Real-world outcomes of an automated physician support system for genome-driven oncology Journal Article


Authors: Tao, J. J.; Eubank, M. H.; Schram, A. M.; Cangemi, N.; Pamer, E.; Rosen, E. Y.; Schultz, N.; Chakravarty, D.; Philip, J.; Hechtman, J. F.; Harding, J. J.; Smyth, L. M.; Jhaveri, K. L.; Drilon, A.; Ladanyi, M.; Solit, D. B.; Zehir, A.; Berger, M. F.; Stetson, P. D.; Gardos, S. M.; Hyman, D. M.
Article Title: Real-world outcomes of an automated physician support system for genome-driven oncology
Abstract: PURPOSE Matching patients to investigational therapies requires new tools to support physician decision making. We designed and implemented Precision Insight Support Engine (PRECISE), an automated, just-in-time, clinical-grade informatics platform to identify and dynamically track patients on the basis of molecular and clinical criteria. Real-world use of this tool was analyzed to determine whether PRECISE facilitated enrollment to early-phase, genome-driven trials. MATERIALS AND METHODS We analyzed patients who were enrolled in genome-driven, early-phase trials using PRECISE at Memorial Sloan Kettering Cancer Center between April 2014 and January 2018. Primary end point was the proportion of enrolled patients who were successfully identified using PRECISE before enrollment. Secondary end points included time from sequencing and PRECISE identification to enrollment. Reasons for a failure to identify genomically matched patients were also explored. RESULTS Data were analyzed from 41 therapeutic trials led by 19 principal investigators. In total, 755 patients were accrued to these studies during the period that PRECISE was used. PRECISE successfully identified 327 patients (43%) before enrollment. Patients were diagnosed with 29 tumor types and harbored alterations in 43 oncogenes, most commonly ERBB2 (21.3%), PIK3CA (14.1%), and BRAF (8.7%). Median time from sequencing to enrollment was 163 days (interquartile range, 66 to 357 days), and from PRECISE identification to enrollment 87 days (interquartile range, 37 to 180 days). Common reasons for failing to identify patients before enrollment included accrual on the basis of molecular alterations that did not match pre-established PRECISE genomic eligibility (140 [33%] of 428) and external sequencing not available for parsing (127 [30%] of 428). CONCLUSION PRECISE identified 43% of all patients accrued to a diverse cohort of early-phase, genome-matched studies. Purpose-built informatics platforms represent a novel and potentially effective method for matching patients to molecularly selected studies. © 2019 by American Society of Clinical Oncology
Keywords: adolescent; adult; aged; major clinical study; gene deletion; missense mutation; cancer patient; gene amplification; epidermal growth factor receptor 2; oncology; automation; oncogene; cancer center; physician; genome; b raf kinase; nonsense mutation; indel mutation; phosphatidylinositol 4,5 bisphosphate 3 kinase; human; male; female; priority journal; article; clinical decision support system
Journal Title: JCO Precision Oncology
Volume: 3
ISSN: 2473-4284
Publisher: American Society of Clinical Oncology  
Date Published: 2019-01-01
Language: English
DOI: 10.1200/po.19.00066
PROVIDER: scopus
PMCID: PMC7446398
PUBMED: 32914018
DOI/URL:
Notes: Article -- Source: Scopus
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MSK Authors
  1. David Solit
    781 Solit
  2. James Joseph Harding
    252 Harding
  3. Marc Ladanyi
    1332 Ladanyi
  4. David Hyman
    354 Hyman
  5. Komal Lachhman Jhaveri
    217 Jhaveri
  6. Ahmet Zehir
    345 Zehir
  7. Michael Forman Berger
    769 Berger
  8. Alexander Edward Drilon
    636 Drilon
  9. Nikolaus D Schultz
    491 Schultz
  10. Alison Michele Schram
    125 Schram
  11. John Philip
    49 Philip
  12. Stuart M Gardos
    21 Gardos
  13. Jaclyn Frances Hechtman
    212 Hechtman
  14. Lillian   Smyth
    42 Smyth
  15. Nicholas A Cangemi
    10 Cangemi
  16. Peter D Stetson
    52 Stetson
  17. Erika   Pamer
    10 Pamer
  18. Michael   Eubank
    5 Eubank
  19. Jessica Jing Tao
    11 Tao
  20. Ezra Y Rosen
    49 Rosen