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1.
J Urol ; 172(6 Pt 1): 2177-81, 2004 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-15538226

RESUMO

PURPOSE: Upper tract transitional cell carcinoma (UTTCC) is a relatively rare tumor. Overall 5-year disease specific survival is in the range of 16.5% to 95% depending on stage. In this study we evaluated predictors associated with disease recurrence and disease specific survival. MATERIALS AND METHODS: We report on 129 patients with a median age of 68 years who underwent nephroureterectomy for UTTCC between July 1989 and June 2002. A total of 67 patients had primary UTTCC and 62 had previous (52) or synchronous (10) transitional cell carcinoma of the bladder (BTCC). Medical records were reviewed and analyzed for possible prognostic predictors (primary tumor stage, grade, multifocality, carcinoma in situ, symptoms and signs at presentation, sex, and history of smoking). Disease specific survival and freedom from bladder recurrence were assessed with the Kaplan-Meier method, and differences between the groups were compared using the log rank test. The Cox proportional hazards regression model was used to assess the significance of each predictor. RESULTS: Disease specific death was reported for 44 patients. In a multivariate analysis using previous BTCC as a predictor (categorized as superficial, invasive or none), primary disease stage and history of BTCC were associated with disease specific survival (p = 0.001 and p = 0.018). History of BTCC grouped the patients into distinct populations in terms of disease specific survival and freedom from bladder recurrence. CONCLUSIONS: This study demonstrates that a history of BTCC (invasive or superficial) has an adverse effect on the prognosis of patients diagnosed with UTTCC independent of primary tumor stage.


Assuntos
Carcinoma de Células de Transição/mortalidade , Neoplasias Renais/mortalidade , Recidiva Local de Neoplasia/mortalidade , Neoplasias Primárias Múltiplas/mortalidade , Neoplasias Ureterais/mortalidade , Neoplasias da Bexiga Urinária/mortalidade , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Invasividade Neoplásica , Prognóstico , Taxa de Sobrevida
2.
J Urol ; 168(6): 2422-5, 2002 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-12441931

RESUMO

PURPOSE: We explored the clinical usefulness of spectrum analysis and neural networks for classifying prostate tissue and identifying prostate cancer in patients undergoing transrectal ultrasound for diagnostic or therapeutic reasons. MATERIALS AND METHODS: Data on a cohort of 215 patients who underwent transrectal ultrasound guided prostate biopsies at Memorial-Sloan Kettering Cancer Center, New York, New York were included in this study. Radio frequency data necessary for 2 and 3-dimensional (D) computer reconstruction of the prostate were digitally recorded at transrectal ultrasound and prostate biopsy. The data were spectrally processed and 2-D tissue typing images were generated based on a pre-trained neural network classification. We used manually masked 2-D tissue images as building blocks for generating 3-D tissue images and the images were tissue type color coded using custom software. Radio frequency data on the study cohort were analyzed for cancer probability using the data set pre-trained by neural network methods and compared with conventional B-mode imaging. ROC curves were generated for the 2 methods using biopsy results as the gold standard. RESULTS: The mean area under the ROC curve plus or minus SEM for detecting prostate cancer for the conventional B-mode and neural network methods was 0.66 +/- 0.03 and 0.80 +/- 0.05, respectively. Sensitivity and specificity for detecting prostate cancer by the neural network method were significantly increased compared with conventional B-mode imaging. In addition, the 2 and 3-D prostate images provided excellent visual identification of areas with a higher likelihood of cancer. CONCLUSIONS: Spectrum analysis could significantly improve the detection and evaluation of prostate cancer. Routine real-time application of spectrum analysis may significantly decrease the number of false-negative biopsies and improve the detection of prostate cancer at transrectal ultrasound guided prostate biopsy. It may also provide improved identification of prostate cancer foci during therapeutic intervention, such as brachytherapy, external beam radiotherapy or cryotherapy. In addition, 2 and 3-D images with prostate cancer foci specifically identified can help surgical planning and may in the distant future be an additional reliable noninvasive method of selecting patients for prostate biopsy.


Assuntos
Imageamento Tridimensional , Neoplasias da Próstata/diagnóstico por imagem , Área Sob a Curva , Biópsia por Agulha , Humanos , Masculino , Redes Neurais de Computação , Antígeno Prostático Específico/sangue , Neoplasias da Próstata/diagnóstico , Neoplasias da Próstata/patologia , Curva ROC , Sensibilidade e Especificidade , Análise Espectral , Ultrassonografia de Intervenção
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