Renal Osteodystrophy: An Individual Management Approach: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Renal Osteodystrophy: An Individual Management Approach (NCT02440581), a randomized na study. The primary outcome is Change in Quantitative Computed Tomography (QCT) Bone Mineral Density of the Hip.

2. Clinical Question

The clinical question is therefore about a treatment strategy matched to turnover status and its relationship to a measured bone-density outcome over one year. The posted results describe group means and statistical comparisons; they do not establish what happened to every individual participant or settle how the strategy should be used in practice.

3. Trial Design

The registry describes a randomized, parallel-group trial with no masking. It enrolled 141 participants and is marked completed. The condition is chronic kidney failure. The record identifies Hartmut Malluche, MD, as sponsor and lists the phase as NA. The start date is 2015-07-01, and the primary completion date is 2021-06-30.

Participants were classified by bone turnover, with low-turnover and high-turnover groups each containing a control arm and a treatment arm. The low-turnover treatment arm received teriparatide and cinacalcet; the high-turnover treatment arm received alendronate. The control arms are described as having no intervention. The registry does not report the allocation procedure beyond identifying the study as randomized, nor does it give further detail about how turnover status was determined or how participants were assigned within the turnover groups.

The primary outcome was change in quantitative computed tomography bone mineral density of the hip, assessed at baseline and one year. The record also lists changes in coronary artery calcifications and serum measures of parathyroid hormone, bone-specific alkaline phosphatase, and fibroblast growth factor 23 as secondary outcomes. Numerical results are posted for only some of these listed secondary outcomes; fibroblast growth factor 23 results are not reported in the registry record.

The original sample-size justification, the trial’s prespecified statistical plan, the handling of missing observations, and the analysis populations are not reported in the registry record. The same is true of any interim analyses. The available descriptions do not establish whether the posted comparisons were prespecified or how the turnover-specific groups were incorporated into the primary analysis.

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

Reasons for not completing this period:

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 Quantitative Computed Tomography (QCT) Bone Mineral Density of the Hip, measured over One Year (at baseline and one year).

The primary endpoint is change in quantitative computed tomography bone mineral density of the total hip, measured at baseline and one year. The registry gives the unit as g/cm^3 and identifies the outcome as a continuous measure summarized by its mean and standard error. QCT is an imaging-based way to quantify bone mineral density at a specified skeletal site; focusing on the hip makes the endpoint a measure of bone status in a clinically relevant location.

Change from baseline is used to describe whether the measured bone density moved over the follow-up period, while comparing treatment and control groups provides a contrast between their reported average changes. The trial’s stated rationale is to test treatment individualized according to turnover status. It proposes that bone formation might be increased in low-turnover participants and bone resorption reduced in normal- or high-turnover participants. The endpoint is therefore intended to assess a bone-density outcome related to that rationale, rather than directly measuring fractures, symptoms, quality of life, or cardiovascular events.

The registry reports the assessment timeframe as one year. It does not report a clinically meaningful threshold for interpreting the size of a QCT change, nor does it provide a conversion from the reported values to another clinical measure. The endpoint should consequently be read as a statistical measure of average change in the recorded unit, with its uncertainty considered alongside the study’s design and limitations.

7. Results Posted in the Registry

• Treatment, Low Turnover: mean 5.72 versus -10.71 on control; difference 16.43 (95% CI 3.31 to 29.55), standardized effect d = 0.61; z-test p = 0.014.
• Control, High Turnover: mean -3.52 versus -10.71 on control; difference 7.19 (95% CI -4.18 to 18.56), standardized effect d = 0.28; z-test p = 0.215.
• Treatment, High Turnover: mean 0.20 versus -10.71 on control; difference 10.91 (95% CI -3.56 to 25.38), standardized effect d = 0.37; z-test p = 0.140.

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.

Change in Coronary Artery Calcifications by Multiple Detector Computed Tomography (MDCT)

• 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:
  • Treatment, Low Turnover: mean 4.48 versus 2.78 on control; difference 1.70 (95% CI -2.95 to 6.35), standardized effect d = 0.19; z-test p = 0.474.
  • Control, High Turnover: mean 4.97 versus 2.78 on control; difference 2.19 (95% CI -2.55 to 6.93), standardized effect d = 0.19; z-test p = 0.365.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Treatment, Low Turnover and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Control, High Turnover and the control. The interval gives the range of effects that remain compatible with the data.

