Study of TNF-Antagonism in the Metabolic Syndrome (II): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study of TNF-Antagonism in the Metabolic Syndrome (II) (NCT00413400), a randomized na study. The primary outcome is C-reactive Protein (CRP).

2. Clinical Question

The trial was randomized, double-masked, and parallel-group. Those design features describe how the comparison was planned at a broad level, but the registry record does not explain how randomization was generated or implemented, who was masked, or whether masking was maintained. The posted primary outcome is a continuous measure: the mean Log10 CRP at 6 months, with standard error reported for each group.

The endpoint is a comparison between group averages at the stated follow-up, not a count of participants whose CRP improved or a measure of individual response. The posted results give a placebo mean of 0.61 and an etanercept mean of 0.68. The unadjusted mean difference is 0.07, with a confidence interval that includes zero. The registry also reports an ANCOVA analysis with p = 0.20, while a simple unadjusted recalculation gives p = 0.712. These analyses answer related but not identical statistical questions because the registry’s model is adjusted and the recalculation uses only the posted group summaries.

The record does not report a detailed primary hypothesis, a clinically meaningful difference, or the design assumptions behind enrollment. Accordingly, the results describe the posted group comparison and its uncertainty, rather than establishing what magnitude of difference would matter clinically.

3. Trial Design

The study, titled “Study of TNF-Antagonism in the Metabolic Syndrome (II),” is recorded as completed and was sponsored by Massachusetts General Hospital. The registry lists a start date of 2006-12 and primary completion in 2009-09. Its phase is recorded as NA. The study concerns metabolic syndrome and compares etanercept with placebo.

Allocation is listed as randomized, masking as double, and the design model as parallel. In general, random allocation is intended to support a fair comparison by reducing systematic differences in how participants enter treatment groups. A parallel design assigns participants to one group for comparison rather than describing a crossover. Double masking indicates that the registry records masking at that level, but the record does not identify which people were masked or explain the masking procedures.

Enrollment is listed as 40. For the primary endpoint, the posted group summaries contain 22 participants in the placebo group and 12 in the etanercept group. The safety record lists 24 at risk in the placebo group and 16 in the etanercept group. These figures describe different posted result summaries; the registry record does not explain why their group counts differ or provide a participant flow that would account for the difference.

The primary endpoint is CRP at 6 months, expressed as Log10 mg/L. The brief study summary describes an investigation of inflammatory indices, glucose tolerance, and endothelial function. Other posted secondary outcomes include white blood cell count, cardiac echo ejection fraction, body composition, TNF receptor, other adipocytokines, and lipid levels. The record lists 12 outcome measures and 11 analyses, and nine secondary outcomes are posted in the outcome data.

The registry record does not report the original sample-size justification, the treatment regimen, detailed inclusion or exclusion criteria, or the full study protocol. It also does not report an interim-analysis plan or the planned approach to missing data. These omissions limit what can be inferred about how the trial was designed and conducted beyond the listed design features and results.

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 C-reactive Protein (CRP), measured over 6 months.

The primary endpoint is the mean CRP level at 6 months, expressed as Log10 mg/L. CRP is identified in the registry record as an inflammatory marker. The study summary names improvement in inflammatory indices as one of the questions under investigation, making CRP a measure related to that stated research aim.

CRP is a continuous measure, so the posted result describes an average for each group rather than the number of people meeting a threshold. Taking the Log10 of CRP expresses the measure on a logarithmic scale. In general, a logarithmic scale can make a highly skewed measurement more amenable to statistical analysis, but the registry record does not state why this scale was selected or give the underlying untransformed CRP values.

The registry reports a placebo mean of 0.61 with standard error 0.06 and an etanercept mean of 0.68 with standard error 0.18. The primary comparison is between those group averages at the specified follow-up. The posted endpoint description does not define a clinically important difference, a target range, or an individual-response threshold. Nor does the record report baseline CRP values alongside this endpoint in a way that would establish how the six-month means relate to baseline.

