A1 Refereed original research article in a scientific journal
Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study
Authors: 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, Shih Natalie NC, Feldman Michael, Gupta Sanjay, Lal Priti, Madabhushi Anant
Publisher: NATURE RESEARCH
Publication year: 2021
Journal: npj Precision Oncology
Journal name in source: NPJ PRECISION ONCOLOGY
Journal acronym: NPJ PRECIS ONCOL
Article number: ARTN 35
Volume: 5
Issue: 1
Number of pages: 11
eISSN: 2397-768X
DOI: https://doi.org/10.1038/s41698-021-00174-3
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/59144027
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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