Development and validation of a new clinical decision support tool to optimize screening for retinopathy of prematurity.

ROP screening clinical decision support tool diagnostic tests/Investigation neovascularisation optimized screening prediction model preterm retinopathy of prematurity

Journal

The British journal of ophthalmology
ISSN: 1468-2079
Titre abrégé: Br J Ophthalmol
Pays: England
ID NLM: 0421041

Informations de publication

Date de publication:
11 2022
Historique:
received: 22 12 2020
revised: 21 04 2021
accepted: 23 04 2021
pubmed: 14 5 2021
medline: 25 10 2022
entrez: 13 5 2021
Statut: ppublish

Résumé

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. 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. 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%. 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.

Sections du résumé

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.

Identifiants

pubmed: 33980506
pii: bjophthalmol-2020-318719
doi: 10.1136/bjophthalmol-2020-318719
pmc: PMC8627649
mid: NIHMS1756987
doi:

Substances chimiques

Peptide Nucleic Acids 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

1573-1580

Subventions

Organisme : NEI NIH HHS
ID : R01 EY017017
Pays : United States
Organisme : NEI NIH HHS
ID : R01 EY030904
Pays : United States
Organisme : NICHD NIH HHS
ID : U54 HD090255
Pays : United States

Informations de copyright

© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

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Auteurs

Aldina Pivodic (A)

Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden aldina.pivodic@gu.se.

Helena Johansson (H)

Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia.
Sahlgrenska Osteoporosis Centre, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden.

Lois E H Smith (LEH)

Department of Ophthalmology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Anna-Lena Hård (AL)

Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

Chatarina Löfqvist (C)

Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Learning and Leadership for Health Care Professionals, Institute of Health Care Science, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

Bradley A Yoder (BA)

Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, Utah, USA.

M Elizabeth Hartnett (ME)

Department of Ophthalmology, John A Moran Eye Center, University of Utah, Salt Lake City, Utah, USA.

Carolyn Wu (C)

Department of Ophthalmology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Marie-Christine Bründer (MC)

Department of Ophthalmology, University Medicine Greifswald, Greifswald, Germany.

Wolf A Lagrèze (WA)

Department of Ophthalmology, Eye Center, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany.

Andreas Stahl (A)

Department of Ophthalmology, University Medicine Greifswald, Greifswald, Germany.

Abbas Al-Hawasi (A)

Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.

Eva Larsson (E)

Department of Neuroscience/Ophthalmology, Uppsala University, Uppsala, Sweden.

Pia Lundgren (P)

Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Department of Ophthalmology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.

Lotta Gränse (L)

Department of Clinical Sciences, Ophthalmology, Skåne University Hospital, Lund University, Lund, Sweden.

Birgitta Sunnqvist (B)

Länssjukhuset Ryhov, Jönköping, Sweden.

Kristina Tornqvist (K)

Department of Clinical Sciences, Ophthalmology, Skåne University Hospital, Lund University, Lund, Sweden.

Agneta Wallin (A)

St. Erik Eye Hospital, Stockholm, Sweden.

Gerd Holmström (G)

Department of Neuroscience/Ophthalmology, Uppsala University, Uppsala, Sweden.

Kerstin Albertsson-Wikland (K)

Department of Physiology/Endocrinology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

Staffan Nilsson (S)

Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden.
Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

Ann Hellström (A)

Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

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