.8%. The consistency between preoperative radiological and postoperative pathological staging was poor (κ = 0.232, P < 0.001). The accuracy of ≤ T2 stage diagnoses was 97.1% (102/105), that of T3 stage was 60.9% (64/105), that of T4a stage was 68.6% (72/105) and that of T4b stage was 91.4% (96/105). The DFS rate of T3 ELI (+) patients was significantly lower than that of both T3 ELI (-) patients (P = 0.000) and pT4a patients (P = 0.013). The DFS rate of T3 ELI (-) patients was significantly higher than that of pT4b patients (P=0.018). T3 ELI (+) (HR (Hazard ratio), 8.444 [95% CI, 1.736-41.067]; P = 0.008), T4b (HR, 57.727[95% CI, 5.547-600.754]; P = 0.001), N2 stage (HR, 10.629 [95% CI, 3.858-29.286]; P < 0.001), stage III (HR, 0.136 [95% CI, 0.31-0.589]; P = 0.008) and perineural invasion (PNI) (HR, 8.393 [95% CI, 2.094-33.637]; P = 0.003) were independent risk factors for postoperative recurrence of stage III colon cancer.

CONCLUSIONS

The consistency between preoperative radiological and postoperative pathological staging was poor, especially for tumors located in the ascending colon and descending colon. Elastic lamina staining is expected to become a stratified indicator of recurrence risk for patients with stage III colon cancer and a guide for individualized adjuvant chemotherapy, thus improving patient prognosis.

Machine learning based prognostic model of Chinese medicine affecting the recurrence and metastasis of I-III stage colorectal cancer: A retrospective study in China

Background

To construct prognostic model of colorectal cancer (CRC) recurrence and metastasis (R&M) with traditional Chinese medicine (TCM) factors based on different machine learning (ML) methods. Aiming to offset the defects in the existing model lacking TCM factors.

Methods

Patients with stage I-III CRC after radical resection were included as the model data set. The training set and the internal verification set were randomly divided at a ratio of 7: 3 by the "set aside method". The average performance index and 95% confidence interval of the model were calculated by repeating 100 tests. Eight factors were used as predictors of Western medicine. Two types of models were constructed by taking "whether to accept TCM intervention" and "different TCM syndrome types" as TCM predictors. The model was constructed by four ML methods: logistic regression, random forest, Extreme Gradient Boosting (XGBoost) and support vector machine (SVM). The predicted target was whether R&M would occur within 3 years and 5 years after radical surgery. The area under curve (AUC) value and decision curve analysis (DCA) curve were used to evaluate accuracy and utility of the model.

Results

The model data set consisted of 558 patients, of which 317 received TCM intervention after radical resection. The model based on the four ML methods with the TCM factor of "whether to accept TCM intervention" showed good ability in predicting R&M within 3 years and 5 years (AUC value > 0.75), and XGBoost was the best method. The DCA indicated that when the R&M probability in patients was at a certain threshold, the models provided additional clinical benefits. When predicting the R&M probability within 3 years and 5 years in the model with TCM factors of "different TCM syndrome types", the four methods all showed certain predictive ability (AUC value > 0.70). With the exception of the model constructed by SVM, the other methods provided additional clinical benefits within a certain probability threshold.

Conclusion

The prognostic model based on ML methods shows good accuracy and clinical utility. It can quantify the influence degree of TCM factors on R&M, and provide certain values for clinical decision-making.

Survival Contradiction in Stage II, IIIA, And IIIB Colon Cancer: A Surveillance, Epidemiology, and End Result-Based Analysis

There exists an inconsistency between stage and survival in the current American Joint Committee on Cancer (AJCC) staging system for colon cancer. In this study, we compared the clinicopathological characteristics and prognosis of colon cancer patients with stage II, IIIA, and IIIB disease based on the surveillance, epidemiology, and end results (SEER) database. Kaplan-Meier analysis was used to generate overall survival (OS) and cancer-specific survival (CSS) curves. The Cox regression was employed to identify risk factors. The competing risk model was completed by the cumulative incidence function and Gray's test. In the final population of 31,361 colon cancer patients, Kaplan-Meier curve analysis showed that stage IIIA had the highest OS and CSS, followed by stage IIA and IIIB, and IIB and IIC showed the worst OS and CSS. In the Cox model, the stage was proven to be an independent prognostic factor. In the competing risk model, stage IIIA colon cancer patients had the lowest 5-year cancer-specific death rate in stages II, IIIA, and IIIB. In conclusion, the prognosis of colon cancer patients in stage IIA was worse than that of patients in stage IIIA, while the survival rate of stage IIB and IIC was lower than that of stage IIIB.

Construction of a new clinical staging system for colorectal cancer based on the lymph node ratio: A validation study

Aim

This study aims to construct a new staging system for colorectal cancer (CRC) based on the lymph node ratio (LNR) as a supplement to the American Joint Committee on Cancer (AJCC) tumor node metastasis (TNM) staging system for predicting the prognosis of CRC patients with <12 lymph nodes.

Methods

The data of 26,695 CRC patients with <12 lymph nodes were extracted from the Surveillance, Epidemiology, and End Results (SEER) database as a training set. A total of 635 CRC patients were also enrolled from Northern Jiangsu People's Hospital affiliated with Yangzhou University as an independent validation set. Classification and regression tree analysis was used to obtain the LNR cutoff value. Survival curves were estimated using the Kaplan–Meier method, and the log-rank test was used for comparisons of differences among the survival curves. The monotonic decreasing trend of the overall survival curve in the staging system was expressed by the linear correlation degree R.

Results

The 5-year survival rates of patients in the training set based on the AJCC staging system from stage I to stage IV were 75.6% (95%CI: 74.4–76.8), 59.8% (95%CI: 58.6–61.0), 42.1% (95%CI: 34.5–49.7), 33.2% (95%CI: 24.6–41.8), 72.0% (95%CI: 69.1–74.9), 48.8% (95%CI: 47.4–50.2), 26.5% (95%CI: 23.0–30.0), and 11.3% (95%CI: 10.3–12.3). The 5-year survival rates of patients in the training set from stage I to stage IIIC were 80.4%, 72.9%, 59.8%, 48.4%, 32.5%, and 15.0%, according to the TNM + LNR (TNRM) staging system. According to the AJCC staging system, the 5-year survival rates of patients in the validation set from stage I to stage IIIC were 91.3%, 90.8%, 72.6%, 61.3%, 72.4%, 58.1%, and 32.8%. Based on the TNRM staging system, the 5-year survival rates of patients in the validation set from stage I to stage IIIC were 99.2%, 90.5%, 81.4%, 78.6%, 60.2%, and 35.8%.

Conclusion

The TNRM staging system successfully eliminated “survival paradox” in the AJCC staging system, which might be superior to the AJCC staging system.

Machine Learning-Based Prognostic Prediction Models of Non-Metastatic Colon Cancer: Analyses Based on Surveillance, Epidemiology and End Results Database and a Chinese Cohort

Purpose

The present study aimed to develop prognostic prediction models based on machine learning (ML) for non-metastatic colon cancer (CRC), which can provide a precise quantitative risk assessment and serve as an assistive method for treatment strategy development. The possibility of improving prediction accuracy using nonlinear methods compared to linear methods was investigated.

