Rhonda Szczesniak1, Weiji Su2, J P Clancy3. 1. Division of Biostatistics & Epidemiology, Cincinnati Children's Hospital, Cincinnati, OH, USA; Division of Pulmonary Medicine, Cincinnati Children's Hospital, Cincinnati, OH, USA. 2. Department of Mathematical Sciences, University of Cincinnati, Cincinnati, OH, USA. 3. Division of Pulmonary Medicine, Cincinnati Children's Hospital, Cincinnati, OH, USA.
Abstract
BACKGROUND: Previous small-sample studies have examined the effect of gastrostomy (g-) tube placement on weight, height, and lung function in adolescent patients with cystic fibrosis (CF), but there are no RCTs to date reporting efficacy. The goal of this study was to implement a dynamic prediction model to 1) understand the role of rapid lung function decline in g-tube placement in real-world clinical settings; 2) provide a prognostic tool with the potential to aid clinicians in optimizing the timing of g-tube placement, in relation to rate of lung function decline and current nutrition status. METHODS: A dynamic prediction model was developed, utilizing data on patients 6-21 years of age from the Cystic Fibrosis Foundation Patient Registry (1997-2013). A joint model was implemented, which coupled a semiparametric mixed model to characterize rapid lung function decline with a time-to-event model to identify risk factors for g-tube initiation. RESULTS: The 4,034 individuals (21.3%) who underwent g-tube placement during adolescence or young adulthood had poorer nutrition and lung function at baseline and initially had increased rates of pancreatic enzyme use, infection and gastroesophageal reflux disease, compared to those who did not receive g-tubes; these associations changed over follow up. Rapid lung function decline was associated with increased risk of g-tube supplementation. CONCLUSIONS: By jointly modeling longitudinal patterns of lung function decline with g-tube delivery, it is possible to construct prognostic aids to evaluate treatment delivery in relation to the onset of rapid lung function decline and other important clinical markers. These algorithms have the potential to enable more effective monitoring of disease progression and promote more timely treatment delivery.
BACKGROUND: Previous small-sample studies have examined the effect of gastrostomy (g-) tube placement on weight, height, and lung function in adolescent patients with cystic fibrosis (CF), but there are no RCTs to date reporting efficacy. The goal of this study was to implement a dynamic prediction model to 1) understand the role of rapid lung function decline in g-tube placement in real-world clinical settings; 2) provide a prognostic tool with the potential to aid clinicians in optimizing the timing of g-tube placement, in relation to rate of lung function decline and current nutrition status. METHODS: A dynamic prediction model was developed, utilizing data on patients 6-21 years of age from the Cystic Fibrosis Foundation Patient Registry (1997-2013). A joint model was implemented, which coupled a semiparametric mixed model to characterize rapid lung function decline with a time-to-event model to identify risk factors for g-tube initiation. RESULTS: The 4,034 individuals (21.3%) who underwent g-tube placement during adolescence or young adulthood had poorer nutrition and lung function at baseline and initially had increased rates of pancreatic enzyme use, infection and gastroesophageal reflux disease, compared to those who did not receive g-tubes; these associations changed over follow up. Rapid lung function decline was associated with increased risk of g-tube supplementation. CONCLUSIONS: By jointly modeling longitudinal patterns of lung function decline with g-tube delivery, it is possible to construct prognostic aids to evaluate treatment delivery in relation to the onset of rapid lung function decline and other important clinical markers. These algorithms have the potential to enable more effective monitoring of disease progression and promote more timely treatment delivery.
Entities:
Keywords:
cystic fibrosis patient registry; functional data analysis; individualized prediction; longitudinal analysis; nutrition; pulmonary function
Authors: Michael W Konstan; Wayne J Morgan; Steven M Butler; David J Pasta; Marcia L Craib; Stefanie J Silva; Dennis C Stokes; Mary Ellen B Wohl; Jeffrey S Wagener; Warren E Regelmann; Charles A Johnson Journal: J Pediatr Date: 2007-06-22 Impact factor: 4.406
Authors: Rhonda D Szczesniak; Gary L McPhail; Leo L Duan; Maurizio Macaluso; Raouf S Amin; John P Clancy Journal: Ann Epidemiol Date: 2013-10-05 Impact factor: 3.797
Authors: Michael J Crowther; Therese M-L Andersson; Paul C Lambert; Keith R Abrams; Keith Humphreys Journal: Stat Med Date: 2015-10-29 Impact factor: 2.373