Thus, the endpoint describes the group-level inflammatory-marker values at 6 months. It does not by itself capture every aspect of inflammation or the other study aims, such as glucose tolerance or endothelial function. The record does not report further rationale for selecting CRP as the primary endpoint.

7. Results Posted in the Registry

• Etanercept: mean 0.68 versus 0.61 on control; difference 0.07 (95% CI -0.30 to 0.44), standardized effect d = 0.16; z-test p = 0.712.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Glucose Tolerance

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • Etanercept: mean 91.00 versus 95.00 on control; difference -4.00 (95% CI -19.31 to 11.31), standardized effect d = -0.18; z-test p = 0.609.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Etanercept and the control. The interval gives the range of effects that remain compatible with the data.

Endothelial Function

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • Etanercept: mean 2.00 versus 1.80 on control; difference 0.20 (95% CI -0.16 to 0.56), standardized effect d = 0.39; z-test p = 0.282.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Etanercept and the control. The interval gives the range of effects that remain compatible with the data.

White Blood Cell (WBC) Count

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • Etanercept: mean -0.04 versus -0.17 on control; difference 0.13 (95% CI -0.86 to 1.12), standardized effect d = 0.10; z-test p = 0.797.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Etanercept and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes cover glucose tolerance, endothelial function, white blood cell count, and other metabolic, inflammatory, cardiac, and body-composition measures. The reported tests do not form a single uniform analysis: the record includes repeated measures ANCOVA, ANCOVA, and a two-sided t-test. The simple recalculations are unadjusted comparisons from posted summaries, so they are not interchangeable with those reported models.

Across the posted secondary results, the unadjusted estimates and their uncertainty vary in direction and size. The registry reports p = 0.02 for glucose tolerance, p = 0.46 for endothelial function, and p = 0.78 for white blood cell count. The corresponding unadjusted recalculations give p = 0.609, p = 0.282, and p = 0.797. Those differences in reported and recalculated p-values reinforce that the model and comparison method matter. The registry does not provide the adjusted effect estimates and confidence intervals for these analyses.

The secondary results do not replace or redefine the primary CRP analysis. They add information about other listed outcomes, but any apparent pattern should be considered alongside the primary endpoint and the different analysis methods. The registry lists 12 outcome measures and 11 analyses, while nine secondary outcomes are posted. The record does not explain the relationship between every listed outcome and analysis or identify a hierarchy among the secondary questions.

In general, multiple outcome tests create more opportunities for an apparently notable result to occur by chance. Unadjusted secondary p-values do not account for the number of comparisons, and the record does not report a multiplicity adjustment or a prespecified hierarchy. Therefore, individual secondary findings carry less confirmatory weight than a result from a clearly prespecified primary analysis. The posted outcomes are best viewed as additional, exploratory context rather than as a set of independent confirmations of the primary result.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Glucose Tolerance
• Endothelial Function
• White Blood Cell (WBC) Count
• Cardiac Echo Ejection Fraction (EF)
• Body Composition
• Tumor Necrosis Factor (TNF) Receptor
• Other Adipocytokines
• Lipid Levels

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is continuous, and the registry reports group means and standard errors. The primary posted analysis is ANCOVA. The posted unadjusted recalculation is a separate comparison based on the group summaries. These approaches are related, but they do not generally produce identical estimates or p-values because adjustment can account for selected covariates while the simple comparison does not.

What does the group mean describe?

A mean is the arithmetic average of the measured values in a group. Here, the values are Log10 CRP at 6 months. A mean gives a concise description of the group, but it does not show the full distribution: participants may have values above or below the average, and the record does not post individual observations. The mean is also sensitive to unusually high or low values, particularly when the distribution is skewed.

The standard error describes the estimated uncertainty in a sample mean. It is not the same as the standard deviation, which describes variation among individual measurements. The registry labels the spread for these means as standard error. The values are 0.06 for placebo and 0.18 for etanercept. The larger standard error indicates less precise estimation of that group mean in the posted summary, but the record does not give the individual-level measurements needed to inspect the distributions.

