Addition of V-Stage to Conventional TNM Staging to Create the TNVM Staging System for Accurate Prediction of Prognosis in Colon Cancer: A Multi-Institutional Retrospective Cohort Study.
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SUBMITTER: Bae JH
PROVIDER: S-EPMC8389700 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveDespite controversy over its origin and definition, the significance of tumour deposit (TD) has been underestimated in the tumour node metastasis (TNM) staging system for colon cancer, especially in stage III patients. We aimed to further confirm the prognostic value of TD in stage III colon cancer and to establish a more accurate 'coN' staging system combining TD and lymph node metastasis (LNM).MethodsInformation on stage III colon cancer patients with a definite TD status was retrospectively collected from the Surveillance, Epidemiology and End Results (SEER) database between 2010 and 2017. The effect of TD on prognosis was estimated using Cox regression analysis. Maximally selected rank statistics were used to select the optimal cut-off value of TD counts. The predictive power of conventional N staging and the new coN staging was evaluated and compared by Akaike's information criterion (AIC), Harrell's concordance index (C-index) and time-dependent receiver operating characteristic (ROC) curves. Clinicopathological data of stage III colon cancer patients in the Xiangya database from 2014 to 2018 were collected to validate the coN staging system.ResultsA total of 39,185 patients with stage III colon cancer were included in our study: 38,446 in the SEER cohort and 739 in the Xiangya cohort. The incidence of TD in stage III colon cancer was approximately 30% (26% in SEER and 30% in the Xiangya database). TD was significantly associated with poorer overall survival (OS) (HR = 1.37, 95% CI 1.31-1.44, p < 0.001 in SEER). The optimal cut-off value of TD counts was 4, and the patients were classified into the TD0 (count = 0), TD1 (count = 1-3) and TD2 (count ≥ 4) groups accordingly. The estimated 5-year OS was significantly different among the three groups (69.4%, 95% CI 68.8%-70.0% in TD0; 60.5%, 95% CI 58.9%-62.2% in TD1 and 42.6%, 95% CI 39.2%-46.4% in TD2, respectively, p < 0.001). The coN system integrating LNM and TD was established, and patients with stage III colon cancer were reclassified into five subgroups (coN1a, coN1b, coN2a, coN2b and coN2c). Compared with conventional N staging, the coN staging Cox model had a smaller AIC (197097.581 vs. 197358.006) and a larger C-index (0.611 vs. 0.601). The AUCs of coN staging at 3, 5 and 7 years were also greater than those of conventional N staging (0.6305, 0.6326, 0.6314 vs. 0.6186, 0.6197, 0.6160). Concomitant with the SEER cohort results, the coN staging Cox model of the Xiangya cohort also had a smaller AIC (2883.856 vs. 2906.741) and a larger C-index (0.669 vs. 0.633). Greater AUCs at 3, 5 and 7 years for coN staging were also observed in the Xiangya cohort (0.6983, 0.6774, 0.6502 vs. 0.6512, 0.6368, 0.6199).ConclusionsNot only the presence but also the number of TDs is associated with poor prognosis in stage III colon cancer. A combined N staging system integrating LNM and TD provides more accurate prognostic prediction than the latest AJCC N staging in stage III colon cancer.
