Literature DB >> 31286500

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

Noelle Cullinan1, Anita Villani1, Stephanie Mourad2, Gino R Somers3, Lara Reichman4, Kalene van Engelen5, Derek Stephens6, Rosanna Weksberg5, William D Foulkes7, David Malkin1, Ronald Grant1, Catherine Goudie2.   

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.
© 2019 UICC.

Entities:  

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

Mesh:

Substances:

Year:  2019        PMID: 31286500     DOI: 10.1002/ijc.32561

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


  5 in total

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

Authors:  Catherine Goudie; Leora Witkowski; Noelle Cullinan; Lara Reichman; Ian Schiller; Melissa Tachdjian; Linlea Armstrong; Katherine A Blood; Josée Brossard; Ledia Brunga; Chantel Cacciotti; Kimberly Caswell; Sonia Cellot; Mary Egan Clark; Catherine Clinton; Hallie Coltin; Kathleen Felton; Conrad V Fernandez; Adam J Fleming; Noemi Fuentes-Bolanos; Paul Gibson; Ronald Grant; Rawan Hammad; Lynn W Harrison; Meredith S Irwin; Donna L Johnston; Sarah Kane; Lucie Lafay-Cousin; Irene Lara-Corrales; Valerie Larouche; Natalie Mathews; M Stephen Meyn; Orli Michaeli; Renée Perrier; Meghan Pike; Angela Punnett; Vijay Ramaswamy; Jemma Say; Gino Somers; Uri Tabori; My Linh Thibodeau; Annie-Kim Toupin; Katherine M Tucker; Kalene van Engelen; Stephanie Vairy; Nicolas Waespe; Meera Warby; Jonathan D Wasserman; James A Whitlock; Daniel Sinnett; Nada Jabado; Paul C Nathan; Adam Shlien; Junne Kamihara; Rebecca J Deyell; David S Ziegler; Kim E Nichols; Nandini Dendukuri; David Malkin; Anita Villani; William D Foulkes
Journal:  JAMA Oncol       Date:  2021-12-01       Impact factor: 33.006

2.  Prevalence of (Epi)genetic Predisposing Factors in a 5-Year Unselected National Wilms Tumor Cohort: A Comprehensive Clinical and Genomic Characterization.

Authors:  Janna A Hol; Roland P Kuiper; Freerk van Dijk; Esmé Waanders; Sophie E van Peer; Marco J Koudijs; Reno Bladergroen; Simon V van Reijmersdal; Lionel M Morgado; Jet Bliek; Maria Paola Lombardi; Saskia Hopman; Jarno Drost; Ronald R de Krijger; Marry M van den Heuvel-Eibrink; Marjolijn C J Jongmans
Journal:  J Clin Oncol       Date:  2022-03-01       Impact factor: 50.717

Review 3.  Diagnostic Strategies and Algorithms for Investigating Cancer Predisposition Syndromes in Children Presenting with Malignancy.

Authors:  Linda Rossini; Caterina Durante; Silvia Bresolin; Enrico Opocher; Antonio Marzollo; Alessandra Biffi
Journal:  Cancers (Basel)       Date:  2022-07-31       Impact factor: 6.575

Review 4.  [Imaging of tumor predisposition syndromes].

Authors:  K Glutig; A Pfeil; D M Renz
Journal:  Radiologe       Date:  2021-06-25       Impact factor: 0.635

Review 5.  TRIM28 variants and Wilms' tumour predisposition.

Authors:  Janna A Hol; Illja J Diets; Ronald R de Krijger; Marry M van den Heuvel-Eibrink; Marjolijn Cj Jongmans; Roland P Kuiper
Journal:  J Pathol       Date:  2021-03-15       Impact factor: 7.996

  5 in total

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