What does the unadjusted comparison do?

The unadjusted mean difference is formed by comparing the posted group means. For etanercept versus placebo, the estimate is 0.07. This simple contrast does not account for baseline values or other covariates. Its confidence interval and p-value are recalculated from the posted summaries, so they represent an unadjusted analysis rather than the registry’s full reported model.

In general, adjustment can improve precision or account for prognostic differences when the covariates and model are appropriate. It can also change the estimated comparison. The registry calls its primary analysis ANCOVA, but does not report the covariates, model details, adjusted difference, or adjusted confidence interval. Therefore, the ANCOVA p-value cannot be used to reconstruct the adjusted effect size.

How should a confidence interval be understood?

In general, a confidence interval gives a range of values compatible with the observed data under the assumptions of the analysis and its repeated-sampling procedure. A narrow interval indicates greater precision than a wide interval. Whether the interval includes zero is relevant to a test of no difference, but does not on its own determine clinical importance. The unadjusted primary interval includes zero, and its breadth leaves uncertainty about the magnitude and direction of the difference.

A confidence interval is not a range containing a fixed proportion of individual participant values, nor is it the probability that the true effect lies in the particular interval. Its interpretation depends on the statistical model and how the interval was calculated. The registry does not report the adjusted ANCOVA interval, so the interval accompanying the recalculated comparison should not be mistaken for the sponsor’s adjusted result.

What do p-values contribute?

A p-value summarizes how unusual the observed data, or data more extreme, would be under a specified null hypothesis and model. Smaller p-values indicate greater incompatibility with that null model, but do not measure the size or importance of an effect. They also do not establish the probability that a treatment has no effect. The registry reports p = 0.20 for ANCOVA; the unadjusted recalculation gives p = 0.712. These values should be read with their respective analyses in mind.

The registry’s adjusted result and the unadjusted recalculation are not necessarily contradictory. They use different statistical approaches, and the registry does not provide enough model detail to explain exactly how adjustment influenced the result. The comparison should therefore retain the distinction between the reported ANCOVA analysis and the summary-statistic recalculation.

Why can over-dispersion matter?

In general, over-dispersion occurs when observed variability is greater than a model assumes. It can make standard errors too small if the model fails to account for that extra variation, which can make confidence intervals too narrow and p-values too small. This concept is particularly relevant to count or binary outcomes, but the primary endpoint is a continuous log-transformed measure. The registry does not report an over-dispersion assessment, and the available summary statistics do not allow one to determine whether it is present.

What is and is not known about the analysis plan?

The registry identifies ANCOVA for the primary comparison and reports the endpoint timeframe and summary measure. It does not report the covariates, the exact model specification, a missing-data procedure, an intention-to-treat definition, or a per-protocol analysis population. It also does not report whether the analysis plan was finalized before outcomes were examined. These details matter because choices about covariate adjustment, population, and missing observations can affect estimates and their uncertainty.

General statistical interpretation should therefore remain tied to the information actually reported: descriptive means and standard errors, an unadjusted comparison calculated from those summaries, and the registry’s ANCOVA p-value. The two analyses should not be collapsed into a single result, and neither should be treated as a complete account of the trial’s statistical plan.

11. Confidence Intervals and Precision

The unadjusted primary estimate is a mean difference of 0.07 Log10 mg/L, with a confidence interval that runs from a negative value to a positive value. Because the interval includes zero, the summary statistics do not rule out no difference under this unadjusted analysis. They also do not rule out differences in either direction. The interval is broad enough that the exact size of the group contrast remains uncertain.

Precision is distinct from the direction of the point estimate. The etanercept group mean is numerically higher than the placebo group mean, but that descriptive ordering does not establish a reliable difference. The confidence interval expresses uncertainty around the unadjusted contrast; it does not resolve what difference might matter clinically, since the registry record does not report a clinical threshold.

