Optimizing laboratory defined macroprolactin algorithm

优化实验室定义的巨催乳素算法

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Abstract

INTRODUCTION: Macroprolactinaemia is a well-known analytical problem in diagnostics of hyperprolactinaemia usually detected with polyethylene glycol (PEG) precipitation method. Since there is no harmonization in macroprolactin detection and reporting results, this study proposes and evaluates the usefulness of in-house developed algorithm. The aims were to determine the most suitable way of reporting results after PEG treatment and the possibilities of rationalizing the precipitation procedure. MATERIALS AND METHODS: This is a retrospective study based on extracted data for 1136 patients. Prolactin concentrations were measured before and after PEG precipitation on Roche cobas e601. Macroprolactinaemia was defined by percentage recovery and post-PEG prolactin concentrations. RESULTS: Prevalence of macroprolactinaemia using recovery criteria of ≤ 40%, ≤ 60%, and post-PEG prolactin concentrations was 3.3%, 8.8% and 7.8%, respectively. Raising the cut-off value from the upper limit of the manufacturer's reference interval to 32.9 µg/L does not drastically change detected macroprolactinaemia with recovery criteria. Post-PEG prolactin concentrations showed more than half of the patients with macroprolactinaemia would be overlooked. Regardless of the criteria, a cut-off of 47.0 µg/L would miss most of the macroprolactinaemic patients. Repeated recovery measurements of follow-up patients showed there is a significant difference with mean absolute bias of 9%. CONCLUSIONS: Post-PEG prolactin concentration with corresponding reference interval is the most suitable way of reporting results. All samples with prolactin concentration above the upper limit of the manufacturer's reference interval should be submitted to PEG precipitation. Follow-up period could be prolonged since the difference between the recoveries of repeated measurements is not clinically significant.

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