A Systematic Review of Parkinson’s Disease Cluster Analysis Research

Abstract

One way to understand the Parkinson’s disease (PD) population is to investigate the similarities and differences among patients through cluster analysis, which may lead to defined, patient subgroups for diagnosis, progression tracking and treatment planning. This paper provides a systematic review of PD patient clustering research, evaluating the variables included in clustering, the cluster methods applied, the resulting patient subgroups, and evaluation metrics. A search was conducted from 1999 to 2021 on the PubMed database, using various search terms including: Parkinson’s disease, cluster, and analysis. The majority of studies included a variety of clinical scale scores for clustering, of which many provide a numerical, but ordinal, categorical value. Even though the scale scores are ordinal, these were treated as numerical values with numerical and continuous values being the focus of the clustering, with limited attention to categorical variables, such as gender and family history, which may also provide useful insights into disease diagnosis, progression, and treatment. The results pointed to two to five patient clusters, with similarities among the age of onset and disease duration. The studies lacked the use of existing clustering evaluation metrics which points to a need for a thorough, analysis framework, and consensus on the appropriate variables to include in cluster analysis. Accurate cluster analysis may assist with determining if PD patients’ symptoms can be treated based on a subgroup of features, if personalized care is required, or if a mix of individualized and group-based care is the best approach.

Cluster Analysis of Categorical Variables of Parkinson’s Disease Patients

“…The intent of PD cluster analysis research is to understand the similarities and differences among patients, which may lead to patient subgroups that can assist with future diagnosis, as well as symptom and progression tracking and treatment. A systematic review of PD patient clustering research was conducted in [10], describing and critiquing the variables included in clustering, the cluster methods applied, the resulting patient subgroups, and the evaluation metrics. The majority of studies included a variety of clinical scale scores for clustering, which provide a numerical, but ordinal, categorical value, even though these values were treated as numerical variables, which was incorrect.…”

“…Furthermore, past cluster results pointed to two to five patient clusters; these values were predefined by the end users, with similarities among the clusters in regard to patient ages and disease durations, pointing to the possibility of excluding these limited-range values in future cluster analyses. The studies also lacked the use of existing clustering evaluation metrics to evaluate the separation of the resulting clusters [10].…”

Data-Driven Subtyping of Parkinson’s Using Acoustic Analysis of Sustained Vowels and Cluster Analysis: Findings in the Parkinson’s Voice Initiative Study

“…For this reason, data-driven approaches to define PD subtypes have received considerable attention in the PD research community over the last few years using cluster analysis [10][11][12][13][14][15]. In the following, we aim to provide a broad overview of studies published in this area placing emphasis on recent work, however, we remark we did not attempt to pursue a systematic literature review.…”

“…Extracting variables from different modalities or clinical instruments to present to clustering algorithms may potentially lead to new insights, however, it makes comparisons across studies particularly challenging and may explain discrepancies in the reported PD subtypes. For example, there is no clear consensus amongst experts on the number of subtypes or the clinical PwP characteristics within those subtypes: a recent systematic review in PD cluster analysis (summarizing the research literature published from 1999 to 2021) found that most studies report the presence of two to five clusters [13]. Almost all reviewed studies in [13] had used PD-specific clinical scales and diverse variables which were diverse across studies, e.g.…”

“…For example, there is no clear consensus amongst experts on the number of subtypes or the clinical PwP characteristics within those subtypes: a recent systematic review in PD cluster analysis (summarizing the research literature published from 1999 to 2021) found that most studies report the presence of two to five clusters [13]. Almost all reviewed studies in [13] had used PD-specific clinical scales and diverse variables which were diverse across studies, e.g. some have used variables extracted from imaging techniques, additional self-reports and tests assessing cognitive status, amongst others [13].…”