Background: The "Cohorte Enfant Scanner", a study designed to investigate the risk of radiation-induced cancer after childhood exposure to CT (computed tomography) examinations, used clinical information contained in the "programme de médicalisation des systèmes d'information" (PMSI) database, the French hospital activities national program based upon diagnosis related groups (DRG). However, the quality and adequacy of the data for the specific needs of the study should be verified. The aim of our work was to estimate the percentage of the cohort's children identified in the PMSI database and to develop an algorithm to individualize the children with a cancer or a disease at risk of cancer from medical diagnoses provided by the DRGs database.
Methods: Of the 1519 children from the "Cohorte Enfant Scanner", who had had a CT scan in the radiology department of a university hospital in 2002, a cross linkage was performed with the DRGs database. All hospitalizations over the period 2002-2009 were taken into account. An algorithm was constructed for the items "cancer" and "disease at risk for cancer" on a sample of 150 children. The algorithm was then tested on the entire population.
Results: Overall, 74% of our population was identified in the DRGs database. The algorithm individualized cancer diagnoses with 91% sensitivity (95% confidence interval [95%CI]: 86%; 97%) and 98% specificity (95%CI: 97%; 99%) and 86% positive predictive value (95%CI: 80%; 93%). For the diagnosis of disease at risk for cancer, the sensitivity, specificity and positive predictive value were respectively 91% (95%CI: 84%; 98%), 94% (95%CI: 92%; 95%) and 52% (95%CI: 43%; 61%).
Conclusion: The DRG database identified with excellent sensitivity and specificity children with diagnoses of cancer or disease at risk for cancer. Hence, potential confounding factors related to the disease of the child can be taken into account for analyses performed with the cohort.
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