Burden of Disease and Current Management of Dementia with Lewy Bodies: A Literature Review
Bibliographic record
Abstract
INTRODUCTION: A significant proportion of dementia is concretely estimated to be attributable to dementia with Lewy bodies (DLB)-one of the most common types of progressive dementia; however, there is a paucity of literature on this disease. We aimed to examine available evidence to gain a better understanding of its treatment landscape, clinical management, and disease burden. METHODS: A systematic literature review captured any DLB studies that report on randomised controlled trials (RCTs), epidemiology, disease progression, and economic data. An additional targeted literature review captured studies reporting on clinical management and quality of life (QoL) in this disease. Publication date was limited to 1 January 2007-26 March 2018, with the exception for RCTs, where no time restrictions were applied. FINDINGS: Of the 3486 studies initially identified, 55 studies were eligible for inclusion. The studies were mainly from Europe (n = 29), the USA (n = 9), and Japan (n = 8). Mini-Mental State Examination and Neuropsychiatric Inventory scores were the most commonly reported clinical outcomes in RCTs (n = 14). The most frequently identified interventions reported in RCTs were donepezil and memantine. Patients with DLB typically reported worse outcomes in relation to efficacy and safety, cognitive impairment, survival, and QoL compared with those with Alzheimer's disease (AD). Additionally, patients with DLB were associated with higher hospitalisation rates and cost of care. Furthermore, there is a reliance on a small number of consensus guidelines. Of these, only one set of guidelines (DLB Consortium) was developed specifically for DLB. CONCLUSION: The paucity of data indicates an unmet need in this therapy area. Although several studies look into the clinical and pathological aspects of DLB, consensus guidelines and studies on healthcare utilisation in patients with dementia have largely focused on AD. Additionally, most of the findings were made in comparison with AD. FUNDING: Eisai Inc.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.019 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".