Koller-Smith Louise Im, Shah Prakesh S, Ye Xiang Y, Sjörs Gunnar, Wang Yueping A, Chow Sharon S W, Darlow Brian A, Lee Shoo K, Håkanson Stellan, Lui Kei
Faculty of Health Science, University of Technology Sydney, Sydney, NSW, Australia.
Department of Pediatrics, Mount Sinai Hospital and University of Toronto, Toronto, ON, Canada.
BMC Pediatr. 2017 Jul 14;17(1):166. doi: 10.1186/s12887-017-0921-x.
Compared to very low gestational age (<32 weeks, VLGA) cohorts, very low birth weight (<1500 g; VLBW) cohorts are more prone to selection bias toward small-for-gestational age (SGA) infants, which may impact upon the validity of data for benchmarking purposes.
Data from all VLGA or VLBW infants admitted in the 3 Networks between 2008 and 2011 were used. Two-thirds of each network cohort was randomly selected to develop prediction models for mortality and composite adverse outcome (CAO: mortality or cerebral injuries, chronic lung disease, severe retinopathy or necrotizing enterocolitis) and the remaining for internal validation. Areas under the ROC curves (AUC) of the models were compared.
VLBW cohort (24,335 infants) had twice more SGA infants (20.4% vs. 9.3%) than the VLGA cohort (29,180 infants) and had a higher rate of CAO (36.5% vs. 32.6%). The two models had equal prediction power for mortality and CAO (AUC 0.83), and similarly for all other cross-cohort validations (AUC 0.81-0.85). Neither model performed well for the extremes of birth weight for gestation (<1500 g and ≥32 weeks, AUC 0.50-0.65; ≥1500 g and <32 weeks, AUC 0.60-0.62).
There was no difference in prediction power for adverse outcome between cohorting VLGA or VLBW despite substantial bias in SGA population. Either cohorting practises are suitable for international benchmarking.
与孕龄极低(<32周,VLGA)队列相比,极低出生体重(<1500g;VLBW)队列更容易出现对小于胎龄(SGA)婴儿的选择偏倚,这可能会影响用于基准比较目的数据的有效性。
使用了2008年至2011年期间3个网络收治的所有VLGA或VLBW婴儿的数据。每个网络队列的三分之二被随机选择用于建立死亡率和综合不良结局(CAO:死亡率或脑损伤、慢性肺病、严重视网膜病变或坏死性小肠结肠炎)的预测模型,其余用于内部验证。比较模型的受试者工作特征曲线(ROC)下面积(AUC)。
VLBW队列(24335名婴儿)的SGA婴儿数量是VLGA队列(29180名婴儿)的两倍(20.4%对9.3%),且CAO发生率更高(36.5%对32.6%)。这两个模型对死亡率和CAO的预测能力相同(AUC 0.83),对所有其他跨队列验证也是如此(AUC 0.81 - 0.85)。对于孕龄出生体重的极端情况(<1500g且≥32周,AUC 0.50 - 0.65;≥1500g且<32周,AUC 0.60 - 0.62),两个模型的表现都不佳。
尽管SGA人群存在显著偏倚,但VLGA或VLBW队列对不良结局的预测能力没有差异。两种队列分组方法都适用于国际基准比较。