Change in Serum Biochemical Bone Markers of Bone Activity - Parathyroid Hormone (PTH)

• 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:
  • Treatment, Low Turnover: mean 379.00 versus 89.00 on control; difference 290.00 (95% CI 49.08 to 530.92), standardized effect d = 0.74; z-test p = 0.018.
  • Control, High Turnover: mean -125.00 versus 89.00 on control; difference -214.00 (95% CI -385.28 to -42.72), standardized effect d = -0.47; z-test p = 0.014.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Treatment, Low Turnover than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Control, High Turnover than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change in Serum Biochemical Bone Markers of Bone Activity - Bone-specific Alkaline Phosphatase (BSAP)

• 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:
  • Treatment, Low Turnover: mean -1.01 versus 0.61 on control; difference -1.62 (95% CI -13.19 to 9.95), standardized effect d = -0.07; z-test p = 0.784.
  • Control, High Turnover: mean -8.92 versus 0.61 on control; difference -9.53 (95% CI -23.53 to 4.47), standardized effect d = -0.27; z-test p = 0.182.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Treatment, Low Turnover and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Control, High Turnover and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes cover more than one biological domain. Coronary artery calcification is an imaging measure of vascular calcification, while parathyroid hormone, bone-specific alkaline phosphatase, and fibroblast growth factor 23 are biochemical measures related to bone activity. Together, these outcomes add context to the primary bone-density measure, but they are not interchangeable endpoints and do not all answer the same question.

Across the secondary outcomes with numerical results, the pattern is not uniform. The biochemical marker results show more group separation in some comparisons than the calcification outcome, while the bone-specific alkaline phosphatase results do not show the same degree of separation. Numerical fibroblast growth factor 23 results are not reported in the registry record. This uneven pattern means the secondary outcomes do not provide a single, consistent confirmation of the primary result.

Secondary outcomes can be useful for understanding whether observed changes extend beyond the primary measure, but their interpretation is more tentative when many outcomes or comparisons are examined. Each additional test creates another opportunity for a result to appear unusual by chance. The registry record does not report a multiplicity adjustment or a hierarchical testing strategy. Accordingly, unadjusted secondary findings carry less weight than a prespecified primary analysis, particularly when the analysis plan and handling of multiple comparisons are not reported.

These outcomes should be read as complementary evidence rather than as substitutes for the primary endpoint or as proof of a broader treatment effect. They do not establish a clinical benefit, and the posted summaries do not explain how missing secondary measurements were handled.

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

• Change in Coronary Artery Calcifications by Multiple Detector Computed Tomography (MDCT)
• Change in Serum Biochemical Bone Markers of Bone Activity - Parathyroid Hormone (PTH)
• Change in Serum Biochemical Bone Markers of Bone Activity - Bone-specific Alkaline Phosphatase (BSAP)
• Change in Serum Biochemical Bone Markers of Bone Activity - Fibroblast Growth Factor 23 (FGF23)

9. Statistical Interpretation

10. Statistical Methods Explained

Continuous outcomes are summarized by a mean and a standard error. The mean describes the average reported change in a group. The standard error describes the statistical precision of that estimated mean; it is not the spread of individual participants’ measurements. A larger standard error generally means less precision in the estimated group mean, although its interpretation also depends on the number of observations and the variability in the data.

What does a mean difference describe?

A mean difference expresses the estimated separation between two group means, using the direction implied by the selected reference group. In the recalculated primary contrasts, control, low turnover is the reference for each listed comparison. Thus, the treatment, low-turnover contrast is a comparison within the low-turnover category, while the high-turnover-arm contrasts compare those arms with the low-turnover control. Those are different questions. A difference between turnover categories can reflect more than the intervention, so it should not be treated as a same-category treatment effect.

The recalculated contrasts are unadjusted re-calculations from posted summary statistics. They are not participant-level analyses and do not account for covariates or any other adjustment unless that adjustment is explicitly reported. No adjusted analysis is described in the registry record. General statistical interpretation: an unadjusted comparison summarizes the observed separation without controlling for other characteristics, whereas an adjusted model attempts to account for specified factors. Without a report of the model and data used, no adjusted result can be inferred.

How should a confidence interval be read?

A confidence interval gives a range of estimates compatible with the data under the method used. It communicates precision as well as direction: a relatively narrow interval indicates more precise estimation than a wider interval. If an interval includes zero for a mean difference, the data are compatible with no difference as well as with values on either side of zero, at the confidence level used. The registry does not post sponsor confidence intervals for the primary analysis; intervals accompanying the listed contrasts are recalculated from the summary statistics.

A confidence interval is not a guarantee that the true effect lies in that particular interval, and it is not a range containing most individual participant outcomes. It also does not resolve whether an estimated difference is clinically important. The registry does not report a clinical threshold for a meaningful change in hip QCT bone mineral density.

