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Eur J Cardiothorac Surg ; 34(3): 473-7; discussion 477-8, 2008 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-18667324

RESUMO

OBJECTIVE: Bronchial typical carcinoid tumors are low-grade malignancies. However, metastases are diagnosed in some patients. Predicting the individual risk of these metastases to determine patients eligible for a radical lymphadenectomy and patients to be followed-up because of distant metastasis risk is relevant. Our objective was to screen for predictive criteria of bronchial typical carcinoid tumor aggressiveness based on a logistic regression model using clinical, pathological and biomolecular data. METHODS: A multicenter retrospective cohort study, including 330 consecutive patients operated on for bronchial typical carcinoid tumors and followed-up during a period more than 10 years in two university hospitals was performed. Selected data to predict the individual risk for both nodal and distant metastasis were: age, gender, TNM staging, tumor diameter and location (central/peripheral), tumor immunostaining index of p53 and Ki67, Bcl2 and the extracellular density of neoformed microvessels and of collagen/elastic extracellular fibers. RESULTS: Nodal and distant metastasis incidence was 11% and 5%, respectively. Univariate analysis identified all the studied biomarkers as related to nodal metastasis. Multivariate analysis identified a predictive variable for nodal metastasis: neo angiogenesis, quantified by the neoformed pathological microvessels density. Distant metastasis was related to male gender. DISCUSSION: Predictive models based on clinical and biomolecular data could be used to predict individual risk for metastasis. Patients under a high individual risk for lymph node metastasis should be considered as candidates to mediastinal lymphadenectomy. Those under a high risk of distant metastasis should be followed-up as having an aggressive disease. CONCLUSION: Individual risk prediction of bronchial typical carcinoid tumor metastasis for patients operated on can be calculated in function of biomolecular data. Prediction models can detect high-risk patients and help surgeons to identify patients requiring radical lymphadenectomy and help oncologists to identify those as having an aggressive disease requiring prolonged follow-up.


Assuntos
Neoplasias Brônquicas/patologia , Tumor Carcinoide/secundário , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Biomarcadores Tumorais/metabolismo , Neoplasias Brônquicas/irrigação sanguínea , Tumor Carcinoide/irrigação sanguínea , Tumor Carcinoide/patologia , Criança , Pré-Escolar , Métodos Epidemiológicos , Feminino , Humanos , Lactente , Metástase Linfática , Masculino , Pessoa de Meia-Idade , Estadiamento de Neoplasias , Neovascularização Patológica , Prognóstico , Fatores Sexuais , Adulto Jovem
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