Assessment of Methods Used in Evaluating Balance Rehabilitation in Parkinson's Patients: Determination of Responsiveness and Minimal Clinically Important Difference Values
Assessment of Methods Used in Evaluating Balance Rehabilitation in Parkinson's Patients: Determination of Responsiveness and Minimal Clinically Important Difference Values
Balance rehabilitation holds an important place in the treatment of Parkinson's patients. Before and after treatment, patients are evaluated using various measurement methods. In calculations of changes post-treatment, although statistically significant changes are detected, clinical differences are often not observed. Jaeschke et al. developed the concept of minimal clinically important difference (MCID) to address this. They have worked on methods to determine the level of MCID. These measurements help clinicians understand which results can be interpreted as clinically meaningful for the patient.
Responsiveness refers to how sensitive a measurement tool is to changes, whereas MCID focuses on determining whether these changes are clinically significant. Both concepts are crucial for understanding and interpreting the performance of measurement tools.
Identifying which patients have a high risk of balance problems and falls, and screening those at risk, is important for making treatment decisions. Determining which change values are clinically significant (MCID) and identifying which tests are more sensitive in detecting changes (responsiveness) are essential in monitoring patients.
Parkinson's disease (PD) is a chronic progressive neurodegenerative disease characterized by the degeneration or loss of dopaminergic neurons in the nigrostriatal and other neuronal systems, along with the formation of Lewy bodies in dopaminergic neurons, and it manifests with both motor and non-motor symptoms and findings. It is the second most common neurodegenerative disease after Alzheimer's disease. The average onset age is between 60-80 years. It is more commonly seen in men and the white race. In Turkey, the prevalence has been reported as 111/100,000. In societies where the average lifespan is increasing, the frequency of PD and the associated economic burden are also expected to increase.
The etiology of Parkinson's disease includes environmental, genetic, and aging-related processes. These factors trigger mechanisms leading to neuron degeneration and loss, causing PD.
The clinical presentation of Parkinson's disease consists of motor and non-motor symptoms and findings. The main motor symptoms are bradykinesia, rigidity, postural instability, and resting tremor. Other observed findings include akinesia, freezing phenomenon, postural and gait disorders, reciprocal movement disorder, masked facial expression, impaired orofacial functions and speech, swallowing disorder, respiratory function impairment, loss of hand dexterity, and coordination. Cognitive impairments, depression, sleep disorders, autonomic dysfunction, loss of smell, fatigue, and sialorrhea are among the non-motor symptoms.
Patients with primary motor findings and accompanying symptoms are evaluated using the Parkinson's Disease United Kingdom Brain Bank Criteria and the National Institute of Neurological Disorders and Stroke (NINDS) diagnostic criteria. A definitive diagnosis is made by pathologically demonstrating Lewy bodies in a biopsy. The Hoehn-Yahr Scale is frequently used to determine the severity of the disease.
The treatment of Parkinson's disease includes medical treatment, surgical treatment, and rehabilitation. Rehabilitation plays an important role at all stages of PD. In the early stages, it helps maintain well-being and improve general conditioning; in the later stages, it is crucial for coping with motor and non-motor complications.
Postural instability and balance disorders in Parkinson's patients lead to sudden falls, progressive disability, and immobility. Patients' fear of falling causes them to limit their activities, which increases immobility and balance problems. Preventing falls and maintaining mobility should involve a multidisciplinary treatment and rehabilitation program. Various rehabilitation approaches are available, including conventional therapy, music therapy, aquatic therapy, dance therapy, virtual reality therapy, robot-assisted gait therapy, and tai chi. Many studies in the literature evaluate the effectiveness of rehabilitation approaches aimed at balance and mobility in Parkinson's disease.
