Development and validation of a new clinical decision support tool to optimize screening for retinopathy of prematurity
Journal article, 2022
Background/Aims Prematurely born infants undergo costly, stressful eye examinations to uncover the small fraction with retinopathy of prematurity (ROP) that needs treatment to prevent blindness. The aim was to develop a prediction tool (DIGIROP-Screen) with 100% sensitivity and high specificity to safely reduce screening of those infants not needing treatment. DIGIROP-Screen was compared with four other ROP models based on longitudinal weights. Methods Data, including infants born at 24–30 weeks of gestational age (GA), for DIGIROP-Screen development (DevGroup, N=6991) originate from the Swedish National Registry for ROP. Three international cohorts comprised the external validation groups (ValGroups, N=1241). Multivariable logistic regressions, over postnatal ages (PNAs) 6–14 weeks, were validated. Predictors were birth characteristics, status and age at first diagnosed ROP and essential interactions. Results ROP treatment was required in 287 (4.1%)/6991 infants in DevGroup and 49 (3.9%)/1241 in ValGroups. To allow 100% sensitivity in DevGroup, specificity at birth was 53.1% and cumulatively 60.5% at PNA 8 weeks. Applying the same cut-offs in ValGroups, specificities were similar (46.3% and 53.5%). One infant with severe malformations in ValGroups was incorrectly classified as not needing screening. For all other infants, at PNA 6–14 weeks, sensitivity was 100%. In other published models, sensitivity ranged from 88.5% to 100% and specificity ranged from 9.6% to 45.2%. Conclusions DIGIROP-Screen, a clinical decision support tool using readily available birth and ROP screening data for infants born GA 24–30 weeks, in the European and North American populations tested can safely identify infants not needing ROP screening. DIGIROP-Screen had equal or higher sensitivity and specificity compared with other models. DIGIROP-Screen should be tested in any new cohort for validation and if not validated it can be modified using the same statistical approaches applied to a specific clinical setting.
Author
A. Pivodic
University of Gothenburg
H. Johansson
University of Gothenburg
Australian Catholic University
Lois E.H. Smith
Harvard Medical School
Anna Lena Hård
University of Gothenburg
Chatarina Löfqvist
University of Gothenburg
Bradley A. Yoder
University of Utah
M. Elizabeth Hartnett
University of Utah
Carolyn Wu
Harvard Medical School
Marie Christine Bründer
Greifswald University Hospital
Wolf A. Lagrèze
University of Freiburg
Andreas Stahl
Greifswald University Hospital
Abbas Al-Hawasi
Linköping University
Eva Larsson
Uppsala University
Pia Lundgren
University of Gothenburg
Örebro University
Lotta Gränse
Skåne University Hospital
Birgitta Sunnqvist
County Hospital Ryhov
Kristina Tornqvist
Skåne University Hospital
Agneta Wallin
St. Erik Eye Hospital
Gerd Holmström
Uppsala University
Kerstin Albertsson-Wikland
University of Gothenburg
Staffan Nilsson
University of Gothenburg
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
Ann Hellström
University of Gothenburg
British Journal of Ophthalmology
0007-1161 (ISSN) 14682079 (eISSN)
Vol. 106 1573-1580 318719Subject Categories
Pediatrics
Ophthalmology
Obstetrics, Gynecology and Reproductive Medicine
DOI
10.1136/bjophthalmol-2020-318719
PubMed
33980506