Clinical Effectiveness of Body Fat Distribution Imaging in Real-World Practice: The BODY-REAL Study: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Clinical Effectiveness of Body Fat Distribution Imaging in Real-World Practice: The BODY-REAL Study (NCT04763772), a randomized na study. The primary outcome is Change in BMI.

2. Clinical Question

The central statistical question is not simply whether participants’ BMI changed. It is whether the pattern of change differed across the randomized combinations of detailed versus basic reporting and participant- versus physician-directed delivery. The trial’s pragmatic focus is reflected in its interest in real-world feasibility and utility, but the registry record does not give detailed feasibility outcomes. It also does not report a separate primary statistical contrast for each factorial component. The results should therefore be read as a small pilot record with an endpoint and four listed groups, rather than as a definitive test of each possible effect of report content and delivery.

3. Trial Design

BODY-REAL is listed as a randomized, single-masked, factorial pilot trial. Its summary describes a 2x2 factorial design: one factor concerns detailed body-fat information versus basic weight information, and the other concerns whether the report is directed to the participant or the physician. The listed arms combine these two factors: Detailed Report + Patient Provided, Basic Weight Information + Patient, Detailed Report + Doctor Provided, and Basic Weight Information + Doctor Provided. In this description, “provided” is part of the arm label in the registry; the practical distinction is who receives the report directly.

The registry records enrollment of 29. The arm-level results list sample sizes of 6, 8, 8, and 7, respectively. Randomization procedures, allocation concealment, the identity of the masked party, and details of how the factorial design was analyzed are not reported in the registry record. Phase is listed as NA. The trial is marked completed, with a start date of 2021-11-01 and primary completion date of 2024-07-31.

The primary endpoint is change in BMI at 6 months. The registry lists least-squares mean estimates and 95% confidence intervals for each arm. It also reports a linear regression analysis using the four listed groups, with a mean difference in final values. The exact contrast represented by that regression result and any covariates included in the model are not reported in the registry record. Consequently, it is not possible to treat that result as a clearly specified factorial effect or as an unambiguous comparison of one particular pair of arms.

The record lists one outcome measure and one analysis. It does not describe planned interim analyses, a detailed statistical analysis plan, or a sample-size justification for the trial itself. The study’s pilot purpose and small arm sizes are important context: estimates can be imprecise, and the registry results do not establish how the design was intended to support confirmatory conclusions.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Change in BMI, measured over 6 months.

The primary endpoint is change in body mass index between groups at 6 months, expressed in kg/m2. BMI is a continuous measure calculated from weight and height; change captures how the measure differs from its starting value over the stated follow-up period. A continuous endpoint preserves the size and direction of the measured change rather than classifying participants only as having or not having an event.

The registry reports least-squares mean estimates for each group. In general, a least-squares mean is a model-based estimate of a group mean, potentially adjusted for variables included in the model. The registry does not identify any adjustment variables for the arm-level estimates, so the specific adjustment cannot be described. It also does not provide baseline BMI values or explain how the change was calculated for individual participants.

BMI is relevant to the study’s stated interest in whether body-fat imaging and reporting might be followed by changes in behavior and clinical outcomes. However, BMI does not directly measure body-fat distribution. The detailed report is intended to communicate information about body composition, while the endpoint is a change in BMI. The outcome therefore captures one clinical measure, not every aspect of risk perception, behavior, body composition, or feasibility named in the study summary. Those other outcomes are not posted as secondary results in the registry record.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

What does a least-squares mean represent?

In general, a least-squares mean is an estimate derived from a statistical model. It can differ from a simple arithmetic average when the model includes adjustment terms or accommodates the study design. The registry identifies the arm results as least-squares means, but does not state the model specification or list adjustment variables. It is therefore safest to describe these as model-based arm estimates and not to assume that they are adjusted for any particular participant characteristic.

The reported arm estimates describe change in BMI. A group’s estimate is not itself a between-group effect. A comparison requires a defined contrast, such as subtracting one group’s estimated change from another’s or estimating a factorial effect across groups. No such contrast can be calculated from the arm summaries without making additional assumptions. The separately posted regression analysis is a between-group result, but the registry does not specify which exact contrast it represents.

How should the confidence intervals be read?

In general, a confidence interval conveys uncertainty around an estimate under the statistical model and its assumptions. It is not a range that guarantees the true effect lies inside it, nor does it give the probability that a particular value is true. The interval is most informative when read with the estimate, endpoint, analysis population, and comparison it belongs to. The regression result is -4.5, with a 95% confidence interval from -14 to 4.8. Because this interval includes zero, the reported estimate is compatible with no difference as well as with differences in either direction. Its breadth also signals limited precision.

The arm-specific intervals are attached to the mean changes, not to contrasts between arms. A confidence interval for one arm’s estimate cannot be substituted for an interval for a difference between that arm and another. The intervals reported as 0.0 to 0.0 for the two basic-information arms warrant particular caution: the record gives no explanation of the method or reason for those degenerate intervals. They should not be taken to demonstrate perfect precision.

What does the regression result say?

