Proposal for an optimised definition of adverse pathology (unfavourable histology) that predicts metastatic risk in prostatic adenocarcinoma independent of grade group and pathological stage

Jane K Nguyen ¹, Lara R Harik ², Eric A Klein ³

¹Robert J. Tomsich Institute of Pathology and Laboratory Medicine, Cleveland Clinic, Cleveland, OH, USA.
²Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA.
³Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH, USA.
⁴Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.
⁵Department of Pathology, University of Florida Health, Jacksonville, FL, USA.
⁶Department of Pathology, University of California San Francisco, San Francisco, CA, USA.
⁷Canary Foundation, Palo Alto, CA, USA.
⁸Fred Hutchinson Cancer Center, Seattle, WA, USA.
⁹Department of Urology, University of Washington Medical Center, Seattle, WA, USA.
¹⁰Department of Urology, University of California San Francisco, San Francisco, CA, USA.
¹¹Department of Urology, Emory University School of Medicine, Atlanta, GA, USA.
¹²Department of Medicine, University of Washington Medical Center, Seattle, WA, USA.
¹³Department of Laboratory Medicine and Pathology, University of Washington Medical Center, Seattle, WA, USA.
¹⁴Department of Pathology, Eastern Virginia Medical School, Norfolk, VA, USA.
¹⁵Department of Urology, Stanford University Medical Center, Stanford, CA, USA.

⁰Robert J. Tomsich Institute of Pathology and Laboratory Medicine, Cleveland Clinic, Cleveland, OH, USA.

Histopathology +

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June 3, 2024

View abstract on PubMed

Summary

A new histological grading model for prostate cancer, termed "unfavourable histology," accurately predicts metastatic potential and improves upon existing grading systems. This simplified model enhances communication and implementation for better patient outcomes.

Area Of Science

Oncology
Pathology
Urology

Background

Current prostate cancer histological grading systems require optimization for accurate metastatic potential prediction.
Large cribriform and intraductal carcinoma are key indicators of aggressive disease but not fully integrated into grading.

Purpose Of The Study

To develop and validate a simplified histological grading model for prostate cancer.
To enhance sensitivity in predicting the metastatic potential of prostate cancer.

Main Methods

Re-review of prostatectomy specimens from two cohorts (n=419 and n=209) to identify "unfavourable histology" patterns.
Kaplan-Meier analysis and multivariable Cox proportional hazards models were used to assess predictive accuracy.
Unfavourable histology was evaluated for its impact on biochemical recurrence, metastasis, and death, and its integration into the MSKCC nomogram.

Main Results

Unfavourable histology demonstrated high sensitivity and specificity for predicting biochemical recurrence (93%/88%), metastasis (100%/48%), and death (100%/46%) at 15 years.
Grade group 2 prostate cancers with unfavourable histology showed independent metastatic risk.
The inclusion of unfavourable histology significantly improved the discriminatory power of the MSKCC post-prostatectomy nomogram for biochemical failure (P < 0.001).

Conclusions

Unfavourable histology is a robust predictor of metastatic risk in prostate cancer, outperforming current grading and staging systems.
This simplified dichotomous model effectively stratifies Grade group 2 prostate cancers by metastatic potential, independent of pathological stage.
Incorporating specific architectural patterns beyond large cribriform/intraductal carcinoma enhances predictive sensitivity, improving clinical communication and implementation.

Keywords:

Gleason adenocarcinoma cribriform grade prostate