What do p-values contribute?

A p-value describes how unusual data at least as incompatible with a specified null hypothesis would be under the assumptions of the statistical test. It is not the probability that the null hypothesis is true, and it does not measure the size or clinical importance of a difference. The sponsor’s reported primary analysis is a two-sided t-test involving the four groups, with p = .443. The exact contrast represented by that test is not described in the registry record.

The recalculated comparisons report unadjusted p-values for specific contrasts. These p-values should not be treated as interchangeable with the sponsor’s four-group result. The differences in comparison structure matter: a multi-group test can address an overall question about groups, while a pairwise comparison addresses a selected pair. The registry record does not explain whether any follow-up comparisons were planned in advance.

Why can over-dispersion matter?

General explanation: over-dispersion occurs when observed variation is greater than a statistical model expects. It can make standard errors too small if the model assumes less variability than the data contain, which can make intervals appear narrower and p-values smaller than they should be. The primary outcome is continuous, and the registry summarizes it with means and standard errors. No over-dispersion assessment or model diagnostic is reported, so it would not be appropriate to claim that over-dispersion was present or that a particular correction was used.

The listed sample-size calculations are planning illustrations based on observed effects, not the trial’s original design calculation. The registry record does not report the original sample-size assumptions, a prespecified minimum important effect, or a detailed statistical analysis plan. For those reasons, the calculations can illustrate how sample size relates to an assumed effect and power, but cannot verify whether the study was designed around a particular target or whether its completed analyses followed a prespecified plan.

11. Confidence Intervals and Precision

Precision is reflected in the width of an interval around an estimated contrast. For the recalculated primary comparison of treatment, low turnover with control, low turnover, the estimated mean difference is 16.43 and the 95% confidence interval runs from 3.305 to 29.55. The interval lies on one side of zero, but it spans a range of possible contrast sizes. The interval describes uncertainty in the estimated average difference, not the range of changes among individual participants.

The recalculated contrast for control, high turnover relative to control, low turnover is 7.19, with a 95% confidence interval from -4.182 to 18.56. For treatment, high turnover relative to control, low turnover, the estimate is 10.91, with a 95% confidence interval from -3.562 to 25.38. Both intervals include zero and are wide enough to include contrasts in either direction. These estimates are also not direct comparisons of treatment and control within the high-turnover category.

The sponsor’s reported four-group analysis does not include a confidence interval in the registry record. The intervals are recalculated from posted summary statistics and do not supersede the sponsor’s own analysis, particularly given the recorded discrepancy. Precision is therefore best assessed by keeping the sponsor’s result separate from the recalculated pairwise estimates and by noting the different comparison structures.

General explanation: confidence intervals quantify statistical uncertainty under their assumptions, but they do not account automatically for missing data, selection of outcomes, or multiple testing. They also do not state whether a range of effects would matter clinically. The registry record does not report a clinically meaningful threshold for the primary endpoint, so statistical precision cannot by itself establish the practical importance of the estimated change.

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 sample-size figures are participants per arm for the continuous-outcome comparisons. They are not total event counts. The planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The assumed effect to detect is the stated fraction of the observed effect. The original design assumptions for the trial are not reported in the registry record.

The 80% power column gives the illustrative number of participants per arm for an 80% chance of detecting the specified effect under those planning assumptions, if that effect and the assumptions are appropriate. The 90% power column gives the corresponding number per arm for a 90% chance. Power is a property of a planned design under assumed conditions; it is not the probability that a particular result is true or a measure of how likely a treatment is to work.

The rows describe planning for 100%, 75%, or 50% of the observed effect. Smaller assumed effects require more participants to maintain the same target power, because smaller differences are harder to distinguish from random variation. These sample-size figures are planning illustrations based on observed effects, not observed power. They should not be read as evidence that the completed trial did or did not have adequate power for its original research question. The registry record does not report that original justification or the effect size the investigators intended to detect.

Each contrast has its own observed estimate and associated illustration, so the planning figures can differ across outcomes and comparisons. They do not account for multiplicity, attrition, missing outcome measurements, or other design considerations unless those are part of the stated assumptions. No such additions are specified in the planning description.