Patients and Methods

A cancer-specific survival (CSS) model constructed using logistic regression, extreme gradient boosting (XGBoost), and random forest algorithms was trained on the Surveillance, Epidemiology, and End Results datasets for 15,254 patients with non-metastatic CRC (split into training [70%] and internal validation [30%] datasets) and externally validated with an outpatient cohort of 311 cases from Xiyuan Hospital in China. A Chinese cohort was also used to develop recurrence and metastasis (R&M) models for CRC patients. The experiments for each model were performed 100 times to obtain average scores and 95% confidence intervals. The model performance was evaluated using the area under the receiver operating characteristic curve (AUC) values.

Results

The XGBoost approach showed the highest AUC values of 0.86 (0.84-0.88), 0.82 (0.81-0.83), and 0.81 (0.79-0.82) for one-, three-, and five-year CSS cohorts, respectively, along with a relatively high generalization ability. The XGBoost approach also performed best for the R&M model, with the AUC values of 0.71 (0.64-0.79), 0.79 (0.74-0.86), and 0.89 (0.82-0.95) for one-, three-, and five-year R&M cohorts, respectively. The rankings of predictor importance for the CSS and R&M models were different, and the higher model accuracy was associated with more prognostic predictors.

Conclusion

Three different ML algorithms for developing prognostic prediction models for non-metastatic CRC were compared. The predictive performance results showed that the nonlinear XGBoost approach performed best, suggesting that it can be used for quantifying the prognostic risk. It was also demonstrated that the model performance can be improved when more prognostic predictors are considered.

Clinicopathological Features Combined With Immune Infiltration Could Well Distinguish Outcomes in Stage II and Stage III Colorectal Cancer: A Retrospective Study

Background

The Immunoscore predicts prognosis in patients with colorectal cancer (CRC). However, a few studies have incorporated the Immunoscore into the construction of comprehensive prognostic models in CRC, especially stage II CRC. We aimed to construct and validate multidimensional models integrating clinicopathological characteristics and the Immunoscore to predict the prognosis of patients with stage II–III CRC.

Methods

Patients (n = 254) diagnosed with stage II–III CRC from 2009 to 2016 were used to generate Cox models for predicting disease-free survival (DFS) and overall survival (OS). The variables included basic clinical indicators, blood inflammatory markers, preoperative tumor biomarkers, mismatch repair status, and the Immunoscore (CD3⁺ and CD8⁺ T-cell densities). Univariate and multivariate Cox proportional regressions were used to construct the prognostic models for DFS and OS. We validated the predictive accuracy and ability of the prognostic models in our cohort of 254 patients.

Results

We constructed two predictive prognostic models with C-index values of 0.6941 for DFS and 0.7138 for OS in patients with stage II–III CRC. The Immunoscore was the most informative predictor of DFS (11.92%), followed by pN stage, carcinoembryonic antigen (CEA), and vascular infiltration. For OS, the Immunoscore was the most informative predictor (8.59%), followed by pN stage, age, CA125, and CEA. Based on the prognostic models, nomograms were developed to predict the 3- and 5-year DFS and OS rates. Patients were divided into three risk groups (low, intermediate, and high) according to the risk scores obtained from the nomogram, and significant differences were observed in the recurrence and survival of the different risk groups (p < 0.0001). Calibration curve and time-dependent receiver operating characteristic (ROC) analysis showed good accuracy of our models. Furthermore, the decision curve analysis indicated that our nomograms had better net benefit than pathological TNM (pTNM) stage within a wide threshold probability. Especially, we developed a website based on our prognostic models to predict the risks of recurrence and death of patients with stage II–III CRC.

Conclusions

Multidimensional models including the clinicopathological characteristics and the Immunoscore were constructed and validated, with good accuracy and convenience, to evaluate the risks of recurrence and death of stage II–III CRC patients.

Development and Validation of the Individualized Prognostic Nomograms in Patients With Right- and Left-Sided Colon Cancer

Background

The overall survival (OS) of patients diagnosed with colon cancer (CC) varied greatly, so did the patients with the same tumor stage. We aimed to design a nomogram that is capable of predicting OS in resected left-sided colon cancers (LSCC) and right-sided colon cancers (RSCC), and thus to stratify patients into different risk groups, respectively.

Methods

Records from a retrospective cohort of 577 patients with complete information were used to construct the nomogram. Univariate and multivariate analyses screened risk factors associated with overall survival. The performance of the nomogram was evaluated with concordance index (c-index), calibration plots, and decision curve analyses for discrimination, accuracy, calibration ability, and clinical net benefits, respectively, which was further compared with the American Joint Committee on Cancer (AJCC) 8th tumor-node-metastasis (TNM) classification. Risk stratification based on nomogram scores was performed with recursive partitioning analysis.

Results

The LSCC nomogram incorporated carbohydrate antigen 12-5 (CA12-5), age and log odds of positive lymph nodes (LODDS), and RSCC nomogram enrolled tumor stroma percentage (TSP), age and LODDS. Compared with the TNM classification, the LSCC and RSCC nomograms both had a statistically higher C-index (0.837, 95% CI: 0.827-0.846 and 0.780, 95% CI 0.773-0.787, respectively) and more clinical net benefits, respectively. Calibration plots revealed no deviations from reference lines. All results were reproducible in the validation cohort.

Conclusions

An original predictive nomogram was constructed and validated for OS in patients with CC after surgery, which had facilitated physicians to appraise the individual survival of postoperative patients accurately and to identify high-risk patients who were in need of more aggressive treatment and follow-up strategies.

Screening and validation of a novel T stage-lymph node ratio classification for operable colon cancer

BACKGROUND

Lymph node ratio (LNR) has advantages in predicting prognosis compared with American Joint Committee on Cancer (AJCC) pathological N stage. However, the prognostic value of a novel T stage-lymph node ratio (TLNR) classification for colon cancer combining LNR and pathological primary tumor stage (T stage) is currently unknown.

METHODS

We included 62,294 patients with stage I-III colon cancer from the Surveillance, Epidemiology, and End Results Program as a training cohort. External validation was performed in 3,327 additional patients. A novel LNR stage was established and combined with T stage in a novel TLNR classification. Patients with similar survival were grouped according to T and LNR stages, with T1LNR1 as a reference.

RESULTS

We developed a novel TLNR classification as follows: stages I (T1LNR1-2, T1LNR4), IIA (T1LNR3, T2LNR1-2, T3LNR1), IIB (T1LNR5, T2LNR3-4, T3LNR2, T4aLNR1), IIC (T2LNR5, T3LNR3-4, T4aLNR2, T4bLNR1), IIIA (T3LNR5, T4aLNR3-4, T4bLNR2), IIIB (T4aLNR5, T4bLNR3-4), and IIIC (T4bLNR5). In the training cohort, the novel TLNR classification had better prognostic discrimination (area under receiver operating characteristic curve, 0.621 vs. 0.608, two-sided P<0.001), superior model-fitting ability for predicting overall survival (Akaike information criteria, 561,129 vs. 562,052), and better net benefits compared with the AJCC 8th tumor/node/metastasis classification. Similar results were found in the validation cohort for predicting both overall and disease-free survival.

CONCLUSIONS

This novel TLNR classification may provide better prognostic discrimination, model-fitting ability, and net benefits than the AJCC 8th TNM classification, for potentially better stratification of patients with operable stage I-III colon cancer; however, further studies are required to validate the novel TLNR classification.

The Stage Migration Should be Reconsidered in Stage IIIA Rectal Cancer: Based on Propensity Score Analysis

BACKGROUND

Few studies have compared the survival outcomes of stages II and IIIA rectal cancer patients who did not receive neoadjuvant treatment. This study aimed to compare oncologic outcomes between 2 groups.

