Grading of prostatic adenocarcinoma: Current state and prognostic implications

Jennifer Gordetsky, Jonathan Epstein

Research output: Contribution to journalReview articlepeer-review


Background: Despite significant changes in the clinical and histologic diagnosis of prostate cancer, the Gleason grading system remains one of the most powerful prognostic predictors in prostate cancer. The correct diagnosis and grading of prostate cancer is crucial for a patient's prognosis and therapeutic options. However, this system has undergone significant revisions and continues to have deficiencies that can potentially impact patient care. Main Body: We describe the current state of grading prostate cancer, focusing on the current guidelines for the Gleason grading system and recent changes from the 2014 International Society of Urological Pathology Consensus Conference on Gleason Grading of Prostatic Carcinoma. We also explore the limitations of the current Gleason grading system and present a validated alternative to the Gleason score. The new grading system initially described in 2013 in a study from Johns Hopkins Hospital and then validated in a multi-institutional study, includes five distinct Grade Groups based on the modified Gleason score groups. Grade Group 1 = Gleason score ≤6, Grade Group 2 = Gleason score 3 + 4 = 7, Grade Group 3 = Gleason score 4 + 3 = 7, Grade Group 4 = Gleason score 8, Grade Group 5 = Gleason scores 9 and 10. Conclusion: As this new grading system is simpler and more accurately reflects prostate cancer biology, it is recommended by the World Health Organization (WHO) to be used in conjunction with Gleason grading.

Original languageEnglish (US)
Article number25
JournalDiagnostic Pathology
Issue number1
StatePublished - Mar 9 2016


  • Grading
  • Prognosis
  • Prostate cancer

ASJC Scopus subject areas

  • Pathology and Forensic Medicine
  • Histology

Fingerprint Dive into the research topics of 'Grading of prostatic adenocarcinoma: Current state and prognostic implications'. Together they form a unique fingerprint.

Cite this