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Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study.

  • Author(s): Leo, Patrick;
  • Janowczyk, Andrew;
  • Elliott, Robin;
  • Janaki, Nafiseh;
  • Bera, Kaustav;
  • Shiradkar, Rakesh;
  • Farré, Xavier;
  • Fu, Pingfu;
  • El-Fahmawi, Ayah;
  • Shahait, Mohammed;
  • Kim, Jessica;
  • Lee, David;
  • Yamoah, Kosj;
  • Rebbeck, Timothy R;
  • Khani, Francesca;
  • Robinson, Brian D;
  • Eklund, Lauri;
  • Jambor, Ivan;
  • Merisaari, Harri;
  • Ettala, Otto;
  • Taimen, Pekka;
  • Aronen, Hannu J;
  • Boström, Peter J;
  • Tewari, Ashutosh;
  • Magi-Galluzzi, Cristina;
  • Klein, Eric;
  • Purysko, Andrei;
  • Nc Shih, Natalie;
  • Feldman, Michael;
  • Gupta, Sanjay;
  • Lal, Priti;
  • Madabhushi, Anant
  • et al.
Abstract

Existing tools for post-radical prostatectomy (RP) prostate cancer biochemical recurrence (BCR) prognosis rely on human pathologist-derived parameters such as tumor grade, with the resulting inter-reviewer variability. Genomic companion diagnostic tests such as Decipher tend to be tissue destructive, expensive, and not routinely available in most centers. We present a tissue non-destructive method for automated BCR prognosis, termed "Histotyping", that employs computational image analysis of morphologic patterns of prostate tissue from a single, routinely acquired hematoxylin and eosin slide. Patients from two institutions (n = 214) were used to train Histotyping for identifying high-risk patients based on six features of glandular morphology extracted from RP specimens. Histotyping was validated for post-RP BCR prognosis on a separate set of n = 675 patients from five institutions and compared against Decipher on n = 167 patients. Histotyping was prognostic of BCR in the validation set (p < 0.001, univariable hazard ratio [HR] = 2.83, 95% confidence interval [CI]: 2.03-3.93, concordance index [c-index] = 0.68, median years-to-BCR: 1.7). Histotyping was also prognostic in clinically stratified subsets, such as patients with Gleason grade group 3 (HR = 4.09) and negative surgical margins (HR = 3.26). Histotyping was prognostic independent of grade group, margin status, pathological stage, and preoperative prostate-specific antigen (PSA) (multivariable p < 0.001, HR = 2.09, 95% CI: 1.40-3.10, n = 648). The combination of Histotyping, grade group, and preoperative PSA outperformed Decipher (c-index = 0.75 vs. 0.70, n = 167). These results suggest that a prognostic classifier for prostate cancer based on digital images could serve as an alternative or complement to molecular-based companion diagnostic tests.

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