PATIENTS AND METHODS

This study analyzed stage II or IIIA rectal cancer patients who underwent radical operation without neoadjuvant treatment between 1996 and 2013. The 3:1 propensity score analysis was used to adjust for several variables. After propensity score matching, 364 stage II rectal cancer, and 172 stage IIIA rectal cancer patients were analyzed.

RESULTS

There were no significant differences in 5-year overall survival or disease-free survival rates between the 2 groups. When stage II rectal cancer was subdivided into stages IIA, IIB, and IIC, the 5-year DFS and OS rates of stage IIIA rectal cancer patients were similar to those of stage IIA cancer patients. Moreover, stage IIIA rectal cancer patients showed a statistically significantly better survival rates than stage IIC rectal cancer patients.

CONCLUSION

Stage IIIA group showed similar survival outcomes compared to stage IIA and IIB group and significantly better outcomes than stage IIC group. Thus, it should be considered to classify stage IIIA as a subgroup of stage II rather than as a subgroup of stage III rectal cancer. It should be also be considered to change to determine whether to do adjuvant treatment according to stage II rectal cancer.

Development and validation of a novel classification scheme for combining pathological T stage and log odds of positive lymph nodes for colon cancer

AIM

Log Odds of Positive Lymph Nodes (LODDS) have a better predictive ability than N stage for colon cancer. However, the prognostic value of developing a novel prognostic classification by combining T stage and LODDS (TLODDS) for colon cancer remains unknown. Therefore, in the present study, we aimed to develop a TLODDS classification for colon cancer, and assess whether or not the novel TLODDS classification could improve survival stratification by comparing its discrimination, model-fitting, and net benefits, with the American Joint Committee on Cancer (AJCC) Tumor/Node/Metastasis (TNM) classification.

METHODS

45,558 Western colon cancers were identified in the Surveillance, Epidemiology, and End Results database as a training set. A novel LODDS stage was established and patients with similar survival rates were grouped by combining T and LODDS stages to develop a novel TLODDS classification. The TLODDS classification was further assessed in a Chinese validation set of 3,515 colon cancers and an application set of 3,053 rectal cancers.

RESULTS

We developed a novel TLODDS classification that incorporated 7 stages: stage I (T1LODDS1), IIA (T2LODDS1, T1LODDS2, T1LODDS3), IIB (T2LODDS2-3, T3LODDS1, T1LODDS4), IIC (T3LODDS2, T2LODDS4, T4aLODDS1), IIIA (T3LODDS3, T1-2LODDS5, T4bLODDS1, T4aLODDS2), IIIB (T3LODDS4-5, T4aLODDS3-4, T4bLODDS2) and IIIC (T4bLODDS3-5, T4aLODDS5). In the training set, it showed significantly better discrimination (area under the receiver operating characteristic (ROC) curve, 0.691 vs. 0.664, P < 0.001), better model-fitting (Akaike information criteria, 265,644 vs. 267,410), and superior net benefits, than the latest AJCC TNM classification. The predictive performance of the TLODDS classification was further validated in colon cancers and was successfully applied in rectal cancers with regards to both overall and disease-free survival.

CONCLUSIONS

The TLODDS classification has better discriminatory ability, model-fitting, and net benefits than the existing TNM classification, and represents an alternative to the current TNM classifications for colon and rectal cancers.

Preoperative Hepatic and Regional Arterial Chemotherapy in Patients Who Underwent Curative Colorectal Cancer Resection: A Prospective, Multi-center, Randomized Controlled Trial

OBJECTIVE

To evaluate the effects of the addition of preoperative hepatic and regional arterial chemotherapy (PHRAC) on prognosis of stage II and III colorectal cancer (CRC) in a multicenter setting.

SUMMARY OF BACKGROUND DATA

Our previous single-center pilot trial suggested that PHRAC in combination with surgical resection could reduce the occurrence of liver metastasis (LM) and improve survival in CRC patients.

METHODS

A prospective multi-center randomized controlled trial was conducted from December 2008 to December 2012 at 5 hospitals in China. Eligible patients with clinical stage II or III CRC who underwent curative resection were randomized to receive PHRAC plus adjuvant therapy (PHRAC arm) or adjuvant therapy alone (control arm). The primary endpoint was DFS. Secondary endpoints were cumulative LM rates, overall survival (OS), and safety (NCT00643877).

RESULTS

A total of 688 patients from 5 centers in China were randomly assigned (1:1) to each arm. The five-year DFS rate was 77% in the PHRAC arm and 65% in the control arm (HR = 0.61, 95% CI 0.46-0.81; P = 0.001). The 5-year LM rates were 7% and 16% in the PHRAC and control arms, respectively (HR = 0.37, 95% CI 0.22-0.63; P < 0.001). The 5-year OS rate was 84% in the PHRAC arm and 76% in the control arm (HR = 0.61, 95% CI 0.43-0.86; P = 0.005). There were no significant differences regarding treatment related morbidity or mortality between the two arms.

CONCLUSIONS

The addition of PHRAC could improve DFS in patients with stage II and III CRC. It reduced the incidence of LM and improved OS without compromising patient safety.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT00643877.

Effect of the duration of the capecitabine regimen following colon cancer surgery in an elderly population: a retrospective cohort study

Background

Only 50–70% of elderly colon cancer patients could complete the recommended 6 months of postoperative chemotherapy. It is unknown whether a shorter duration of postoperative capecitabine-alone chemotherapy would compromise survival. We thus conducted this study to analyze the association between postoperative chemotherapy duration of a capecitabine-alone regimen and cancer-specific survival (CSS) and disease-free survival (DFS) of surgery-treated elderly colon cancer patients.

Methods

We performed a retrospective cohort study of surgically treated stage III and high-risk stage II colon cancer patients aged ≥ 70 treated at two medical centers. Cox proportional hazard regression models were utilized to calculate crude and adjusted hazard ratios (HRs). The nonlinear relationship between postoperative chemotherapy duration and survival was analyzed through restricted cubic spline regression analysis, and the threshold effect was calculated by the two-piecewise Cox proportional hazard model.

Results

A total of 1217 surgery-treated colon cancer patients between August 1, 2013, and September 1, 2019, were reviewed, and 257 stage III and high-risk stage II patients aged ≥ 70 were enrolled. Postoperative chemotherapy with capecitabine was administered to 114 patients, and 143 patients only received surgery. As the duration of chemotherapy increased by 1 week, the risk of cancer-specific death was reduced by 11% (HR = 0.89, 95% confidence interval (CI) 0.82–0.96), and the risk of recurrence was reduced by 10% (HR = 0.90, 0.82–0.96). Nonlinearity exploration suggested a threshold effect of capecitabine duration on CSS in stage III disease. The HR for death was 0.79 (95% CI, 0.68–0.92) with duration ≤ 16 weeks and 1.34 (95% CI, 0.91–1.97) with duration > 16 weeks.

Conclusions

The postoperative capecitabine duration was significantly associated with a decrease in death risk and recurrence risk in elderly colon cancer patients. However, the threshold effect of capecitabine duration on survival suggests that short-term chemotherapy may improve survival in elderly stage III colon cancer patients.

Association of the Collagen Signature in the Tumor Microenvironment With Recurrence and Survival of Patients With T4N0M0 Colon Cancer

BACKGROUND

The current clinicopathological risk factors do not accurately predict disease recurrence in patients with T4N0M0 colon cancer. We hypothesized that the collagen signature combined with clinicopathological risk factors (new model) had a better prognostic value than clinicopathological risk factors alone (clinicopathological model).

