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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ABSTRACT:
SUBMITTER: Bae JH
PROVIDER: S-EPMC8389700 | biostudies-literature |
REPOSITORIES: biostudies-literature
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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: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: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
Project description:Ann Arbor stage has limited utility in the prognostication and treatment decision making in patients with NK/T-cell lymphoma (NKTCL), as NKTCL is almost exclusively extranodal and the majority is localized at presentation for which radiotherapy is the most important treatment and local invasiveness is the most important prognostic factor. In this study, we attempted to establish a TNM (Tumor-Node-Metastasis) staging system for nasal NKTCL (N-NKTCL). The staging rules of other head and neck cancers were used as reference along with the data of our 271 eligible patients. The primary tumor was classified into T1 to T4, and cervical lymph node metastasis was classified into N0 to N2 according to the extent of involvement. Any lesions outside the head and neck were classified as M1. N-NKTCL thereby was classified into four stages: stage I comprised T1-2N0M0; stage II comprised T1-2N1M0 and T3N0M0; stage III comprised T3N1M0, T1-3N2M0, and T4N0-2M0; and stage IV comprised TanyNanyM1. This staging system showed excellent performance in prognosticating survival. In the current series, the 5-year survival rates of patients with stages I, II, III, and IV N-NKTCL were 92%, 64%, 23%, and 0, respectively. Moreover, the predictive value of several currently used factors was abrogated in the presence of the TNM stage. The TNM staging system is highly effective in stratifying tumor burden and survival risk, which may have significant implications in the treatment decision making for patients with N-NKTCL.
| S-EPMC4476596 | biostudies-literature
Project description:Purpose:The modification of the cancer classification system aimed to improve the classical anatomy-based tumor, node, metastasis (TNM) staging by considering tumor biology, which is associated with patient prognosis, because such information provides additional precision and flexibility. Materials and Methods:We previously developed an mRNA expression-based single patient classifier (SPC) algorithm that could predict the prognosis of patients with stage II/III gastric cancer. We also validated its utilization in clinical settings. The prognostic single patient classifier (pSPC) differentiates based on 3 prognostic groups (low-, intermediate-, and high-risk), and these groups were considered as independent prognostic factors along with TNM stages. We evaluated whether the modified TNM staging system based on the pSPC has a better prognostic performance than the TNM 8th edition staging system. The data of 652 patients who underwent gastrectomy with curative intent for gastric cancer between 2000 and 2004 were evaluated. Furthermore, 2 other cohorts (n=307 and 625) from a previous study were assessed. Thus, 1,584 patients were included in the analysis. To modify the TNM staging system, one-grade down-staging was applied to low-risk patients according to the pSPC in the TNM 8th edition staging system; for intermediate- and high-risk groups, the modified TNM and TNM 8th edition staging systems were identical. Results:Among the 1,584 patients, 187 (11.8%), 664 (41.9%), and 733 (46.3%) were classified into the low-, intermediate-, and high-risk groups, respectively, according to the pSPC. pSPC prognoses and survival curves of the overall population were well stratified, and the TNM stage-adjusted hazard ratios of the intermediate- and high-risk groups were 1.96 (95% confidence interval [CI], 1.41-2.72; P<0.001) and 2.54 (95% CI, 1.84-3.50; P<0.001), respectively. Using Harrell's C-index, the prognostic performance of the modified TNM system was evaluated, and the results showed that its prognostic performance was better than that of the TNM 8th edition staging system in terms of overall survival (0.635 vs. 0.620, P<0.001). Conclusions:The pSPC-modified TNM staging is an alternative staging system for stage II/III gastric cancer.
| S-EPMC6026714 | biostudies-literature
Project description:PURPOSE:The role of lymph node ratio (LNR, ratio of metastatic to examined nodes) in the staging of multiple human malignancies has been reported. We aim to evaluate its value in salivary gland cancer (SGC). METHODS:Records of SGC patients from Surveillance, Epidemiology, and End Results database (SEER, training set, N?=?4262) and Fudan University Shanghai Cancer Center (FUSCC, validating set, N?=?154) were analyzed for the prognostic value of LNR. Kaplan-Meier survival estimates, the Log-rank ?2 test and Cox proportional hazards model were used for univariate and multivariate analysis. Optimal LNR cutoff points were identified by X-tile. RESULTS:Optimal LNR cutoff points classified patients into four risk groups, R0, R1 (??0.17), R2 (0.17-0.56) and R3 (>?0.56), corresponding to 5-year cause-specific survival in SEER patients of 88.6%, 57.2%, 53.1% and 39.7%, disease-free survival in FUSCC patients of 69.2%, 63.3%, 34.6% and 0%, and disease-specific survival in FUSCC patients of 92.3%, 90.0%, 71.4% and 0%, respectively. Compared with TNM staging, TNM?+?R staging showed smaller AIC values and higher C-index values in the Cox regression model in both patient sets. CONCLUSIONS:LNR classification should be considered as a complementary system to TNM staging and LNR classification based clinical trials deserve further research.
| S-EPMC6858905 | biostudies-literature