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Invited Commentary
February 18, 2021

Is It Always Better to Get Faster Results in Temporal Artery Biopsies?

Author Affiliations
  • 1Department of Pathology and Genomic Medicine, Houston Methodist Hospital, Houston, Texas
JAMA Ophthalmol. 2021;139(4):413-414. doi:10.1001/jamaophthalmol.2020.6895

Diagnosis and treatment of giant cell arteritis (GCA) have evolved throughout the years. Before the 1990s, the diagnosis relied entirely on temporal artery biopsy (TAB)–proven disease to start the eyesight-saving steroid treatment. Pathologists used to do frozen sections to rapidly render a diagnosis that would inform the decision of whether or not to have the patient start corticosteroid treatment. This sounds like an ideal practice for patient care, so why have we stopped favoring this approach? Primarily, it is because we have reached a better understanding of GCA physiopathology, which has balanced the accuracy vs speed of diagnosis.

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    1 Comment for this article
    Studies Suggesting Pre-test Likelihood of Giant Cell Arteritis May Be More Important than the Biopsy-Processing Technique
    Edsel Ing, MD, PhD, FRCSC, MPH, MIAD | University of Toronto
    The pre-test probability of giant cell arteritis (GCA) may influence the final diagnosis more than the technique used to process the temporal artery biopsy (given an adequate length harvest is performed on the symptomatic side).

    A neural network and logistic regression (NN-LR) prediction model (n=1,201) found that age and platelets (both maintained as continuous variables), vision loss, and jaw claudication were stronger predictors for a positive temporal artery biopsy than ESR, CRP, new onset headache, scalp tenderness, diplopia and gender.

    Even the preliminary version of the ten-factor model (n=530 patients who underwent a temporal artery biopsy)
    with AUROC = 0.820 outperformed the American College of Rheumatology criteria with AUROC =0.634. https://pubmed.ncbi.nlm.nih.gov/29200816/

    The NN-LR prediction model can be combined with the results of either ultrasound, MRI or temporal artery biopsy to determine the post-test likelihood of GCA.
    DOI: 10.26226/morressier.5e9852a0df8760da4ba873fc

    It should be noted that prediction models are only a guide for patient-physician shared decision making and glucocorticoid initiation. Misclassification remains a concern, but the calculator provides cutoff values for 95% and 99% sensitivities (https://goo.gl/THCnuU).


    Ing EB, Miller NR, Nguyen A, Su W, Bursztyn LLCD, Poole M, Kansal V, Toren A, Albreki D, Mouhanna JG, Muladzanov A, Bernier M, Gans M, Lee D, Wendel C, Sheldon C, Shields M, Bellan L, Lee-Wing M, Mohadjer Y, Nijhawan N, Tyndel F, Sundaram ANE, Ten Hove MW, Chen JJ, Rodriguez AR, Hu A, Khalidi N, Ing R, Wong SWK, Torun N. Neural network and logistic regression diagnostic prediction models for giant cell arteritis: development and validation. Clin Ophthalmol. 2019 Feb 21;13:421-430.

    Ing EB, Lahaie Luna G, Toren A, Ing R, Chen JJ, Arora N, Torun N, Jakpor OA, Fraser JA, Tyndel FJ, Sundaram AN, Liu X, Lam CT, Patel V, Weis E, Jordan D, Gilberg S, Pagnoux C, Ten Hove M. Multivariable prediction model for suspected giant cell arteritis: development and validation. Clin Ophthalmol. 2017 Nov 22;11:2031-2042.

    Liu J, Chuo J, Pagnoux C, Torun N, Ing EB. The Post-test Probability of GCA after US, MRI, or Temporal Artery Biopsy. Canadian Ophthalmological Society, April 2020. DOI: 10.26226/morressier.5e9852a0df8760da4ba873fc