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| Content Provider | Springer Nature : BioMed Central |
|---|---|
| Author | Ouyang, Yongdong Li, Fan Li, Xiaojuan Bynum, Julie Mor, Vincent Taljaard, Monica |
| Abstract | Background Cluster randomized trials (CRTs) are increasingly important for evaluating interventions embedded in health care systems. An essential parameter in sample size calculation to detect both overall and heterogeneous treatment effects for CRTs is the intra-cluster correlation coefficient (ICC) of both outcome and covariates of interest. However, obtaining advance estimates for the ICC can be challenging. When trial outcomes will be obtained from routinely collected data sources, there is an opportunity to obtain reliable ICC estimates in advance of the trial. Using USA national Medicare data, we estimated ICCs for a range of outcomes to inform the design of CRTs for people living with Alzheimer’s and related dementias (ADRD). Method Data from 2018 Medicare Fee-for-Service beneficiaries, specifically, 1,898,812 individuals (≥ 65 years) with diagnosis of ADRD within 3436 hospital service areas (treated as clusters) and 306 hospital referral regions (treated as fixed strata), were used to calculate unadjusted and adjusted ICC estimates for three outcomes: death, any hospitalizations, and any emergency department (ED) visits and three covariates: age, race and sex. We present both overall and stratum-specific ICC estimates. We illustrate their use in sample size calculations for overall treatment effects as well as detecting treatment effect heterogeneity. Results The unadjusted overall ICCs for death, hospitalizations, and ED visits were 0.001, 0.010, and 0.017 respectively. Stratum-specific ICCs varied widely across the 306 HRRs: median 0.001, 0.010 and 0.025 for death, hospitalizations, and ED visits respectively and 0.007, 0.001, and 0.080 for age, sex and race. An interactive R Shiny app is provided that allows users to retrieve estimates overlayed on a map of the USA. Conclusions We presented both adjusted and unadjusted ICCs for outcomes as well as unadjusted ICCs for covariates of potential interest from population-level data in the USA and demonstrated how the estimates may be used in sample size calculations for CRTs in ADRD. |
| Related Links | https://trialsjournal.biomedcentral.com/counter/pdf/10.1186/s13063-024-08404-2.pdf |
| Ending Page | 10 |
| Page Count | 10 |
| Starting Page | 1 |
| File Format | HTM / HTML |
| ISSN | 17456215 |
| DOI | 10.1186/s13063-024-08404-2 |
| Journal | Trials |
| Issue Number | 1 |
| Volume Number | 25 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2024-10-30 |
| Access Restriction | Open |
| Subject Keyword | Medicine Public Health Biomedicine Statistics for Life Sciences Health Sciences Intra-cluster correlation coefficient Cluster randomized trials Interactive R shiny app Treatment effect heterogeneity Sample size calculation Power Medicine/Public Health |
| Content Type | Text |
| Resource Type | Article |
| Subject | Medicine Pharmacology (medical) |
| Journal Impact Factor | 2/2023 |
| 5-Year Journal Impact Factor | 2.1/2023 |
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