The registry identifies the analysis method as linear regression and the reported parameter as a mean difference in final values. Linear regression, in general, models a continuous outcome in relation to one or more predictors. Its meaning depends on how the groups are coded, which terms are included, the outcome scale, and any adjustment variables. The record gives the estimate, interval, and p-value, but does not report these details. It also does not make clear how a final-value comparison relates to the arm-level estimates of change. Thus, the regression result should be quoted as reported and not recast as a specific factorial effect.

A p-value is a measure of how inconsistent the observed data are with a specified null model, assuming that model and analysis assumptions hold. It is not the probability that the null hypothesis is true, and it does not measure the size or importance of an effect. The reported p = 0.2 does not establish that the groups are equivalent or that an effect is absent. The interval and the limited precision are essential parts of interpretation.

How does the factorial structure matter?

In general, a factorial design can estimate the effects of more than one study factor within one trial. Here, the listed factors are report content and the route by which the report is directed. Analysis can examine the effect of each factor and whether their effects interact, but the interpretation depends on the specific model and planned contrasts. The registry does not report those details. It would therefore be inappropriate to infer separate effects of detailed imaging, report delivery, or an interaction from the listed arm estimates alone.

The method for allocation, treatment of missing observations, handling of any departures from assigned groups, and the analysis population are not reported in the registry record. These details affect how a model-based result should be understood. The registry also does not provide standard errors or dispersion measures for the arm estimates, beyond the confidence intervals.

What are the sample-size illustrations?

In general, sample-size planning estimates how many participants may be needed for a future study under stated assumptions. The registry’s planning assumptions describe a two-sided significance level of 0.05, equal allocation, and a normal approximation, with the effect to detect expressed as a stated fraction of the observed effect. Such planning figures are illustrations based on those assumptions, not observed power and not evidence that the current trial had a particular design target. The trial’s own sample-size justification is not reported in the registry record. Planning outputs should therefore be read as hypothetical design aids, not as a retrospective measure of how likely the trial was to find a result.

10. Analyses Reported by the Sponsor

The registry’s reported inferential result is the linear regression analysis: mean difference in final values -4.5, 95% confidence interval -14 to 4.8, and p = 0.2. The registry record does not describe the exact contrast, model terms, or covariate adjustment, so that result should not be assigned to a particular comparison beyond the groups listed in the analysis.

The arm-level least-squares mean changes offer a different view: they describe estimates within each group rather than a single between-group contrast. They do not independently reproduce the regression result, and the record does not give the information needed to calculate a matching unadjusted comparison from the arm summaries. A separate recalculated two-arm result is not estimable from the posted information, as indicated by the record’s note that values are missing or not estimable for a two-arm comparison of this continuous endpoint.

No discrepancy is flagged between the reported analysis and a recalculation. The appropriate reading is therefore to retain the registry’s regression estimate as the posted analysis, while recognizing that its contrast is insufficiently described for a more specific interpretation. The arm-level estimates and intervals provide context, but they should not be used to reverse-engineer or replace the reported model result.

11. Multiplicity, Missing Data and Analysis Populations

The registry lists one primary outcome measure and one analysis, and no secondary outcomes are posted. It does not report a multiplicity plan, such as whether any adjustment was intended for multiple outcomes, comparisons, or factorial effects. The single listed outcome does not establish that only one hypothesis or contrast was examined; details of the analysis plan are not reported in the registry record. The p-value should consequently be read as the result attached to the posted regression analysis, not as proof that all possible comparisons were prespecified or controlled for multiplicity.

Missing-data handling is not reported in the registry record. The record does not explain whether every randomized participant had a six-month BMI assessment, how missing follow-up measurements were handled, or whether any imputation or other method was used. The participant counts attached to the arm estimates are listed, but the record does not clarify whether these represent all randomized participants, all participants with endpoint data, or the analysis population for the regression. Reasons for missing observations or exclusions are also not reported.

The analysis population is not reported in the registry record. It is not possible to determine from the posted information whether the analysis followed all randomized participants according to assigned group, included only participants with observed outcomes, or used another rule. The registry also does not report interim analyses, stopping criteria, prespecified subgroup analyses, or a detailed statistical analysis plan. These omissions limit assessment of how completely the posted result represents the trial’s intended analysis.

In general, multiplicity and missing-data decisions can affect uncertainty and the interpretation of a p-value. Without the relevant plans and participant-flow details, the result should be treated as the analysis reported in the registry rather than as a fully documented account of all analyses performed.

12. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

The adverse-event record lists zero serious adverse events and zero other adverse events in each of the four groups. The numbers at risk are listed as 6, 8, 8, and 7, respectively, and deaths are listed as zero for every group. These are counts in the registry, not estimates of the likelihood of an event beyond the recorded trial experience.

Zero recorded events do not establish that an event is impossible or that the intervention is free from risk. In a small study, the observation of no events provides limited information about uncommon outcomes. The record does not describe adverse-event definitions, collection procedures, follow-up duration for safety, or whether events were assessed for relation to an intervention. It also does not give additional detail about the monitoring process.

The safety figures should therefore be understood narrowly: no serious or other adverse events and no deaths are listed for the participants at risk in the registry’s adverse-event summary. They do not establish a comparative safety advantage among the groups, particularly because the groups are small and the record does not report a formal safety comparison.

