Evidence map›Paper›PMID 33203468›Full record

ReviewTrials2020

Analysis and reporting of stratified cluster randomized trials-a systematic survey.

Sayem Borhan, Alexandra Papaioannou, Jinhui Ma, Jonathan Adachi, Lehana Thabane

Open access · goldAbstract readReview
In one paragraph

Review in Trials, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.2field-weighted citation impact, top 37% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Sayem BorhanDepartment of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada.ORCID http://orcid.org/0000-0002-2821-0849
Alexandra PapaioannouDepartment of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada.
Jinhui MaDepartment of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada.
Jonathan AdachiGERAS Centre, Hamilton Health Sciences, Hamilton, ON, Canada.
Lehana ThabaneDepartment of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada. ThabanL@mcmaster.ca.
Impact · CAHamilton Health Sciences · CASt. Joseph’s Healthcare Hamilton · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn order to correctly assess the effect of intervention from stratified cluster randomized trials (CRTs), it is necessary to adjust for both clustering and stratification, as failure to do so leads to misleading conclusions about the intervention effect. We have conducted a systematic survey to examine the current practices about analysis and reporting of stratified CRTs.

methodWe used the search terms to identify the stratified CRTs from MEDLINE since the inception to July 2019. In phase 1, we screened the title and abstract for English-only studies and selected, including the main results paper of the identified protocols, for the next phase. In phase 2, we screened the full text and selected studies for data abstraction. The data abstraction form was piloted and developed using the REDCap. We abstracted data on multiple design and methodological aspects of the study including whether the primary method adjusted for both clustering and stratification, reporting of sample size, randomization, and results.

resultsWe screened 2686 studies in the phase 1 and selected 286 studies for phase 2-among them 185 studies were selected for data abstraction. Most of the selected studies were two-arm 140/185 (76%) and parallel-group 165/185 (89%) trials. Among these 185 studies, 27 (15%) of them did not provide any sample size or power calculation, while 105 (57%) studies did not mention any method used for randomization within each stratum. Further, 43 (23%) and 150 (81%) of 185 studies did not provide the definition of all the strata, while more than 60% of the studies did not include all the stratification variable(s) in the flow chart or baseline characteristics table. More than half 114/185 (62%) of the studies did not adjust the primary method for both clustering and stratification.

conclusionStratification helps to achieve the balance among intervention groups. However, to correctly assess the intervention effect from stratified CRTs, it is important to adjust the primary analysis for both stratification and clustering. There are significant deficiencies in the reporting of methodological aspects of stratified CRTs, which require substantial improvements in several areas including definition of strata, inclusion of stratification variable(s) in the flow chart or baseline characteristics table, and reporting the stratum-specific number of clusters and individuals in the intervention groups.

Indexed as

Research DesignResearch ReportCluster AnalysisHumansRandomized Controlled Trials as TopicSample SizeCluster randomized trialRandomized trialStratificationStratified clusterSystematic survey

Identifiers

PMID33203468
PMCPMC7672868
OpenAlexW3102879733

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.