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

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.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Mild hypophosphatasia may be twice as prevalent as previously estimated: an effective clinical algorithm to detect undiagnosed cases ; volume:62 ; number:1 ; year:2024 ; pages:128-137 ; extent:10
Clinical chemistry and laboratory medicine ; 62, Heft 1 (2024), 128-137 (gesamt 10)

Creator
González-Cejudo, Trinidad
Villa-Suárez, Juan Miguel
Ferrer-Millán, María
Andújar-Vera, Francisco
Contreras-Bolívar, Victoria
Andreo-López, María Carmen
Gómez-Vida, José María
Martínez-Heredia, Luis
González-Salvatierra, Sheila
de Haro Muñoz, Tomás
García-Fontana, Cristina
Muñoz-Torres, Manuel
García-Fontana, Beatriz

DOI
10.1515/cclm-2023-0427
URN
urn:nbn:de:101:1-2023112713493055837107
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
15.08.2025, 7:38 AM CEST

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Associated

  • González-Cejudo, Trinidad
  • Villa-Suárez, Juan Miguel
  • Ferrer-Millán, María
  • Andújar-Vera, Francisco
  • Contreras-Bolívar, Victoria
  • Andreo-López, María Carmen
  • Gómez-Vida, José María
  • Martínez-Heredia, Luis
  • González-Salvatierra, Sheila
  • de Haro Muñoz, Tomás
  • García-Fontana, Cristina
  • Muñoz-Torres, Manuel
  • García-Fontana, Beatriz

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