13. What the Result Does, and Does Not, Mean

The posted results describe a pilot trial of detailed body-fat reporting and basic weight information, with reports directed either to participants or physicians. The primary outcome is six-month change in BMI. The arm-level estimates vary, and their confidence intervals are broad for the groups with nonzero estimates. The reported regression result has an estimate of -4.5, a 95% confidence interval from -14 to 4.8, and p = 0.2. Taken together, the posted results do not provide a statistically clear difference, while leaving substantial uncertainty about the size and direction of any difference.

That finding does not show that the groups are equivalent. Equivalence requires a defined margin and an analysis designed to test whether differences fall within that margin; neither is reported in the registry record. Nor does the result establish that detailed imaging has no effect on risk perception, behavior, or other clinical outcomes. Those questions are part of the study’s stated goal, but the registry posts only the BMI outcome as a result measure.

The trial also does not answer every possible question about the factorial design. Without a clearly described contrast and model, the reported regression estimate cannot be attributed confidently to report content, delivery route, or their interaction. The arm estimates are useful descriptions, but they are not substitutes for those factorial comparisons.

The evidence is best read as limited and imprecise pilot information. The registry records enrollment and outcome estimates, but not a complete analysis plan, participant-flow account, or detailed explanation of model construction. The findings can inform how a future study might define its contrasts and report uncertainty. They should not be used alone to make claims about effectiveness or to infer that an unobserved outcome changed.

14. Why This Trial Matters Statistically

This trial raises a useful statistical distinction between changing what information people see and testing whether the way that information is delivered matters. Its factorial design combines detailed versus basic reporting with participant- versus physician-directed delivery. That structure can be efficient, but only if the analysis makes the intended effects and interactions clear. The registry does not specify those contrasts, making interpretation of the single regression result difficult.

The endpoint also illustrates a gap between the intervention concept and the measured outcome. The study aims to use body-fat distribution images to influence risk perception and behavior, while its posted primary outcome is change in BMI. BMI is a continuous clinical measure, but it does not directly capture body-fat distribution, risk perception, or behavior. The registry does not post results for those other stated aims.

Precision is central to interpreting a small pilot. The broad confidence intervals around the nonzero arm estimates and the regression result show why an estimate alone is not enough. The reported p-value does not resolve the uncertainty or demonstrate equivalence. In particular, a small trial can produce an inconclusive estimate without establishing that meaningful group differences are absent.

Finally, clear reporting of analysis populations, missing-data methods, factorial contrasts, and the model specification would make the results more reproducible and useful for planning subsequent research. The registry record’s limited methodological detail does not erase the value of the pilot, but it narrows the conclusions that can responsibly be drawn from its posted BMI results.

15. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

Several limitations specific to this registry record affect interpretation. The enrollment is 29, and the arm-level sample sizes are small. The record does not report a sample-size justification for the trial, so it is not possible to assess whether it was designed to estimate a particular effect with a particular precision. Planning illustrations based on observed effects should not be confused with the original design rationale.

The most important interpretive limitation is that the regression contrast is unclear. Although the registry lists four groups and reports a linear regression mean difference in final values, it does not state the exact comparison, coding, or adjustment variables. The arm-level results, meanwhile, are described as least-squares mean changes. Those two presentations cannot be reconciled into a clearly specified factorial effect from the registry record alone.

The two basic-information groups have estimates and confidence intervals reported as 0.0 and 0.0 to 0.0. The record does not explain these values or the method behind them. Baseline BMI, individual changes, dispersion statistics, and detailed model specifications are also not reported. As a result, the arm-level precision and the relationship between the reported change estimates and final-value regression result cannot be fully assessed.

The registry does not describe the analysis population, missing-data methods, participant flow, or any multiplicity plan. It also does not report outcomes for the stated aims involving risk perception, behavior, or other clinical outcomes. Safety reporting lists no events, but supplies no detailed event definitions or assessment procedures. These limits apply to what can be learned from the registry record and do not, by themselves, establish that particular analyses or procedures were absent from the conduct of the trial.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Clinical Effectiveness of Body Fat Distribution Imaging in Real-World Practice: The BODY-REAL Study — NCT04763772.
• Registry record last updated 2025-03-25; status last verified 2025-03.
• Results first posted 2025-03-25.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

19. Record Summary

BODY-REAL is listed as a completed, randomized, single-masked factorial pilot trial sponsored by University Hospitals Cleveland Medical Center. Its summary describes rapid MRI and a comparison of detailed body-fat reporting with basic weight information, with reports directed to participants or physicians. The registry records enrollment of 29 and lists four combined groups.

The primary outcome is change in BMI at 6 months. Arm-level least-squares mean estimates are reported with 95% confidence intervals. A linear regression analysis reports a mean difference in final values of -4.5, with a 95% confidence interval from -14 to 4.8 and p = 0.2. The precise contrast and model details are not reported in the registry record. No adverse events or deaths are listed. The record does not post secondary outcomes or describe the analysis population, missing-data methods, or multiplicity plan.