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Conduct Science promotes new generations of tools for science tech transferred from academic institutions including mazes, digital health apps, virtual reality and drones for science. Our news promotes the best new methodologies in science.
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Real-world Data in Parkinson’s Disease Explained

Real-world evidence is essential in medical research. Real-world data has numerous benefits over randomized controlled trials, particularly in studying Parkinson’s disease. In fact, Parkinson’s is one of the most prevalent neurodegenerative diseases worldwide, with no current treatments being able to cure the disease. Only in the US, there are more than 630,000 people affected by this condition (Tanguy, Jonsson & Ishihara, 2017).

Since managing Parkinson’s disease can be challenging, with symptoms fluctuating daily and between patients, collecting health-related data in real time is vital. Note that real-world data is defined as medical information collected in non-experimental environments. Sources vary from administrative claims to social media channels. Data across real-life settings and diverse populations can provide valuable insights into disease progression, natural history of the disease, treatment programs, and socioeconomic burdens. It can reveal important aspects of the daily lives of people with Parkinson’s disease and the effectiveness of novel treatments. Consequently, longitudinal real-world data can improve interoperability, Parkinson’s disease management, and financial decisions.

Real-world Data and Areas of Assessment in Parkinson’s Disease

Research in the field of oncology is sensitive and challenging. Note that there are various cancer treatments, with radiation therapy and chemotherapy being among the most common interventions (“Types of Cancer Treatments,” 2017). With the increasing use of digital health solutions and experimental cancer therapies, though, real-world data can support numerous aspects of medical research and routine clinical practice. Some of its applications include:

Parkinson’s disease is a complicated medical condition, defined as a central nervous system disorder. The wide range of symptoms and complications requires the use of different measurements for the effective management of the disease. Interestingly, a recent literature review explored the benefits of various Parkinson’s disease measurements, classified into the following dimensions of assessment (Tanguy, Jonsson & Ishihara, 2017).

  • Motor and neurological function: Parkinson’s disease, as explained earlier, is a complex disorder of the central nervous system. Common symptoms include shaking, difficulty with walking, and rigidity (Opara et al., 2017). Patients are also prone to falls. Comparing motor tests is one of the most significant indicators employed in Parkinson’s research. There are various motor assessments (e.g. of hand function), such as the Hoehn and Yahr stages of progression of the disease, the Unified Parkinson’s Disease Rating Scale, and the Timed Up and Go Test. Note that the latest advancements in medical technology allow the three-dimensional analysis of gait and movement in participants. Since motor symptoms affect patients’ daily living and quality of life, real-world data is needed to improve Parkinson’s disease assessment and treatment options. Note that preventing falls is one of the leading goals in routine clinical practice.
  • Cognition: Cognitive changes also occur in patients with Parkinson’s disease, especially in the late stages of the disease (Romann et al., 2012). Although there are various medications and existing treatments, delaying Parkinson’s symptoms is still a challenge in medical research. As mentioned earlier, there’s no cure for Parkinson’s; each patient receives treatment based on their individual symptoms. Note that in some cases, Parkinson’s treatments (e.g., deep brain stimulation) may worsen a patient’s cognitive functioning. Some of the common tools used to assess dementia in Parkinson’s patients include the Clock Drawing Test, Stroop Test, Digit Span, Trail Making Test, Wisconsin Card Sorting Test, and Verbal Fluency Test. In addition, real-world evidence can provide a comprehensive picture of one’s cognitive abilities and changes.
  • Psychiatric symptoms: Psychiatric symptoms can also be observed in Parkinson’s disease. Neuropathological findings indicate that brain dysfunction, medications, and the impact on daily living can lead to psychotic episodes, shame, and depression. Common scales to assess this dimension in patients with Parkinson’s include the Beck Depression Inventory, Parkinson Psychosis Questionnaire, Clinician Global Impression of Change, and Geriatric Depression Scale. Interestingly, when it comes to depression, statistics show that 40% of Parkinson’s patients experience depression and distress. Real-life data can benefit Parkinson’s research, including patient health outcomes.
  • Activities of daily living: Parkinson’s disease has a negative impact on daily living, especially in the late stages of the disease (Lee et al., 2016). Basic activities, such as feeding, bathing, and dressing, can be severely affected. Hence, the caregiver’s role is vital. Since Parkinson’s is a progressive neurological condition, real-world data is essential for the assessment of disease management and treatment. The Unified Parkinson’s Disease Rating Scale and self-reported outcomes are among the most popular tools used to study Parkinson’s disease and its impact on daily living.
  • Sleep quality: Sleep quality in patients with Parkinson’s disease declines over time (“Sleep disorders in Parkinson’s disease: Diagnosis and management,” 2011). Note that the Epworth Sleepiness Scale Sleep, the Apnea Scale of Sleep Disorders Questionnaire, and the Parkinson’s disease sleep scale can be utilized to assess this domain in patients with Parkinson’s disease. In addition, polysomnography can provide valuable clinical insights into a patient’s sleep patterns and symptoms. Interestingly, practice shows that the bed partner can also be affected (e.g., due to limb movements that prevent them from sleeping). Thus, longitudinal real-world data is needed to benefit patients and families.
  • Treatment: Although various treatments and medications (e.g., dopamine agonists) exist, Parkinson’s disease still challenges researchers and practitioners. Note that Levodopa is among the most effective medications to treat Parkinson’s. Research, however, shows that some medications can cause severe side effects. Therefore, Parkinson’s disease rehabilitation (including speech therapy, physiotherapy, and education) is becoming a leading approach in research. Real-world data, such as administrative claims, can provide beneficial information about treatment effectiveness, adherence, and long-term effects.
  • Quality of life: Quality of life is one of the main areas of digital health research. Real-world data can be utilized to improve patients’ quality of life. Since Parkinson’s disease leads to numerous symptoms, such as shaking, depression, and dementia, patients report low levels of quality of life (Opara et al., 2012). We should note that the quality of life is a complex construct, which includes physical, mental, and social aspects. It’s not surprising that the quality of life is becoming one of the leading factors in digital health research. Satisfaction with treatment, self-image, and social support also influence a patient’s well-being. Subjective measures are usually employed to measure the quality of life in patients with Parkinson’s disease. Assessments such as the Quality of Life in Neurological Disorders, 39-item Parkinson’s Disease Quality of Life, and 36-item Short Form can be utilized to measure a patient’s well-being and treatment effectiveness.
  • Autonomic symptoms: Research shows that autonomic symptoms in Parkinson’s disease include blood pressure, constipation, swallowing, sweating, and sexual dysfunction. Note that autonomic s