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. 2024 Mar 1;153(3):e2023063101.
doi: 10.1542/peds.2023-063101.

Missing Outcome Data in Recent Perinatal and Neonatal Clinical Trials

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Missing Outcome Data in Recent Perinatal and Neonatal Clinical Trials

Guowei Li et al. Pediatrics. .

Abstract

Missing outcome data in clinical trials may jeopardize the validity of the trial results and inferences for clinical practice. Although sick and preterm newborns are treated as a captive patient population during their stay in the NICUs, their long-term outcomes are often ascertained after discharge. This greatly increases the risk of attrition. We surveyed recently published perinatal and neonatal randomized trials in 7 high-impact general medical and pediatric journals to review the handling of missing primary outcome data and any choice of imputation methods. Of 87 eligible trials in this survey, 77 (89%) had incomplete primary outcome data. The missing outcome data were not discussed at all in 9 reports (12%). Most study teams restricted their main analysis to participants with complete information for the primary outcome (61 trials; 79%). Only 38 of the 77 teams (49%) performed sensitivity analyses using a variety of imputation methods. We conclude that the handling of missing primary outcome data was frequently inadequate in recent randomized perinatal and neonatal trials. To improve future approaches to missing outcome data, we discuss the strengths and limitations of different imputation methods, the appropriate estimation of sample size, and how to deal with data withdrawal. However, the best strategy to reduce bias from missing outcome data in perinatal and neonatal trials remains prevention. Investigators should anticipate and preempt missing data through careful study design, and closely monitor all incoming primary outcome data for completeness during the conduct of the trial.

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Comment in

  • Making the Most of Missing Data.
    Kilpatrick R, Greenberg RG. Kilpatrick R, et al. Pediatrics. 2024 Mar 1;153(3):e2023064938. doi: 10.1542/peds.2023-064938. Pediatrics. 2024. PMID: 38389480 No abstract available.

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