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 = 16.430; pooled standard deviation σ = 26.745.
2. n = 2 × (1.96 + 0.842)² × 26.745² / 16.430² = 41.6, rounded up to 42 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 <- 16.43                      # observed difference in means
sigma <- 26.7451303978874                     # 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(2440581)
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 = 42 (80% power), 56 (90% power)
 75% of observed effect: n per arm = 74 (80% power), 99 (90% power)
 50% of observed effect: n per arm = 167 (80% power), 223 (90% power)
power.t.test: 42.6 
Simulated power at n = 42 per arm: 0.798 (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 reports a two-sided t-test involving all four primary-outcome groups, with p = .443. It does not report a sponsor confidence interval or identify the precise contrast tested. Separate recalculations from the posted arm summaries produce unadjusted contrasts and confidence intervals, including a low-turnover treatment-versus-control comparison. Those calculations use summary statistics and do not reproduce the sponsor’s stated four-group test.

The difference between these results is not necessarily a direct contradiction: they may address different comparisons. However, the registry flags a discrepancy, and the sponsor’s own analysis takes precedence. The recalculated contrasts are useful for understanding the posted group means and for illustrating uncertainty, but they should not be presented as the trial’s definitive primary analysis or used to overrule the sponsor’s reported result.

The record does not describe the sponsor test’s exact estimand, the method used to form the test statistic, or how the four arms were incorporated. It also does not provide enough information to reconcile the reported result with each recalculated contrast. The safest reading is to report the sponsor’s result as the official analysis and clearly label the other contrasts as unadjusted recalculations from posted summaries.

15. Multiplicity, Missing Data and Analysis Populations

The registry lists one primary outcome and several secondary outcomes, with multiple groups and comparisons represented in the posted results. Testing multiple outcomes or contrasts raises a multiplicity issue: even if every null hypothesis were true, the chance of at least one apparently notable result can increase as more tests are conducted. General statistical practice may address this through prespecified outcome hierarchies, adjusted significance thresholds, or other methods, but the registry record does not report a multiplicity adjustment or a testing hierarchy.

The sponsor reports a two-sided t-test involving the four primary-outcome groups. The registry does not describe the test’s specific contrast or how it relates to the individual arm comparisons. The posted recalculations are unadjusted. The record does not say whether those comparisons were prespecified, whether they were exploratory, or whether other unreported analyses were conducted. The analysis plan is not reported in the registry record, so the distinction between planned and post hoc analyses cannot be established.

Missing-data handling is also not reported in the registry record. The record does not describe how absent one-year measurements were treated, whether any imputation was used, or whether the analysis included all randomized participants, participants with observed outcomes, or another population. The number enrolled is reported, and the outcome summaries give arm-level sample sizes, but the record does not explain the relationship between those counts and the analysis population or any exclusions.

These omissions limit assessment of possible bias from missing observations and of whether the reported analyses preserve the intended randomized comparisons. Interim analyses are not reported in the registry record. The original statistical plan, detailed allocation procedure, and rules for handling multiple tests are also not reported. None of these missing details can be inferred from the posted p-values or summary statistics.

16. 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.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: death (29.2%), weakness (16.7%), uti (8.3%), soa (8.3%), right foot ulcer (8.3%).

The registry reports counts of participants affected by serious adverse events and other adverse events in each group, along with deaths. Serious adverse events were reported for 16 of 37 participants in control, low turnover; 10 of 24 in treatment, low turnover; 21 of 50 in control, high turnover; and 16 of 30 in treatment, high turnover. Other adverse events were reported for 16 of 37, 16 of 24, 19 of 50, and 17 of 30 participants in those respective groups.

The death counts were 0 in each low-turnover group, 7 in control, high turnover, and 5 in treatment, high turnover. The registry also lists serious-event terms, including Death, Weakness, UTI, SOA, Right foot ulcer, and Left great toe amputation. The term proportions are reported in the record, but their denominator is not explained in the available safety summary.

These are descriptive counts. They do not establish that an event was caused by a study intervention, and they do not by themselves compare risk while accounting for follow-up time, participant characteristics, or event severity beyond the registry categories. The safety information should be interpreted with the trial’s group sizes and the limited detail in the registry record in mind.

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

The posted results describe average one-year changes in hip QCT bone mineral density across four groups organized by turnover status and intervention. The low-turnover treatment-versus-control recalculation has an estimated contrast whose confidence interval excludes zero. The other recalculated primary contrasts use the low-turnover control as their reference, and their confidence intervals include zero. The sponsor’s reported four-group test has p = .443, and the registry flags a discrepancy between the sponsor analysis and the recalculations. The sponsor’s own analysis takes precedence.

These results do not establish that the treatment strategy is effective or ineffective. A p-value is not a measure of treatment benefit, and a statistical difference is not automatically a clinically meaningful difference. The registry does not state a threshold for an important change in QCT bone mineral density. Nor do the posted summaries show whether individual participants experienced improvement, stability, or worsening.

