FabryScan Screening Tool Shows Promise in Diagnosing Disease
The screening tool FabryScan — consisting of a physical assessment and a questionnaire — may be useful in diagnosing Fabry disease among people with unclassified pain, according to a new study.
The study, “Stratification of patients with unclassified pain in the FabryScan database,” was published in the Journal of Pain Research.
Pain is a hallmark of many conditions, including Fabry disease. But because pain as a symptom is very nonspecific, people who are experiencing pain due to undiagnosed or misdiagnosed Fabry disease often have difficulty getting a proper diagnosis. It can take a decade or more, and around a quarter of Fabry patients may initially be incorrectly diagnosed.
Thus, there is a need for tools that can help physicians sort out people with Fabry from people experiencing pain due to other conditions. One such tool is FabryScan, which consists of a patient-answered questionnaire and a physician-administered physical assessment. By totaling scores from these measurements, patients can be classified as “likely,” “possible,” or “unlikely” to have Fabry disease.
That’s the idea, but how well does the assessment work?
Researchers from the new study sent FabryScan forms to hundreds of clinics and hospitals and got results for 187 patients, all of whom suffered from severe pain — four with diagnosed Fabry disease, the rest with unspecified pain. About two-thirds of the patients were female; the average age was 50.7 years.
Based on patients’ FabryScan scores, 40 patients were classified as “likely,” 96 as “possible,” and 47 as “unlikely.” All four of the known Fabry patients were classified as “likely,” which supports the validity of the screening tool.
The groups did not differ significantly in reported pain, but there were significant differences in most of the other factors assessed, such as “pain due to fever,” “reduced sweating,” “pain localization in hand/feet,” or “pain due to heat.” Notable exceptions were “morning stiffness” and “joint swelling,” which did not differ across the groups.
“Therefore,” the researchers stated, “the parameters ‘morning stiffness’ and ‘joint swelling’ might have a less discriminatory power as previously expected.”
The researchers also used statistical models to “blindly” divide the patients into three groups based on similarities in the FabryScan scores. One of the resultant “clusters” contained 52 people who exhibited Fabry-like characteristics, including angiokeratoma (benign, wart-like skin lesions), pain due to heat, and reduced sweating. The four Fabry patients were also grouped into this cluster, again supporting the validity of the tool.
The major limitation of this study is the lack of a definitive diagnosis for most of the patients; further research will be needed to fully validate FabryScan.
Still, the researchers concluded that “due to the stratification of Fabry patients in the correct cluster, the FabryScan still presents a useful tool to identify patients previously unrecognized with Fabry disease. Moreover, such an algorithm even represents an elegant method to confirm validity of previous stratification approaches and to retrospectively identify patients with rare diseases in general.”