Mild hypophosphatasia may be twice as prevalent as previously estimated: an effective clinical algorithm to detect undiagnosed cases

Abstract

Objectives: Since the prevalence of hypophosphatasia (HPP), a rare genetic disease, seems to be underestimated in clinical practice, in this study, a new diagnostic algorithm to identify missed cases of HPP was developed and implemented.

Methods: Analytical determinations recorded in the Clinical Analysis Unit of the Hospital Universitario Clínico San Cecilio in the period June 2018 - December 2020 were reviewed. A new clinical algorithm to detect HPP-misdiagnosed cases was used including the following steps: confirmation of persistent hypophosphatasemia, exclusion of secondary causes of hypophosphatasemia, determination of serum pyridoxal-5'-phosphate (PLP) and genetic study of ALPL gene.

Results: Twenty-four subjects were selected to participate in the study and genetic testing was carried out in 20 of them following clinical algorithm criteria. Eighty percent of patients was misdiagnosed with HPP following the current standard clinical practice. Extrapolating these results to the current Spanish population means that there could be up to 27,177 cases of undiagnosed HPP in Spain. In addition, we found a substantial proportion of HPP patients affected by other comorbidities, such as autoimmune diseases (∼40 %).

Conclusions: This new algorithm was effective in detecting previously undiagnosed cases of HPP, which appears to be twice as prevalent as previously estimated for the European population. In the near future, our algorithm could be globally applied routinely in clinical practice to minimize the underdiagnosis of HPP. Additionally, some relevant findings, such as the high prevalence of autoimmune diseases in HPP-affected patients, should be investigated to better characterize this disorder.

Keywords: diagnostic algorithm; hypophosphatasia; prevalence; rare diseases.