Predictive modeling of hypophosphatasia based on a case series of adult patients with persistent hypophosphatasemia
Abstract
UNLABELLED: Approximately half of individuals with hypophosphatasemia (low levels of serum alkaline phosphatase) have hypophosphatasia, a rare genetic disease in which patients may have stress fractures, bone and joint pain, or premature tooth loss. We developed a predictive model based on specific biomarkers of this disease to better diagnose this condition.
INTRODUCTION: Hypophosphatasemia is a condition in which low levels of alkaline phosphatase (ALP) are detected in the serum. Some individuals presenting with this condition may have a rare genetic disease called hypophosphatasia (HPP), which involves mineralization of the bone and teeth. Lack of awareness of HPP and its nonspecific symptoms make this genetic disease difficult to diagnose. We developed a predictive model based on biomarkers of HPP such as ALP and pyridoxal 5'-phosphate (PLP), because clinical manifestations sometimes are not recognized as symptoms of HPP.
METHODS: We assessed 325,000 ALP results between 2010 and 2015 to identify individuals suspected of having HPP. We performed univariate and multivariate analyses to characterize the relationship between hypophosphatasemia and HPP. Using several machine learning algorithms, we developed several models based on biomarkers and compared their performance to determine the best model.
RESULTS: The final cohort included 45 patients who underwent a genetic test. Half (23 patients) showed a mutation of the ALPL gene that encodes the tissue-nonspecific ALP…
How strong is the evidence?
Evidence Hub reads this as a case series, done in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health. Reported size: 45 participants or records.
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