A Phase 2 Multi-Center Study To Evaluate The Efficacy And Safety Of A Chemokine CCR2/5 Receptor Antagonist In Adults With Type 2 Diabetes And Overt Nephropathy: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for A Phase 2 Multi-Center Study To Evaluate The Efficacy And Safety Of A Chemokine CCR2/5 Receptor Antagonist In Adults With Type 2 Diabetes And Overt Nephropathy (NCT01712061), a randomized phase 2 study. The primary outcome is Percent Reduction From Baseline in Urinary Albumin to Creatinine Ratio (UACR) at Week 12.

2. Clinical Question

3. Trial Design

This was a phase 2, randomized, double-blind, placebo-controlled, parallel-group, multicenter study of PF-04634817 in adults with type 2 diabetes and overt nephropathy. The registry record lists an enrollment of 226 and a completed study. The recorded start was 2012-12, and primary completion was 2014-09. The intervention was a once-daily chemokine CCR2/5 receptor antagonist, with placebo as the comparator.

The primary outcome was percent reduction from baseline in urinary albumin to creatinine ratio at Week 12. The registry describes albumin and creatinine concentrations as obtained from spot urine samples, and identifies urinary albumin as a marker of kidney disease. The primary population was the Full Analysis Set, defined as randomized participants who had received at least one dose of randomized treatment and had at least one post-dose efficacy measurement. The reported arm counts for this endpoint were 159 for PF-04634817 200 mg/150 mg and 51 for placebo.

The record lists secondary outcomes covering UACR, urinary protein to creatinine ratio, estimated glomerular filtration rate using MDRD and cystatin formulas, serum creatinine, serum cystatin C, HbA1c, and plasma pharmacokinetic concentrations. It lists 8 secondary outcomes and 16 outcome measures. These additional measures broaden the range of biological and treatment-related observations but do not replace the primary endpoint.

Further details of the randomization procedure, allocation concealment, site count, treatment adherence, and visit schedules beyond those attached to listed outcomes are not reported in the registry record. The registry record also does not report the trial’s original sample-size justification or its planned statistical analysis details. The posted design labels establish the broad comparison, but they do not answer those more specific protocol questions.

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.

Before assignment: The primary entry criterion for participants was based on presence of macroalbuminuria (urine albumin to creatinine ratio \[UACR\] greater than or equal to (\>=)300 milligrams per gram (mg/g).

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The Full Analysis Set (FAS) was defined as all participants randomized and who had received at least 1 dose of randomized treatment and had at least 1 post-dose efficacy measurement; n=number of participants analyzed in respective arms for category.

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 Percent Reduction From Baseline in Urinary Albumin to Creatinine Ratio (UACR) at Week 12, measured over Baseline and Week 12.

The primary endpoint is percent reduction from baseline in urinary albumin to creatinine ratio (UACR) at Week 12. Albumin in urine, described in the registry as macroalbuminuria, is a marker of kidney disease. The ratio relates urinary albumin to urinary creatinine in a spot urine sample, and is used to assess urinary albumin while accounting for the urine sample’s creatinine concentration. The registry’s stated hypothesis treated a reduction in urinary albumin as a surrogate for improved glomerular filtration. A surrogate is a measured biological marker used in place of a more direct clinical outcome; a change in the marker should not be equated automatically with a change in kidney function or how a participant feels or functions.

The posted arm-level mean reductions were 13.27% for PF-04634817 200 mg/150 mg and 5.02% for placebo. These are group summaries, not statements about every participant. Their confidence intervals are broad, and the unadjusted recalculated comparison also has a confidence interval spanning no difference. The sponsor’s posted analysis uses a ratio of geometric mean changes from an ANCOVA model, rather than the unadjusted mean difference. Those summaries are on different statistical scales, so they should be interpreted as distinct analyses rather than treated as interchangeable versions of the same estimate.

The registry lists baseline and Week 12 as the primary timeframe. It does not report in this record the exact handling of values below assay limits, the details of any transformation for the primary outcome, or the clinical threshold that would constitute an important change. The endpoint therefore supports an interpretation of the measured UACR result and its uncertainty, not a conclusion about the clinical importance of a particular magnitude.

7. Results Posted in the Registry

• PF-04634817 200 mg/150 mg: mean 13.27 versus 5.02 on control; difference 8.25 (95% CI -8.84 to 25.34), standardized effect d = 0.13; z-test p = 0.344.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary endpoint is continuous: it is a percent reduction in UACR, and the registry identifies the reported arm summaries as means with 95% confidence intervals. A mean summarizes the central value across participants in an arm. It can be useful for describing an average response, while still concealing variation between individuals. A confidence interval describes uncertainty around an estimate under the analysis assumptions; it is not a range that must contain each participant’s result.

