Algorithms Developed to Aid Acute, Cutaneous Porphyria Diagnosis
Researchers developed two algorithms using information from a literature search, patient data, expert opinions
Two new algorithms that can accurately diagnose acute and cutaneous porphyria have been developed and validated, a study from Belgium reports.
According to study’s authors, these algorithms can be used to help clinicians correctly interpret porphyria-related lab tests.
“To our knowledge, this is the first time that diagnostic algorithms for acute and cutaneous porphyria have been developed and validated with an analysis of the sensitivity and specificity,” the researchers wrote.
The study, “Development and validation of diagnostic algorithms for the laboratory diagnosis of porphyrias,” was published in the Journal of Inherited Metabolic Disease.
Porphyria is an umbrella term for a group of disorders wherein heme precursor molecules and porphyrins accumulate and damage different tissues and organs. Heme is a molecule required for oxygen transport in living cells.
Several genetic and environmental factors are thought to trigger porphyria in susceptible people.
There are two major groups of porphyria: cutaneous porphyrias and acute porphyrias. While cutaneous porphyrias mainly affect the skin, acute porphyrias are marked by sudden and potentially severe attacks that generally affect multiple organs and systems in the body.
Acute porphyrias include ALAD deficiency porphyria (ADP) and acute intermittent porphyria (AIP). Types of cutaneous porphyria include porphyria cutanea tarda (PCT), erythropoietic protoporphyria (EPP), X-linked erythropoietic protoporphyria (XLEPP), hepatoerythropoietic porphyria (HEP) and congenital erythropoietic porphyria (CEP).
People with hereditary coproporphyria (HCP) and variegate porphyria (VP) can experience acute attacks, as in acute porphyrias, or have skin symptoms.
A diagnosis is highly dependent on blood, urine, stool, and genetic tests. Many clinicians have difficulties selecting and interpreting lab tests when making a diagnosis, however.
Algorithms to aid diagnosis
Scientists at University Hospitals Leuven (UZ Leuven) and Katholieke Universiteit (KU Leuven), Belgium sought to develop algorithms to better diagnose acute and cutaneous porphyrias.
Porphyria patients were identified in the patient database of UZ Leuven, and data from porphyria-related lab tests ordered between January 2000 and September 2020 were retrieved.
The research team ultimately included 639 patients who had available clinical information. A total of 222 were diagnosed with porphyria, while the remaining 417 were diagnosed with other conditions. Researchers developed two algorithms, one for acute porphyria and another for cutaneous porphyria, using information from a literature search, patient data, and expert opinions.
The acute porphyria algorithm begins with the assessment of heme precursor molecules, PBG and dALA, and porphyrins in the urine. Acute porphyria is excluded if patients have negative results in all three tests while experiencing symptoms. Plasma and stool porphyrins, as well as PBG deaminase activity, which is low in people with AIP, are also tested.
In the cutaneous porphyria algorithm, plasma and urine porphyrins are evaluated when the patient has blistering lesions. If the patient has acute, painful photosensitivity, plasma porphyrins and total erythrocyte protoporphyrin measurements are performed.
Statistical analyses determined the algorithms’ sensitivity and specificity. In this study, sensitivity (or the true positive rate) refers to the proportion of people with acute or cutaneous porphyria who truly have the disease. Specificity (also known as the true negative rate) was used as as indicator of how well algorithms were able to identify those who did not have the disease.
The sensitivity of the algorithm for acute porphyria was 100%. Thirteen cases of AIP and one of VP were identified. Its specificity was 98.5%.
For cutaneous porphyria, the sensitivity of the algorithm was 100% with a specificity of 93.9%. Seven cases of VP, 59 of PCT, 23 of EPP, and two of XLEPP were identified.
Algorithms were also validated using cases from the external quality program of the European porphyria network (EPNET). A total of 18 out of 19 EPNET porphyria cases were correctly identified by the algorithms.
“The strength of our study is that the algorithms were validated using patient data. All algorithms available in the literature are constructed based on a literature search and expert opinion, but there is no mention of validation of the algorithms with clinical patient samples,” the researchers wrote. “Both algorithms showed high sensitivity and specificity and can be used to aid the physician in correctly interpreting the laboratory findings of porphyria related tests.”
Researchers noted that there were no available diagnoses of HCP, ADP, CEP, or HEP, meaning the sensitivity of the algorithm for these types of porphyria could not be validated.
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