The standard errors are 0.06 for placebo and 0.18 for etanercept. They characterize the uncertainty in the estimated group means, not the spread of individual participants’ CRP values. The primary endpoint counts are 22 for placebo and 12 for etanercept, and the uncertainty should be read in the context of these relatively limited posted group summaries. The record does not report a reason for the smaller endpoint count in the etanercept group compared with placebo or explain the relation of these counts to enrollment.

The registry’s ANCOVA result has p = 0.20 but no adjusted effect estimate or confidence interval. A p-value alone cannot communicate the range of adjusted effects compatible with the data. The unadjusted interval is informative for the simple comparison, but it is not a substitute for the missing adjusted interval. As a result, precision for the registry’s reported adjusted analysis cannot be assessed from its posted p-value alone.

In general, confidence intervals narrow when information is more precise and widen when uncertainty is greater. They depend on the data and analysis assumptions. The posted interval is a useful uncertainty summary for the unadjusted comparison, but it should not be read as proof of equality or as a measure of clinical importance.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are participants per arm, not total events. They are illustrations based on the observed effect, not the trial’s original design calculation. The listed assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect set at the stated fraction of the observed effect. The registry record does not report the original sample-size assumptions or justification.

The 80% power column describes the illustrative number of participants per arm under those assumptions for a design with an 80% chance of detecting the specified effect if that effect were the true one. The 90% power column describes the corresponding planning target for a 90% chance. These are design concepts, not probabilities that the observed trial result is correct. The figures are calculated separately for planning for 100%, 75%, and 50% of the observed effect.

Smaller target effects require more participants because a smaller difference is harder to distinguish from random variation. The entries therefore increase as the planned effect becomes a smaller fraction of the observed estimate. The precise figures depend on the assumptions, including equal allocation and the use of the normal approximation. A different effect target or design assumption would give different planning figures.

These sample-size calculations are not observed power. They do not tell whether the completed study had a particular probability of finding a result after its data were collected. They are prospective planning illustrations derived from the observed effect, and the registry’s own original planning rationale is not reported.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = 0.070; pooled standard deviation σ = 0.431.
2. n = 2 × (1.96 + 0.842)² × 0.431² / 0.070² = 594.7, rounded up to 595 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- 0.0700000000000001                      # observed difference in means
sigma <- 0.430842198490352                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(413400)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 595 (80% power), 797 (90% power)
 75% of observed effect: n per arm = 1,058 (80% power), 1,416 (90% power)
 50% of observed effect: n per arm = 2,379 (80% power), 3,185 (90% power)
power.t.test: 595.6 
Simulated power at n = 595 per arm: 0.803 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Analyses Reported by the Sponsor

The registry’s primary analysis is ANCOVA and reports p = 0.20. It does not post the adjusted mean difference, the adjusted confidence interval, or the covariates included in the model. The simple recalculation from the posted means and standard errors gives an unadjusted difference of 0.07 and p = 0.712, with a confidence interval that includes zero.

These results should be kept distinct. ANCOVA is an adjusted analysis, while the recalculation is an unadjusted comparison based on group summaries. Adjustment can change the estimate and its uncertainty, so a difference between the p-values does not by itself show an error or inconsistency. The registry record does not provide enough detail to identify exactly why the p-values differ or to reproduce the adjusted model.

The registry’s result is the sponsor-reported analysis, while the recalculation is a transparent, simple comparison of the posted summaries. Because the record does not post the adjusted effect estimate or interval, the adjusted p-value alone cannot show the size or precision of the ANCOVA effect. The unadjusted recalculation should not be presented as a replacement for that analysis; it provides a complementary view with different assumptions.

