Can a decision support system accelerate rare disease diagnosis? Evaluating the potential impact of Ada DX in a retrospective study

Abstract

Background: Rare disease diagnosis is often delayed by years. A primary factor for this delay is a lack of knowledge and awareness regarding rare diseases. Probabilistic diagnostic decision support systems (DDSSs) have the potential to accelerate rare disease diagnosis by suggesting differential diagnoses for physicians based on case input and incorporated medical knowledge. We examine the DDSS prototype Ada DX and assess its potential to provide accurate rare disease suggestions early in the course of rare disease cases. Results: Ada DX suggested the correct disease earlier than the time of clinical diagnosis among the top five fit disease suggestions in 53.8% of cases (50 of 93), and as the top fit disease suggestion in 37.6% of cases (35 of 93). The median advantage of correct disease suggestions compared to the time of clinical diagnosis was 3 months or 50% for top five fit and 1 month or 21% for top fit. The correct diagnosis was suggested at the first documented patient visit in 33.3% (top 5 fit), and 16.1% of cases (top fit), respectively. Wilcoxon signed-rank test shows a significant difference between the time to clinical diagnosis and the time to correct disease suggestion for both top five fit and top fit (z-score-6.68, respective-5.71, α=0.05, p-value <0.001). Conclusion: Ada DX provided accurate rare disease suggestions in most rare disease cases. In many cases, Ada DX provided correct rare disease suggestions early in the course of the disease, sometimes at the very beginning of a patient journey. The interpretation of these results indicates that Ada DX has the potential to suggest rare diseases to physicians early in the course of a case. Limitations of this study derive from its retrospective and unblinded design, data input by a single user, and the optimization of the knowledge base during the course of the study. Results pertaining to the system's accuracy should be interpreted cautiously. Whether the use of Ada DX reduces the time to diagnosis in rare diseases in a clinical setting should be validated in prospective studies.

Increasing Incidence of Liposarcoma: A Population-Based Study of National Surveillance Databases, 2001–2016

“…Differences between SEER and CNCPR findings emphasize the need for nationwide cancer surveillance.have a considerable impact on the overall cancer outcomes. Limited treatment options, high costs of existing treatments, and frequent misdiagnosis of rare cancers burden patients, physicians, and health systems [4]. The lack of epidemiological knowledge about the risk factors associated with many rare cancers precludes the development of viable prevention, making it one of the most dramatic unresolved public health problems [1,3,5].…”

“…The existing gaps in research and treatment are reflected in rare cancer survival rates. The 5-year survival for rare cancers is worse compared to common cancers: 49% vs. 63% in Europe [5]; and the U.S., 55% vs. 75% among males and 60% vs. 74% among females [4]. In light of these facts, population-based surveillance of rare cancers and their descriptive epidemiology provide the foundation for advancing etiological and clinical research with the ultimate goal of reducing the public health burden of rare cancers.This research focuses on the under-studied rare cancer liposarcoma.…”

Artificial Intelligence (AI) in Rare Diseases: Is the Future Brighter?

“…Although medicine has entered the genomic era with NGS, the molecular cause of many diseases is often hard to determine. Hence, clinical phenotype is an invaluable resource for accurate and faster diagnosis of RDs [4]. Electronic health records (EHR) and biomedical literature contain extensive clinical information with huge potential in the development of decision support systems (DSS).…”

“…Ada XD RD patients' dataset derives from manually annotated and continuously updated EHR and medical literature data. In contrast to the aforementioned DDSS, Ada XD does not require a unique/specific nomenclature (e.g., HPO) [4].…”

“…About 80% of RDs have a genetic origin and approximately 75% affect children [1,2]. Although individually rare, collectively, RDs are estimated to affect 350 million people globally [3,4].…”