Systematic Review and Meta-Analysis of Combination Therapy with Cholinesterase Inhibitors and Memantine in Alzheimer’s Disease and Other Dementias
Bibliographic record
Abstract
BACKGROUND: N-methyl-D-aspartic acid antagonists (memantine) and cholinesterase inhibitors (ChEIs) are the only two approved classes of drugs to treat dementia; this paper explores the evidence for using these two treatments in combination. OBJECTIVE: To determine the efficacy and safety of using combination therapy with memantine and a ChEI to treat dementia in comparison to monotherapy with either memantine or a ChEI. METHODS: In March 2012, we systematically searched MEDLINE/PubMed, EMBASE, Cochrane library, and grey literature databases. All study types were included, except for case series or reports, which looked at combination therapy versus monotherapy in various dementing disorders. Data was pooled for blinded randomized controlled trials (RCTs) only; mean differences and standardized mean differences were used to determine effect sizes. RESULTS: Thirteen studies were included in this review; 3 were blinded RCTs, with a total of 971 Alzheimer's disease (AD) patients, which were included into the meta-analysis. No papers were found that primarily addressed combination therapy in other dementias. In the meta-analysis, small but statistically significant effect sizes were seen in favor of combination therapy among patients with moderate to severe AD on the scales of cognition (0.45-0.52; p < 0.0001), scales of functional outcomes (0.23-0.3; p < 0.01), and the neuropsychiatric inventory (3.7-4.4; p < 0.0001). Among the open-label studies, 3 out of 6 suggested benefits, as did the 4 included cohort studies. However, the high risk of bias encountered in the latter two study designs limits deducing any conclusions about benefit. CONCLUSION: Although there were statistically significant changes in favor of combination therapy in moderate to severe AD, heterogeneity in scales and patient characteristics exists. However, it is unclear if clinically significant outcomes can be achieved using the combination therapy. More studies are required before a recommendation for combination therapy can be made.
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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 | 0.019 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.044 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".