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  • Title: Bone marrow hypermetabolism on 18F-FDG PET as a survival prognostic factor in non-small cell lung cancer.
    Author: Prévost S, Boucher L, Larivée P, Boileau R, Bénard F.
    Journal: J Nucl Med; 2006 Apr; 47(4):559-65. PubMed ID: 16595487.
    Abstract:
    UNLABELLED: PET is now widely used in the diagnosis and staging of lung cancer with (18)F-FDG. The purpose of the study was to evaluate the prognostic value of diffuse bone marrow hypermetabolism along with other PET prognostic factors with respect to survival and compare them with other established prognostic factors in a large cohort of patients. METHODS: Of 255 patients referred for evaluation of a suspicious lung lesion by PET over an 8-mo period (May 1999 to January 2000), the outcome of 120 patients with a final diagnosis of primary non-small cell lung cancer was analyzed retrospectively after excluding subjects with benign, metastatic, or recurrent lesions, using the available follow-up information and a provincial mortality database. Kaplan-Meier survival curves were compared using the mean and the maximal tumor standardized uptake value (SUV), bone marrow SUV, PET stage, various laboratory parameters, sex, age, conventional imaging stage, and pathologic stage. A stepwise Cox proportional hazard model was built using the significant variables on univariate analysis. RESULTS: The primary tumor SUV (>10), bone marrow uptake of (18)F-FDG, (18)F-FDG PET stage, pathologic stage, hypercalcemia, lactate dehydrogenase, hemoglobin, albumin, thrombocytopenia, thrombocytosis, and leukocytosis were predictors of mortality on univariate analysis. On multivariate analysis, bone marrow hypermetabolism, (18)F-FDG PET nodal stage, and some hematologic parameters (hemoglobin, platelets, white blood cell counts) remained significant independent predictors of mortality. CONCLUSION: Bone marrow hypermetabolism and the PET nodal stage were strong independent predictors of mortality in patients with lung cancer. The primary tumor SUV, though predictive on univariate analysis, was not an independent predictor of mortality in our model.
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