What does the unadjusted mean difference represent?

The recalculated comparison subtracts the placebo arm mean from the PF-04634817 arm mean using the posted summary statistics. It gives a mean difference of 8.25 percentage points, with a 95% confidence interval from -8.845 to 25.34. This is a simple, unadjusted comparison. It does not use covariate adjustment, and it should not be mistaken for the sponsor’s ANCOVA result. The unadjusted p-value is 0.344. It is a test statistic summary under a null hypothesis and a particular calculation, not a measure of effect size or evidence that the treatments are identical.

The arm sizes differ: the endpoint analysis reports 159 participants for PF-04634817 200 mg/150 mg and 51 for placebo. Unequal group sizes influence the precision of a comparison. The registry record does not explain the reasons for this allocation pattern or provide the original allocation ratio. It is therefore appropriate to describe the observed arm sizes without inferring the trial’s planned allocation scheme or why the analysis counts differ.

Why can the sponsor result look different?

The sponsor reports ANCOVA with a ratio of geometric mean changes. ANCOVA is a regression-based method that compares an outcome across groups while adjusting for included covariates. Adjustment can account for measured baseline factors included in the model, but the registry record does not identify the covariates or provide the full model specification. Geometric means are based on a multiplicative scale, so a ratio of geometric means is not directly comparable to an arithmetic mean difference. The posted estimate is 0.92 and its 95% confidence interval is 0.75 to 1.09. Since the confidence interval includes the ratio null value of 1, it does not exclude that value under the reported interval. The record does not report a p-value for this analysis.

ANCOVA can improve precision when its assumptions and covariate choices are suitable, but it does not automatically eliminate bias or resolve missing data. The validity of an adjusted estimate depends on the model, how the outcome is represented, and the analysis population. Those details are not reported in the registry record. The registry also does not state whether this model was designated as primary in the protocol or provide a multiplicity plan.

What do confidence intervals and p-values tell readers?

A confidence interval combines the estimate and its precision. A narrower interval indicates greater precision under the model; a wider interval indicates more uncertainty. Whether the interval includes the relevant null value is one aspect of interpretation, but it does not establish equivalence or clinical importance. For a difference, the null is no difference; for a ratio, the null is 1. The unadjusted difference interval includes no difference, and the sponsor’s ratio interval includes 1. These results should be read on their respective scales.

A p-value describes how unusual data at least as incompatible with a specified null model would be if that null model and analysis assumptions held. It is not the probability that the null hypothesis is true, the probability that the findings are due to chance, or a measure of clinical importance. The p-value of 0.344 belongs to the unadjusted recalculation, not to the sponsor’s ANCOVA estimate. The sponsor p-value is not reported in the registry record.

Why do distributional assumptions matter?

Standard mean-based analyses often rely on assumptions about the sampling behavior of estimates and the model’s residuals. UACR measurements can be skewed in some settings, making a geometric-mean analysis a plausible modeling choice in general. This is general statistical context, not a claim about the distribution in this trial: the registry record does not report the observed distribution, diagnostic checks, transformations, or residual analyses. When variability is greater than a model allows, over-dispersion can make standard errors too small and confidence intervals too narrow. That concern is general; the record does not report evidence of over-dispersion in this study.

The summary-statistic recalculation uses the posted means, standard errors, and pooled standard deviation. It is an unadjusted illustration rather than a reconstruction of the sponsor’s model. No independent adjustment for baseline values, sites, or other covariates can be inferred from the summary data. The record does not report interim analyses, stopping rules, or the original sample-size justification. Statistical planning assumptions used for the separate planning illustration are described with that illustration and should not be attributed to the trial’s original design.

Finally, statistical significance and clinical relevance are different questions. A test evaluates compatibility with a specified statistical null; clinical relevance depends on the importance of the measured change and its relation to outcomes that matter to patients. The registry record provides no threshold for a clinically meaningful UACR change and no basis for treating the surrogate result as a direct measure of kidney function. The most faithful reading is to retain the estimated scale, interval, analysis method, and limitations together.

10. Confidence Intervals and Precision

The arm-level 95% confidence interval for mean percent reduction in UACR is 3.14% to 24.62% for PF-04634817 200 mg/150 mg. For placebo it is -7.9% to 18.7%. These intervals indicate appreciable uncertainty about each arm’s mean. The placebo interval includes values consistent with an increase as well as a reduction, while the PF-04634817 interval is also broad. Arm-level intervals are not themselves a direct test of the difference between arms.

