Dataset Information

Computed Tomography Features associated With the Eighth Edition TNM Stage Classification for Thymic Epithelial Tumors.

ABSTRACT: PURPOSE:The eighth edition of the TNM classification of malignant tumors for the first time includes an official staging system for thymic epithelial tumors (TETs) recognized by the American Joint Committee on Cancer (AJCC) and the Union for International Cancer Control (UICC). Staging is critical for the management of TETs, and determining stage accurately from imaging has the potential to improve clinical outcomes. We examine preoperative computed tomography (CT) characteristics of TETs associated with AJCC/UICC pathologic TNM stage. MATERIALS AND METHODS:In this retrospective study, patients were included if they met all the following criteria: (1) diagnosis of TET, (2) had primary curative intent surgery performed at Stanford University, and (3) had available preoperative CT imaging for review. Tumor pathology was staged according to the eighth edition TNM classification. Fifteen CT scan features were examined from each patient case according to the International Thymic Malignancy Interest Group standard report terms in a blinded manner. A Lasso-regularized multivariate model was used to produce a weighted scoring system predictive of pathologic TNM stage. RESULTS:Examining the 54 patients included, the following CT characteristics were associated with higher pathologic TNM stage when using the following scoring system: elevated hemidiaphragm (score of 6), vascular endoluminal invasion (score of 6), pleural nodule (score of 2), lobulated contour (score of 2), and heterogeneous internal density (score of 1). Area under the receiver operating characteristic curve was 0.76. CONCLUSIONS:TETs with clearly invasive or metastatic features seen on CT are associated with having higher AJCC/UICC pathologic TNM stage, as expected. However, features of lobulated contour and heterogeneous internal density are also associated with higher stage disease. These findings need to be validated in an independent cohort.

SUBMITTER: Padda SK

PROVIDER: S-EPMC6368176 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Computed Tomography Features associated With the Eighth Edition TNM Stage Classification for Thymic Epithelial Tumors.

Padda Sukhmani K SK Terrone Donato D Tian Lu L Khuong Amanda A Neal Joel W JW Riess Jonathan W JW Berry Mark F MF Hoang Chuong D CD Burt Bryan M BM Leung Ann N AN Schwartz Erich J EJ Shrager Joseph B JB Wakelee Heather A HA

Journal of thoracic imaging 20180501 3

<h4>Purpose</h4>The eighth edition of the TNM classification of malignant tumors for the first time includes an official staging system for thymic epithelial tumors (TETs) recognized by the American Joint Committee on Cancer (AJCC) and the Union for International Cancer Control (UICC). Staging is critical for the management of TETs, and determining stage accurately from imaging has the potential to improve clinical outcomes. We examine preoperative computed tomography (CT) characteristics of TET ...[more]

PMID: 29219888

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Project description:BackgroundThe UICC 8th TNM classification of lung cancer has been changed dramatically, especially in measuring methods of T-desriptors. Different from squamous- or small-cell carcinomas, in which the solid- and the invasive-diameter mostly agree with each other, the diameter of the radiological solid part and that of pathological invasive part in adenocarcinomas often does not match.AimWe aimed to determine radiological and pathological tumor diameters of pulmonary adenocarcinomas with clinicopathological factors and evaluate the validity of the 8th edition in comparison with the 7th edition.Methods and resultsWe retrospectively analyzed clinicopathological factors of 429 patients with surgically resected pulmonary adenocarcinomas. The maximum tumor and their solid-part diameters were measured using thin-sectioned computed tomography and compared with pathological tumor and invasive diameters. Overall survival (OS) rate was determined using the Kaplan-Meier method for different subgroups of clinicopathological factors. Akaike's information criteria (AIC) was used as a discriminative measure for the univariate Cox model for the 7th and 8th editions. Multivariate Cox regression analysis was performed to explore independent prognostic factors. Correlation coefficients between radiological and pathological diameters in the 7th and 8th editions were 0.911 and 0.888, respectively, without a significant difference. The major reasons for the difference in the 8th edition were the presence of intratumoral fibrosis and papillary growth pattern. The weighted kappa coefficients in the 8th edition were superior those in the 7th edition for both the T and Stage classifications. In the univariate Cox model, AIC levels were the lowest in the 8th edition. Multivariate analysis revealed that age, lymphovascular invasion, pT(8th), and stage were the most important determinants for OS.ConclusionThe UICC 8th edition is a more discriminative classification than the 7th edition. For subsolid nodules, continuous efforts are necessary to increase the universality of the measurement of solid and invasive diameters.

