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Int J Cancer. 2020 Feb 15;146(4):1010-1017. doi: 10.1002/ijc.32561. Epub 2019 Jul 30.

An eHealth decision-support tool to prioritize referral practices for genetic evaluation of patients with Wilms tumor.

Author information

1
Division of Hematology-Oncology, The Hospital for Sick Children, Department of Pediatrics, University of Toronto, Toronto, ON, Canada.
2
Division of Hematology-Oncology, Montreal Children's Hospital, Department of Pediatrics, McGill University, Montreal, QC, Canada.
3
Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.
4
Research Institute of the McGill University Health Centre, Child Health and Human Development, McGill University, Montreal, QC, Canada.
5
Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Department of Pediatrics, University of Toronto, Toronto, ON, Canada.
6
Division of Biostatistics, Design and Analysis, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada.
7
Department of Human Genetics, Research Institute of the McGill University Health Centre and Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, QC, Canada.

Abstract

Over 10% of children with Wilms tumor (WT) have an underlying cancer predisposition syndrome (CPS). Cognizant of increasing demand for genetic evaluation and limited resources across health care settings, there is an urgent need to rationalize genetic referrals for this population. The McGill Interactive Pediatric OncoGenetic Guidelines study, a Canadian multi-institutional initiative, aims to develop an eHealth tool to assist physicians in identifying children at elevated risk of having a CPS. As part of this project, a decisional algorithm specific to WT consisting of five tumor-specific criteria (age <2 years, bilaterality/multifocality, stromal-predominant histology, nephrogenic rests, and overgrowth features) and universal criteria including features of family history suspicious for CPS and congenital anomalies, was developed. Application of the algorithm generates a binary recommendation-for or against genetic referral for CPS evaluation. To evaluate the algorithm's sensitivity for CPS identification, we retrospectively applied the tool in consecutive pediatric patients (n = 180) with WT, diagnosed and/or treated at The Hospital for Sick Children (1997-2016). Odds ratios were calculated to evaluate the strengths of associations between each criterion and specific CPS subtypes. Application of the algorithm identified 100% of children with WT and a confirmed CPS (n = 27). Age <2 years, bilaterality/multifocality, and congenital anomalies were strongly associated with pathogenic variants in WT1. Presence of >1 overgrowth feature was strongly associated with Beckwith-Wiedemann syndrome. Stromal-predominant histology did not contribute to CPS identification. We recommend the incorporation of the WT algorithm in the routine assessment of children with WT to facilitate prioritization of genetic referrals in a sustainable manner.

KEYWORDS:

Wilms tumor; cancer genetics; cancer predisposition syndrome; decision-support tool; pediatric oncology

PMID:
31286500
DOI:
10.1002/ijc.32561

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