For the unadjusted mean difference, the estimate is 8.25 percentage points, with a 95% confidence interval from -8.845 to 25.34. This interval crosses zero, so the recalculated result is compatible with no mean difference under its assumptions. It also spans values in both directions, which signals limited precision about the direction and size of the contrast. The unadjusted p-value is 0.344, but the interval gives a more informative view of the range of contrast values compatible with the calculation.

The sponsor’s ANCOVA ratio estimate is 0.92, with a 95% confidence interval from 0.75 to 1.09. That interval includes 1, the null value for a ratio. Its meaning is tied to the ratio scale and the model; it should not be converted into the unadjusted percentage-point difference. The registry record does not report the model’s covariates or a p-value for this analysis.

Confidence intervals express statistical uncertainty under analysis assumptions; they do not capture every uncertainty, such as the choice of outcome, missing-data assumptions, or whether a surrogate is clinically meaningful. The intervals do not demonstrate equivalence, and they do not establish that an effect is absent. They show that the available estimates are not highly precise about the between-arm contrast.

11. 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 sample-size table and curve are planning illustrations based on the observed effect, not the trial’s original design calculation. The rows consider planning for 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. The accompanying assumptions are a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The effect to detect is the stated fraction of the observed effect.

For this continuous endpoint, the figures are participants per arm, not total events. The 80% power column gives the illustrative number of participants per arm for 80% power under the stated assumptions; the 90% power column gives the corresponding number per arm for 90% power. Power is the probability, under a specified effect and analysis model, of rejecting the null hypothesis when that effect is present. It is a planning property, not a characteristic that can be read off the completed trial after results are known.

The displayed requirements rise as the assumed effect becomes smaller: planning for 75% of the observed effect requires more participants per arm than planning for the full observed effect, and planning for 50% requires more still. The same pattern applies when comparing the 80% and 90% power targets: the higher target requires more participants per arm under these assumptions. For example, the listed planning figures are 967 and 1,295 participants per arm for 80% and 90% power when using 100% of the observed effect; for 75%, they are 1,719 and 2,301; for 50%, they are 3,867 and 5,177.

These are not observed power calculations. They are hypothetical planning illustrations using the observed effect as a reference and the stated assumptions. The trial’s own sample-size justification, target effect, and original planning assumptions are not reported in the registry record. The illustration should not be treated as evidence that the completed study was designed with these participant counts or assumptions.

12. 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 = 8.250; pooled standard deviation σ = 64.739.
2. n = 2 × (1.96 + 0.842)² × 64.739² / 8.250² = 966.6, rounded up to 967 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 <- 8.25                      # observed difference in means
sigma <- 64.7391385171363                     # 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(1712061)
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 = 967 (80% power), 1,295 (90% power)
 75% of observed effect: n per arm = 1,719 (80% power), 2,301 (90% power)
 50% of observed effect: n per arm = 3,867 (80% power), 5,177 (90% power)
power.t.test: 967.6 
Simulated power at n = 967 per arm: 0.804 (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.

13. Analyses Reported by the Sponsor

The sponsor’s posted primary analysis used ANCOVA and reported a ratio of geometric mean changes of 0.92, with a 95% confidence interval from 0.75 to 1.09. The interval includes 1, the null value for a ratio. A p-value for this analysis is not reported in the registry record. The registry record does not provide the model covariates, detailed specification, or ratio orientation, so the estimate should be presented on its reported scale without translating it into a directional claim.

The recalculated comparison is an unadjusted difference in arm means: 8.25 percentage points, with a 95% confidence interval from -8.845 to 25.34 and an unadjusted p-value of 0.344. It is based on posted summary statistics and is not a reproduction of the ANCOVA model. A mean difference and a geometric-mean ratio use different scales and may answer different statistical questions, especially when adjustment and transformation choices differ.

The registry record indicates no declared discrepancy between the analyses. That does not make them interchangeable. The sponsor’s model-based result is the posted trial analysis; the recalculation is a transparent unadjusted comparison that can help readers understand the arm summaries. Their intervals both include their respective null values, but neither should be used to claim equivalence or a clinically meaningful effect. The registry record does not explain whether the ANCOVA was prespecified or how it relates to any protocol-defined primary analysis.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists one posted primary analysis and 8 secondary outcomes, with 16 outcome measures. Secondary measures include UACR at other listed visits, urinary protein to creatinine ratio, estimated glomerular filtration rate by MDRD and cystatin formulas, serum creatinine, serum cystatin C, HbA1c, and pharmacokinetic concentrations. Considering multiple outcomes and time points can increase the chance that some findings appear notable by chance if no adjustment or hierarchy is used. The registry record does not report a multiplicity adjustment, testing hierarchy, or how secondary results were intended to support inference.

