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    Grade Group accuracy is improved by extensive prostate biopsy sampling, but unrelated to prostatectomy specimen sampling or use of immunohistochemistry

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    Assessing the accurate Grade Group of a prostate needle biopsy specimen is essential for choosing the adequate therapeutic modality for prostate cancer patients. However, it is well-known that biopsy Grade Group tends to up- or downgrade significantly at radical prostatectomy. We aimed to investigate the correlation between accuracy and biopsy core number, performed immunohistochemical staining (IHC) or prostatectomy specimen sampling, with the latest also being correlated with higher detection rates of adverse pathological features, e.g., positive surgical margins, higher pathological stage or presence of perineural invasion (PnI status). The study cohort consisted of 315 consecutive patients diagnosed with prostate adenocarcinoma via transrectal ultrasound-guided needle biopsy who later underwent radical prostatectomy. We grouped and compared patients based on Grade Group accuracy, presence of IHC on biopsy, margin status, pathological stage, and PnI status. Inter-observer reproducibility was also calculated. Statistical analyzes included ANOVA, Tukey’s multiple comparisons post hoc test, Chi-squared test, and Fleiss kappa statistics. Undergraded cases harboured a significantly lower number of biopsy cores (p < 0.05), than accurately graded cases. Using IHC did not affect grading accuracy significantly, nor did the number of slides from prostatectomy specimens. The mean number of slides was virtually identical when margin status, pathological stage and PnI status of prostatectomy specimens were compared. Inter-observer reproducibility at our institute was calculated as fair (overall kappa = 0.29). Grade Group accuracy is significantly improved by obtaining more cores at biopsy but is unrelated to performed IHC. The extent of sampling prostatectomy specimens, however, did not affect accuracy and failed to significantly improve detection of adverse pathological features
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