ArticleClinical ophthalmology (Auckland, N.Z.)2017
Multivariable prediction model for suspected giant cell arteritis: development and validation.
Article in Clinical ophthalmology (Auckland, N.Z.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis 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
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Diagnostic Accuracy of Symptoms, Physical Signs, and Laboratory Tests for Giant Cell Arteritis: A Systematic Review and Meta-analysis.JAMA internal medicine · 2020Pooled it
- Article
- Musculoskeletal ultrasound findings in GCA with PMR and isolated PMR.Rheumatology advances in practice · 2026Article
- Assessment and comparison of probability scores to predict giant cell arteritis.Clinical rheumatology · 2024Article
- Clinical, biological, and ophthalmological characteristics differentiating arteritic from non-arteritic anterior ischaemic optic neuropathy.Eye (London, England) · 2023Article
- Presenting Features of Giant Cell Arteritis with Active Versus Healed Arteritis on Biopsy.Neuro-ophthalmology (Aeolus Press) · 2023Article
- Can a Giant Cell Arteritis (GCA) Risk Stratification Score Be Helpful in Clinical Practice?Cureus · 2022Article
- Giant Cell Arteritis: Updates and Controversies.Frontiers in ophthalmology · 2022Review
- Article
- A Diagnostic Algorithm Based on a Simple Clinical Prediction Rule for the Diagnosis of Cranial Giant Cell Arteritis.Journal of clinical medicine · 2021Article
- Aptamers for Proteins Associated with Rheumatic Diseases: Progress, Challenges, and Prospects of Diagnostic and Therapeutic Applications.Biomedicines · 2020Review
- A new era for giant cell arteritis.Eye (London, England) · 2020Review
- Giant cell arteritis: is the clinical spectrum of the disease changing?BMC geriatrics · 2019Review
- Ultrasound versus temporal artery biopsy in patients with Giant cell arteritis: a prospective cohort study.BMC medical imaging · 2019Article
- Systematic Review of the Yield of Temporal Artery Biopsy for Suspected Giant Cell Arteritis.Neuro-ophthalmology (Aeolus Press) · 2019Review
- Local anesthesia and anxiolytic techniques for oculoplastic surgery.Clinical ophthalmology (Auckland, N.Z.) · 2019Review
- The utility of ESR, CRP and platelets in the diagnosis of GCA.BMC rheumatology · 2019Article
- Neural network and logistic regression diagnostic prediction models for giant cell arteritis: development and validation.Clinical ophthalmology (Auckland, N.Z.) · 2019Article
- The Use of a Nomogram to Visually Interpret a Logistic Regression Prediction Model for Giant Cell Arteritis.Neuro-ophthalmology (Aeolus Press) · 2018Article
- Recent Advances in Giant Cell Arteritis.Current rheumatology reports · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo develop and validate a diagnostic prediction model for patients with suspected giant cell arteritis (GCA).
methodsA retrospective review of records of consecutive adult patients undergoing temporal artery biopsy (TABx) for suspected GCA was conducted at seven university centers. The pathologic diagnosis was considered the final diagnosis. The predictor variables were age, gender, new onset headache, clinical temporal artery abnormality, jaw claudication, ischemic vision loss (VL), diplopia, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and platelet level. Multiple imputation was performed for missing data. Logistic regression was used to compare our models with the non-histologic American College of Rheumatology (ACR) GCA classification criteria. Internal validation was performed with 10-fold cross validation and bootstrap techniques. External validation was performed by geographic site.
resultsThere were 530 complete TABx records: 397 were negative and 133 positive for GCA. Age, jaw claudication, VL, platelets, and log CRP were statistically significant predictors of positive TABx, whereas ESR, gender, headache, and temporal artery abnormality were not. The parsimonious model had a cross-validated bootstrap area under the receiver operating characteristic curve (AUROC) of 0.810 (95% CI =0.766-0.854), geographic external validation AUROC's in the range of 0.75-0.85, calibration p
conclusionOur prediction rule with calculator and nomogram aids in the triage of patients with suspected GCA and may decrease the need for TABx in select low-score at-risk subjects. However, misclassification remains a concern.
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.