Abstract

IntroductionSerum protein electrophoresis (SPEP) is commonly used to detect monoclonal paraproteins to meet laboratory diagnostic criteria for plasma cell neoplasms. We propose an automated screening method for paraprotein detection that uses minimal computational resources for training and deployment. MethodsA model screening for paraproteins based on the presence of high-frequency components in the spatial frequency spectrum of the SPEP densitometry curve was calibrated on a set of 330 samples, and evaluated on representative (n=110) and external (n=1,321) test sets. The model takes as input a patient’s serum densitometry curve and a standardized control curve and outputs a prediction of whether a paraprotein is present. We built an interactive web application allowing users to easily perform paraprotein screening given inputs for densitometry curves, as well as a macro-enabled spreadsheet for easy automated screening. ResultsWhen tuned to maximize likelihood ratio with minimum sensitivity 0.90, the model achieved AUC 0.90, sensitivity 0.90, positive-predictive value 0.64, specificity 0.55, and accuracy 0.72 in the representative test set. In the external test set, the model achieved AUC 0.90, sensitivity 0.97, positive-predictive value 0.42, specificity 0.29, and accuracy 0.52. A subset analysis showed sensitivities of 0.90, 0.96, and 1.0 in detecting low (0.1–0.5 g/dL), medium (0.5–3.0 g/dL), and high paraprotein levels (≥3.0 g/dL), respectively. We have released a web service allowing users to score their own SPEP data, and also released the algorithm and application programming interface in an open-source package allowing users to customize the model to their needs. ConclusionsWe developed a proof of concept for an automated method for paraprotein screening using only the characteristics of the SPEP curve. Future work should focus on testing the method with other laboratory data including immunofixation gels, as well as incorporation of outside data sources including clinical data.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.