| S-EPMC9939212 | biostudies-literature
Project description:This study focused on improving the American Joint Committee on Cancer TNM staging system and demonstrated an improvement in prognostic accuracy and clinical management of colon cancer using the P-TNM staging system.Eligible patients (N=56,800) were identified from the Surveillance, Epidemiology, and End Results database between January 1, 2010, and December 31, 2014. The P-stage (P0 or P1) was assigned to each patient based on age at diagnosis, tumor grade, and tumor size. The outcome of interest was cancer-specific survival (CSS). The Cox proportional hazards regression analyses were used to identify independent prognostic factors and analyze the CSS probabilities of patients with colon cancer having different P-TNM stages, respectively.A total of 29,627 patients were assigned to P0-stage and 27,173 patients were assigned to P1-stage. The P1-stage was associated with a 98.1% increased risk of cancer-specific mortality (hazard ratio =1.981, 95% confidence interval =1.891-2.076, P<0.001), which was higher in patients with nonmetastatic colon cancer. The P1-stage patients had improvement in CSS compared with those in P0-stage in respective stages (P<0.001). Moreover, CSS decreased in stage I-P1 compared with stage IIA-P0 or IIIA-P0 (P<0.001), stage IIIA-P1 compared with stage IIA-P0 (P<0.001), stage IIB-P1 compared with stage IIIB-P0 or IIC-P0 (P<0.001), stage IIIB-P1 compared with stage IIC-P0 (P<0.001), and stage IIC-P1 compared with stage IIIC-P0 (P<0.001).P-stage was an independent prognostic factor for colon cancer. This study strongly supported the incorporation of P-stage into the American Joint Committee on Cancer TNM staging system for a better approach to prognostication and, thus, more individualized risk-adaptive therapies in colon cancer.
| S-EPMC6074826 | biostudies-other
Project description:BackgroundSurvival outcomes are significantly different in stage II colorectal cancer (CRC) patients with diverse clinicopathological features. The objective of this study is to establish a credible prognostic nomogram incorporating easily obtained parameters for stage II CRC patients.MethodsA total of 1708 stage II CRC patients seen at Fudan University Shanghai Cancer Center (FUSCC) from 2008 to 2013 were retrospectively analyzed in this study. Cases were randomly separated into a training set (n = 1084) and a validation set (n = 624). Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors that were subsequently incorporated into a nomogram. The performance of the nomogram was evaluated by the predicted concordance index (C-index) and ROC curve to calculate the area under the curve (AUC). The clinical utility of the nomogram was evaluated using decision curve analysis (DCA).ResultsIn univariate and multivariate analyses, eight parameters were correlated with disease-free survival (DFS), which were subsequently selected to generate a prognostic nomogram based on DFS. For DFS predictions, the C-index values of the nomogram were 0.842 (95% confidence interval (CI) 0.710-0.980), and 0.701 (95% CI 0.610-0.770) for the training and validation sets, respectively. The AUC values of the ROC curves for the nomogram to predicted 1, 3 and 5-year survival were 0.869, 0.858, and 0.777 (training group) and 0.673, 0.714, and 0.706 (validation group), respectively. The recurrence probability calibration curve showed good consistency between actual observations and nomogram-based predictions. DCA showed better clinical application value for the nomogram than the TNM staging system.ConclusionA novel nomogram was established and validated in a large population, and the nomogram is a simple-to-use tool for physicians to facilitate postoperative personalized prognostic evaluation and determine therapeutic strategies for stage II CRC patients.
| S-EPMC7339452 | biostudies-literature
Project description:Tumour budding has been described as an independent prognostic feature in several tumour types. We report for the first time the relationship between tumour budding and survival evaluated in patients with muscle invasive bladder cancer. A machine learning-based methodology was applied to accurately quantify tumour buds across immunofluorescence labelled whole slide images from 100 muscle invasive bladder cancer patients. Furthermore, tumour budding was found to be correlated to TNM (p = 0.00089) and pT (p = 0.0078) staging. A novel classification and regression tree model was constructed to stratify all stage II, III, and IV patients into three new staging criteria based on disease specific survival. For the stratification of non-metastatic patients into high or low risk of disease specific death, our decision tree model reported that tumour budding was the most significant feature (HR = 2.59, p = 0.0091), and no clinical feature was utilised to categorise these patients. Our findings demonstrate that tumour budding, quantified using automated image analysis provides prognostic value for muscle invasive bladder cancer patients and a better model fit than TNM staging.
| S-EPMC6435679 | biostudies-other
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.
