Sophie Laurenson, PhD
In the US, an orphan disease is defined as a medical condition that affects less than 200,000 people across the country. Worldwide, there are estimated to be approximately 7,000 diseases that can be classified as orphan diseases. These rare diseases can be difficult to diagnose. A recent study in Germany suggested that the mean time to diagnosis is around six years, and that during this period, a patient may receive multiple incorrect diagnoses.
In 2013, a survey commissioned by Global Genes, a leading patient advocacy organization focusing on rare diseases, revealed “an urgent need to bridge the knowledge gap by educating and connecting patients, families, physicians, and specialists.” The associated report highlighted several key points affecting diagnosis of rare diseases. The survey showed that the majority of physicians welcomed the challenge of diagnosing and treating rare diseases. However, 40 percent of primary care providers and 24 percent of specialists reported that they do not have adequate time to perform a clinical workup on patients, even when a rare disease is suspected. Furthermore, almost half of the 805 patients analyzed agreed with the statement: “Because of a slow diagnosis, treatment was delayed and the impact on my condition has been negative.”
As a step toward shortening time to diagnosis, Global Genes encourages patients to educate themselves and their healthcare providers about novel diagnostics technologies, such as genetic testing. The Undiagnosed Patient Program was launched to expand access to specialist testing for patients seeking a diagnosis.
Studies such as these highlight the social and economic imperative to improve the diagnosis of rare diseases. In response, several organizations have attempted to use clinical informatics and data analytics techniques to help patients accurately diagnose their symptoms. Examples include FindZebra.com and Orphanet, both freely available tools to assist in rare disease identification. Orphanet provides a portal for users to search out laboratory tests that could aid in rare disease diagnosis. In addition, they maintain a list of clinical labs that are capable of performing diagnostic tests for orphan diseases.
For some patients, engaging with an institute conducting clinical research into orphan diseases may be a route to diagnosis. The Undiagnosed Diseases Network (UDN) is a network of clinical centers across America, engaged in research around rare diseases. Its goal is to bridge the gap between research and clinical care by analyzing genetic data and clinical samples as well as training healthcare providers in new approaches to diagnostics.
Most of the initiatives described above place the onus on the patient to acquire an accurate diagnosis for their condition in order to receive appropriate treatment. By contrast, the Rare and Undiagnosed Diseases Diagnostic Service (RUDDS) in Western Australia is a laboratory service offering genomic analysis to assist in the diagnosis of orphan disease—the only government-run service of its kind. Their aim is to transform previously specialized genomic services into routine clinical care. With advances in Next-Generation Sequencing (NGS), these platforms have potential to find their way into mainstream laboratory analysis.
The challenge with new diagnostic platforms and methods of analysis is to integrate them into medical practice. Laboratory tests are becoming increasingly complex, often providing reems of data that healthcare providers may have difficulty interpreting. This presents an opportunity for clinical laboratories to offer value-added services to healthcare providers such as educational materials and clinical decision support tools that assist physicians in making accurate diagnoses. These tools can be adapted to map clinical pathways and optimize treatment selection, by underscoring the relevance of test results to a patient’s ailment.
Access to real-world data from genetic tests, biomarker studies, and clinical tests, as well as patient medical histories uniquely positions clinical laboratories within the healthcare system. Laboratories can leverage this data to provide even greater value to healthcare providers by adding context to a patient’s test results. This could be achieved by framing patient data in the context of the wider population or other patients with similar data points. In this way, clinical labs have an opportunity to add value and differentiate their service offering to the healthcare providers who order lab testing.