15. Multiplicity, Missing Data and Analysis Populations

The registry record lists 12 outcome measures and 11 analyses, with nine secondary outcomes posted. It does not report whether the investigators used a family-wise error adjustment, a false-discovery procedure, a hierarchical testing strategy, or another approach to multiplicity. It also does not say which secondary outcomes, if any, were designated as confirmatory. Without that information, the secondary p-values should be treated cautiously because repeated testing can increase the chance of at least one apparently unusual result.

The primary outcome is identified as CRP at 6 months, and ANCOVA is listed as its analysis method. However, the registry does not report the covariates, the full model specification, or a prespecified analysis plan. It is also not reported in the registry record whether the primary analysis was defined before examining the outcome data. Those omissions do not negate the posted results, but they limit assessment of how faithfully the reported analysis corresponds to the original plan.

Missing-data handling is not reported in the registry record. The primary endpoint summaries list 22 participants in the placebo group and 12 in the etanercept group, while enrollment is 40 and the safety at-risk counts differ from the endpoint counts. The record does not provide participant flow, reasons for missing endpoint observations, or the method used to handle incomplete data. It is therefore not possible to determine from the record whether the outcome analysis included all randomized participants or how missing observations may have affected the estimate.

The analysis population is not reported in the registry record as intention-to-treat, modified intention-to-treat, or per-protocol. The record also does not report sensitivity analyses for missing data or departures from model assumptions. These absences make it harder to evaluate robustness and generalizability. They are limitations in the reporting available in the registry, rather than evidence that any particular analysis choice was made.

16. Safety Results

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

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 1% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: operative surgical procedure (6.2%), paresthesia (6.2%), schizophrenia (4.2%).

The safety record lists serious adverse events in 2 of 24 participants at risk in the placebo group and 2 of 16 participants at risk in the etanercept group. Other adverse events are listed for 8 of 24 participants at risk in the placebo group and 6 of 16 participants at risk in the etanercept group. These are the registry’s counts; they should not be converted into a comparative claim without considering the limited information about event definitions, follow-up, and analysis.

The record lists “Operative Surgical Procedure” and “Paresthesia” at 6.2%, and “Schizophrenia” at 4.2%, among the top serious-event terms. It does not give enough detail in these summaries to establish the timing, clinical context, relationship to treatment, or whether the listed terms occurred in a particular group. Deaths are not reported in the registry record.

These figures are descriptive safety information, not evidence that an event was caused by an intervention. The at-risk counts differ from the primary endpoint counts, and the registry does not explain participant flow or provide a detailed safety analysis. The small posted group sizes also mean that counts alone give limited information about comparative risk.

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

The primary endpoint data describe CRP averages at 6 months in the two groups. The unadjusted mean difference is 0.07 Log10 mg/L, and its confidence interval includes zero. The registry’s ANCOVA analysis reports p = 0.20. Together, these results indicate that the posted record does not establish a clear difference in the primary endpoint, while also leaving uncertainty about the size and direction of any underlying difference.

This is not the same as demonstrating that the groups are equivalent. The registry does not report an equivalence margin or a non-inferiority framework, and the confidence interval is not evidence that all clinically important effects have been excluded. Conversely, the numerical ordering of the group means does not establish that etanercept has a meaningful effect. The clinical significance of the values cannot be determined from a threshold because none is reported.

The study summary also concerns glucose tolerance and endothelial function, and the posted data include additional secondary outcomes. Those results add context but involve different outcomes and analysis methods. Their p-values should not be used as substitutes for the primary result, particularly because multiplicity handling is not reported.

The registry reports randomized, double-masked, parallel-group design features, but does not supply detailed information about eligibility, treatment administration, adherence, participant flow, analysis populations, or missing observations. Those gaps limit interpretation of how the posted endpoint groups relate to all enrolled participants and how robust the estimates are to analysis choices.

These findings describe the record’s statistical results; they do not amount to medical advice and do not determine whether treatment is appropriate for any person. They also do not settle whether etanercept improves or fails to improve the broader set of outcomes named in the study summary. The record supports a careful account of estimates, uncertainty, and reporting limits rather than a definitive clinical conclusion.

