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10.1177/2045893217695567

http://scihub22266oqcxt.onion/10.1177/2045893217695567
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C5467922!5467922!28597754
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suck abstract from ncbi


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pmid28597754      Pulm+Circ 2017 ; 7 (2): 348-60
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  • Characteristics of pediatric pulmonary hypertension trials registered on ClinicalTrials gov #MMPMID28597754
  • Awerbach JD; Krasuski RA; Hill KD
  • Pulm Circ 2017[Jun]; 7 (2): 348-60 PMID28597754show ga
  • The investigation of pediatric pulmonary hypertension (PH) drugs has been identified as a high priority by the United States National Institutes of Health (NIH). Studying pediatric PH is challenging due to the rare and heterogeneous nature of the disease. We sought to define the pediatric PH clinical trials landscape, to evaluate areas of trial success or failure, and to identify potential obstacles to the study of pediatric PH drugs. Interventional pediatric (ages 0?17 years) PH trials registered on ClinicalTrials.gov from June 2005 through December 2014 were analyzed. There were 45 pediatric PH trials registered during the study period. Median (IQR) projected trial enrollment was 40 (24?63), with seven trials (16%) targeting?>?100 participants. Industry was the most common trial sponsor (n?=?23, 50%), with only two (4.4%) NIH-sponsored trials. Phosphodiesterase inhibitors were the most frequently studied drug (n?=?18, 39%). Single group study designs were used in 44% (n?=?20) with an active comparator (parallel, factorial, or cross-over designs) in 25 trials, including 22 with randomization and ten that were double-blinded. Study outcomes varied markedly with inconsistent use of known surrogate and composite endpoints. One-third of trials (n?=?15, 33%) were terminated, predominantly due to poor participant enrollment. Of the 17 completed trials, 11 had published results and only three efficacy trials met their primary endpoint. There are unique challenges to drug development in pediatric PH, including enrolling patients, identifying appropriate study endpoints, and conducting randomized, controlled, double-blind trials where the likelihood of meeting the study endpoint is optimized.
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