Purpose We developed three absolute risk models for second primary thyroid cancer to assist with long-term clinical monitoring of childhood cancer survivors. Patients and Methods We used data from the Childhood Cancer Survivor Study (CCSS) and two nested case-control studies (Nordic CCSS; Late Effects Study Group). Model M1 included self-reported risk factors, model M2 added basic radiation and chemotherapy treatment information abstracted from medical records, and model M3 refined M2 by incorporating reconstructed radiation absorbed dose to the thyroid. All models were validated in an independent cohort of French childhood cancer survivors. Results M1 included birth year, initial cancer type, age at diagnosis, sex, and past thyroid nodule diagnosis. M2 added radiation (yes/no), radiation to the neck (yes/no), and alkylating agent (yes/no). Past thyroid nodule was consistently the strongest risk factor (M1 relative risk [RR], 10.8; M2 RR, 6.8; M3 RR, 8.2). In the validation cohort, 20-year absolute risk predictions for second primary thyroid cancer ranged from 0.04% to 7.4% for M2. Expected events agreed well with observed events for each model, indicating good calibration. All models had good discriminatory ability (M1 area under the receiver operating characteristics curve [AUC], 0.71; 95% CI, 0.64 to 0.77; M2 AUC, 0.80; 95% CI, 0.73 to 0.86; M3 AUC, 0.75; 95% CI, 0.69 to 0.82). Conclusion We developed and validated three absolute risk models for second primary thyroid cancer. Model M2, with basic prior treatment information, could be useful for monitoring thyroid cancer risk in childhood cancer survivors.
Absolute Risk Prediction of Second Primary Thyroid Cancer Among 5-Year Survivors of Childhood Cancer
