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Prognosticsignificance of SUVon PET/CT in patientswith esophagealcancer: a systematicreview andmeta-analysis Lingling PanPing GuGang Huang2009 год

Prognostic significance of SUV on PET/CT in patients with esophageal cancer: a systematic review and meta-analysis

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Аннотация: Background and purpose Esophageal cancer is the third most common gastrointestinal malignancy with a poor long-term survival and high mortality. Surgical resection provides the only chance of cure. The tumor-node metastasis stage classification system is a strong prognostic parameter predicting the prognosis. We performed the present meta-analysis to comprehensively review the evidence for use of standardized uptake value (SUV) measured on tumor to predict prognosis of esophageal cancer. Methods We searched for articles published in English or Chinese; limited to esophageal cancer; 18F-fluoro-2-deoxy-glucose (18F-FDG) uptake on positron emission tomography (PET) performed on a dedicated device; dealt with the impact of SUV on survival. We extracted an estimate of the log hazard ratios (HR) and their variances and performed meta-analysis. Results Without the study dealt by the pretreatment SUV measured on metastasis sites, there were seven studies dealt by the prognostic value of SUV measured on FDG-PET for overall survival. The combined HR was 1.86, meaning that high SUV indicated worse survival prognosis; and there were three studies dealt with the prognostic value of SUV measured on FDG-PET for disease-free survival. The combined HR was 2.52, indicating that high SUV was associated with more significantly higher risk for recurrence than low SUV. Conclusion SUV measured in patients with esophageal cancer, reflecting the metabolic activity of tumor and malignancy, could serve as a prognostic factor. Considering that the FDG-PET can add important information of metabolism in detection and staging to conventional imaging modality, we anticipate that SUV could be used in patients with esophageal carcinoma.
Год издания: 2009
Авторы: Lingling Pan, Ping Gu, Gang Huang, Huiping Xue, Shuqi Wu
Издательство: Lippincott Williams & Wilkins
Источник: European Journal of Gastroenterology & Hepatology
Ключевые слова: Esophageal Cancer Research and Treatment, Medical Imaging Techniques and Applications, Radiomics and Machine Learning in Medical Imaging
Другие ссылки: European Journal of Gastroenterology & Hepatology (HTML)
PubMed (HTML)