Comparison of Five TSH-Receptor Antibody Assays in Graves' disease: results from an observational pilot study.


Journal

BMC endocrine disorders
ISSN: 1472-6823
Titre abrégé: BMC Endocr Disord
Pays: England
ID NLM: 101088676

Informations de publication

Date de publication:
25 Apr 2019
Historique:
received: 04 01 2019
accepted: 01 04 2019
entrez: 27 4 2019
pubmed: 27 4 2019
medline: 21 8 2019
Statut: epublish

Résumé

Early diagnosis and relapse prediction in Graves' disease influences treatment. We assessed the abilities of four TSH-receptor antibody tests [TRAb] and one cyclic adenosine monophosphate bioassay to predict relapse of Graves' disease. Observational study investigating patients presenting with Graves' disease at a Swiss hospital endocrine referral center or an endocrine outpatient clinic. Main outcomes were diagnosis and relapse of Graves' disease after stop of anti-thyroid drugs. We used Cox regression to study associations of TRAb levels with relapse risk and calculated c-statistics [AUC] to assess discrimination. Blood draws took place as close as possible to treatment initiation. AUCs ranged from 0.90 (TSAb Biossay by RSR) to 0.97 (IMMULITE TSI by Siemens). Highest sensitivity (94.0%) was observed for IMMULITE TSI and RSR TRAb Fast, while the greatest specificity (97.9%) was found with the EliA anti-TSH-R (by Thermo Fisher). In Cox regression analysis comparing the highest versus the lower quartiles, the highest hazard ratio [HR] for relapse was found for BRAHMS TRAK (by Thermo Fisher) (2.98, 95% CI 1.13-7.84), IMMULITE TSI (2.40, 95% CI 0.91-6.35), EliA anti-TSH-R (2.05, 95% CI 0.82-5.10), RSR Fast TRAb (1.80, 95% CI 0.73-4.43), followed by RSR STIMULATION (1.18, 95% CI 0.46-2.99). Discrimination analyses showed respective AUCs of 0.68, 0.65, 0.64, 0.64, and 0.59. The assays tested had good diagnostic power and relapse risk prediction with few differences among the new assays. Due to the small sample size and retrospective design with possible selection bias, our data need prospective validation.

Sections du résumé

BACKGROUND BACKGROUND
Early diagnosis and relapse prediction in Graves' disease influences treatment. We assessed the abilities of four TSH-receptor antibody tests [TRAb] and one cyclic adenosine monophosphate bioassay to predict relapse of Graves' disease.
METHODS METHODS
Observational study investigating patients presenting with Graves' disease at a Swiss hospital endocrine referral center or an endocrine outpatient clinic. Main outcomes were diagnosis and relapse of Graves' disease after stop of anti-thyroid drugs. We used Cox regression to study associations of TRAb levels with relapse risk and calculated c-statistics [AUC] to assess discrimination. Blood draws took place as close as possible to treatment initiation.
RESULTS RESULTS
AUCs ranged from 0.90 (TSAb Biossay by RSR) to 0.97 (IMMULITE TSI by Siemens). Highest sensitivity (94.0%) was observed for IMMULITE TSI and RSR TRAb Fast, while the greatest specificity (97.9%) was found with the EliA anti-TSH-R (by Thermo Fisher). In Cox regression analysis comparing the highest versus the lower quartiles, the highest hazard ratio [HR] for relapse was found for BRAHMS TRAK (by Thermo Fisher) (2.98, 95% CI 1.13-7.84), IMMULITE TSI (2.40, 95% CI 0.91-6.35), EliA anti-TSH-R (2.05, 95% CI 0.82-5.10), RSR Fast TRAb (1.80, 95% CI 0.73-4.43), followed by RSR STIMULATION (1.18, 95% CI 0.46-2.99). Discrimination analyses showed respective AUCs of 0.68, 0.65, 0.64, 0.64, and 0.59.
CONCLUSION CONCLUSIONS
The assays tested had good diagnostic power and relapse risk prediction with few differences among the new assays. Due to the small sample size and retrospective design with possible selection bias, our data need prospective validation.

Identifiants

pubmed: 31023276
doi: 10.1186/s12902-019-0363-6
pii: 10.1186/s12902-019-0363-6
pmc: PMC6482584
doi:

Substances chimiques

Antithyroid Agents 0
Autoantibodies 0
Biomarkers 0
Receptors, Thyrotropin 0

Types de publication

Comparative Study Journal Article Observational Study

Langues

eng

Pagination

38

Subventions

Organisme : Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
ID : PP00P3_150531 / 1
Organisme : Research Council of the Kantonsspital Aarau
ID : 1410.000.044

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Auteurs

Tristan Struja (T)

Medical University Department, Clinic for Endocrinology, Diabetes & Metabolism, Kantonsspital Aarau, Tellstrasse, CH-5001, Aarau, Switzerland. tristan.struja@gmail.com.

Rebecca Jutzi (R)

Medical University Department, Clinic for Endocrinology, Diabetes & Metabolism, Kantonsspital Aarau, Tellstrasse, CH-5001, Aarau, Switzerland.

Noemi Imahorn (N)

Medical University Department, Clinic for Endocrinology, Diabetes & Metabolism, Kantonsspital Aarau, Tellstrasse, CH-5001, Aarau, Switzerland.

Marina Kaeslin (M)

Medical University Department, Clinic for Endocrinology, Diabetes & Metabolism, Kantonsspital Aarau, Tellstrasse, CH-5001, Aarau, Switzerland.

Fabienne Boesiger (F)

Medical University Department, Clinic for Endocrinology, Diabetes & Metabolism, Kantonsspital Aarau, Tellstrasse, CH-5001, Aarau, Switzerland.

Alexander Kutz (A)

Medical University Department, Clinic for Endocrinology, Diabetes & Metabolism, Kantonsspital Aarau, Tellstrasse, CH-5001, Aarau, Switzerland.

Esther Mundwiler (E)

Department of Laboratory Medicine, Kantonsspital Aarau, Aarau, Switzerland.

Andreas Huber (A)

Department of Laboratory Medicine, Kantonsspital Aarau, Aarau, Switzerland.

Marius Kraenzlin (M)

Endonet, Basel, Switzerland.

Beat Mueller (B)

Medical University Department, Clinic for Endocrinology, Diabetes & Metabolism, Kantonsspital Aarau, Tellstrasse, CH-5001, Aarau, Switzerland.
Medical Faculty of the University of Basel, Basel, Switzerland.

Christian Meier (C)

Medical Faculty of the University of Basel, Basel, Switzerland.
Endonet, Basel, Switzerland.

Luca Bernasconi (L)

Department of Laboratory Medicine, Kantonsspital Aarau, Aarau, Switzerland.

Philipp Schuetz (P)

Medical University Department, Clinic for Endocrinology, Diabetes & Metabolism, Kantonsspital Aarau, Tellstrasse, CH-5001, Aarau, Switzerland.
Medical Faculty of the University of Basel, Basel, Switzerland.

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Classifications MeSH