Risk Stratification Model for Resected Squamous-Cell Lung Cancer Patients According to Clinical and Pathological Factors
| Autor: | Sabrina Vari, Luisa Carbognin, Felice Mucilli, Antonio Marchetti, Matteo Brunelli, Tiziana Vavalà, Francesco Puma, Lucio Crinò, Francesco Facciolo, Stefania Kinspergher, Silvia Novello, Emiolio Bria, Isabella Sperduti, Giovanni Leuzzi, Antonio Santo, Umberto Peretti, Sara Pilotto, Marco Chilosi, Aldo Scarpa, Giampaolo Tortora, Michele Milella |
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| Rok vydání: | 2015 |
| Předmět: |
Oncology
Male Pulmonary and Respiratory Medicine medicine.medical_specialty Multivariate statistics Multivariate analysis Squamous lung cancer Prognosis Prognostic model clinicopathological predictors Clinicopathological predictors Prognosis Prognostic model Squamous lung cancer Aged Carcinoma Non-Small-Cell Lung Carcinoma Squamous Cell Female Humans Risk Factors Survival Analysis Medicine (all) Internal medicine Medicine Non-Small-Cell Lung Lung cancer Grading (tumors) Pathological Survival analysis Clinical pathology business.industry Proportional hazards model Carcinoma medicine.disease Surgery Squamous Cell business |
| Zdroj: | Journal of Thoracic Oncology. 10(9):1341-1348 |
| ISSN: | 1556-0864 |
| DOI: | 10.1097/jto.0000000000000628 |
| Popis: | The aim of this analysis (AIRC-MFAG project no. 14282) was to define a risk classification for resected squamous-cell lung cancer based on the combination of clinicopathological predictors to provide a practical tool to evaluate patients' prognosis.Clinicopathological data were retrospectively correlated to disease-free/cancer-specific/overall survival (DFS/CSS/OS) using a Cox model. Individual patient probability was estimated by logistic equation. A continuous score to identify risk classes was derived according to model ratios and dichotomized according to prognosis with receiver operating characteristic analysis.Data from 573 patients from five institutions were gathered. Four hundred ninety-four patients were evaluable for clinical analysis (median age: 68 years; male/female: 403/91; T-descriptor according to TNM 7th edition 1-2/3-4: 330/164; nodes 0/0: 339/155; stages I and II/III and IV: 357/137). At multivariate analysis, age, T-descriptor according to TNM 7th edition, nodes, and grading were independent predictors for DFS and OS; the same factors, except age and grading, predicted CSS. Multivariate model predict individual patient probability with high prognostic accuracy (0.67 for DFS). On the basis of receiver operating characteristic-derived cutoff, a two-class model significantly differentiated low-risk and high-risk patients for 3-year DFS (64.6% and 32.4%, p0.0001), CSS (84.4% and 44.5%, p0.0001), and OS (77.3% and 38.8%, p0.0001). A three-class model separated low-risk, intermediate-risk, and high-risk patients for 3-year DFS (64.6%, 39.8%, and 21.8%, p0.0001), CSS (84.4%, 55.4%, and 30.9%, p0.0001), and OS (77.3%, 47.9%, and 27.2%, p0.0001).A risk stratification model including often adopted clinicopathological parameters accurately separates resected squamous-cell lung cancer patients into different risk classes. The project is currently ongoing to integrate the clinicopathological model with investigational molecular predictors. |
| Databáze: | OpenAIRE |
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