Clinical impact of a rapid genetic testing model for advanced prostate cancer patients Journal Article


Authors: Breen, K. E.; Symecko, H.; Spielman, K.; Gebert, R.; Shah, I. H.; Pundock, S.; Batson, M.; Narayan, V. K.; Stadler, Z. K.; Autio, K. A.; Abida, W.; Danila, D. C.; Scher, H. I.; Morris, M. J.; Hamilton, J. G.; Robson, M. E.; Domchek, S. M.; Carlo, M. I.
Article Title: Clinical impact of a rapid genetic testing model for advanced prostate cancer patients
Abstract: Purpose:Genetic testing may alter clinical management for individuals with metastatic prostate cancer by identifying additional therapies. Traditional counseling models are unlikely to enable time-sensitive therapeutic decision-making. This study aimed to determine the feasibility and clinical impact of an alternative hereditary genetic testing model.Materials and Methods:As part of a multicenter, single-arm prospective trial, individuals with advanced prostate cancer were referred by their oncologist for testing of 14 genes associated with hereditary prostate cancer. Pretest education (brochure and video) was provided in the oncology clinic. Questionnaires assessing participant satisfaction with both pretest education and decision to undergo genetic testing were collected. A genetic counselor contacted participants by phone to obtain family history and discuss results. Medical records were queried to determine whether a change in clinical management was discussed.Results:Of 501 participants consented to germline analysis, 51 (10.2%) had at least 1 pathogenic/likely pathogenic variant. Change in treatment was discussed with 22/48 (45.8%) of eligible participants who tested positive. Feasibility of this model was assessed by participant satisfaction and turnaround time. Average±SD satisfaction with the pretest education (15.5±2.2, 4-20 scale) and with the decision to undergo genetic testing (17.1±2.9, 4-20 scale) were both high. Results were returned 20 days (median) after sample collection.Conclusions:Oncologist-initiated germline genetic testing in collaboration with a genetic counselor is a feasible approach to testing advanced prostate cancer patients with impactful clinical actionability. The testing model and educational material serve as resources to clinicians treating prostate cancer patients. © 2023 Lippincott Williams and Wilkins. All rights reserved.
Keywords: adult; controlled study; human tissue; human cell; major clinical study; genetics; clinical trial; cancer patient; prospective study; prospective studies; counseling; cancer susceptibility; heredity; progression free survival; breast cancer; patient education; patient education as topic; food and drug administration; brca1 protein; brca2 protein; videorecording; protein p53; prostate cancer; gleason score; prostatic neoplasms; questionnaire; feasibility study; immunotherapy; multicenter study; family history; prostate tumor; medical record; satisfaction; nicotinamide adenine dinucleotide adenosine diphosphate ribosyltransferase inhibitor; checkpoint kinase 2; epithelial cell adhesion molecule; genetic screening; protein msh6; health care delivery; resource allocation; mismatch repair protein pms2; genetic testing; delivery of health care; selection bias; genetic counseling; turnaround time; health literacy; telemedicine; oncologist; pretest posttest design; poly(adenosine diphosphate ribose); experimental therapy; humans; human; male; article; hereditary tumor syndrome; mutl protein homolog 1; dna mismatch repair protein msh2; partner and localizer of brca2; patient volume; counselor; familial prostate cancer; german democratic republic
Journal Title: Journal of Urology
Volume: 209
Issue: 5
ISSN: 0022-5347
Publisher: Elsevier Science, Inc.  
Date Published: 2023-05-01
Start Page: 918
End Page: 927
Language: English
DOI: 10.1097/ju.0000000000003186
PUBMED: 36974724
PROVIDER: scopus
PMCID: PMC10081955
DOI/URL:
Notes: Article -- MSK Cancer Center Support Grant (P30 CA008748) acknowledged in PubMed and PDF -- MSK corresponding author in Maria Carlo -- Export Date: 1 May 2023 -- Source: Scopus
Altmetric
Citation Impact
BMJ Impact Analytics
MSK Authors
  1. Michael Morris
    583 Morris
  2. Mark E Robson
    681 Robson
  3. Karen Anne Autio
    120 Autio
  4. Zsofia Kinga Stadler
    393 Stadler
  5. Howard Scher
    1130 Scher
  6. Daniel C Danila
    155 Danila
  7. Wassim Abida
    158 Abida
  8. Maria Isabel Carlo
    165 Carlo
  9. Jada Gabrielle Hamilton
    113 Hamilton
  10. Ibrahim Hussein Shah
    8 Shah
  11. Kelsey E Breen
    18 Breen
  12. Rebecca Gebert
    18 Gebert