ReviewBMJ open2021
Minimal clinically important difference in means in vulnerable populations: challenges and solutions.
Review in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Minimal Clinically Important Difference (MCID) for the Short Musculoskeletal Function Assessment (SMFA) in Severe Lower Extremity Trauma: Pooled Data from 7 Multicenter, Prospective Clinical Trials.The Journal of bone and joint surgery. American volume · 2024Pooled it
- Efficacy of Mobile Instant Messaging-Delivered Brief Motivational Interviewing for Parents to Promote Physical Activity in Pediatric Cancer Survivors: A Randomized Clinical Trial.JAMA network open · 2022Trial
- Using Coding to Improve Executive Functioning in Children with Sickle Cell Disease: A Multiple-Baseline Single-Case Study.Journal of Intelligence · 2026Article
- Making Statistics Clinically Meaningful.Clinical epidemiology · 2026Review
- Do small effects matter more in vulnerable populations? an investigation using Environmental influences on Child Health Outcomes (ECHO) cohorts.BMC public health · 2024Article
- Perinatal Outcomes during versus Prior to the COVID-19 Pandemic and the Role of Maternal Depression and Perceived Stress: A Report from the ECHO Program.American journal of perinatology · 2024Article
- Minimal clinically important differences in six-minute walking distance in late-onset Pompe disease.Orphanet journal of rare diseases · 2024Article
- Relationship between risk factors for impaired bone health and HR-pQCT in young adults with type 1 diabetes.Frontiers in endocrinology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introduction and motivationMany health studies measure a continuous outcome and compare means between groups. Since means for biological data are often difficult to interpret clinically, it is common to dichotomise using a cut-point and present the 'percentage abnormal' alongside or in place of means. Examples include birthweight where 'abnormal' is defined as <2500 g (low birthweight), systolic blood pressure with abnormal defined as >140 mm Hg (high blood pressure) and lung function with varying definitions of the 'limit of normal'. In vulnerable populations with low means, for example, birthweight in a population of preterm babies, a given difference in means between two groups will represent a larger difference in the percentage with low birthweight than in a general population of babies where most will be full term. Thus, in general, the difference in percentage of patients with abnormal values for a given difference in means varies according to the reference population's mean value. This phenomenon leads to challenges in interpreting differences in means in vulnerable populations and in defining an outcome-specific minimal clinically important difference (MCID) in means since the proportion abnormal, which is useful in interpreting means, is not constant-it varies with the population mean. This has relevance for study power calculations and data analyses in vulnerable populations where a small observed difference in means may be difficult to interpret clinically and may be disregarded, even if associated with a relatively large difference in percentage abnormal which is clinically relevant.
methodsTo address these issues, we suggest both difference in means and difference in percentage (proportion) abnormal are considered when choosing the MCID, and that both means and percentages abnormal are reported when analysing the data.
conclusionsWe describe a distributional approach to analyse proportions classified as abnormal that avoids the usual loss of precision and power associated with dichotomisation.
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Registered trials
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.