Amyotrophic lateral sclerosis (ALS) would benefit from a new classification system, according to a group of researchers who highlighted the shortcomings of current systems for diagnosing the disease and allocating patients to subtypes of the condition.
The opinion article, “Amyotrophic lateral sclerosis: moving towards a new classification system,” published in the journal The Lancet Neurology, laid out a roadmap to a strategy that could combine systematic classification systems with the highly varied symptoms encountered in real life — improving both patient care and research in the process.
During the 1930s, researchers agreed that the term ALS, or motor neuron disease, should encompass conditions affecting both upper and lower motor neurons. Today, scientists are still debating whether ALS is one condition or several different diseases.
Researchers at King’s College London, along with colleagues from a range of international institutions, argue that the current classification systems are inconsistent and do not enable accurate descriptions of ALS symptoms.
Today, there are two systems used: the Awaji-Shima criteria, which is a revised version of the El Escorial criteria, and the International Classification of Diseases (ICD).
El Escorial system
According to the El Escorial criteria and its revisions, an ALS diagnosis is dependent on symptoms of motor neuron disease that can be divided into four body regions.
ALS is diagnosed with various degrees of certainty, and the researchers report that the system is sometimes at odds with clinical observations. For example, they mention that a patient could be classified as having possible ALS when physicians have in fact ruled out all other explanations for the symptoms. This, they state, could lead to confusion in discussions with patients.
Problems with ICD system
The ICD, however, can be particularly valuable when comparing data between research institutions. But the ICD is frequently revised, and as the classification of ALS and its symptoms is based on clinical findings, while no method exists for defining the classification, each ICD revision ends up differing substantially from the previous one.
Although the difference in symptoms and disease progression among patients may be used to identify treatments that benefit certain groups of patients, researchers stress that a good classification system should separate diagnosis and symptom classifications so that a diagnosis can be made with high certainty, while enabling the identification of patient groups when needed
Classification systems need to take into account the predominant type of motor involvement, the age of onset and disease progression, non-movement symptoms, and genetic and molecular biomarkers. Such a development depends on a deeper understanding of disease mechanisms, but all these factors are surrounded by interpretation and other types of difficulties.
For example, there are no definitions of what an early disease onset is, or how to determine that a type of ALS is familial. Since these definitions are up to the individual physician or researcher, it becomes difficult for studies to advance the general understanding of the disease.
To get around these obstacles, the researchers suggest that scientists and clinicians need to dramatically change how they think about ALS, particularly building new knowledge on multidisciplinary studies linking symptoms to genetic and molecular findings.
Standard description of ALS
As a first step toward a better classification system that is useful for both research and clinical practice, the team suggests a standard description of ALS. This description would need to have information on the clinical stage of the disease; any striking disease features such as young age of onset or slow progression; the balance between upper and lower motor neuron symptoms; and possibly the presence of relevant risk factors or biomarkers; and the certainty of ALS type according to the El Escorial criteria.
The diagnostic category could be further modified by adding information of a familial disease type, if the disease is found in a first-degree relative, or the presence of frontotemporal dementia.
This system, they argue, could provide key information in a systematic way, while allowing descriptions of disease manifestations. Future discoveries could be integrated into such a system, which also allows a precision approach to research and treatment since it provides clinicians and scientists with details about the cause, the balance of upper and lower motor neuron involvement, and clinical stage.
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