Potential impact of 18F-FDG PET/CT on patients selection for neoadjuvant chemotherapy before radical cystectomy.

BACKGROUND: The detection of lymph node metastases in bladder cancer has a major impact on treatment decisions and patients prognosis. Due to limited value of conventional imaging, the place of molecular and functional imaging needs to be precised, particularly in the neoadjuvant setting. METHODS: From June 2011 to June 2013, 102 patients with clinically localized BCa were simultaneously staged with (18)F-FDG PET/CT before RC. This study assessed the diagnostic accuracy of (18)F-FDG PET/CT for the detection of metastases in normal-sized lymph nodes using extended pelvic lymph node dissection and histopathology as the reference standard. RESULTS: A total of 1211 LNs were examined histopathologically. Sixty-seven (5.5%) metastatic nodes were found in 26/102 patients (25.5%). Lymph node density was 22%. On patient-based analysis, sensitivity, specificity, predictive positive value (PPV), negative positive value (NPV) and accuracy for (18)F-FDG PET/CT were calculated as 50%, 96.2%, 80%, 86.2% and 85.3% respectively. On a field-based analysis, sensitivity, specificity, PPV, NPV and accuracy for (18)F-FDG PET/CT were calculated as 50.0%, 99.0%, 71.9%, 97.4%, and 96.5% respectively. The majority of missed metastases were micrometastasis <5 mm in long axis diameter. CONCLUSIONS: (18)F-FDG PET/CT improves diagnostic efficacy for lymph node staging in patients staged N0 with conventional cross-sectional imaging. (18)F-FDG PET/CT could be used as a surrogate marker for detection of metastases in non-enlarged pelvic lymph nodes and enhances management strategy guiding patients selection for neoadjuvant chemotherapy.

[Prognostic factors in renal cell carcinoma]. / Les facteurs pronostiques du cancer du rein.

Identification of prognostic factors in renal cell carcinoma is very important today for three goals: providing patient information, giving appropriate treatments and selecting patients for adapted treatment schedules as well as new clinical trials. Prognostic factors in RCC include: anatomical (TNM classification), histological (Fuhrmann grade and histological subtype), clinical (symptoms and performance status) and molecular factors. For improving predicative accuracy of prognostic systems such as the TNM classification, new prognostic algorithms or nomograms have been designed combining independent prognostic variables. UISS and SSIGN are the 2 most effective prognostic systems within localized RCC. In metastatic disease, the two main systems that have been used for predicting response to immunotherapy are the model of the French Group of Immunotherapy and the Motzer model. With the arrivals of new molecular factors, these systems will perhaps have to evaluate: these new systems will require further validation as part of large prospective clinical trials.