ArticleDiabetologia2014
Validation of a model to estimate personalised screening frequency to monitor diabetic retinopathy.
Article in Diabetologia, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 5 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 5 syntheses or guidelines pooled it, 46 citations in OpenAlex.
- Machine Learning Models for Prediction of Diabetic Microvascular Complications.Journal of diabetes science and technology · 2024Pooled it
- Prognostic models of diabetic microvascular complications: a systematic review and meta-analysis.Systematic reviews · 2021Pooled it
- Prediction models for development of retinopathy in people with type 2 diabetes: systematic review and external validation in a Dutch primary care setting.Diabetologia · 2020Pooled it
- Incidence of sight-threatening diabetic retinopathy in people with Type 2 diabetes mellitus and numbers needed to screen: a systematic review.Diabetic medicine : a journal of the British Diabetic Association · 2019Pooled it
- Prognostic prediction models for diabetic retinopathy progression: a systematic review.Eye (London, England) · 2019Pooled it
- Retinopathy prevalence, incidence and trajectories in type 2 diabetes: The Fremantle diabetes study phase II.Diabetic medicine : a journal of the British Diabetic Association · 2023Trial
- Safety and cost-effectiveness of individualised screening for diabetic retinopathy: the ISDR open-label, equivalence RCT.Diabetologia · 2021Trial
- Frequency of Evidence-Based Screening for Retinopathy in Type 1 Diabetes.The New England journal of medicine · 2017Trial
- Artificial Intelligence-Based Screening System for Diabetic Retinopathy in Primary Care.Diagnostics (Basel, Switzerland) · 2024Article
- Referable Diabetic Retinopathy Prediction Algorithm Applied to a Population of 120,389 Type 2 Diabetics over 11 Years Follow-Up.Diagnostics (Basel, Switzerland) · 2024Article
- Testing the performance of risk prediction models to determine progression to referable diabetic retinopathy in an Irish type 2 diabetes cohort.The British journal of ophthalmology · 2022Article
- Validation of an Algorithm for the Prediction of Diabetic Retinopathy in Type 1 Diabetic Patients in a Spanish Population.Clinical ophthalmology (Auckland, N.Z.) · 2022Article
- Real-world outcomes of a clinical decision support system for diabetic retinopathy in Spain.BMJ open ophthalmology · 2022Article
- Diabetic Retinopathy Screening in Patients with Diabetes Using a Handheld Fundus Camera: The Experience from the South-Eastern Region in Hungary.Journal of diabetes research · 2021Article
- A personalised screening strategy for diabetic retinopathy: a cost-effectiveness perspective.Diabetologia · 2020Article
- Personalising screening of sight-threatening diabetic retinopathy - qualitative evidence to inform effective implementation.BMC public health · 2020Article
- Article
- The unmet need for better risk stratification of non-proliferative diabetic retinopathy.Diabetic medicine : a journal of the British Diabetic Association · 2019Review
- Personalized risk-based screening for diabetic retinopathy: A multivariate approach versus the use of stratification rules.Diabetes, obesity & metabolism · 2019Article
- Individualised variable-interval risk-based screening for sight-threatening diabetic retinopathy: the Liverpool Risk Calculation Engine.Diabetologia · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aims/hypothesisOur study aimed to validate a model to determine a personalised screening frequency for diabetic retinopathy.
methodsA model calculating a personalised screening interval for monitoring retinopathy based on patients' risk profile was validated using the data of 3,319 type 2 diabetic patients in the Diabetes Care System West-Friesland, the Netherlands. Two-field fundus photographs were graded according to the EURODIAB coding system. Sight-threatening retinopathy (STR) was considered to be grades 3-5. Validity of the model was assessed using calibration and discrimination measures. We compared model-based time of screening with time of STR diagnosis and calculated the differences in the number of fundus photographs using the model compared with those in annual or biennial screening.
resultsDuring a mean of 53 months of follow-up, 76 patients (2.3%) developed STR. Using the model, the mean screening interval was 31 months, leading to a reduced screening frequency of 61% compared with annual screening and 23% compared with biennial screening. STR incidence occurred after a mean of 26 months after the model-based time of screening in 67 patients (88.2%). In nine patients (11.8%), STR had developed before the model-based time of screening. The discriminatory ability of the model was good (C-statistic 0.83; 95% CI 0.74, 0.92). Calibration showed that the model overestimated STR risk. CONCLUSIONS/
interpretationA large reduction in retinopathy screening was achieved using the model in this population of patients with a very low incidence of retinopathy. Considering the number of potentially missed cases of STR, there is room for improvement in the model. Use of the model for personalised screening may eventually help to reduce healthcare use and costs of diabetes care.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.