Balance disorders are a significant motor problem in individuals with PD. It is necessary to identify at-risk patients through appropriate tests and to organize treatment accordingly. Although there are many scales available to evaluate patients' balance to determine their rehabilitation needs, there is no clarity on which scale(s) are more sensitive in assessing changes. Additionally, knowing which change scores in the scales the investigators use are clinically significant is important for evaluating treatment outcomes. Knowing the sensitivity and minimal clinically important difference (MCID) values of tests for balance and fall concerns in Parkinson's patients can guide clinicians in selecting scales for screening patients before treatment and understanding which changes are clinically significant when evaluating outcomes after treatment.
In 1989, Jaeschke et al. developed the concept of minimal clinically important difference (MCID). Jaeschke and colleagues noted that, while statistically significant changes were often detected in post-treatment change calculations, clinically significant differences were not observed and attempted to determine the smallest clinically important change level. This allowed patients to directly participate in the process of evaluating their condition. These measurements help clinicians understand which treatments yield better results. MCID is the smallest change that a patient would identify as important and that would indicate a difference in the patient's management. After R. A. Fisher defined the p-value and the 0.05 cutoff point, all clinical studies began to evaluate whether results were statistically significant, but the p-value, despite being an objective result, has two major issues. One is failing to detect a difference due to insufficient sample size despite an important difference (Type II error), and the other is that the statistically significant difference does not actually represent a meaningful change for the patient. Therefore, statistical significance may not carry clinical importance. MCID helps clinicians determine whether a treatment has a meaningful effect on the patient. Additionally, MCID is a valuable tool in planning scientific studies and calculating sample size. Understanding the minimal clinically important difference helps researchers design studies that are both significant and applicable to clinical practice. In summary, MCID is a critical concept that bridges clinical practice and research, emphasizing the impact of treatments from the patient's perspective. Understanding and applying MCID is essential for making correct treatment decisions and conducting meaningful scientific studies in healthcare. It is important to remember that the concept of MCID is variable and can differ between health conditions. In recent years, clinicians and researchers have started to focus on patient-reported outcome assessments.
The investigators also aim to determine the MCID values of measurement tools used to evaluate balance in Parkinson's disease in our study.
There are two commonly used methods for calculating MCID:
Anchor-based approach Distribution-based approach In the anchor-based approach, a comparison is made between a result measure reflecting the patient's condition (e.g., post-treatment measurement value) and an external criterion. This external criterion can be the patient's own perception or the clinician's assessment. In this method, changes between scores are compared with an anchor question that serves as a reference to determine whether the patient has improved compared to baseline. To understand the perception of change, a global rating scale ("much worse," "a little worse," "almost the same," "a little better," and "much better") can be used. The anchor question should be easily understandable and relevant to patients.
The distribution-based approach attempts to estimate the likelihood that a detected difference in measurement tools is meaningful. It uses statistical data such as fractions of standard deviation, effect size, and mean standard error. It does not include the perceptions based on the experiences of experts or patients. Since it does not include individual patient perceptions, it should not be the first choice for determining MCID. In this method, as there is no anchor question to evaluate what is important for patients, significant and clinically meaningful results cannot be defined. In fact, scores calculated with distribution-based methods are sometimes referred to as "minimal detectable change" instead of MCID. Therefore, this method is not recommended as the first choice for determining MCID.
However, some authors have suggested that a single MCID value can be misleading and that providing a range might be more appropriate. For this reason, in our study, the investigators will use both anchor-based and distribution-based approaches to calculate MCID, aiming to find a range of values. In the anchor-based approach, the investigators plan to use two anchor questions: a patient-based and a clinician-based global assessment scale.
Responsiveness refers to the ability of a measurement tool to detect true changes among individuals. A sensitive scale responds accurately to the changes experienced. Responsiveness is typically assessed using statistical analyses such as effect size and standard deviation and is used to evaluate the performance of measurement tools.
While responsiveness indicates how sensitive a measurement tool is to changes, MCID indicates whether these changes are meaningful from the patient's or clinician's perspective. In other words, a responsive measurement tool has the potential to capture clinically significant changes. Both concepts are important for understanding and interpreting the performance of measurement tools. Determining the responsiveness and MCID of a measurement tool provides clinicians with a more comprehensive assessment in research studies and patient follow-up.
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