Project description:ObjectiveThymic epithelial tumors (TETs) are rare tumors that originated from thymic epithelial cells, with limited studies investigating their prognostic factors. This study aimed to investigate the prognostic factors of TETs and develop a new risk classifier to predict their overall survival (OS).MethodsThis retrospective study consisted of 1224 TETs patients registered in the Surveillance, Epidemiology, and End Results (SEER) database, and 75 patients from the First Affiliated Hospital of Xi'an Jiaotong University. The univariate and multivariate Cox regression analyses were adopted to select the best prognostic variables. A nomogram was developed to predict the OS of these patients. The discriminative and calibrated abilities of the nomogram were assessed using the receiver operating characteristics curve (ROC) and calibration curve. Decision curve analysis (DCA), net reclassification index (NRI), and integrated discrimination improvement (IDI) were adopted to assess its net clinical benefit and reclassification ability.ResultsThe multivariate analysis revealed that age, sex, histologic type, TNM staging, tumor grade, surgery, radiation, and tumor size were independent prognostic factors of TETs, and a nomogram was developed to predict the OS of these patients based on these variables. The time-dependent ROC curves displayed that the nomogram yielded excellent performance in predicting the 12-, 36- and 60-month OS of these patients. Calibration curves presented satisfying consistencies between the actual and predicted OS. DCA illustrated that the nomogram will bring significant net clinical benefits to these patients compared to the classic TNM staging system. The estimated NRI and IDI showed that the nomogram could significantly increase the predictive ability of 12-, 36- and 60-month OS compared to the classic TNM staging system. Consistent findings were discovered in the internal and external validation cohorts.ConclusionThe constructed nomogram is a reliable risk classifier to achieve personalized survival probability prediction of TETs, and could bring significant net clinical benefits to these patients.

Project description:Objectives: Since the eighth edition of the American Joint Committee on Cancer tumor-node-metastasis (AJCC/TNM) cancer staging system introduced some significant changes, we investigated whether patients with stage T1-2N1M1 differentiated thyroid cancer (DTC) should be placed in stage IVB, with the goal of providing suggestions for improved survival prediction. Materials and Methods: We divided 30,234 DTC patients aged ?55 years enrolled from the Surveillance, Epidemiology, and End Results (SEER) database into different stage groups based on the new stage system but in a more thorough manner. Univariate and multivariate Cox regression analyses were conducted to explore the clinicopathological factors associated with cancer-specific survival. Survival of different stage groups was assessed by mortality rates per 1,000 person-years, Cox proportional hazards regression analyses, and Kaplan-Meier analyses with log-rank tests and the propensity score matching method. Results: Univariate and multivariate analyses demonstrated that age at diagnosis, T stage, lymph node metastasis, distant metastasis, histological types, extrathyroidal extension, and radiation therapy were associated with cancer-specific survival. Patients with stage T1-2N1M1 had a lower cancer-specific mortality rate per 1,000 person-years (28.081, 95% confidence interval [CI]: 12.616-62.505) and all-cause mortality rate per 1,000 person-years (70.203, 95% CI: 42.323-116.448) than those with low-level stages such as stage T4aN1M0, stage IVA, and stage T1-2N0M1. Cox proportional hazards regression analyses suggested that patients with stage T4bN1M0 belonging to stage IVA (hazard ratio: 2.529, 95% CI: 1.018-6.278, p = 0.046) had a significantly higher risk of cancer-specific mortality than those with stage T1-2N1M1. Kaplan-Meier analyses with log-rank tests suggested that the cancer-specific survival curve of patients with stage T1-2N1M1 had a more modest decline than that of stage T4bN1M0 (p = 0.0125), and the cancer-specific survival curve and all-cause survival curve of patients with stage T1-2N1M1 were not different from those of stage T3N1M0, stage T4aN0M0, stage T4aN1M0, stage T4bN0M0, and stage T1-2N0M1 (all, p > 0.05). The analysis yielded similar results after propensity score matching for other clinicopathological characteristics. Conclusion: Patients aged ?55 years with stage T1-2N1M1 DTC according to the eighth edition AJCC/TNM cancer staging system should be downstaged and those with stage T4bN1M0 upstaged accordingly.

Dataset Information

Computed Tomography Features associated With the Eighth Edition TNM Stage Classification for Thymic Epithelial Tumors.

Publications

Computed Tomography Features associated With the Eighth Edition TNM Stage Classification for Thymic Epithelial Tumors.

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