The primary outcome is specified at Week 12, while secondary outcomes include several other time points. The registry’s list of outcome measures does not by itself indicate which results were confirmatory, exploratory, or adjusted for repeated comparisons. The record does not report interim analyses or stopping rules. In the absence of these details, the primary endpoint should remain the central inferential result, and secondary outcomes should be treated as contextual rather than as independent confirmations.

The analysis population is the Full Analysis Set, defined as all randomized participants who received at least one dose and had at least one post-dose efficacy measurement. This definition differs from an analysis of every randomized participant because it excludes participants without the specified post-dose measurement. The record does not report how many randomized participants failed to meet this definition, the reasons for exclusion, or whether the population differed from the randomized population in important ways.

Missing-data handling is not reported in the registry record. The record does not explain how missing baseline or Week 12 UACR measurements were treated, whether imputation was used, or whether sensitivity analyses assessed alternative assumptions. Missingness can affect a treatment estimate if the likelihood of observing an outcome is related to the outcome itself or to treatment. This is a general concern, not evidence that missing data biased this study. Without the relevant details, the robustness of the primary estimate to missingness cannot be assessed.

The registry record also does not report the statistical analysis plan, covariates used in ANCOVA, model diagnostics, or original sample-size assumptions. Those omissions limit assessment of prespecification, multiplicity control, and the handling of incomplete observations. They do not negate the posted results, but they narrow what can be concluded from the registry record alone.

15. 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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: pneumonia (6.7%), renal failure acute (6.7%), cardiac failure (3.3%), septic shock (3.3%), dehydration (3.3%).

The registry reports serious adverse event counts by safety group. For PF-04634817 150 mg, 6 of 30 participants at risk were affected by a serious adverse event. For PF-04634817 200 mg, 11 of 140 at risk were affected. For placebo, 5 of 56 at risk were affected. These are counts within the listed groups; they are not adjusted comparisons and should not be read as proof that one group had a higher or lower risk.

The most frequently listed serious adverse event terms include pneumonia and acute renal failure, each reported as 6.7%. Cardiac failure, septic shock, dehydration, and hypokalaemia are each listed as 3.3%. These percentages are presented as registry terms; the record excerpt does not provide the event counts behind each term or explain whether participants could contribute more than one event. The treatment and placebo safety groups differ from the two-arm primary endpoint presentation, so their denominators should not be substituted for the primary analysis counts.

Deaths are not reported in the registry record. The safety information does not provide enough detail to assess timing, severity beyond the serious-event classification, relatedness to treatment, exposure duration, or differences in follow-up. Safety counts describe what was recorded in the listed groups; they do not establish causation or comparative safety.

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

The primary result is a comparison of a urinary marker at Week 12 in adults with type 2 diabetes and overt nephropathy. The mean percent reduction was 13.27% in the PF-04634817 200 mg/150 mg arm and 5.02% in the placebo arm. The unadjusted recalculated mean difference was 8.25 percentage points, but its 95% confidence interval, -8.845 to 25.34, includes no difference. The sponsor’s ANCOVA estimate is a geometric-mean ratio of 0.92, with a 95% confidence interval from 0.75 to 1.09. These estimates are imprecise and should be kept on their separate scales.

The findings do not establish a precise between-arm difference in the primary endpoint. They also do not prove that there is no difference: the confidence intervals permit a range of values. A nonsignificant result, or an interval that includes the null, is not equivalent to evidence of equivalence. Equivalence requires a defined margin and a design and analysis suited to that question; such a margin is not reported in the registry record.

The trial hypothesis described urinary albumin reduction as a surrogate for improved glomerular filtration. A surrogate is not itself the clinical outcome it is intended to represent. The posted primary result therefore cannot be taken as direct evidence of improved kidney function, fewer clinical events, or improved quality of life. The record does not report a threshold for a clinically meaningful UACR change, and it does not provide a direct patient-important primary outcome.

The registry lists renal-function measures among the secondary outcomes, including eGFR using MDRD and cystatin formulas, serum creatinine, and serum cystatin C. Their presence identifies additional measurements of interest, but the primary result alone cannot answer what those analyses showed. Nor can the trial’s phase 2 designation and limited endpoint description establish the extent to which findings would generalize to other populations, treatment regimens, or longer follow-up.

