Αρχειοθήκη ιστολογίου

Τρίτη 26 Σεπτεμβρίου 2017

Quantitative Clinical Staging for Patients With Malignant Pleural Mesothelioma

Abstract
Background
Analysis of the International Association for the Study of Lung Cancer (IASLC) Malignant Pleural Mesothelioma (MPM) database revealed that clinical (cTNM) staging minimally stratified survival and was discrepant with pathological (pTNM) staging. To improve prognostic classification of MPM, alternative staging models based on quantitative parameters were explored.
Methods
An institutional review board–approved MPM registry was queried to identify patients with available pathological and preoperative imaging data. Qualifying patients were randomly assigned to training and test sets in a 1:2 ratio. Computed cTNM and pTNM staging (AJCC Cancer Staging Manual, 7th ed.) were compared. Quantitative image analysis included tumor volume assessed from three-dimensional reconstruction of computed tomography scans (VolCT) and maximal fissural thickness (Fmax). Survival was estimated using the Kaplan-Meier method, and the relationship with VolCT was examined by Cox regression analysis to identify optimized cut-points. Performance of cTNM and quantitative models derived was compared in the test set using Harrell's C index.
Results
A total of 472 patients met inclusion criteria. TNM staging was concordant with pathological TNM staging in 171 of 472 (36.2%), understaged in 209 (44.2%), and overstaged in 92 (19.4%) patients. The most concordant feature was involvement of interlobar fissures. A quantitative clinical staging model comprising VolCT and Fmax (c-index = 0.638, 95% confidence interval [CI] = 0.603 to 0.673) performed statistically significantly better as a prognostic classifier when compared in the test set with cTNM (c-index = 0.562, 95% CI = 0.525 to 0.599, P = .001).
Conclusions
Improved prognostic performance may be achievable by quantitative clinical staging combining VolCT and Fmax, providing a cost-effective and clinically relevant surrogate for clinical TNM stage.

from #ORL-AlexandrosSfakianakis via ola Kala on Inoreader http://ift.tt/2wiw0o5

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