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  • A Novel, Multi-variate Decision Making Tool for Evaluating Mildly Elevated Serum Prolactin

    Final Number:
    525

    Authors:
    Jason S. Cheng MD; Ryan Salinas MS; Annette Molinaro MA, PhD; Edward F. Chang MD; Sandeep Kunwar MD; Lewis Blevins MD; Manish Kumar Aghi MD PhD

    Study Design:
    Clinical Trial

    Subject Category:

    Meeting: Congress of Neurological Surgeons 2013 Annual Meeting

    Introduction: Hyperprolactinemia occurs both in patients with a pituitary prolactinoma and in those with a sellar mass compressing the pituitary stalk. Distinguishing these two diagnostic possibilities guides treatment with dopamine agonist therapy or surgical resection. To date, no diagnostic algorithm exists to reliably differentiate true prolactinomas from other masses causing stalk effect. We aimed to identify a simple diagnostic algorithm using common pre-operative variables to aid in the evaluation of a mildly elevated serum prolactin in a patient with a sellar mass.

    Methods: A case-control analysis of pathologically confirmed prolactinomas and non-endocrine secreting controls with elevated prolactin between 10 and 100 ug/L from the University of California, San Francisco was performed. From 2001 to 2011, this resulted in 61 cases of prolactinomas and 37 control cases. CART analysis determined the significance of demographic variables, patient symptoms, laboratory values, and radiographic findings in distinguishing true prolactinomas.

    Results: CART analysis demonstrated that of the 98 patients, those with with preoperative prolactin > 39.7 (n=60) had a 91.6% chance of having a prolactinoma. Further stratifying this sub-group by size <= or > 25mm correctly identified 98.2% of prolactinomas (n=54) and 80% of non-prolactinomas (n=4). Similarly, of the remaining 38 patients with prolactin <= 39.7 84.2 % were correctly classified as non-prolactinomas (n=32). Further stratifying by IGF-1 <= or > 364.1 resulted in correctly classifying 87.9% of the non-prolactinomas (n=29) and 40% of the prolactinomas (n=2). Overall, the mis-classification rate was 8.1% (8/98) with this model.

    Conclusions: We identified pre-operative prolactin, size, and IGF-1 as three pre-operative variables which when analyzed together, correctly classified 91.9 % of patients with a prolactin < 100 ug/L in our study. This algorithm can aid pre-operative assessment and decision making in patients with mildly elevated serum prolactin.

    Patient Care: By providing commmunity and academic practitioners with a simple diagnostic tool for better differentiating an elevated serum prolactin due to a prolactinoma or stalk effect.

    Learning Objectives: By the conclusion of this session, participants should be able to: 1) Describe the importance of carefully evaluating an elevated serum prolactin 2) Discuss, in small groups diagnostic tools to differentiate an elevated prolactin due to a prolactinoma versus stalk effect 3) Identify an effective treatment for stalk effect or a true prolactinoma

    References:

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