The study’s stated rationale links turnover-specific treatment to bone formation or resorption, but the primary endpoint is a measured bone-density change. It is not a direct measure of fracture occurrence, quality of life, cardiovascular events, or survival. The secondary outcomes provide additional measures, but their results are incomplete in the registry record and are subject to the uncertainty associated with multiple testing.

The findings are also bounded by what is reported: the analysis plan, missing-data methods, analysis population, and original sample-size justification are not reported in the registry record. The trial enrolled a specific chronic kidney failure population divided into turnover groups; the record alone does not show how broadly its results apply to other populations or care settings. Interpretation should remain tied to the reported measures, comparisons, and uncertainty rather than extending to clinical recommendations.

18. Why This Trial Matters Statistically

This trial is statistically informative because it combines randomized parallel groups with treatment choices differentiated by bone-turnover category. That structure makes the definition of the comparison especially important. A treatment-versus-control contrast within a turnover category addresses a different question from a contrast between groups that differ in both turnover status and intervention. The recalculated comparisons use control, low turnover as the reference across the listed contrasts, so their labels and reference groups matter for interpretation.

The record also illustrates why a reported overall test and recalculated pairwise estimates should not be treated as interchangeable. The sponsor’s primary analysis is a two-sided t-test involving the four groups, whereas the recalculations compare selected arm means. Their different structures can yield different summaries of the data. Because the registry flags a discrepancy, the sponsor analysis takes precedence, while the recalculations remain descriptive checks based on the posted summaries.

Precision and multiplicity are also central. The confidence intervals communicate uncertainty around estimated contrasts, while the several secondary outcomes create multiple opportunities for apparently notable results. Without a reported adjustment strategy, secondary findings should be interpreted cautiously. Missing-data methods and the analysis population are also absent, limiting evaluation of how fully the posted results reflect the randomized groups.

More broadly, this record shows why statistical interpretation depends on more than a p-value. The endpoint, reference group, comparison structure, uncertainty, and completeness of reporting all shape what a result can support. The registry contains useful arm-level summaries, but important elements of the original analysis plan are not reported.

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 specific to this trial affect interpretation. First, the sponsor’s reported primary result is a four-group two-sided t-test with p = .443, while the posted recalculations give separate contrasts from summary statistics. The registry flags a discrepancy, does not describe the exact estimand for the sponsor test, and provides no sponsor confidence interval. The sponsor’s analysis therefore takes precedence, but the available record does not permit a complete reconciliation.

Second, the recalculated primary contrasts do not all compare treatment with control within the same turnover category. The low-turnover treatment contrast uses the low-turnover control as reference, whereas the high-turnover arm contrasts also use that low-turnover control. This makes those latter estimates mixtures of differences in turnover category and treatment assignment, rather than direct high-turnover treatment effects.

Third, the registry does not report the original sample-size justification, detailed statistical plan, analysis population, or missing-data handling. It is therefore not possible to determine from the record whether the analysis followed a prespecified plan, how absent one-year measurements were managed, or whether the study was designed around a particular target effect. The reported analyses also do not state a multiplicity adjustment.

Fourth, numerical results for fibroblast growth factor 23 are not reported, despite its listing as a secondary outcome. The registry does not explain the denominator behind the listed serious-event term percentages. Finally, the primary endpoint is a one-year imaging measure, and the record does not report a clinically meaningful threshold for interpreting its magnitude. These limitations do not erase the posted observations, but they narrow the conclusions that can be drawn from them.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Renal Osteodystrophy: An Individual Management Approach — NCT02440581.
• Registry record last updated 2023-01-05; status last verified 2022-12.
• Results first posted 2023-01-05.
• 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

The registry record describes a completed randomized, parallel-group trial with no masking and 141 participants, studying treatment individualized by bone-turnover status in chronic kidney failure. Low-turnover participants in the treatment group received teriparatide and cinacalcet; high-turnover participants received alendronate. The control groups are described as receiving no intervention.

The primary outcome was one-year change in hip QCT bone mineral density. The sponsor reports a two-sided four-group t-test with p = .443. Unadjusted recalculations from posted summaries give additional contrasts, but the registry flags a discrepancy; the sponsor’s own analysis takes precedence. Secondary outcomes address coronary calcification and biochemical markers, with fibroblast growth factor 23 numerical results not reported in the registry record.

The original sample-size rationale, statistical plan, missing-data methods, analysis populations, and multiplicity approach are not reported in the registry record. The results should therefore be interpreted as posted group summaries and analyses, with attention to comparison structure, uncertainty, and incomplete reporting.