Catherine Goudie1,2, Leora Witkowski3, Noelle Cullinan4,5, Lara Reichman2,3, Ian Schiller6, Melissa Tachdjian2, Linlea Armstrong7, Katherine A Blood7,8, Josée Brossard9, Ledia Brunga10, Chantel Cacciotti11, Kimberly Caswell10, Sonia Cellot12, Mary Egan Clark13, Catherine Clinton14, Hallie Coltin5, Kathleen Felton15, Conrad V Fernandez16, Adam J Fleming17, Noemi Fuentes-Bolanos18,19, Paul Gibson17, Ronald Grant5, Rawan Hammad5,20, Lynn W Harrison13, Meredith S Irwin5, Donna L Johnston21, Sarah Kane22, Lucie Lafay-Cousin23, Irene Lara-Corrales24, Valerie Larouche25, Natalie Mathews5, M Stephen Meyn26,27, Orli Michaeli5, Renée Perrier28, Meghan Pike16, Angela Punnett5, Vijay Ramaswamy5, Jemma Say29, Gino Somers30, Uri Tabori5, My Linh Thibodeau5,10, Annie-Kim Toupin31,32, Katherine M Tucker33, Kalene van Engelen34, Stephanie Vairy9,12, Nicolas Waespe35,36, Meera Warby33, Jonathan D Wasserman37,38, James A Whitlock5, Daniel Sinnett12, Nada Jabado1,2, Paul C Nathan5, Adam Shlien10,38, Junne Kamihara14, Rebecca J Deyell39, David S Ziegler18,19, Kim E Nichols13, Nandini Dendukuri6, David Malkin5, Anita Villani5, William D Foulkes40,41,42. 1. Division of Hematology-Oncology, Department of Pediatrics, McGill University Health Centre, Montreal, Quebec, Canada. 2. Department of Child Health and Human Development, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada. 3. McGill University Health Centre, Department of Human Genetics, Montreal, Quebec, Canada. 4. Department of Haematology-Oncology, Children's Health Ireland, Crumlin, Dublin, Ireland. 5. Division of Pediatric Hematology/Oncology, Department of Pediatrics, The Hospital for Sick Children, Toronto, Ontario, Canada. 6. Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, McGill University, Montreal, Quebec, Canada. 7. Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada. 8. Hereditary Cancer Program, BC Cancer, Vancouver, British Columbia, Canada. 9. Division of Pediatric Hematology-Oncology, Department of Pediatrics, CIUSSS de l'Estrie - CHUS, Sherbrooke, Quebec, Canada. 10. Department of Genetics and Genome Biology, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada. 11. Department of Pediatric Oncology-Hematology, Children's Hospital-London Health Sciences Centre, London, Ontario, Canada. 12. Charles-Bruneau Cancer Centre, Pediatric Hematology-Oncology Division, Centre Hospitalier Universitaire (CHU) Sainte-Justine Research Centre, Montreal, Quebec, Canada. 13. Cancer Predisposition Division, Department of Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee. 14. Department of Pediatric Oncology, Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, Massachusetts. 15. Pediatric Hematology/Oncology, Jim Pattison Children's Hospital, University of Saskatchewan, Saskatoon, Saskatchewan, Canada. 16. Division of Hematology/Oncology, Department of Pediatrics, IWK Health Centre, Halifax, Nova Scotia, Canada. 17. Division of Pediatric Hematology/Oncology, McMaster Children's Hospital, Hamilton, Ontario, Canada. 18. Children's Cancer Institute, Lowy Cancer Centre, University of New South Wales Sydney, Kensington, New South Wales, Australia. 19. Kids Cancer Centre, Sydney Children's Hospital, Randwick, New South Wales, Australia. 20. Department of Haematology, King Abdulaziz University, Jeddah, Makkah, Saudi Arabia. 21. Division of Hematology/Oncology, Children's Hospital of Eastern Ontario, Ottawa, Ontario, Canada. 22. Division of Clinical Genetics, Department of Hereditary Cancer and Genetics, Memorial Sloan-Kettering Cancer Center, Basking Ridge, New Jersey. 23. Section of Pediatric Hematology Oncology and Bone Marrow Transplantation, Alberta Children's Hospital, Calgary, Alberta, Canada. 24. Section of Dermatology, Department of Pediatrics, The Hospital for Sick Children, Toronto, Ontario, Canada. 25. Department of Pediatrics, Centre mère-enfant Soleil du CHU de Québec-Université Laval, Québec City, Quebec, Canada. 26. Center for Human Genomics and Precision Medicine, University of Wisconsin School of Medicine and Public Health, Madison. 27. Division of Clinical and Metabolic Genetics, Department of Pediatrics, and Genetics and Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada. 28. Department of Medical Genetics, Alberta Children's Hospital and Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada. 29. Paediatric Haematology/Oncology Programme, Bristol Children's Hospital, Bristol, United Kingdom. 30. Division of Pathology, Department of Pediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada. 31. Faculty of Medicine, Université Laval, Quebec, Canada. 32. Northern Ontario School of Medicine Residency Program, Sudbury, Ontario, Canada. 33. Hereditary Cancer Centre, Department of Oncology and Haematology, Prince of Wales Hospital, Randwick, New South Wales, Australia. 34. Medical Genetics Program of Southwestern Ontario, London Health Sciences Centre, London, Ontario, Canada. 35. CANSEARCH Research Platform in Pediatric Oncology and Hematology of the University of Geneva, Geneva, Switzerland. 36. Childhood Cancer Research Group, Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland. 37. Division of Endocrinology, The Hospital for Sick Children, Toronto, Ontario, Canada. 38. Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada. 39. Division of Pediatric Hematology/Oncology/BMT, University of British Columbia, British Columbia Children's Hospital and Research Institute, Vancouver, British Columbia, Canada. 40. Department of Medicine, McGill University, Montreal, Quebec, Canada. 41. Department of Human Genetics, McGill University, Montreal, Quebec, Canada. 42. Department of Oncology, McGill University, Montreal, Quebec, Canada.
Abstract
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.
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.
Authors: Michael E Baser; J M Friedman; Dana Aeschliman; Harry Joe; Andrew J Wallace; Richard T Ramsden; D Gareth R Evans Journal: Am J Hum Genet Date: 2002-08-22 Impact factor: 11.025
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Authors: Anna Byrjalsen; Thomas V O Hansen; Ulrik K Stoltze; Mana M Mehrjouy; Nanna Moeller Barnkob; Lisa L Hjalgrim; René Mathiasen; Charlotte K Lautrup; Pernille A Gregersen; Henrik Hasle; Peder S Wehner; Ruta Tuckuviene; Peter Wad Sackett; Adrian O Laspiur; Maria Rossing; Rasmus L Marvig; Niels Tommerup; Tina Elisabeth Olsen; David Scheie; Ramneek Gupta; Anne-Marie Gerdes; Kjeld Schmiegelow; Karin Wadt Journal: PLoS Genet Date: 2020-12-17 Impact factor: 5.917
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Authors: Sarah Scollon; Mohammad K Eldomery; Jacquelyn Reuther; Frank Y Lin; Samara L Potter; Lauren Desrosiers; Kenneth L McClain; Valeria Smith; Jack Meng-Fen Su; Rajkumar Venkatramani; Jianhong Hu; Viktoriya Korchina; Neda Zarrin-Khameh; Richard A Gibbs; Donna M Muzny; Christine Eng; Angshumoy Roy; D Williams Parsons; Sharon E Plon Journal: Pediatr Blood Cancer Date: 2022-06-30 Impact factor: 3.838