Tumor deposits counted as positive lymph nodes in TNM staging for advanced colorectal cancer: a retrospective multicenter study

Li, Jun; Yang, Shixing; Hu, Junjie; Liu, Hao; Du, Feng; Yin, Jie; Liu, Sai; Li, Ci; Xing, Shasha; Yuan, Juan; Lv, Bo; Fan, Jun; Leng, Shusheng; Zhang, Xin; Wang, Bing

doi:10.18632/oncotarget.7756

Cited by 37 publications

(25 citation statements)

References 15 publications

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“…However, TNM staging fails to evaluate survival outcomes accurately in many patients undergoing surgical resection [ 5 ]. Conflict outcomes even existed among patients with same stage category [ 6 , 7 ]. Besides that, although the version of TNM staging has been continuously updating in the past decade, the prognosis value does not increase significantly [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

An integrated lncRNA, microRNA and mRNA signature to improve prognosis prediction of colorectal cancer

et al. 2017

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Although the outcome of patients with colorectal cancer (CRC) has improved significantly, prognosis evaluation still presents challenges due to the disease heterogeneity. Increasing evidences revealed the close correlation between aberrant expression of certain RNAs and the prognosis. We envisioned that combined multiple types of RNAs into a single classifier could improve postoperative risk classification and add prognostic value to the current stage system. Firstly, differentially expressed RNAs including mRNAs, miRNAs and lncRNAs were identified by two different algorithms. Then survival and LASSO analysis was conducted to screen survival-related DERs and build a multi-RNA-based classifier for CRC patient stratification. The prognostic value of the classifier was self-validated in the TCGA CRC cohort and further validated in an external independent set. Finally, survival receiver operating characteristic analysis was used to assess the performance of prognostic prediction. We found that the multi-RNA-based classifier consisted by 12 mRNAs, 1miRNA and 1 lncRNA, which could divide the patients into high and low risk groups with significantly different overall survival (training set: HR 2.54, 95%CI 1.67-3.87, p<0.0001; internal testing set: HR 2.54, 95%CI 1.67-3.87, p<0.0001; validation set: HR 5.02, 95% CI 2.2–11.6; p=0·0002). In addition, the classifier is not only independent of clinical features but also with a similar prognostic ability to the well-established TNM stage (AUC of ROC 0.83 versus 0.74, 95% CI = 0.608-0.824, P =0.0878). Furthermore, combination of the multi-RNA-based classifier with clinical features was a more powerful predictor of prognosis than either of the two parameters alone. In conclusion, the multi-RNA-based classifier may have important clinical implications in the selection of patients with CRC who are at high risk of mortality and add prognostic value to the current stage system.

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Section: Introductionmentioning

confidence: 99%

An integrated lncRNA, microRNA and mRNA signature to improve prognosis prediction of colorectal cancer

et al. 2017

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“…The prognosis of patients with CRC has gradually improved in recent decades, however, many issues remain to be resolved. Changes in the definition of TDs have caused considerable confusion among researchers and have had a significant impact on the choices of post-operative treatment and on precise prognosis ( 13 ). Gabriel et al depicted TDs as a result of vascular tumor dissemination in 1935, however, given that TDs were located in the pericolic or perirectal fattiness not continuous with the primary tumor and unassociated with nodes, it was difficult to distinguish between TDs and LNs ( 18 ).…”

Section: Discussionmentioning

confidence: 99%

“…The possibility of counting TDs as the number of positive lymph nodes (pLNs) in the CRC has recently been investigated, and the results indicated that counting TDs as pLNs improved the predictive ability for assessing prognosis and survival in patients with CRC (12,13). However, previous studies only included a limited number of Asian patients, with no validation cohorts from western countries.…”

Section: Introductionmentioning

confidence: 99%

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

Pei

Zhang

et al. 2020

Front. Med.

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

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“…Although the TNM staging system is widely used as the risk stratification of CRC patients, it is insufficient in the prediction of prognosis and estimation for some patients. 32 , 33 Conflict clinical outcomes may exist among some CRC patients with the same stage. 31 , 32 To date, there are no clinically utilized prognostic biomarkers in CRC patients.…”

Section: Discussionmentioning

confidence: 99%

Development and validation of an immunity-related classifier of nine chemokines for predicting recurrence in stage I-III patients with colorectal cancer after operation

Zhou

2018

CMAR

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IntroductionChemokines are closely related with tumor immunity, progression, and metastasis. We aimed to construct a multi-RNA classifier of chemokine family genes for predicting tumor recurrence in stage I–III patients with colorectal cancer (CRC) after operation.Patients and methodsBy analyzing microarray data, the Cox regression analysis was conducted to determine survival-related chemokine family genes and develop a multi-RNA classifier in the training set. The prognostic value of this multi-RNA classifier was further validated in the internal validation and external independent sets. Receiver operating characteristic curves were used to compare the prediction ability of the combined model of this multi-RNA classifier and stage, and this multi-RNA classifier and stage alone.ResultsNine survival-related chemokines were identified in the training set. We identified a nine-chemokine classifier and classified the patients as high-risk or low-risk. Compared with CRC patients with high-risk scores, CRC patients with low-risk scores had longer disease-free survival in the training (HR=2.353, 95% CI=1.480–3.742, P<0.001), internal validation (HR=2.389, 95% CI=1.428–3.996, P<0.001), and external independent (HR=3.244, 95% CI=1.813–5.807, P<0.001) sets. This nine-chemokine classifier was an independent prognostic factor in these datasets (P<0.05). The combined model of this nine-chemokine classifier and tumor stage may tend to have higher accuracy than stage alone in the training (area under curve 0.727 vs 0.626, P<0.01), internal validation (0.668 vs 0.584, P=0.03), and external independent (0.704 vs 0.678, P>0.05) sets. This nine-chemokine classifier may only be applied in Marisa’s C2, C5, and C6 subtypes patients.ConclusionOur nine-chemokine classifier is a reliable prognostic tool for some specific biological subtypes of CRC patients. It might contribute to guide the personalized treatment for high-risk patients.

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Tumor deposits counted as positive lymph nodes in TNM staging for advanced colorectal cancer: a retrospective multicenter study

Cited by 37 publications

References 15 publications

An integrated lncRNA, microRNA and mRNA signature to improve prognosis prediction of colorectal cancer

An integrated lncRNA, microRNA and mRNA signature to improve prognosis prediction of colorectal cancer

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

Development and validation of an immunity-related classifier of nine chemokines for predicting recurrence in stage I-III patients with colorectal cancer after operation

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