A positive surgical margin (PSM) following radical prostatectomy (RP) for prostate cancer is associated with increased risk of biochemical recurrence. We sought to examine whether the pathologist is an independent predictor of PSMs.
We performed a retrospective review of 3,557 men who underwent RP for localized prostate cancer at our institution from 2003 to 2015. We evaluated 29 separate pathologists. Univariate and multivariable logistic regression were used to test variables previously shown to influence PSM rates.
Overall rate of PSM was 18.9%. Compared with patients without PSM, patients with PSM had higher body mass index (mean: 28.8 vs. 28.3), Gleason score≥7 (84% vs. 66%), extracapsular extension (51% vs. 20%), and median prostate-specific antigen (5.9 vs. 5.1ng/ml) (all P<0.05). Univariate logistic regression showed that surgeon experience, pathologist experience, and pathologist genitourinary fellowship training were all predictors of PSMs (all P<0.05). Multivariable regression analysis confirmed that decreased surgeon experience, increased pathologist experience, higher pathologic Gleason score, higher pathologic stage, and higher prostate-specific antigen were significant predictors of PSMs. Increasing surgeon experience was associated with decreased odds of PSM (odds ratio = 0.79 per 1 standard deviation increase, 95% CI [0.70-0.89]). In contrast, increasing pathologist experience was associated with increased odds of PSM (odds ratio = 1.11 per 1 standard deviation increase, 95% CI [1.03-1.19]). The relationship between pathologist experience and PSM appeared to be nonlinear (Fig. 2).
Greater pathologist experience appears to be associated with greater odds of PSMs following radical prostatectomy, even after controlling for case mix, pathologist fellowship training, and surgeon experience. Based on these findings, pathologists with less experience reviewing RP specimens may consider requesting rereview by a dedicated genitourinary pathologist.
This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 January 2018.
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