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Missing Outcome Data in Recent Perinatal and Neonatal Clinical Trials.
Li, Guowei; Liu, Yingxin; Zhang, Jingyi; DeMauro, Sara B; Meng, Qiong; Mbuagbaw, Lawrence; Schmidt, Barbara; Kirpalani, Haresh; Thabane, Lehana.
Afiliación
  • Li G; Center for Clinical Epidemiology and Methodology.
  • Liu Y; Father Sean O'Sullivan Research Centre, St Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada.
  • Zhang J; Center for Clinical Epidemiology and Methodology.
  • DeMauro SB; Center for Clinical Epidemiology and Methodology.
  • Meng Q; Division of Neonatology, Children's Hospital of Philadelphia.
  • Mbuagbaw L; Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Schmidt B; Department of Pediatrics, Guangdong Second Provincial General Hospital, Guangzhou, China.
  • Kirpalani H; Father Sean O'Sullivan Research Centre, St Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada.
  • Thabane L; Evidence, and Impact; Department of Health Research Methods.
Pediatrics ; 153(3)2024 Mar 01.
Article en En | MEDLINE | ID: mdl-38389453
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Líquidos Corporales / Trastorno de Personalidad Antisocial Límite: Child / Female / Humans / Newborn / Pregnancy Idioma: En Revista: Pediatrics Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Líquidos Corporales / Trastorno de Personalidad Antisocial Límite: Child / Female / Humans / Newborn / Pregnancy Idioma: En Revista: Pediatrics Año: 2024 Tipo del documento: Article