OBJECTIVE

This study aimed to establish a collagen signature in the tumor microenvironment and to validate its role in predicting the recurrence of T4N0M0 colon cancer.

DESIGN

This was a retrospective study.

SETTINGS

This study took place at a tertiary medical center.

PATIENTS

Patients with T4N0M0 colon cancer who underwent surgery at our center between 2009 and 2015 (n = 416) were included.

INTERVENTION

A total of 142 collagen features were analyzed in the tumor microenvironment in specimens of colon cancer by using second-harmonic generation imaging. A collagen signature was constructed using a least-absolute shrinkage and selection operator Cox regression model.

MAIN OUTCOME MEASURES

The primary outcomes measured were disease-free survival and overall survival.

RESULTS

The training and testing cohorts consisted of 291 and 125 randomly assigned samples, with recurrence rates of 19.9% and 22.4%. A 3-feature-based collagen signature predicted the recurrence risk at 1, 3, and 5 years, with the area under the receiver-operating characteristic curves of 0.808, 0.832, and 0.791 in the training cohort and 0.836, 0.807, and 0.794 in the testing cohort. Multivariate analysis revealed that the collagen signature could independently predict the disease-free survival (HR = 7.17, p < 0.001) and overall survival rates (HR = 5.03, p < 0.001). The new model had a better prognostic value than the clinicopathological model, which included 4 clinicopathological risk factors: obstruction or perforation, lymphovascular invasion, tumor budding, and no chemotherapy.

LIMITATIONS

This study was limited by its retrospective design.

CONCLUSIONS

The collagen signature in the tumor microenvironment may be a new prognostic marker that can effectively predict the recurrence and survival of patients with T4N0M0 colon cancer. See Video Abstract at http://links.lww.com/DCR/B503. ASOCIACIÓN DE LA RÚBRICA DE COLÁGENO EN EL MICROAMBIENTE TUMORAL CON LA RECIDIVA Y LA SOBREVIDA DE PACIENTES CON CÁNCER DE COLON T4N0M0: Los factores de riesgo clínico-patológicos actuales no predicen con precisión la recurrencia de la enfermedad en pacientes con cáncer de colon estadío T4N0M0. Presumimos que la rúbrica de colágeno combinada con factores de riesgo clínico-patológicos (nuevo modelo) tendrían un mejor valor pronóstico que los factores de riesgo clínico-patológicos solos (modelo clínico-patológico).El establecer una rúbrica de colágeno en el microambiente tumoral y validar su papel en la predicción de la recidiva del cáncer de colon T4N0M0.Estudio retrospectivo.Investigación llevada a cabo en un centro médico terciario.Se incluyeron pacientes con cáncer de colon T4N0M0 operados en nuestro centro entre 2009 y 2015 (n = 416).Se analizaron un total de 142 características de colágeno en el microambiente tumoral en muestras de cáncer de colon utilizando imágenes de segunda generación armónica. Se construyó una rúbrica de colágeno utilizando un modelo de regresión LASSO Cox.Sobrevida libre de enfermedad y sobrevida global.Las cohortes de entrenamiento y prueba consistieron en 291 y 125 muestras asignadas al azar, con tasas de recurrencia del 19,9% y 22,4%, respectivamente. La rúbrica del colágeno basada en 3 características predijo el riesgo de recurrencia a 1, 3 y 5 años, con el área bajo las curvas características operativas del receptor de 0,808, 0,832 y 0,791 en la cohorte de entrenamiento y 0,836, 0,807 y 0,794 en la cohorte de prueba, respectivamente. El análisis multivariado reveló que la firma de colágeno podría predecir de forma independiente la supervivencia libre de enfermedad (HR = 7,17, p <0,001) y las tasas de sobrevida general (HR = 5,03, p <0,001). El nuevo modelo tuvo un mejor valor pronóstico que el modelo clínico-patológico, que incluyó cuatro factores de riesgo clínico-patológicos: obstrucción o perforación, invasión linfovascular, gemación tumoral y ausencia de quimioterapia.Este estudio estuvo limitado por su diseño retrospectivo.La rúbrica de colágeno en el microambiente tumoral puede ser un nuevo marcador pronóstico para predecir eficazmente la recurrencia y la subrevida de los pacientes con cáncer de colon T4N0M0. Consulte Video Resumen en http://links.lww.com/DCR/B503. (Traducción-Dr. Xavier Delgadillo).

Prognostic value of lymphovascular invasion in stage II colorectal cancer patients with an inadequate examination of lymph nodes

BACKGROUND

Lymphovascular invasion (LVI) is defined as the presence of cancer cells in lymphatics or blood vessels. This study aimed to evaluate the prognostic value of LVI in stage II colorectal cancer (CRC) patients with inadequate examination of lymph nodes (ELNs) and further combined LVI with the TNM staging system to determine the predictive efficacy for CRC prognosis. Adjuvant chemotherapy (ACT) was then evaluated for stage II CRC patients with LVI positivity (LVI+).

METHODS

In order to avoid the effects of different ACT regimens, among 409 stage II patients, we chose 121 patients who received FOLFOX regimen and the 144 patients who did not receive ACT as the object of study. LVI was examined by hematoxylin-eosin (HE) staining. Kaplan-Meier analysis followed by a log-rank test was used to analyze survival rates. Univariate and multivariate analyses were performed using a Cox proportional hazards model. Harrell's concordance index (C-index) was used to evaluate the accuracy of different systems in predicting prognosis.

RESULTS

The LVI+ status was significantly associated with pT stage, degree of differentiation, tumor stage, serum CEA and CA19-9 levels, perineural invasion (PNI), tumor budding (TB), and KRAS status. The 5-year overall survival (OS) rate of stage II patients with < 12 ELNs and LVI+ was less than stage IIIA. Multivariate analyses showed that LVI, pT-stage, serum CEA and CA19-9 levels, PNI, TB, and KRAS status were significant prognostic factors for stage II patients with < 12 ELNs. The 8th TNM staging system combined with LVI showed a higher C-index than the 8th TNM staging system alone (C-index, 0.895 vs. 0.833). Among patients with LVI+, the ACT group had a significantly higher 5-year OS and 5-year disease-free survival (DFS) than the surgery alone (SA) group (5-year OS, 66.7% vs. 40.9%, P = 0.004; 5-year DFS, 64.1% vs. 36.3%, P = 0.002).

CONCLUSIONS

LVI is an independent prognostic risk factor for stage II CRC patients. Combining LVI with the 8th TNM staging system improved the predictive accuracy for CRC prognosis. ACT in stage II CRC patients with LVI+ is beneficial for survival.

Survival in stage IIB/C compared to stage IIIA rectal cancer: an Australian experience affirming that size does matter

BACKGROUND

Colorectal cancer (CRC) is one of the most commonly diagnosed malignancies globally; however, a survival paradox has been observed unique to this malignancy. The aim of this study was to review survival outcomes of patients diagnosed with stage II and stage III rectal cancer, to determine whether a survival paradox is present in our centre and assess for patient-related factors that can explain the observed paradox or were predictors of prognosis.

METHODS

A retrospective review of data collected from 2006 to 2018 of patients diagnosed with rectal cancer in three separate centres was conducted. Percentages pertaining to patient and tumour characteristics, presentation, management and subsequent recurrence were reported. Preoperative and postoperative factors associated with survival were determined using univariable and multivariable logistic regression analysis.

