Delaney, Sarah

Abstract Background Urine drug testing (UDT) is a standard practice used for monitoring controlled and illicit substances in ambulatory care patients. Point-of-care (POC) UDTs are useful tools that allow for drug identification within minutes, providing rapid and objective diagnostic assistance for clinicians. The objective of this study was to evaluate the performance characteristics of 3 different POC UDT devices compared to reference methods. Methods A total of 106 residual urine specimens were collected to evaluate the 3 POC UDT devices: the Profile®-V MEDTOX Scan® drugs of abuse test, Quidel Triage® TOX Drug screen, and Quidel Triage Rapid OXY-BUP-MDMA panel. Device performance was assessed by their ability to identify drug classes/compounds compared to manufacturer and reference method (mass spectrometry) cutoffs. Results The results from quantitative mass spectrometry showed that 77% (84/106) of the samples were positive for one or more drugs. Each device had variable performance across each drug class. Overall, the specificity of the Profile-V MEDTOX Scan test was 90.1%, while the Quidel Triage TOX Drug Screen and Rapid OXY-BUP-MDMA devices had specificities of 89.0% and 50.0% using their respective manufacturer-stated cutoffs. Overall sensitivity was determined to be 98.6%, 97.0%, and 100% for the Profile-V MEDTOX Scan, Quidel Triage TOX Drug Screen, and Rapid OXY-BUP-MDMA, respectively. Conclusions Of the 3 POC UDT devices evaluated, the Profile-V MEDTOX Scan demonstrated the best overall sensitivity and specificity compared to reference methods. False positive and negative results are possible with UDTs, ultimately the best device may depend on patient population and drugs of interest.

Abstract Objective Regulations for clinical laboratories in the United States are complex. The goal of this review is to improve the clarity of laboratory-developed test (LDT) regulation to facilitate innovation. Methods A literature and regulation review of current legislation for compliance by U.S. clinical laboratories was performed, and examples of the steps to implement LDTs within compliance with the regulatory environment are shared. Results Many federal and state jurisdictions are critical to the functionality of a laboratory in addition to upcoming potential promulgation of the Verifying Accurate Leading-Edge IVCT Development Act. Increased regulation, although imperative to maintain consistent, high-standard clinical care, could mean additional costs for developers and healthcare while also hindering innovation. Conclusion An extensive discussion of proposed regulations for LDTs needs to occur. Laboratory testing requires the sustained use of innovative methods at a cost that will permit continued, timely, uninterrupted high-quality service.

Abstract Background Pathologic causes of hyperprolactinemia include prolactin-secreting pituitary adenoma (prolactinoma), diseases of the hypothalamus, primary hypothyroidism, and renal failure. Another cause of hyperprolactinemia is the presence of macroprolactin, a high-molecular-mass complex of prolactin and immunoglobulins, which constitutes a biologically inactive form of prolactin. Detection of macroprolactin is important to avoid misdiagnosis and inappropriate treatment; however, relatively little is known about the persistence of macroprolactin in patients over time or how macroprolactin concentrations evolve within patients. The objective of this study was to examine the changes in macroprolactin and prolactin over time in a large clinical population. Methods All physician-ordered macroprolactin tests from December 2011 to October 2018 (n = 5,318 unique patients) were examined. Data were extracted from patients with repeat collections (≥2 timepoints) during this 7-year period (n = 269). Macroprolactin testing was performed using the Roche Elecsys Prolactin II assay. Prior to analysis, an equal volume of 25% polyethylene glycol (PEG) was added to patient serum, causing macroprolactin to precipitate. Following centrifugation, unprecipitated prolactin was measured in the supernatant, as well as an aliquot of the native sample (measuring total prolactin). Macroprolactin (precipitated prolactin) was calculated by subtracting the unprecipitated prolactin from the total prolactin concentration. For this study, a specimen was considered positive for macroprolactin if the percentage of precipitated prolactin was ≥60%. Results A total of 14% (37/269) of patients tested positive for macroprolactin in at least one of the sequential determinations. For all patients with two or more timepoints, the mean interdetermination change in percent macroprolactin was +0.6% and the mean interdetermination change in total prolactin was –11.6 ng/mL. The mean time between determinations in these patients was 303 days. For the 37 patients that had a positive macroprolactin determination, 25 remained positive across all sample collections (mean interdetermination change of +0.5% macroprolactin, mean interdetermination change in total prolactin of +0.4 ng/mL), seven samples went from positive to negative (mean interdetermination change of –10% macroprolactin, mean change in total prolactin of +0.2 ng/mL), and two samples went from negative to positive (mean interdetermination change of +5.5% macroprolactin, mean change in total prolactin of +1.3 ng/mL). The remaining 3 of the 37 specimens had more than two determinations that fluctuated above and below the predefined cutoff. Conclusions The results from this study suggest that the presence of macroprolactin largely but not exclusively persists over time. Additionally, macroprolactin rarely appears after a previously negative assessment (2/235 patients). Furthermore, only small increases in sequential percent macroprolactin determinations were observed in this data set. The prevalence of the persistence of macroprolactin protein over time might have important implications for patient prolactin monitoring.