Objectives: To determine the prevalence and predictors of subclinical giant cell arteritis (GCA) in patients with newly diagnosed polymyalgia rheumatica (PMR). Methods: PubMed, Embase, and Web of Science Core Collection were systematically searched (date of last search July 14, 2021) for any published information on any consecutively recruited cohort reporting the prevalence of GCA in steroid-naïve patients with PMR without cranial or ischemic symptoms. We combined prevalences across populations in a random-effect meta-analysis. Potential predictors of subclinical GCA were identified by mixed-effect logistic regression using individual patient data (IPD) from cohorts screened with PET/(CT). Results: We included 13 cohorts with 566 patients from studies published between 1965 to 2020. Subclinical GCA was diagnosed by temporal artery biopsy in three studies, ultrasound in three studies, and PET/(CT) in seven studies. The pooled prevalence of subclinical GCA across all studies was 23% (95% CI 14%-36%, I2=84%) for any screening method and 29% in the studies using PET/(CT) (95% CI 13%-53%, I2=85%) (n=266 patients). For seven cohorts we obtained IPD for 243 patients screened with PET/(CT). Inflammatory back pain (OR 2.73, 1.32-5.64), absence of lower limb pain (OR 2.35, 1.05-5.26), female sex (OR 2.31, 1.17-4.58), temperature >37° (OR 1.83, 0.90-3.71), weight loss (OR 1.83, 0.96-3.51), thrombocyte count (OR 1.51, 1.05-2.18), and haemoglobin level (OR 0.80, 0.64-1.00) were most strongly associated with subclinical GCA in the univariable analysis but not C-reactive protein (OR 1.00, 1.00-1.01) or erythrocyte sedimentation rate (OR 1.01, 1.00-1.02). A prediction model calculated from these variables had an area under the curve of 0.66 (95% CI 0.55-0.75). Conclusion: More than a quarter of patients with PMR may have subclinical GCA. The prediction model from the most extensive IPD set has only modest diagnostic accuracy. Hence, a paradigm shift in the assessment of PMR patients in favour of implementing imaging studies should be discussed.
Subclinical giant cell arteritis in new onset polymyalgia rheumatica A systematic review and meta-analysis of individual patient data
Camellino D.;Cimmino M. A.;
2022-01-01
Abstract
Objectives: To determine the prevalence and predictors of subclinical giant cell arteritis (GCA) in patients with newly diagnosed polymyalgia rheumatica (PMR). Methods: PubMed, Embase, and Web of Science Core Collection were systematically searched (date of last search July 14, 2021) for any published information on any consecutively recruited cohort reporting the prevalence of GCA in steroid-naïve patients with PMR without cranial or ischemic symptoms. We combined prevalences across populations in a random-effect meta-analysis. Potential predictors of subclinical GCA were identified by mixed-effect logistic regression using individual patient data (IPD) from cohorts screened with PET/(CT). Results: We included 13 cohorts with 566 patients from studies published between 1965 to 2020. Subclinical GCA was diagnosed by temporal artery biopsy in three studies, ultrasound in three studies, and PET/(CT) in seven studies. The pooled prevalence of subclinical GCA across all studies was 23% (95% CI 14%-36%, I2=84%) for any screening method and 29% in the studies using PET/(CT) (95% CI 13%-53%, I2=85%) (n=266 patients). For seven cohorts we obtained IPD for 243 patients screened with PET/(CT). Inflammatory back pain (OR 2.73, 1.32-5.64), absence of lower limb pain (OR 2.35, 1.05-5.26), female sex (OR 2.31, 1.17-4.58), temperature >37° (OR 1.83, 0.90-3.71), weight loss (OR 1.83, 0.96-3.51), thrombocyte count (OR 1.51, 1.05-2.18), and haemoglobin level (OR 0.80, 0.64-1.00) were most strongly associated with subclinical GCA in the univariable analysis but not C-reactive protein (OR 1.00, 1.00-1.01) or erythrocyte sedimentation rate (OR 1.01, 1.00-1.02). A prediction model calculated from these variables had an area under the curve of 0.66 (95% CI 0.55-0.75). Conclusion: More than a quarter of patients with PMR may have subclinical GCA. The prediction model from the most extensive IPD set has only modest diagnostic accuracy. Hence, a paradigm shift in the assessment of PMR patients in favour of implementing imaging studies should be discussed.
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