RESULTS

Stage IIB/C patients had significantly higher carcinoembryonic antigen (CEA) levels compared to stage IIA and stage IIIA patients (P < 0.001). Stage IIB/C patients had significantly larger primary rectal tumour and were more symptomatic (i.e. rectal bleeding, altered bowel habits and obstruction) at the time of diagnosis (P = 0.007). Preoperative CEA was an independent prognostic factor for cancer-specific survival in patients diagnosed with stage IIB/C and stage IIIA disease (P = 0.008) on multivariable analysis. Overall survival was greatest in stage IIIA disease, which was significantly greater than stage IIB/C disease.

CONCLUSION

This study confirms the existence of a survival paradox in patients diagnosed with CRC in an Australian tertiary centre and adds further weight to the revision of the TNM staging to provide more emphasis on the T stage.

A Novel TNM Classification for Colorectal Cancers based on the Metro-ticket Paradigm

Background: Several revisions of the TNM classifications for colorectal cancer (CRC) have acknowledged that the oncological outcomes of stage IIB/IIC CRC are worse than those of stage IIIA. We aimed to develop a novel TNM (nTNM) classification based on the metro-ticket paradigm. Methods: We identified eligible CRC patients from the Surveillance, Epidemiology, and End Results database. The nTNM was developed using distance from the origin on a Cartesian plane incorporating the pN (x-axis) and pT (y-axis) stages, and was compared with the AJCC TNM classification. The areas under the curves (AUCs), calibration curves, and Akaike's information criterion (AIC) were used to evaluate the predictive performances of the two classifications. Clinical benefits were further estimated by decision curve analyses. The validation cohort was applied to validate these findings. Results: A total of 58,192 CRC patients (40,736 training cohort, 17,456 validation cohort) were finally included. In the training cohort, 18,476 patients (45.4%) experienced upstaging and 15,907 patients (39.0%) experienced downstaging in the nTNM classification compared with the TNM classification. Taking the prognosis of stage I as the reference, survival decreased with increasing nTNM stage. The nTNM classification showed better discrimination (AUC, 0.678 vs. 0.667, P<0.001), model-fitting (AIC, 236,525 vs. 237,741), and clinical benefits than the TNM classification. Similar results were found in the validation cohort. Conclusions: The nTNM classification for CRC has better predictive performances and superior accuracy for predicting prognosis compared with the TNM classification. The nTNM classification should therefore be considered in future revisions of the TNM classification.

Current Treatment Approaches and Outcomes in the Management of Rectal Cancer Above the Age of 80

Background: The number of cases of rectal cancer in our older cohort is expected to rise with our ageing population. In this study, we analysed patterns in treatment and the long-term outcomes of patients older than 80 years with rectal cancer across a health district. Methods: All cases of rectal cancer managed at the Illawarra Cancer Care Centre, Australia between 2006 and 2018 were analysed from a prospectively maintained database. Patients were stratified into three age groups: ≤65 years, 66–79 years and ≥80 years of age. The clinicopathological characteristics, operative and non-operative treatment approach and survival outcomes of the three groups were compared. Results: Six hundred and ninety-nine patients with rectal cancer were managed, of which 118 (17%) were aged 80 and above. Patients above 80 were less likely to undergo surgery (71% vs. 90%, p < 0.001) or receive adjuvant/neoadjuvant chemoradiotherapy (p < 0.05). Of those that underwent surgical resection, their tumours were on average larger (36.5 vs. 31.5 mm, p = 0.019) and 18 mm closer the anal verge (p = 0.001). On Kaplan–Meier analysis, those above 80 had poorer cancer-specific survival when compared to their younger counterparts (p = 0.032), but this difference was no longer apparent after the first year (p = 0.381). Conclusion: Patients above the age of 80 with rectal cancer exhibit poorer cancer-specific survival, which is accounted for in the first year after diagnosis. Priority should be made to optimise care during this period. There is a need for further research to establish the role of chemoradiotherapy in this population, which appears to be underutilised.

Identifying Stage II Colorectal Cancer Recurrence Associated Genes by Microarray Meta-Analysis and Building Predictive Models with Machine Learning Algorithms

Background

Stage II colorectal cancer patients had heterogeneous prognosis, and patients with recurrent events had poor survival. In this study, we aimed to identify stage II colorectal cancer recurrence associated genes by microarray meta-analysis and build predictive models to stratify patients' recurrence-free survival.

Methods

We searched the GEO database to retrieve eligible microarray datasets. The microarray meta-analysis was used to identify universal recurrence associated genes. Total samples were randomly divided into the training set and the test set. Two survival models (lasso Cox model and random survival forest model) were trained in the training set, and AUC values of the time-dependent receiver operating characteristic (ROC) curves were calculated. Survival analysis was performed to determine whether there was significant difference between the predicted high and low risk groups in the test set.

Results

Six datasets containing 651 stage II colorectal cancer patients were included in this study. The microarray meta-analysis identified 479 recurrence associated genes. KEGG and GO enrichment analysis showed that G protein-coupled glutamate receptor binding and Hedgehog signaling were significantly enriched. AUC values of the lasso Cox model and the random survival forest model were 0.815 and 0.993 at 60 months, respectively. In addition, the random survival forest model demonstrated that the effects of gene expression on the recurrence-free survival probability were nonlinear. According to the risk scores computed by the random survival forest model, the high risk group had significantly higher recurrence risk than the low risk group (HR = 1.824, 95% CI: 1.079-3.084, p = 0.025).

Conclusions

We identified 479 stage II colorectal cancer recurrence associated genes by microarray meta-analysis. The random survival forest model which was based on the recurrence associated gene signature could strongly predict the recurrence risk of stage II colorectal cancer patients.

MicroRNAs differential expression profile in metastatic colorectal cancer: A pilot study with literature review

BACKGROUND AND OBJECTIVES

Colorectal cancer is still one of the leading causes of cancer-related deaths worldwide and specific tools to improve disease assessment and treatment response are advocated. The aim of this study was to analyze miRNAs expression in metastatic and non-metastatic colorectal cancer, in order to identify reliable biomarkers suitable for prognosis, treatment and patient's monitoring.

MATERIAL AND METHODS

Among 25 patients (mean age 71 ± 12 years; Female/Male: 12/13) submitted to laparoscopic colorectal resection between August 2017 and February 2019, miRNAs were extracted from fresh frozen tissues of solid tumors. Gene expression's analysis arising from microarray technology was performed.

RESULTS

Pathological evaluation identified 15 metastatic patients (8 presenting with stage III and 7 with stage IV cancers) and 10 non-metastatic patients (4 presenting with stage I and 6 stage II cancers). Bioinformatic analysis of solid biopsies revealed 16 miRNAs (11 upregulated and 5 downregulated) differently expressed between metastatic and non-metastatic groups, with three miRNAs (miR-7515, miR-7109-5p and miR-6831-5p) never linked to colorectal cancer before.

CONCLUSIONS

Our study showed an association between miRNAs and metastatic colorectal cancer, suggesting their potential role as biomarkers for tumor management, if confirmed by further studies.

Staging Paradox and Discrepancy in Adjuvant Chemotherapy in Patients with T4N0, T1-2N1, and T3N1 Colon Cancer

BACKGROUND

A survival paradox between T4N0 (stage IIB/C) and T3N1 (stage IIIB) colon cancer has been rarely reported. The indication and regimen of adjuvant chemotherapy are separately described in the guidelines. This study aimed to elucidate the prognostic factors and investigate proper adjuvant treatment in colon cancer patients at these stages.

