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Measuring cancer burden in prostatic needle core biopsies: simplified assessments outperform complex measurements in assessing outcome: evidence to assist pathologist efficiency and minimize datasets.
Berney, Daniel M; Finnegan, Kier; Chu, Kim; Fine, Samson W; Varma, Murali; Cuzick, Jack; Beltran, Luis.
Afiliación
  • Berney DM; Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London, UK.
  • Finnegan K; Department of Cellular Pathology, Barts Health NHS Trust, The Royal London Hospital, London, UK.
  • Chu K; Centre for Prevention, Detection and Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, UK.
  • Fine SW; Centre for Prevention, Detection and Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, UK.
  • Varma M; Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Cuzick J; Department of Cellular Pathology, University Hospital of Wales, Cardiff, WLS, UK.
  • Beltran L; Centre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London, UK.
Histopathology ; 82(7): 1021-1028, 2023 Jun.
Article en En | MEDLINE | ID: mdl-36779238
ABSTRACT

AIMS:

The optimal method of measuring cancer extent in prostate cancer (PCa) biopsies is unknown. METHODS AND

RESULTS:

Nine hundred eighty-one men with clinically localised PCa managed conservatively were reviewed with follow up. The number of positive cores (NPC), the Maximum Cancer Length in a core (MCL), Total Cancer Length (TCL), and percentage of positive cores (%+cores) was calculated and univariate and multivariate analysis performed using prostate-specific antigen (PSA), T-stage, and Gleason score. The presence of stromal gaps (SG) was recorded. Univariate models were run where SG made a difference to the MCL. All variables showed significant association with PCa death in univariate models. In multivariate models, incorporating PSA, T-stage, and Gleason score, only %+cores was a significant predictor of outcome, with a 10% increase in %+cores resulting in a hazard ratio (HR) of 1.07 (likelihood-ratio test P > Χ2  = 0.01). There were 120 patients where SG made a difference to the MCL and a total of 20 events in this group. Including SG, on univariate analysis the median MCL was 10 mm and HR was 1.16 (P = 0.007), not including SG, the median MCL was 6 mm and HR was 1.23 (P = 6.3 × 10-4 ). Inclusion or exclusion of SG made no significant difference to TCL as a predictor of outcome.

CONCLUSION:

Cancer extent is a strong predictor of PCa death but only %+cores added to the multivariate model. Expressed as a fraction of NPC/total number of cores, this is the simplest method of assessment, which we favour over more complicated methods in nontargeted biopsies.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias de la Próstata / Antígeno Prostático Específico Tipo de estudio: Prognostic_studies Límite: Humans / Male Idioma: En Revista: Histopathology Año: 2023 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias de la Próstata / Antígeno Prostático Específico Tipo de estudio: Prognostic_studies Límite: Humans / Male Idioma: En Revista: Histopathology Año: 2023 Tipo del documento: Article País de afiliación: Reino Unido