18. Why This Trial Matters Statistically

This trial illustrates why an estimated effect, its precision, and a p-value should be read together. The primary unadjusted difference is 0.07, but the confidence interval includes zero and spans values in both directions. The registry’s ANCOVA p-value is reported without an adjusted effect estimate or confidence interval. A p-value by itself cannot convey the magnitude of a group difference or how precisely it has been estimated.

The record also makes the distinction between a sponsor-reported model and a summary-statistic recalculation visible. ANCOVA and an unadjusted comparison are not the same analysis. Reporting the method without the adjusted estimate and interval leaves readers with limited information about the effect size from the sponsor’s model, even though the p-value is posted.

Sample-size planning provides another statistical lesson. The planning illustrations use the observed effect and vary the fraction targeted; the required participants per arm increase for smaller effects. Such calculations can show how design targets depend on the effect a study aims to detect, but they cannot replace the trial’s original planning rationale, which is not reported. Nor are those planning figures an assessment of observed power.

Finally, the different endpoint counts, unreported missing-data methods, and lack of reported multiplicity handling show how design and reporting details shape interpretation beyond the headline result. A statistically careful reading distinguishes what was measured, what analysis was reported, what uncertainty remains, and what the registry does not explain. That approach is useful for clinical research because it avoids treating a single test result as a complete account of evidence.

19. 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 are specific to the information recorded for this trial. Although enrollment is 40, the primary endpoint summaries list 22 participants in the placebo group and 12 in the etanercept group, while the safety summaries use at-risk counts of 24 and 16. The registry does not reconcile these counts, provide participant flow, or state why the endpoint counts differ from enrollment and safety counts. The relationship between randomized participants and analyzed participants is therefore unclear.

The primary endpoint is reported on a Log10 scale, but the record does not give the underlying untransformed values, baseline CRP summaries, or an explanation for the transformation. The primary ANCOVA is identified by name, yet the covariates, adjusted estimate, confidence interval, and detailed model specification are not reported. This prevents a full assessment or reproduction of the sponsor’s primary comparison from the registry record.

The registry also does not report the original sample-size justification, eligibility criteria, treatment dose or schedule, adherence, analysis populations, missing-data procedures, or sensitivity analyses. Without these details, interpretation of both the endpoint estimates and their applicability is limited. The record does not say whether all enrolled participants were analyzed according to their randomized group.

There are multiple listed outcomes, but the registry does not report a multiplicity strategy or explain the prespecified status of each secondary endpoint. The range of listed tests and methods makes secondary findings more difficult to interpret as confirmatory evidence. The record also does not provide sufficient detail about the serious adverse events to establish timing, attribution, or group-specific patterns for the listed terms.

These are reporting limitations in the registry record. They do not establish that the trial lacked procedures or analyses; those details are simply not reported in the registry record.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Study of TNF-Antagonism in the Metabolic Syndrome (II) — NCT00413400.
• Registry record last updated 2010-12-02; status last verified 2010-11.
• Results first posted 2010-12-02.
• 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.

23. Record Summary

NCT00413400 is a completed randomized, double-masked, parallel-group study of etanercept versus placebo in people with metabolic syndrome, sponsored by Massachusetts General Hospital. Enrollment is 40, and the phase is listed as NA. The primary endpoint is mean Log10 CRP at 6 months.

The placebo mean was 0.61 and the etanercept mean was 0.68. The unadjusted mean difference is 0.07, with a confidence interval that includes zero; the unadjusted recalculation gives p = 0.712. The registry reports an ANCOVA p-value of 0.20 but does not report the adjusted effect estimate or interval.

Secondary outcomes address glucose tolerance, endothelial function, and other measures. The record lists 12 outcome measures, 11 analyses, and nine posted secondary outcomes. Original sample-size assumptions, multiplicity procedures, missing-data handling, analysis populations, and participant flow are not reported in the registry record.