| S-EPMC6413460 | biostudies-literature
Project description:BackgroundThe Chinese Society of Clinical Oncology guidelines 2018 and the recent update of that (version 2020) recommends accurate examination before major treatment for decision(s) in cases of colon cancer. Also, the difficulty in the identification of the lesion during colectomy may lead to resection of a wrong segment of the colon or a more extensive resection than planned. Accurate pre-colectomy local staging of colon cancer is required to make decisions for treatment of colon cancer. The objective of the study was to evaluate the diagnostic performance of the computed tomography colonography (CTC) for pre-colectomy tumor location and tumor, node, and metastasis (TNM) staging of colon cancer.MethodsData of preoperative colonoscopies, CTC, surgeries, and surgical pathology of a total of 269 patients diagnosed with colon cancer by colonoscopy and biopsy and underwent pre-colectomy location and TNM staging by CTC were collected and analyzed. The consistency between the radiological and the surgery/surgical-pathological for location and TN stages of colon tumor were estimated with the weighted kappa or kappa coefficient (κ) at 95% confidence interval (CI).ResultsCTC detected 261 (93%) and colonoscopy detected 201 (72%) correct locations of tumors. Sensitivity and accuracy of CTC for detection of location of colon tumors were 100% and 92.58% (κ = 0.89; 95% Cl: 0.83-0.95). 72.48% sensitivity, 90.64% specificity, and 83.57% accuracy were reported for CTC in differentiation of tumors confined to the colon wall (T1/T2) from advanced tumors (T3/T4) (κ = 0.69, 95% Cl: 0.51-0.75). 81.01% sensitivity, 89.11% specificity, and 83.93% accuracy of CTC was reported for differentiation of tumors between low-intermediate risk and high risk (κ = 0.68, 95% Cl: 0.53-0.75). 69.31% sensitivity, 66.15% specificity, and 67.14% accuracy of CTC were reported for N staging of tumors (κ = 0.41, 95% Cl: 0.59-0.69).ConclusionsCTC has high diagnostic parameters for pre-colectomy location and T staging of colon tumors except patients of colon cancer who received neoadjuvant chemotherapy.Level of evidenceIII.Technical efficacy stage2.
| S-EPMC8051039 | biostudies-literature
Project description:ObjectiveOver the past decades, many studies have used data mining technology to predict the 5-year survival rate of colorectal cancer, but there have been few reports that compared multiple data mining algorithms to the TNM classification of malignant tumors (TNM) staging system using a dataset in which the training and testing data were from different sources. Here we compared nine data mining algorithms to the TNM staging system for colorectal survival analysis.MethodsTwo different datasets were used: 1) the National Cancer Institute's Surveillance, Epidemiology, and End Results dataset; and 2) the dataset from a single Chinese institution. An optimization and prediction system based on nine data mining algorithms as well as two variable selection methods was implemented. The TNM staging system was based on the 7(th) edition of the American Joint Committee on Cancer TNM staging system.ResultsWhen the training and testing data were from the same sources, all algorithms had slight advantages over the TNM staging system in predictive accuracy. When the data were from different sources, only four algorithms (logistic regression, general regression neural network, bayesian networks, and Naïve Bayes) had slight advantages over the TNM staging system. Also, there was no significant differences among all the algorithms (p>0.05).ConclusionsThe TNM staging system is simple and practical at present, and data mining methods are not accurate enough to replace the TNM staging system for colorectal cancer survival prediction. Furthermore, there were no significant differences in the predictive accuracy of all the algorithms when the data were from different sources. Building a larger dataset that includes more variables may be important for furthering predictive accuracy.
| S-EPMC3404978 | biostudies-literature
Project description:The current AJCC staging system for gastric cancer (AJCC7) incorporated several major revisions to the previous edition. The T and N categories and the stage groups were newly defined, and adenocarcinoma of the esophagogastric junction (EGJ) was reclassified and staged according to the esophageal system. Studies to validate these changes showed inconsistent results. The International Gastric Cancer Association (IGCA) launched a project to support evidence-based revisions to the next edition of the AJCC staging system.Clinical and pathological data on patients who underwent curative gastrectomy at 59 institutions in 15 countries between 2000 and 2004 were retrospectively collected. Patients lost to follow-up within 5 years of surgery were excluded. Patients treated with neoadjuvant therapy were excluded. The data were analyzed in total, and separately by region of treatment.Of 25,411 eligible cases, 84.8 % were submitted from 24 institutions of Japan and Korea, 6.4 % from other Asian countries, and 8.8 % from 29 Western institutions. The T and N categories of AJCC7 clearly stratified the patient survival. Patients with pN3a and pN3b showed distinct prognosis in all regions, and by introducing pN3a and pN3b into a cluster analysis, we established a new stage grouping with better stratification than AJCC7, especially among stage III subgroups. Survival of Siewert type 2 and 3 EGJ tumors was better stratified by this IGCA stage grouping than by either esophageal or gastric scheme of AJCC7.For the next revision of AJCC classification, we propose a new stage grouping based on a large, worldwide data collection.