METHODS

Patients who underwent R0 resection for pathological T4N0 (n = 49), T1-2N1 (n = 31), or T3N1 (n = 82) colon cancer between 2008 and 2016 at a single institute were retrospectively reviewed. The clinicopathological characteristics, status of adjuvant chemotherapy, and oncologic outcomes of patients with T4N0 tumors were compared with those of patients with T1-2N1 and T3N1 tumors.

RESULTS

The biological characteristics of T4N0 tumors were more aggressive compared with the characteristics of T1-2N1 tumors and were similar to those of T3N1 tumors. The usage rate of oxaliplatin as an adjuvant chemotherapy was significantly lower in T4N0 patients than in T1-2N1 and T3N1 patients. The rate of local recurrence was the highest in patients with T4N0 tumors, and the survival outcomes for patients with T4N0 tumors were significantly worse compared with those of T1-2N1 patients and were similar to those of T3N1 patients. A multivariate analysis revealed that lack of adequate use of oxaliplatin for adjuvant chemotherapy was the only prognostic factor.

CONCLUSIONS

T4N0 colon cancer had similar oncological characteristics and survival outcomes to T3N1 colon cancer. Systematic adjuvant chemotherapy, including oxaliplatin, should be incorporated into the therapy for T4N0 patients as well as T3N1 patients.

Accurate nomograms with excellent clinical value for locally advanced rectal cancer

Background

Rectal cancer accounts for approximately 30–50% of colorectal cancer. Despite its widespread use and convenience, the American Joint Committee on Cancer (AJCC) staging system for predicting survival is prone to inaccuracy, even including a survival paradox for locally advanced rectal cancer (LARC). An accurate risk stratification of LARC is essential for proper treatment selection and prognostic evaluation. Therefore, we aimed to create prognostic nomograms for LARC capable of assessing overall survival (OS) and cancer-specific survival (CSS) precisely and intuitively.

Methods

The Surveillance, Epidemiology, and End Results (SEER) database was accessed. All of the significant variables in the multivariate analysis were integrated to build the nomograms.

Results

Data for a total of 23,055 patients with LARC were collected from the SEER database in this study. Based on the multivariate Cox regression analysis, both OS and CSS were significantly associated with 13 variables: age, marital status, race, pathological grade, histological type, T stage, N stage, surgery, radiotherapy, chemotherapy, regional nodes examined (RNE), tumor size, and carcinoembryonic antigen (CEA). These were included in the construction of nomograms for OS and CSS. Time-dependent receiver operating characteristic (ROC) curves, decision curve analysis (DCA), concordance index, and calibration curves demonstrated the discriminative superiority of the nomograms.

Conclusions

The nomograms, which effectively solve the issue of the survival paradox in the AJCC staging system regarding LARC, may act as excellent tools for integrating clinical characteristics and to guiding therapeutic choices for LARC patients.

Assessment of Duration and Effects of 3 vs 6 Months of Adjuvant Chemotherapy in High-Risk Stage II Colorectal Cancer: A Subgroup Analysis of the TOSCA Randomized Clinical Trial

Importance

The addition of oxaliplatin to the standard 6-month fluorouracil-based adjuvant chemotherapy in stage II colorectal cancer has been reported to reduce the risk of relapse although it does not increase survival. The Three or Six Colon Adjuvant (TOSCA) trial compared 3 months with 6 months of adjuvant fluoropyrimidine and oxaliplatin-based chemotherapy in patients with stage III colon cancer. The utility remains unknown.

Objective

To assess the noninferiority and toxic effects of 3 vs 6 months of FOLFOX (fluorouracil, leucovorin, and oxaliplatin) or CAPOX (capecitabine plus oxaliplatin) adjunct chemotherapy among patients with high-risk stage II resected colorectal cancer enrolled in the TOSCA trial.

Design, Setting, and Participants

The TOSCA study was a noninferiority phase 3 randomized clinical trial conducted from June 2007 to March 2013 in 130 Italian centers. Included patients had resected colorectal cancer located 12 cm from the anal verge by endoscopy or above the peritoneal reflection at surgery. In this preplanned study assessing the per-protocol population, 5-year relapse-free survival was evaluated in 1254 patients with high-risk stage II resected colorectal cancer who had received adjuvant FOLFOX (fluorouracil, leucovorin, and oxaliplatin) or CAPOX (capecitabine plus oxaliplatin).

Interventions

Patients were originally randomized (1:1) in the TOSCA trial to receive 3 months (experimental group) or 6 months (control) of standard doses of FOLFOX or CAPOX at the discretion of the treating physician.

Main Outcome and Measures

A hazard ratio of at least 1.2 between the 3-month and 6-month chemotherapy groups was set to reject the null hypothesis of noninferiority.

Results

Overall, 1254 patients (mean [SD] age, 62.4 [9.8] years; 565 women [45.1%]) with clinical high-risk stage II resected colorectal cancer were analyzed at a median follow-up of 62 months (interquartile range, 53-71) months. Of them, 301 patients (24.0%) had pT4N0M0 tumors, and the remaining 953 patients (76.0%) had high-risk pT3N0M0 tumors; 776 patients (61.9%) received FOLFOX and 478 (38.1%) received CAPOX. The 5-year relapse-free survival was 82.2% for the 3-month arm and 88.2% for the 6-month arm, with an estimated hazard ratio of 1.41 (95% CI, 1.05-1.89; P = .86 for noninferiority). For CAPOX, the 5-year relapse-free survival was similar in the 2 arms (difference, 0.76% favoring the 6-month arm; 95% CI, -6.28% to 7.80%), whereas for FOLFOX, the difference was pronounced: 8.56% in favor of the longer-duration arm (95% CI, 3.45%-13.67%). Nevertheless, the test for an interaction between duration and regimen was not statistically significant. Neurotoxicity was approximately 5 times lower in the shorter duration arm than in the longer duration arm.

Conclusions and Relevance

In the 3-month arm, the treatment was significantly less toxic than in the 6-month arm. Noninferiority was not shown for 5-year relapse-free survival. However, a possible regimen effect was observed, suggesting that either 3 months of CAPOX or 6 months of FOLFOX therapy can be used whenever an oxaliplatin doublet is indicated for treatment of patients with stage II colorectal cancer.

Trial Registration

ClinicalTrials.gov Identifier: NCT0064660.

Development and validation of prognostic nomograms for early-onset locally advanced colon cancer

BACKGROUND

The incidence of colorectal cancer in patients younger than 50 years has been increasing in recent years.

OBJECTIVE

Develop and validate prognostic nomograms predicting overall survival (OS) and cancer-specific survival (CSS) for early-onset locally advanced colon cancer (EOLACC) based on the Surveillance, Epidemiology, and End Results (SEER) database.

RESULTS

The entire cohort comprised 13,755 patients with EOLACC. The nomogram predicting OS for EOLACC displayed that T stage contributed the most to prognosis, followed by N stage, regional nodes examined (RNE) and surgery. The nomogram predicting CSS for EOLACC demonstrated similar results. Various methods identified the discriminating superiority of the nomograms. X-tile software was used to classify patients into high-risk, medium-risk, and low-risk according to the risk score of the nomograms. The risk stratification effectively avoided the survival paradox.

CONCLUSIONS

We established and validated nomograms for predicting OS and CSS based on a national cohort of almost 13,000 EOLACC patients. The nomograms could effectively solve the issue of survival paradox of the AJCC staging system and be an excellent tool to integrate the clinical characteristics to guide the therapeutic choice for EOLACC patients.

METHODS

Nomograms were constructed based on the SEER database and the Cox regression model.

