Performance of the eHealth decision support tool, MIPOGG, for recognising children with Li-Fraumeni, DICER1, Constitutional mismatch repair deficiency and Gorlin syndromes.

BACKGROUND: Cancer predisposition syndromes (CPSs) are responsible for at least 10% of cancer diagnoses in children and adolescents, most of which are not clinically recognised prior to cancer diagnosis. A variety of clinical screening guidelines are used in healthcare settings to help clinicians detect patients who have a higher likelihood of having a CPS. The McGill Interactive Pediatric OncoGenetic Guidelines (MIPOGG) is an electronic health decision support tool that uses algorithms to help clinicians determine if a child/adolescent diagnosed with cancer should be referred to genetics for a CPS evaluation. METHODS: This study assessed MIPOGG's performance in identifying Li-Fraumeni, DICER1, Constitutional mismatch repair deficiency and Gorlin (nevoid basal cell carcinoma) syndromes in a retrospective series of 84 children diagnosed with cancer and one of these four CPSs in Canadian hospitals over an 18-year period. RESULTS: MIPOGG detected 82 of 83 (98.8%) evaluable patients with any one of these four genetic conditions and demonstrated an appropriate rationale for suggesting CPS evaluation. When compared with syndrome-specific clinical screening criteria, MIPOGG's ability to correctly identify children with any of the four CPSs was equivalent to, or outperformed, existing clinical criteria respective to each CPS. CONCLUSION: This study adds evidence that MIPOGG is an appropriate tool for CPS screening in clinical practice. MIPOGG's strength is that it starts with a specific cancer diagnosis and incorporates criteria relevant for associated CPSs, making MIPOGG a more universally accessible diagnostic adjunct that does not require in-depth knowledge of each CPS.

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

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.

Use of continuous glucose monitoring to identify glucose dysregulation in growth hormone insensitivity syndrome.

BACKGROUND/AIMS: Monogenic forms of growth hormone insensitivity (GHI) and its treatment with recombinant insulin-like growth factor-1 (rIGF-1) are both associated with glucose dysregulation. We used the information provided by continuous glucose monitoring systems (CGMS) for the clinical management of two children with monogenic GHI prior to the commencement of therapy as well as during the years when they received rIGF-1 treatment and continued to do so after the cessation of therapy. METHODS: We evaluated the extent of hyper- and hypoglycaemia with CGMS. RESULTS: In one patient, before treatment CGMS identified self-limiting nocturnal hypoglycaemia. Initiation of rIGF-1 treatment resulted in severe and persistent hypoglycaemia with an absence of spontaneous recovery. Corrective dietary measures were instituted. In a second patient, who had a poor growth response to rIGF-1 therapy, CGMS identified significant fluctuations in daytime glucose levels whilst on treatment with evidence of postprandial hyperglycaemia and both rebound and nocturnal hypoglycaemia. Given the lack of improved growth and the documented glucose dysregulation, treatment was stopped and repeat measurements with CGMS 1 month afterwards showed complete resolution. CONCLUSIONS: We have demonstrated that CGMS is an effective tool to assess glucose dysregulation in patients with GHI and alters clinical management.