| S-EPMC4992472 | biostudies-literature
Project description:Objectives: We aimed to explore reasonable lymph node classification strategies for left-sided colon cancer (LCC) patients. Methods: 48,425 LCC patients from 2010 to 2015 were identified in the US Surveillance, Epidemiology, and End Results database. We proposed an innovative revised nodal (rN) staging of the 8th American Joint Committee on Cancer (AJCC) Tumor/Node/Metastasis (TNM) classification based on the cut-off value of retrieved lymph nodes and survival analyses in patients with LCC. Log odds of positive lymph nodes (LODDS) stage is a numerical classification strategy obtained by a formula that incorporates the numbers of retrieved and positive lymph nodes. To develop the TrN or TLODDS classification, patients with similar survival rates were grouped by combining T and rN or LODDS stage. The TrN or TLODDS classification was further evaluated in a validation set of 12,436 LCC patients from 2016 to 2017 in the same database and a Chinese application set of 958 LCC patients. Results: We developed novel TrN and TLODDS classifications for LCC patients that incorporated 7 stages with reference to the AJCC staging system. In comparison to the 8th AJCC TNM and TrN classifications, TLODDS classification demonstrated significantly better discrimination (area under the receiver operating characteristic curve, 0.650 vs. 0.656 vs. 0.661, p < 0.001), better model-fitting (Akaike information criteria, 309,287 vs. 308,767 vs. 308,467), and superior net benefits. The predictive performance of the TrN and TLODDS classifications was further verified in the validation and application sets. Conclusion: Both the TrN and TLODDS classifications have better discriminatory ability, model-fitting, and net benefits than the existing TNM classification, and represent an alternative to the current TNM classification for LCC patients.
| S-EPMC9998476 | biostudies-literature
Project description:BackgroundThere are few systematic evaluations regarding the sixth and seventh editions of the UICC/AJCC TNM Staging System (TNM6th, TNM7th) and Chinese 2008 Staging System (TNMc2008) for nasopharyngeal carcinoma (NPC).MethodsWe classified 2333 patients into intensity-modulated radiotherapy (IMRT) cohort (n=941) and conventional radiotherapy (CRT) cohort (n=1392). Tumour staging defined by TNM6th, TNM7th and TNMc2008 was compared based on Akaike information criterion (AIC) and Harrell's concordance index (c-index).ResultsFor T-classification, TNM6th (AIC=2585.367; c-index=0.6390385) had superior prognostic value to TNM7th (AIC=2593.242; c-index=0.6226889) and TNMc2008 (AIC=2593.998; c-index=0.6237146) in the IMRT cohort, whereas TNMc2008 was superior (AIC=5999.054; c-index=0.623547) in the CRT cohort. For N-classification, TNMc2008 had the highest prognostic value in both cohorts (AIC=2577.726, c-index=0.6297874; AIC=5956.339, c-index=0.6533576). Similar results were obtained when patients were stratified by chemotherapy types, age and gender. Using staging models in the IMRT cohort, we failed to identify better stage migrations than TNM6th T-classification and TNMc2008 N-classification. We therefore proposed to combine these categories; resultantly, stage groups of the proposed staging system showed superior prognostic value over TNM6th, TNM7th and TNMc2008.ConclusionTNM6th T-classification and TNMc2008 N-classification have superior prognostic value in the IMRT era. By combining them with slight modifications, TNM criteria can be unified and its prognostic value be improved.
| S-EPMC3859943 | biostudies-literature