Re-Evaluation of the Survival Paradox Between Stage IIB/IIC and Stage IIIA Colon Cancer

Objective

We conducted this large population-based study to re-evaluate the survival paradox between stage IIB/C and stage IIIA colon cancer based on the newest staging criteria.

Methods

Colon cancer patients were recruited from the Surveillance, Epidemiology, and End Results (SEER) database using SEER*Stat software (version 8.3.4) with strict inclusion criteria. We used Chi-square test to compare categorical variables between patients diagnosed with stage IIB/IIC and stage IIIA colon cancer. Survival probabilities were then assessed using the Kaplan–Meier method. Cox proportional hazards models were used to analyze hazard ratios (HRs) and 95% confidence intervals (CIs) of clinicopathologic characteristics in stage IIB/IIC and stage IIIA colon cancer patients.

Results

In the current study, a total of 9,227 eligible colon cancer patients were collected from the SEER database between 2010 and 2015. It was found that stage IIIA had 66.4% decreased risk of colon cancer-specific mortality compared with stage IIB (HR = 0.336, 95%CI = 0.286–0.394 for stage IIIA, P < 0.001, using stage IIB as the reference) after the adjustment for other known prognostic factors. And T1N2a colon cancer had significantly lower 5-year overall survival (OS) rate compared with T2N1 disease (74.7% vs. 57.1%, P = 0.018).

Conclusions

Our study confirmed the existence of survival paradox between stage IIB/IIC and stage IIIA colon cancer based on the newest staging criteria. What is more, the subgroup analyses revealed that T1N2a had the least influence on the survival paradox. N2a colon cancer seemed to be associated with worse prognosis than T2 disease, which would give us a better understanding of tumor biology of colon cancer and be conducive to the refinement of individualized treatment regimens in stage III disease.

Clinical Impact of Combined Modified Glasgow Prognostic Score and C-Reactive Protein/Albumin Ratio in Patients with Colorectal Cancer

The prognostic impact of the combination of the modified Glasgow prognostic score (mGPS) and C-reactive protein/albumin ratio (CAR) in colorectal cancer (CRC) is unclear. We aimed to investigate the clinical usefulness of this combination as a predictor of survival in CRC patients. We retrospectively evaluated 769 CRC patients who had undergone surgery between January 2006 and March 2014. The CAR and mGPS within 1 month postoperation were examined. The integrated area under the curve (iAUC) was compared among mGPS, CAR, and the combined classification (CC). The optimal CAR cut-off for discriminating overall survival was 0.14. Based on this cut-off, the mGPS 0 group was divided into the mGPS 0 with low CAR and the mGPS 0 with high CAR groups, whereas all mGPS 1 and 2 patients were classified into the high CAR group. CC was an independent prognostic factor, and its iAUC value (0.587, 95% CI 0.553–0.624) was superior to those of the mGPS (0.544, 95% CI 0.516–0.576) (bootstrap iAUC mean difference = 0.043; 95% CI = 0.015–0.072) and CAR (0.578, 95% CI 0.545–0.613) (bootstrap iAUC mean difference = 0.009; 95% CI = 0.002–0.017), respectively. In conclusion, the combination of mGPS and CAR has a synergistic effect and has a higher prognostic accuracy than mGPS or CAR alone in patients with CRC.

A Modified Tumor-Node-Metastasis Classification for Primary Operable Colorectal Cancer

Background

The American Joint Committee on Cancer (AJCC) 8th tumor-node-metastasis (TNM) classification for colorectal cancer (CRC) has limited ability to predict prognosis.

Methods

We included 45 379 eligible stage I-III CRC patients from the Surveillance, Epidemiology, and End Results Program. Patients were randomly assigned individually to a training (n = 31 772) or an internal validation cohort (n = 13 607). External validation was performed in 10 902 additional patients. Patients were divided according to T and N stage permutations. Survival analyses were conducted by a Cox proportional hazard model and Kaplan-Meier analysis, with T1N0 as the reference. Area under receiver operating characteristic curve and Akaike information criteria were applied for prognostic discrimination and model fitting, respectively. Clinical benefits were further assessed by decision curve analyses.

Results

We created a modified TNM (mTNM) classification: stages I (T1-2N0-1a); IIA (T1N1b, T2N1b, T3N0); IIB (T1-2N2a-2b, T3N1a-1b, T4aN0); IIC (T3N2a, T4aN1a-2a, T4bN0); IIIA (T3N2b, T4bN1a); IIIB (T4aN2b, T4bN1b); and IIIC (T4bN2a-2b). In the internal validation cohort, compared with the AJCC 8th TNM classification, the mTNM classification showed superior prognostic discrimination (area under receiver operating characteristic curve = 0.675 vs 0.667, respectively; 2-sided P < .001) and better model fitting (Akaike information criteria = 70 937 vs 71 238, respectively). Similar findings were obtained in the external validation cohort. Decision curve analyses revealed that the mTNM had superior net benefits over the AJCC 8th TNM classification in the internal and external validation cohorts.

Conclusions

The mTNM classification provides better prognostic discrimination than AJCC 8th TNM classification, with good applicability in various populations and settings, to help better stratify stage I-III CRC patients into prognostic groups.

Adjuvant Chemotherapy for Stage II Colon Cancer

Simple Summary

Stage II colon cancer is defined as an early stage of the tumor disease, without the involvement of lymph nodes or distant organs. In this group of patients, surgery alone is associated with high cure rate and the role of post-operative chemotherapy is still a matter of debate. In patients with tumor features associated with a high risk of recurrence, post-operative chemotherapy is recommended even if it has a small survival benefit. This clinical issue leads to the need for identifying patients who may benefit from post-operative chemotherapy based on their risk of recurrence. The purpose of this review is to highlight and discuss the uncertainties of the previous trials about the risk stratification, the weight of each prognostic factor and the therapeutic benefit of adjuvant chemotherapy in stage II colon cancer patients. Moreover, we summarize the data from previous studies in a decision algorithm that could help clinicians in clinical practice.

Abstract

In stage II colon cancer management, surgery alone has shown a high cure rate (about 80%), and the role of adjuvant chemotherapy is still a matter of debate. Patients with high-risk features (T4, insufficient nodal sampling, grading, etc.) have a poorer prognosis and, usually, adjuvant chemotherapy is recommended. The purpose of the present study is to highlight and discuss what is still unclear and not completely defined from the previous trials regarding risk stratification and therapeutic benefit of adjuvant chemotherapy. With all the limitations of generalizing, we make the effort of trying to quantify the relative contribution of each prognostic factor and the benefit of adjuvant chemotherapy for stage II colon cancer. Finally, we propose a decision algorithm with the aim of summarizing the current evidence and translating it to clinical practice.

Radiomic signature-based nomogram to predict disease-free survival in stage II and III colon cancer

PURPOSE

To develop a radiomic nomogram to predict disease-free survival (DFS) in patients with colon cancer.

METHODS

We retrospectively identified 302 patients with stage III colon cancer and 269 patients with stage II colon cancer who had undergone multidetector computed tomography (MDCT) and radical resection between January 2009 and December 2015. Patients were divided into a training cohort (n = 322) and an external validation cohort (n = 249). Radiomic features were extracted from MDCT images, and a radiomic signature was built as to predict DFS. A radiomic nomogram integrating the radiomic signature and clinicopathologic characteristics was developed using multivariable logistic regression. The nomogram was evaluated with regard to calibration, discrimination, and clinical utility.

