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Purpose: To develop and validate prediction models for low and very low bone mineral density (BMD) on the basis of clinical and treatment characteristics that identify adult survivors of childhood cancer who require screening by dual-energy x-ray absorptiometry., Patients and Methods: White survivors of childhood cancer (n = 2,032; median attained age, 29.3 years [range, 18.1 to 40.9 years]) enrolled in the St Jude Lifetime Cohort (SJLIFE; development) and survivors treated at the Erasmus Medical Center (validation) in the Netherlands (n = 403; median age, 24.2 years [range, 18.0 to 40.9 years]) were evaluated with dual-energy x-ray absorptiometry to determine lumbar spine BMD and total-body BMD. Low and very low BMD were defined as lumbar spine BMD and/or total-body BMD z scores of -1 or lower or -2 or lower, respectively. Multivariable logistic regression was used to build prediction models; performance was assessed using receiver operating characteristic curves. Diagnostic values were calculated at different probabilities., Results: Low BMD was present in 51% and 45% of SJLIFE and Dutch participants, respectively, and very low BMD was present in 20% and 10%, respectively. The model for low BMD included male sex (odds ratio [OR], 3.07), height (OR, 0.95), weight (OR, 0.98), attained age (OR, 0.97), current smoking status (OR, 1.48), and cranial irradiation (OR, 2.11). Areas under the curve were 0.72 (95% CI, 0.70 to 0.75) in the SJLIFE cohort and 0.69 (95% CI, 0.64 to 0.75) in the Dutch cohort. The sum of the sensitivity (69.0%) and specificity (64.0%) was maximal at the predicted probability of 50%. The model for very low BMD included male sex (OR, 3.28), height (OR, 0.95), weight (OR, 0.97), attained age (OR, 0.98), cranial irradiation (OR, 2.07), and abdominal irradiation (OR, 1.61), yielding areas under the curve of 0.76 (95% CI, 0.73 to 0.78; SJLIFE cohort) and 0.75 (95% CI, 0.67 to 0.83; Dutch cohort)., Conclusion: Validated prediction models for low and very low BMD, using easily measured patient and treatment characteristics, correctly identified BMD status in most white adult survivors through age 40 years.

Purpose: To create clinically useful models that incorporate readily available demographic and cancer treatment characteristics to predict individual risk of heart failure among 5-year survivors of childhood cancer., Patients and Methods: Survivors in the Childhood Cancer Survivor Study (CCSS) free of significant cardiovascular disease 5 years after cancer diagnosis (n = 13,060) were observed through age 40 years for the development of heart failure (ie, requiring medications or heart transplantation or leading to death). Siblings (n = 4,023) established the baseline population risk. An additional 3,421 survivors from Emma Children's Hospital (Amsterdam, the Netherlands), the National Wilms Tumor Study, and the St Jude Lifetime Cohort Study were used to validate the CCSS prediction models., Results: Heart failure occurred in 285 CCSS participants. Risk scores based on selected exposures (sex, age at cancer diagnosis, and anthracycline and chest radiotherapy doses) achieved an area under the curve of 0.74 and concordance statistic of 0.76 at or through age 40 years. Validation cohort estimates ranged from 0.68 to 0.82. Risk scores were collapsed to form statistically distinct low-, moderate-, and high-risk groups, corresponding to cumulative incidences of heart failure at age 40 years of 0.5% (95% CI, 0.2% to 0.8%), 2.4% (95% CI, 1.8% to 3.0%), and 11.7% (95% CI, 8.8% to 14.5%), respectively. In comparison, siblings had a cumulative incidence of 0.3% (95% CI, 0.1% to 0.5%)., Conclusion: Using information available to clinicians soon after completion of childhood cancer therapy, individual risk for subsequent heart failure can be predicted with reasonable accuracy and discrimination. These validated models provide a framework on which to base future screening strategies and interventions., (© 2014 by American Society of Clinical Oncology.)