Mastrangelo G, et al. – Integrating clinical, laboratory and genetic factors, Researchers established the first etiologic prediction model for aromatic amine related bladder cancer. It was concluded that discriminatory ability was excellent, especially for the full model, allowing individualized predictions. In addition, validation of the model in external populations is necessary for practical use in the clinical setting.

Methods

• Researchers included a total of 199 bladder cancer patients.
• In this research, clinical, laboratory and genetic data were predictors in logistic regression models (full and short) in which the dependent variable was 1 for 15 patients with aromatic amines related bladder cancer and 0 otherwise.
• They adoped receiver operating characteristics approach; the area under the curve was used to evaluate discriminatory ability of models.

Results

• Area under the curve was 0.93 for the full model (including age, smoking and coffee habits, DNA adducts, 12 genotypes) and 0.86 for the short model (including smoking, DNA adducts, 3 genotypes).
• Percentage of cases correctly classified was 92% (full model) against 75% (short model) applying the “best cut–off” of predicted probability of a positive outcome.
• For etiological diagnosis, cancers divided as “positive outcome” are those to be referred for evaluation by an occupational physician; these patients were 28 (full model) or 60 (short model).
• Applying 3 genotypes instead of 12 can double the number of patients with suspect of aromatic amine related cancer, therefore increasing costs of etiologic appraisal.