Dataset Information

Combination of preoperative tumour markers and lymphovascular invasion with TNM staging as a cost and labour efficient subtyping of colorectal cancer.

ABSTRACT: Tumour-Node-Metastasis (TNM) staging of colorectal cancer (CRC) needs further classification for better treatment because of disease heterogeneity. Although molecular classifications which are expensive and laborious are under study, cost and labour efficient subtyping is desirable. We assessed the combinations of preoperative tumour marker (TM) elevation and tumour lymphovascular invasion (LVI) as a solution. We used the pooled data of 7151 colon cancer (CC) patients and 4620 rectal cancer (RC) patients who received curative surgery between 2004 and 2008 in Japan. The best-matched subtyping for predicting relapse-free survival (RFS) was statistically selected using the c-index and Akaike's information criterion. This subtyping (TM-LVI), which consisted of three categories by TM elevation status and severity of LVI status, was an independent prognostic factor for RFS of CC (stage IIa, IIIb, and IIIc) and RC (stage I, IIa, IIb, IIIa, and IIIb) and also for disease specific survival of CC (stage IIa, IIb, IIIb, and IIIc) and RC (all stage except for IIc). Although TM-LVI classified CRC patients into low and high recurrence risk groups, the application of adjuvant therapy was not accordance with the TM-LVI status. TM-LVI may be a cost and labour efficient subtyping of colorectal cancer for better treatment strategy.

SUBMITTER: Yamano T

PROVIDER: S-EPMC7314851 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Combination of preoperative tumour markers and lymphovascular invasion with TNM staging as a cost and labour efficient subtyping of colorectal cancer.

Yamano Tomoki T Yamauchi Shinichi S Igeta Masataka M Takenaka Yuya Y Song Jihyung J Kimura Kei K Yasuhara Michiko M Babaya Akihito A Kataoka Kozo K Beppu Naohito N Ikeda Masataka M Tomita Naohiro N Sugihara Kenichi K

Scientific reports 20200624 1

Tumour-Node-Metastasis (TNM) staging of colorectal cancer (CRC) needs further classification for better treatment because of disease heterogeneity. Although molecular classifications which are expensive and laborious are under study, cost and labour efficient subtyping is desirable. We assessed the combinations of preoperative tumour marker (TM) elevation and tumour lymphovascular invasion (LVI) as a solution. We used the pooled data of 7151 colon cancer (CC) patients and 4620 rectal cancer (RC) ...[more]

PMID: 32581258

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Project description:BackgroundThis study sought to explore whether lymphovascular invasion can affect the prognosis of patients with stage N0 gastric cancer and to evaluate the survival benefit of adjuvant chemotherapy for such patients.MethodFrom January 2006 to December 2011, a total of 2102 gastric cancer patients undergoing radical gastric resection were enrolled in this study. Homogeneity, discriminatory ability, and monotonicity of gradients in the combination of lymphovascular invasion and the 8th edition of the AJCC staging system and the 8th edition of the AJCC staging system alone were compared using linear trend χ2, likelihood ratio χ2 statistics, and Akaike information criterion (AIC) calculations. The Kaplan-Meier method and the log-rank test were used to analyze between-group differences in survival rate.ResultThe median follow-up time of the whole group was 58 months, and the average age of the whole group was 63.9 years (range 21-89 years). The 3-year and 5-year overall survival rates in N0 patients with lymphovascular invasion were lower than those in N0 patients without lymphovascular invasion (3-year OS: 78.3% vs 92.5%, 5-year OS: 70.0% vs 88.3%, p < 0.001). A multivariate analysis showed that age (p < 0.001), lymphovascular invasion (p < 0.001), and pT (p < 0.001) were independent risk factors for the prognosis of N0 patients. Compared with the 8th edition of the AJCC staging system alone, the 8th AJCC staging system combined with lymphovascular invasion demonstrated a better linear trend χ2, likelihood ratio χ2 statistics, and AIC value (68.99 vs 58.58, 70.18 vs 58.36, 1473.38 vs 1485.04). In pT3N0M0 patients with lymphovascular invasion, the 3-year and 5-year overall survival rates of the adjuvant chemotherapy group were higher than those of the surgery alone group (3-year OS: 83.3% vs 68.2%, 5-year OS: 72.3% vs 50.0%, p = 0.048).ConclusionLymphovascular invasion is an independent prognostic factor in N0 patients. The 8th AJCC staging system combined with lymphovascular invasion can improve the accuracy of the AJCC staging system for N0 patients. Moreover, adjuvant chemotherapy improves the survival of pT3N0M0 patients with lymphovascular invasion.

Project description:BackgroundDetection of lymphovascular space invasion (LVSI) in early cervical cancer (CC) is challenging. To date, no standard clinical markers or screening tests have been used to detect LVSI preoperatively. Therefore, non-invasive risk stratification tools are highly desirable.ObjectiveTo train and validate a multi-parametric magnetic resonance imaging (mpMRI)-based radiomics model to detect LVSI in patients with CC and investigate its potential as a complementary tool to enhance the efficiency of risk assessment strategies.Materials and methodsThe model was developed from the tumor volume of interest (VOI) of 125 patients with CC. A total of 1037 radiomics features obtained from conventional magnetic resonance imaging (MRI), including a small field-of-view (sFOV) high-resolution (HR)-T2-weighted MRI (T2WI), apparent diffusion coefficient (ADC), T2WI, fat-suppressed (FS)-T2WI, as well as axial and sagittal contrast-enhanced T1-weighted MRI (T1c). We conducted a radiomics-based characterization of each tumor region using pretreatment image data. Feature selection was performed using the least absolute shrinkage and selection operator method on the training set. The predictive performance was compared with single variates (clinical data and single-layer radiomics signatures) analyzed using a receiver operating characteristic (ROC) curve. Three-fold cross-validation performed 20 times was used to evaluate the accuracy of the trained classifiers and the stability of the selected features. The models were validated by using a validation set.ResultsFeature selection extracted the six most important features (3 from sFOV HR-T2WI, 1 T2WI, 1 FS-T2WI, and 1 T1c) for model construction. The mpMRI-combined radiomics model (area under the curve [AUC]: 0.940) reached a significantly higher performance (better than the clinical parameters [AUC: 0.730]), including any single-layer model using sFOV HR-T2WI (AUC: 0.840), T2WI (AUC: 0.770), FS-T2WI (AUC: 0.710), ADC maps (AUC: 0.650), sagittal, and axial T1c values (AUC: 0.710, 0.680) in the validation set.ConclusionBiomarkers using multi-parametric radiomics features derived from preoperative MR images could predict LVSI in patients with CC.

Dataset Information

Combination of preoperative tumour markers and lymphovascular invasion with TNM staging as a cost and labour efficient subtyping of colorectal cancer.

Publications

Combination of preoperative tumour markers and lymphovascular invasion with TNM staging as a cost and labour efficient subtyping of colorectal cancer.

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