Optimization of Opioid Discharge Prescriptions Following Thyroid and Parathyroid Surgery.

OBJECTIVE: To evaluate the impact of a quality improvement bundle on opioid discharge prescribing following thyroidectomy and parathyroidectomy. METHODS: This before-and-after study included patients undergoing thyroidectomy or parathyroidectomy at an academic medical center. The quality improvement bundle included a patient education flyer, electronic health record order sets with multimodal analgesia regimens, and provider education. The preimplementation cohort included patients treated from January 2018 to December 2019. The postimplementation cohort included patients treated from June 2021 to August 2021. The primary outcome was the proportion of patients who received new opioid discharge prescriptions. RESULTS: A total of 160 patients were included in the preimplementation cohort, and the first 80 patients treated after bundle implementation were included in the postimplementation cohort. Patients receiving new opioid discharge prescriptions decreased from 80% (128/160) in the preimplementation cohort to 35% (28/80) in the postimplementation cohort with an unadjusted absolute reduction of 45% (95% CI, 33%-57%; P < .001; number needed to treat = 3) and an adjusted odds ratio (OR) of 0.08 (95% CI, 0.04-0.19; P < .001). The bundle was associated with reductions in opioid discharge prescriptions that exceeded 112.5 oral morphine milligram equivalents (33% pre- vs 10% postimplementation; adjusted OR, 0.20; P = .001) or 5 days of therapy (17% pre- vs 6% postimplementation; adjusted OR, 0.34; P = .049). DISCUSSION: Implementation of a pain management quality improvement bundle reduced opioid discharge prescribing following thyroidectomy and parathyroidectomy. IMPLICATIONS FOR PRACTICE: Unnecessary opioid prescriptions generate unused opioids in patients' homes that can lead to opioid misuse. We believe that this bundle reduced the risk for opioid misuse in our community. REGISTRATION: The study was registered at ClinicalTrials.gov (NCT04955444) before implementation.

Features of Multiple Endocrine Neoplasia Type 1 and 2A in a Patient with Both RET and MEN1 Germline Mutations.

The coexistence of multiple endocrine neoplasia type 1 (MEN1) and type 2A (MEN2A) is a rare occurrence and has been reported only twice in the literature. We present a patient with primary hyperparathyroidism and medullary thyroid cancer with strong family history of both MEN1- and MEN2A-associated conditions. Genetic testing showed the patient had a novel MEN1 loss-of-function mutation, c0.525_526insTT (p.Ala176Leufs*10), and an uncommon Cys630Tyr RET mutation. This case highlights the importance of obtaining a detailed family history when heritable endocrine disorders are suspected.

Gene expression profiling for molecular staging of cutaneous melanoma in patients undergoing sentinel lymph node biopsy.

BACKGROUND: A gene expression profile (GEP) test able to accurately identify risk of metastasis for patients with cutaneous melanoma has been clinically validated. OBJECTIVE: We aimed for assessment of the prognostic accuracy of GEP and sentinel lymph node biopsy (SLNB) tests, independently and in combination, in a multicenter cohort of 217 patients. METHODS: Reverse transcription polymerase chain reaction (RT-PCR) was performed to assess the expression of 31 genes from primary melanoma tumors, and SLNB outcome was determined from clinical data. Prognostic accuracy of each test was determined using Kaplan-Meier and Cox regression analysis of disease-free, distant metastasis-free, and overall survivals. RESULTS: GEP outcome was a more significant and better predictor of each end point in univariate and multivariate regression analysis, compared with SLNB (P < .0001 for all). In combination with SLNB, GEP improved prognostication. For patients with a GEP high-risk outcome and a negative SLNB result, Kaplan-Meier 5-year disease-free, distant metastasis-free, and overall survivals were 35%, 49%, and 54%, respectively. LIMITATIONS: Within the SLNB-negative cohort of patients, overall risk of metastatic events was higher (∼30%) than commonly found in the general population of patients with melanoma. CONCLUSIONS: In this study cohort, GEP was an objective tool that accurately predicted metastatic risk in SLNB-eligible patients.

Development of a prognostic genetic signature to predict the metastatic risk associated with cutaneous melanoma.

PURPOSE: The development of a genetic signature for the identification of high-risk cutaneous melanoma tumors would provide a valuable prognostic tool with value for stage I and II patients who represent a remarkably heterogeneous group with a 3% to 55% chance of disease progression and death 5 years from diagnosis. EXPERIMENTAL DESIGN: A prognostic 28-gene signature was identified by analysis of microarray expression data. Primary cutaneous melanoma tumor tissue was evaluated by RT-PCR for expression of the signature, and radial basis machine (RBM) modeling was performed to predict risk of metastasis. RESULTS: RBM analysis of cutaneous melanoma tumor gene expression reports low risk (class 1) or high risk (class 2) of metastasis. Metastatic risk was predicted with high accuracy in development (ROC = 0.93) and validation (ROC = 0.91) cohorts of primary cutaneous melanoma tumor tissue. Kaplan-Meier analysis indicated that the 5-year disease-free survival (DFS) rates in the development set were 100% and 38% for predicted classes 1 and 2 cases, respectively (P < 0.0001). DFS rates for the validation set were 97% and 31% for predicted classes 1 and 2 cases, respectively (P < 0.0001). Gene expression profile (GEP), American Joint Committee on Cancer stage, Breslow thickness, ulceration, and age were independent predictors of metastatic risk according to Cox regression analysis. CONCLUSIONS: The GEP signature accurately predicts metastasis risk in a multicenter cohort of primary cutaneous melanoma tumors. Preliminary Cox regression analysis indicates that the signature is an independent predictor of metastasis risk in the cohort presented.