Faculty Bibliography

Objectives Few studies have assessed the role of socioeconomic health care disparities in skull base pathologies. We compared the clinical history and outcomes of pituitary tumors at private and public hospitals to delineate whether health care disparities exist in pituitary tumor surgery. Methods We reviewed the records of patients who underwent transsphenoidal pituitary tumor resection at NYU Langone Health and Bellevue Hospital. Seventy-two consecutive patients were identified from each hospital. The primary outcome was time-to-surgery from initial recommendation. Secondary outcomes included postoperative diabetes insipidus, cerebrospinal fluid (CSF) leak, and gross total resection. Results Of 144 patients, 23 (32%) public hospital patients and 24 (33%) private hospital patients had functional adenomas (p = 0.29). Mean ages for public and private hospital patients were 46.5 and 51.1 years, respectively (p = 0.06). Private hospital patients more often identified as white (p < 0.001), spoke English (p < 0.001), and had private insurance (p < 0.001). The average time-to-surgery for public and private hospital patients were 46.2 and 34.8 days, respectively (p = 0.39). No statistically significant differences were found in symptom duration, tumor size, reoperation, CSF leak, or postoperative length of stay; however, public hospital patients more frequently required emergency surgery (p = 0.03), developed transient diabetes insipidus (p = 0.02), and underwent subtotal resection (p = 0.04). Conclusion Significant socioeconomic differences exist among patients undergoing pituitary surgery at our institution's hospitals. Public hospital patients more often required emergency surgery, developed diabetes insipidus, and underwent subtotal tumor resection. Identifying these differences is an imperative initial step in improving the care of our patients.

Prolactin is a polypeptide hormone that is well known for its role in reproductive physiology. Recent studies highlight its role in neurohormonal appetite regulation and metabolism. Elevated prolactin levels are widely associated with worsening metabolic disease, but it appears that low prolactin levels could also be metabolically unfavorable. This review discusses the pathophysiology of prolactin related metabolic changes, and the less commonly recognized effects of prolactin on adipose tissue, pancreas, liver, and small bowel. Furthermore, the effect of dopamine agonists on the metabolic profiles of patients with hyperprolactinemia are discussed as well.

PURPOSE/OBJECTIVE:Both prolactinomas and nonfunctioning adenomas (NFAs) can present with hyperprolactinemia. Distinguishing them is critical because prolactinomas are effectively managed with dopamine agonists, whereas compressive NFAs are treated surgically. Current guidelines rely only on serum prolactin (PRL) levels, which are neither sensitive nor specific enough. Recent studies suggest that accounting for tumor volume may improve diagnosis. The objective of this study is to investigate the diagnostic utility of PRL, tumor volume, and imaging features in differentiating prolactinoma and NFA. METHODS:Adult patients with pathologically confirmed prolactinoma (n = 21) or NFA with hyperprolactinemia (n = 58) between 2013 and 2020 were retrospectively identified. Diagnostic performance of clinical and imaging variables was analyzed using receiver-operating characteristic curves to calculate area under the curve (AUC). RESULTS:with sensitivity of 100% and specificity of 82.76%. Binary logistic regression found that PRL was a significant positive predictor of prolactinoma diagnosis, whereas tumor volume, presence of CSI not previously defined, and T2 hyperintensity were significant negative predictors. The regression model had an AUC of 0.9915 (p < 0.0001). CONCLUSIONS:Consideration of tumor volume improves differentiation between prolactinomas and NFAs, which in turn leads to effective management.

OBJECTIVE:Prolactin secreting tumors respond well to medical management with a small fraction of patients requiring surgery. We conducted a systematic review and meta-analysis to study the determinants of surgical remission in these tumors. METHODS:We searched PubMed to identify eligible studies reporting postoperative remission in patients treated with transsphenoidal surgery for prolactinoma. Primary outcomes included postoperative remission, follow-up remission, and recurrence. Postoperative and follow-up remission were defined as normoprolactinemia at less than and greater than one-year post-operation respectively. Recurrence was defined as hyperprolactinemia after initial normalization of prolactin levels. Odds ratios (OR) were calculated, stratified by radiological size, tumor extension, and tumor invasion, and analyzed using a random-effects model meta-analysis. RESULTS:Thirty-five studies were included. Macroadenomas were associated with lower rates of postoperative remission OR 0.20, 95% confidence interval [CI] 0.16-0.24) and lower rates of remission at follow-up (OR 0.11, 95% CI 0.053-0.22). Postoperative remission was less likely in tumors with extra- or suprasellar extension (OR 0.16, 95% CI 0.06-0.43) and tumors with cavernous sinus invasion (OR 0.03, 95% CI 0.01-0.13). Female gender and absence of preoperative dopamine agonist (DA) treatment were also associated with higher remission rates. Across the included studies, there was considerable heterogeneity in each primary outcome (postoperative remission I2=94%, follow-up remission I2=86%, recurrence I2=68%). CONCLUSIONS:Transsphenoidal surgery for prolactinomas may be particularly effective in small, non-invasive, treatment naive tumors and may provide a viable first-line alternative to dopamine agonist therapy in such patients.

OBJECTIVE:Pituitary carcinoma is a rare tumor, defined as a tumor of adenohypophyseal cells with systemic or craniospinal metastasis. We present a case of a growth hormone (GH)-secreting pituitary carcinoma with a review of literature to better characterize this disease. DESIGN:Case report and literature review of 25 cases of GH-secreting pituitary carcinomas RESULTS: The age of diagnosis of GH-secreting carcinomas ranged 24-69 years old with a mean age of 44.4 with 52% of cases present in females. Mean latency period between diagnosis of acromegaly and transition to pituitary carcinoma was 11.4 years with mean survival being 3.4 years. CONCLUSION:Growth hormone (GH)-secreting pituitary carcinomas are rare and hard to distinguish from aggressive pituitary adenomas. From review of literature, treatment options include debulking surgery, radiotherapy, or chemotherapy with dismal outcomes. There are no diagnostic markers or features which can predict metastatic progression of these tumors. Future studies with genomic landscapes and relevant tumor markers are needed to identify pituitary tumors most likely to metastasize.

PURPOSE/OBJECTIVE:Biochemical control is the main determinant of survival, clinical manifestations and comorbidities in acromegaly. Transsphenoidal selective adenomectomy (TSA) is the initial treatment of choice with reported biochemical remission rates varying between 32 and 85%. Understanding the limiting factors is essential for identification of patients who require medical treatment. METHODS:We reviewed the English literature published in Medline/Pubmed until Dec 31, 2019 to identify eligible studies that described outcomes of TSA as primary therapy and performed analyses to determine the main predictors of remission. RESULTS:Most publications reported single-institution, retrospective studies. The following preoperative parameters were consistently associated with lower remission rates: cavernous sinus invasion by imaging, larger tumor size and higher GH levels. Young age and preoperative IGF-1 levels were predictive in some studies. When controlled for covariates, the best single preoperative predictor was cavernous sinus invasion, followed by preoperative GH levels. Conversely, low GH level in the first few days postoperatively was a robust predictor of durable remission. The influence of tumor histology (sparsely granular pattern, co-expression of prolactin and proliferation markers) on surgical remission remains to be established. Few studies developed predictive models that yielded much higher predictive values than individual parameters. CONCLUSION/CONCLUSIONS:Surgical outcome prognostication systems could be further generated by machine learning algorithms in order to support development and implementation of personalized care in patients with acromegaly.