A Clinical Probability-Based, Stepwise Algorithm for the Diagnosis of Giant Cell Arteritis: Study Protocol and Baseline Characteristics of the First 50 Patients Included in the Prospective Validation Study with Focus on Cranial Symptoms
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Study Objectives
- To determine the diagnostic accuracy of hrCS compared to temporal artery biopsy (TAB) in the diagnosis of cranial GCA.
- To determine the additional diagnostic benefit of sonographic examination of the facial and axillary arteries in the diagnosis of cranial and extracranial GCA.
- To determine the benefit of gender- and risk-adapted stratification of the cut-off values of hrCS.
- To determine the influence of clinical pre-test probability on the diagnostic accuracy of hrCS.
- To determine the impact of glucocorticoid treatment (dose and duration) on the diagnostic accuracy of the applied test procedures and the diagnostic algorithm.
2.2. Clinical Prediction Rule and Diagnostic Algorithm
2.3. Study Population
2.4. Sonographic Protocol
2.5. Temporal Artery Biopsy and Histology
2.6. Final Reference Diagnosis
2.7. Data Handling
2.8. Statistical Considerations
2.9. Accompanying Study on Determining Reference Values of hrCS
3. Results
3.1. Baseline Characteristics of the First 50 Patients Included in PREDICT-GCA
3.2. Comparison of Patients with and Without Positive TAB
3.3. Headache Characteristics
3.4. Clinical Probability Assessment and Amendment of the Clinical Prediction Rule
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Inclusion Criteria | Exclusion Criteria |
---|---|
Age > 50 years | Age < 50 years |
Substantiated clinical suspicion of GCA | Pre-existing diagnosis of GCA |
Signed informed consent | Glucocorticoid treatment with a daily dose of at least 20 mg prednisolone for >7 days |
Previous glucocorticoid treatment with a daily dose of >20 mg for at least 30 days within the preceding 3 months | |
Previous therapy with the interleukin-6 receptor antagonist tocilizumab |
Variables | Overall Cohort, n = 50 |
---|---|
Female sex | 27 (54) |
Age ≥ 70 years | 32 (64) |
New onset headache | 37 (74) |
Jaw claudication | 26 (52) |
Scalp tenderness | 19 (38) |
Temporal artery tenderness | 25 (50) |
Diplopia | 10 (20) |
Amaurosis fugax | 10 (20) |
Permanent visual impairment | 26 (52) |
Bilateral visual impairment | 8 (16) |
Anterior ischemic optic neuropathy | 18 (36) |
Polymyalgia rheumatica | 5 (10) |
Constitutional symptoms | 21 (42) |
Extremity claudication | 3 (6) |
Manifest cardiovascular disease 1 | 15 (30) |
Arterial hypertension | 26 (52) |
Diabetes mellitus | 11 (22) |
Active or former smoking | 24 (48) |
Dyslipidemia | 23 (46) |
Known rheumatic disease 2 | 9 (18) |
History of cancer | 4 (8) |
Temporal artery swelling | 18 (36) |
Temporal artery tenderness on palpation | 24 (48) |
Temporal artery induration | 23 (46) |
Pre-existing low-dose glucocorticoid treatment | 4 (8) |
Pre-existing treatment with glucocorticoid sparing agents | 3 (6) |
Glucocorticoid treatment started for suspected GCA | 34 (68) |
Daily (methyl-)prednisolone dose (mg) | 237 ± 361 |
Time interval between start of glucocorticoid treatment and TAB (days) | 3.5 ± 3.3 |
C-reactive protein (mg/dL) | 4.3 ± 5.7 |
C-reactive protein elevated | |
>0.5 mg/dL | 37 (74) |
>2.5 mg/dL | 21 (42) |
Variable | Odds Ratio (95% CI) | p-Value |
---|---|---|
Cranial symptoms | ||
Bilateral headache | 3.5 (1.1–11.4) | 0.05 |
Headache in >3 regions | 2.0 (0.5–7.1) | 0.35 |
Jaw claudication | 8.1 (2.2–29.6) | <0.01 |
Scalp tenderness | 4.1 (1.2–14.2) | 0.04 |
Temporal artery tenderness | 4.3 (1.3–14.3) | 0.04 |
Physical examination findings | ||
Temporal artery tenderness (on palpation) | 2.1 (0.66–6.5) | 0.26 |
Temporal artery induration | 4.2 (1.3–14.0) | 0.02 |
Temporal artery swelling | 8.5 (2.2–33.2) | <0.01 |
Variable | Description | Score |
---|---|---|
Age (years) | <70 years | 0 |
≥70 years | 1 | |
New onset headache | No | 0 |
Yes | 1 | |
Symptoms of cranial ischemia (jaw claudication, scalp tenderness) and/or temporal artery swelling 1 | No | 0 |
Yes | 2 | |
Permanent visual impairment due to anterior ischemic optic neuropathy | No | 0 |
Unilateral | 1 | |
Bilateral | 2 | |
Score (range 0–6) | Low clinical probability | Score < 2 |
Non-low clinical probability | Score ≥ 2 |
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Thielmann, L.-C.; Findik-Kilinc, M.; Füeßl, L.; Lottspeich, C.; Löw, A.; Henke, T.; Hasmann, S.; Prearo, I.; von Bismarck, A.; Reik, L.U.; et al. A Clinical Probability-Based, Stepwise Algorithm for the Diagnosis of Giant Cell Arteritis: Study Protocol and Baseline Characteristics of the First 50 Patients Included in the Prospective Validation Study with Focus on Cranial Symptoms. J. Clin. Med. 2025, 14, 2254. https://doi.org/10.3390/jcm14072254
Thielmann L-C, Findik-Kilinc M, Füeßl L, Lottspeich C, Löw A, Henke T, Hasmann S, Prearo I, von Bismarck A, Reik LU, et al. A Clinical Probability-Based, Stepwise Algorithm for the Diagnosis of Giant Cell Arteritis: Study Protocol and Baseline Characteristics of the First 50 Patients Included in the Prospective Validation Study with Focus on Cranial Symptoms. Journal of Clinical Medicine. 2025; 14(7):2254. https://doi.org/10.3390/jcm14072254
Chicago/Turabian StyleThielmann, Lukas-Caspar, Melike Findik-Kilinc, Louise Füeßl, Christian Lottspeich, Anja Löw, Teresa Henke, Sandra Hasmann, Ilaria Prearo, Amanda von Bismarck, Lilly Undine Reik, and et al. 2025. "A Clinical Probability-Based, Stepwise Algorithm for the Diagnosis of Giant Cell Arteritis: Study Protocol and Baseline Characteristics of the First 50 Patients Included in the Prospective Validation Study with Focus on Cranial Symptoms" Journal of Clinical Medicine 14, no. 7: 2254. https://doi.org/10.3390/jcm14072254
APA StyleThielmann, L.-C., Findik-Kilinc, M., Füeßl, L., Lottspeich, C., Löw, A., Henke, T., Hasmann, S., Prearo, I., von Bismarck, A., Reik, L. U., Wirthmiller, T., Nützel, A., Mackert, M. J., Priglinger, S., Schulz, H., Mayr, D., Haas-Lützenberger, E., Gebhardt, C., Schulze-Koops, H., & Czihal, M. (2025). A Clinical Probability-Based, Stepwise Algorithm for the Diagnosis of Giant Cell Arteritis: Study Protocol and Baseline Characteristics of the First 50 Patients Included in the Prospective Validation Study with Focus on Cranial Symptoms. Journal of Clinical Medicine, 14(7), 2254. https://doi.org/10.3390/jcm14072254