The fair interpretation is narrow: the posted summaries describe a numerically larger average UACR reduction in the PF-04634817 arm, with considerable uncertainty in the between-arm estimate. The sponsor’s adjusted ratio also has a confidence interval that includes its null value. These statistics neither demonstrate a clinically important benefit nor rule one out. Interpretation is further limited by unreported missing-data handling, model details, multiplicity procedures, and clinical thresholds.

17. Why This Trial Matters Statistically

This trial illustrates why the estimated difference, its uncertainty, and the analysis scale should be read together. A larger point estimate in one arm may draw attention, but the interval for the unadjusted contrast spans zero and a broad range in both directions. The sponsor’s adjusted estimate uses a different scale and also has an interval that includes its null value. The distinction prevents a simple ranking of point estimates from being mistaken for strong evidence of a treatment contrast.

It also demonstrates that the primary endpoint is a surrogate marker. UACR is relevant to kidney disease and was selected as the primary measure, but it is not identical to glomerular filtration or a patient-important outcome. Statistical evidence about a surrogate and evidence about clinical benefit are separate questions. Naming the endpoint and the registry hypothesis helps define what the analysis can address without extending the conclusion beyond the measured result.

The study also offers a practical example of how a sponsor analysis and an unadjusted recalculation can coexist. ANCOVA with a ratio of geometric mean changes is not interchangeable with a difference in arithmetic means. Readers need the estimate, confidence interval, reference value, and model description to understand what each result represents. Where model details are absent, careful description is preferable to assuming equivalence between methods.

Finally, the planning illustration shows how power calculations depend on an assumed effect size and target power. Smaller effects require more participants per arm under the stated assumptions. These figures are planning aids, not evidence about the power actually achieved by a completed study. Keeping that distinction clear is important when interpreting both phase 2 findings and sample-size projections.

18. 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.

The registry record leaves several trial-specific interpretive details unresolved. It lists the primary arm as PF-04634817 200 mg/150 mg but does not explain the dosing notation. The broad design is randomized, double-blind, placebo-controlled, and parallel group, but the randomization method, allocation concealment, number of centers, and site-level procedures are not reported in the registry record.

The sponsor’s ANCOVA result is reported as a ratio of geometric mean changes, but the covariates, model specification, transformation details, diagnostics, and ratio orientation are not reported in the registry record. The unadjusted recalculation does not reproduce that model. Although the two analyses are not flagged as discrepant, the lack of full model detail restricts independent assessment of the sponsor estimate.

The primary Full Analysis Set excludes randomized participants without at least one dose or at least one post-dose efficacy measurement. The record does not report the count or reasons for any exclusions, or how missing baseline or Week 12 observations were handled. It also does not report sensitivity analyses that might show how robust the endpoint estimate is to missing-data assumptions.

The endpoint is UACR, a surrogate marker, and the registry record does not state a threshold for a clinically important change. The primary timeframe is Week 12; the record does not establish what the reported result means for longer-term kidney function or patient-important outcomes. Secondary renal-function outcomes are listed, but their results are not part of the primary comparison.

The record does not report the trial’s original sample-size justification, the statistical analysis plan, multiplicity procedures, interim analyses, or stopping rules. These omissions constrain assessment of whether the analyses followed prespecified choices and how multiple outcomes were handled. Safety information is also limited to group counts and listed serious-event terms; deaths are not reported in the registry record, and detailed event timing, exposure, and relatedness are not available.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: A Phase 2 Multi-Center Study To Evaluate The Efficacy And Safety Of A Chemokine CCR2/5 Receptor Antagonist In Adults With Type 2 Diabetes And Overt Nephropathy — NCT01712061.
• Registry record last updated 2015-10-21; status last verified 2015-09.
• Results first posted 2015-10-21.
• 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.

22. Record Summary

NCT01712061 is a completed phase 2 randomized, double-blind, placebo-controlled, parallel-group, multicenter study of once-daily PF-04634817 in adults with type 2 diabetes and overt nephropathy. The registry record lists enrollment of 226, a start of 2012-12, and primary completion in 2014-09.

The primary endpoint was percent reduction from baseline in UACR at Week 12. The reported mean reductions were 13.27% for PF-04634817 200 mg/150 mg and 5.02% for placebo. The unadjusted recalculated mean difference was 8.25 percentage points, with a 95% confidence interval from -8.845 to 25.34 and an unadjusted p-value of 0.344. The sponsor’s ANCOVA estimate was a ratio of geometric mean changes of 0.92, with a 95% confidence interval from 0.75 to 1.09.

Both estimates are uncertain and use different statistical scales. The primary endpoint is a urinary surrogate, and the registry record does not report enough detail to assess all analysis choices, missing-data handling, or clinical thresholds.