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Br J Cancer ; 119(12): 1552-1556, 2018 12.
Artigo em Inglês | MEDLINE | ID: mdl-30425350

RESUMO

BACKGROUND: The National Comprehensive Cancer Network (NCCN) guidelines provide recommendations for staging of prostate cancer patients in the objective regarding presence of locoregional lymph node metastases (LNM) and bone metastases. We tested the performance characteristics of these recommendations in a community setting. METHODS: Within the Surveillance, Epidemiology, and End Results database (2004-2014), we identified patients with available Gleason, clinical stage and prostatic specific antigen. Performance characteristics endpoints consisted of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NVP), overall accuracy and the number needed to image (NNI). RESULTS: Totally, 191,308 patients were assessable for the validation of the LNM staging recommendations. Sensitivity ranged from 80.6 to 86.3%, specificity from 74.7 to 79.3%, PPV from 7.8 to 8.0%, overall accuracy from 75.0 to 79.3% and NPV was 99.5%. The respective NNI values were 12.5 and 12.8. 197,408 patients were assessable for the validation of bone scan recommendations. These recommendations resulted in 90.8% sensitivity, 76.3% specificity, PPV of 5.7%, NPV of 99.8% and overall accuracy of 76.5%. The NNI was 17.5. CONCLUSION: The NCCN recommendations for locoregional LNM miss few patients with clinical LNM (0.3-0.4%) and provide a virtually perfect NPV of 99.5%. Also, the recommendations for bone scan miss a marginal number of patients with established bone metastases (0.14%) and yield a virtually perfect NPV of 99.8%.


Assuntos
Neoplasias Ósseas/secundário , Osso e Ossos/diagnóstico por imagem , Linfonodos/diagnóstico por imagem , Guias de Prática Clínica como Assunto , Neoplasias da Próstata/patologia , Idoso , Neoplasias Ósseas/diagnóstico por imagem , Humanos , Metástase Linfática , Masculino , Pessoa de Meia-Idade , Estadiamento de Neoplasias , Valor Preditivo dos Testes , Neoplasias da Próstata/diagnóstico por imagem , Programa de SEER
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