Scientific article

Performance of the McGill Interactive Pediatric OncoGenetic Guidelines for Identifying Cancer Predisposition Syndromes

Published inJAMA oncology, vol. 7, no. 12, p. 1806-1814
Publication date2021-12-01
First online date2021-10-07

Importance: Prompt recognition of a child with a cancer predisposition syndrome (CPS) has implications for cancer management, surveillance, genetic counseling, and cascade testing of relatives. Diagnosis of CPS requires practitioner expertise, access to genetic testing, and test result interpretation. This diagnostic process is not accessible in all institutions worldwide, leading to missed CPS diagnoses. Advances in electronic health technology can facilitate CPS risk assessment.

Objective: To evaluate the diagnostic accuracy of a CPS prediction tool (McGill Interactive Pediatric OncoGenetic Guidelines [MIPOGG]) in identifying children with cancer who have a low or high likelihood of having a CPS.

Design, setting, and participants: In this international, multicenter diagnostic accuracy study, 1071 pediatric (<19 years of age) oncology patients who had a confirmed CPS (12 oncology referral centers) or who underwent germline DNA sequencing through precision medicine programs (6 centers) from January 1, 2000, to July 31, 2020, were studied.

Exposures: Exposures were MIPOGG application in patients with cancer and a confirmed CPS (diagnosed through routine clinical care; n = 413) in phase 1 and MIPOGG application in patients with cancer who underwent germline DNA sequencing (n = 658) in phase 2. Study phases did not overlap. Data analysts were blinded to genetic test results.

Main outcomes and measures: The performance of MIPOGG in CPS recognition was compared with that of routine clinical care, including identifying a CPS earlier than practitioners. The tool's test characteristics were calculated using next-generation germline DNA sequencing as the comparator.

Results: In phase 1, a total of 413 patients with cancer (median age, 3.0 years; range, 0-18 years) and a confirmed CPS were identified. MIPOGG correctly recognized 410 of 412 patients (99.5%) as requiring referral for CPS evaluation at the time of primary cancer diagnosis. Nine patients diagnosed with a CPS by a practitioner after their second malignant tumor were detected by MIPOGG using information available at the time of the first cancer. In phase 2, of 658 children with cancer (median age, 6.6 years; range, 0-18.8 years) who underwent comprehensive germline DNA sequencing, 636 had sufficient information for MIPOGG application. When compared with germline DNA sequencing for CPS detection, the MIPOGG test characteristics for pediatric-onset CPSs were as follows: sensitivity, 90.7%; specificity, 60.5%; positive predictive value, 17.6%; and negative predictive value, 98.6%. Tumor DNA sequencing data confirmed the MIPOGG recommendation for CPS evaluation in 20 of 22 patients with established cancer-CPS associations.

Conclusions and relevance: In this diagnostic study, MIPOGG exhibited a favorable accuracy profile for CPS screening and reduced time to CPS recognition. These findings suggest that MIPOGG implementation could standardize and rationalize recommendations for CPS evaluation in children with cancer.

  • Child
  • Child, Preschool
  • Early Detection of Cancer
  • Genetic Predisposition to Disease
  • Genetic Testing / methods
  • Humans
  • Neoplasms / diagnosis
  • Neoplasms / genetics
  • Syndrome
Citation (ISO format)
GOUDIE, Catherine et al. Performance of the McGill Interactive Pediatric OncoGenetic Guidelines for Identifying Cancer Predisposition Syndromes. In: JAMA oncology, 2021, vol. 7, n° 12, p. 1806–1814. doi: 10.1001/jamaoncol.2021.4536
Main files (1)
Article (Published version)
Secondary files (3)
ISSN of the journal2374-2437

Technical informations

Creation10/03/2022 12:36:51 PM
First validation08/11/2023 6:46:09 AM
Update time08/11/2023 6:46:09 AM
Status update08/11/2023 6:46:09 AM
Last indexation02/01/2024 10:30:50 AM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack