Clinical and Genetic Risk Prediction of Subsequent CNS Tumors in Survivors of Childhood Cancer: A Report From the COG ALTE03N1 Study

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Survivors of childhood cancer are at risk for developing subsequent CNS tumors. Recent adult studies identified inherited predispositions to glioma and meningioma. This study aimed to use genetic information from adult studies and clinical information (including radiation exposure, age) to create a prediction model that identifies survivors of childhood cancer at high or low risk of developing CNS tumors.
Multicentre COG study ALTE03N1. Eligible participants were individuals diagnosed with a primary cancer at age 21 years or younger who subsequently developed a histologically distinct CNS tumor. For each participant, four controls were selected from a pool of survivors of childhood cancer with no evidence of subsequent neoplasms. All participants provided blood or saliva for germline DNA to identify specific single nucleotide polymorphisms (SNPs). 
Phase 1: multivariate analysis to study association between SNPs and subsequent tumors in 82 participants and 228 matched controls. Phase 2: developed prediction models to identify survivors at high or low risk for subsequent CNS tumors. Phase 3: validated these models in an independent matched case-control sample with 25 participants and 54 controls.
Association between six previously published SNPs and subsequent CNS tumors in survivors of childhood cancer. Prediction model applying genetic variants with primary cancer, sex, cranial radiation had a sensitivity of 87.5%, specificity of 83.5%, PPV was 60.9% and NPV was 95.8% for predicting survivors at highest of lowest risk of subsequent CNS tumour. Validated in independent sample.
Survival bias as only living survivors included in this study. Survivors who already died due to CNS tumour were missed in this study thus underestimation of the effect size for genotypes associated with increased lethality. Slightly different cohort and control groups in the validation group but not statistically significant.
Developed prediction tool can identify childhood cancer survivors at lowest and highest risk of subsequent CNS tumors but need genetic information to apply this tool. Identifying survivors at highest risk may allow for a more intense individualized approach to screening and early detection in this patient population.
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