RESULTS

The radiomic signature was an independent prognostic factor for DFS in the training cohort (HR = 1.102; 95 % CI: 1.052-1.156; P < 0.001) and the external validation cohort (HR = 1.157; 95 % CI: 1.030-1.301; P = 0.014). The radiomic signature-based nomogram was more effective at predicting DFS than either the TNM staging system or a clinicopathologic nomogram. The C-indices of the radiomic nomogram and TNM staging system were 0.780 (95 % CI: 0.734-0.847) and 0.738 (0.687-0.784) respectively. The radiomic signature-based nomogram demonstrated good fitness (shown by calibration curves) and clinical usefulness (shown by decision curve analysis).

CONCLUSION

A radiomic signature derived from MDCT images can effectively predict DFS in patients with stage II and III colon cancer and could be used as a supplement for risk stratification.

Survival impact of adjuvant chemotherapy in patients with stage IIA colon cancer: Analysis of the National Cancer Database

Utility of adjuvant chemotherapy for stage II cancer remains a matter of debate. Clinical guidelines suggest adjuvant chemotherapy for stage II tumors with high-risk features, in particular T4 tumors. However, limited consensus exists regarding the importance of other high-risk features (lymphovascular or perineural invasion, microsatellite instability). Our study aimed to investigate the impact of adjuvant chemotherapy for stage IIA (T3N0) colon cancer patients. Patients who underwent colectomy for stage IIA colon adenocarcinoma (2010-2015) were identified in the National Cancer Database (NCDB) and divided in two groups based on receipt of adjuvant chemotherapy vs observation. Inverse probability of treatment weighting (IPTW)-adjusted Kaplan-Meier and Cox proportional hazards regression analyses were performed to compare overall survival between the two groups. Subgroup analysis of patients with specific high-risk features LVI, PNI and MSI was performed. Among 46 688 surgical patients with stage IIA colon adenocarcinoma 5937 (12.7%) received adjuvant chemotherapy, while 40 751 (87.3%) were observed. Five-year IPTW-adjusted survival was higher in the adjuvant chemotherapy group (79.7% [95% CI 79.1, 80.2]) compared to the observation group (70.3% [95% CI 69.7, 70.9]). Patients with high-risk pathological features showed an estimated 5-year survival benefit of 11.3% (78.2% [95% CI 77.4, 79.1] vs 66.9% [95% CI 65.9, 67.8]) when treated with adjuvant chemotherapy. This NCDB analysis revealed a survival benefit for patients with stage IIA colon adenocarcinoma and high-risk features that were treated with adjuvant chemotherapy.

Patient Selection for Adjuvant Chemotherapy in High-Risk Stage II Colon Cancer: A Systematic Review and Meta-Analysis

OBJECTIVES

Patients with high-risk stage II colon cancer (CC) are recommended to undergo adjuvant chemotherapy (ACT). However, whether such patients can benefit from ACT remains unclear. This meta-analysis aimed to investigate the clinicopathologic parameters that are important for selecting patients for ACT in high-risk stage II CC.

METHODS

We systematically retrieved articles from PubMed, the Cochrane Library, and Embase that were published up to September 13, 2018. We analyzed overall survival (OS) and disease-free survival (DFS) based on hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

A total of 23 cohort studies and 1 randomized controlled trial were included in our study. Overall analyses showed that ACT improved OS (HR=0.64, 95% CI=0.51-0.80, P<0.001) and DFS (HR=0.46, 95% CI=0.28-0.76, P=0.002) in patients with high-risk stage II CC. Subgroup analyses showed that ACT improved OS in patients with localized intestinal perforation and obstruction and pT4 lesions and improved OS and DFS in patients with <12 sampled lymph nodes. However, ACT had no significant effect on OS in patients with lymphovascular invasion, perineural invasion, or poorly differentiated histology.

CONCLUSIONS

Our study suggests that not all high-risk factors (lymphovascular invasion, perineural invasion, poorly differentiated histology) show a benefit from ACT. Randomized controlled trials selectively targeting high-risk patients will need to be conducted in the future.

A chemokine/chemokine receptor signature potentially predicts clinical outcome in colorectal cancer patients

BACKGROUND

Differential expression of chemokines/chemokine receptors in colorectal cancer (CRC) may enable molecular characterization of patients' tumors for predicting clinical outcome.

OBJECTIVE

To evaluate the prognostic ability of these molecules in a CRC cohort and the CRC TCGA-dataset.

METHODS

Chemokine (CXCL-12α, CXCL-12β, IL-17A, CXCL-8, GM-CSF) and chemokine receptor (CXCR-4, CXCR-7) transcripts were analyzed by RT-qPCR in 76 CRC specimens (normal: 27, tumor: 49; clinical cohort). RNA-Seq data was analyzed from the TCGA-dataset (n= 375). Transcript levels were correlated with outcome; analyses: univariate, multivariable, Kaplan-Meier.

RESULTS

In the clinical cohort, chemokine/chemokine receptor levels were elevated 3-10-fold in CRC specimens (P⩽ 0.004) and were higher in patients who developed metastasis (P= 0.03 - < 0.0001). CXCR-4, CXCR-7, CXCL-12α, CXCL-8, IL-17 and GM-CSF levels predicted metastasis (P⩽ 0.0421) and/or overall survival (OS; P⩽ 0.0373). The CXCR-4+CXCR-7+CXCL-12 marker (CXCR-4/7+CXCL-12 (α/b) signature) stratified patients into risk for metastasis (P= 0.0014; OR, 2.72) and OS (P= 0.0442; OR, 2.7); sensitivity: 86.67%, specificity: 97.06%. In the TCGA-dataset, the CXCR-4/7+CXCL-12 signature predicted metastasis (P= 0.011; OR, 2.72) and OS (P= 0.0006; OR: 4.04). In both datasets, the signature was an independent predictor of clinical outcome.

CONCLUSIONS

Results of 451 specimens from both cohorts reveal that the CXCR-4/7+CXCL-12 signature potentially predicts outcome in CRC patients and may allow earlier intervention.

The role of double-strand break repair, translesion synthesis, and interstrand crosslinks in colorectal cancer progression-clinicopathological data and survival

BACKGROUND AND OBJECTIVES

DNA repair is a new and important pathway that explains colorectal carcinogenesis. This study will evaluate the prognostic value of molecular modulation of double-strand break repair (XRCC2 and XRCC5); DNA damage tolerance/translesion synthesis (POLH, POLK, and POLQ), and interstrand crosslink repair (DCLRE1A) in sporadic colorectal cancer (CRC).

METHODS

Tumor specimens and matched healthy mucosal tissues from 47 patients with CRC who underwent surgery were assessed for gene expression of XRCC2, XRCC5, POLH, POLK, POLQ, and DCLRE1A; protein expression of Polk, Ku80, p53, Ki67, and mismatch repair MLH1 and MSH2 components; CpG island promoter methylation of XRCC5, POLH, POLK, POLQ, and DCLRE1A was performed.

RESULTS

Neoplastic tissues exhibited induction of POLK (P < .001) and DCLRE1A (P < .001) expression and low expression of POLH (P < .001) and POLQ (P < .001) in comparison to healthy paired mucosa. Low expression of POLH was associated with mucinous histology and T1-T2 tumors (P = .038); low tumor expression of POLK was associated with distant metastases (P = .042). CRC harboring POLK promoter methylation exhibited better disease-free survival (DFS) (P = .005).

CONCLUSIONS

This study demonstrated that low expression or unmethylated POLH and POLK were related to worse biological behavior tumors. However, POLK methylation was associated with better DFS. POLK and POLH are potential prognostic biomarkers in CRC.