Diagnostic Cytogenetic Analysis in Pediatric Acute Myeloid Leukemia (AML): Evaluation of Methodological Issues with a Special Focus On Missing Data.

Abstract Abstract 4688 Background Acquired clonal chromosomal alterations are common and considered to have prognostic implications in acute myeloid leukemia (AML). Although bone marrow cytogenetic analysis is required for the classification of AML subtypes and is often used for guiding therapy, the prognostic relevance of the cytogenetic abnormalities in children with AML remains controversial, limiting their value in risk-stratified therapy. Hence we reviewed the reports published by four major pediatric AML study groups to assess the strength of their evidence for the use of cytogenetics as a predictor variable in risk stratification of children with AML, focusing closely on the impact of missing data. Methods Reports of consecutive phase III clinical trials published by cooperative study groups that used cytogenetic features for risk stratification of children with de novo AML were reviewed for their methods of assessing the predictive strength of diagnostic cytogenetic analysis (predictor variable) for clinical outcomes, as well as the extent and impact of missing data. We focused on publications by the North American [Pediatric Oncology Group (POG) and Children's Cancer Group (CCG)] and the European [United Kingdom Medical Research Council (UK MRC) and Berlin-Frankfurt-Munster (BFM) group] consortia as they represent major pediatric AML study groups in their respective continents and each of these groups has conducted several multicenter pediatric AML studies with large sample sizes. Results During the period 1979-2003, four large pediatric AML study groups conducted 12 Phase III studies evaluating diagnostic cytogenetics. In all, 20 publications reporting the results of these trials were studied to evaluate the impact of diagnostic cytogenetics on clinical outcome. Across all study groups, large amount of cytogenetic data were missing (mean ± SD 31.5% ±17.5%; range 5.3% to 58.1%), but neither the causes of “missingness” nor the methods used to handle the missing data were reported or discussed. In addition, we found a lack of uniformity in the assessment of the predictor variable and outcome measures, lack of a priori estimation of sample size to address the impact of diagnostic cytogenetics and the absence of a validation process. Conclusions Missing data were a common but often unidentified problem in a series of large clinical trials testing various treatment strategies in children with AML. This problem, together with other methodological issues in the assessment of the predictor variable and clinical outcome measures, may have biased the estimates of the prognostic strength of diagnostic cytogenetic analysis. Disclosures: No relevant conflicts of interest to declare.

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