Evaluation of Approved Weight-Based Dose Compared to Fixed Dose of Plerixafor in Patients With Non-Hodgkin's Lymphoma (NHL) Weighing Less Than 70 Kilograms: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Evaluation of Approved Weight-Based Dose Compared to Fixed Dose of Plerixafor in Patients With Non-Hodgkin's Lymphoma (NHL) Weighing Less Than 70 Kilograms (NCT01164475), a randomized phase 4 study. The primary outcome is Proportion of Patients Who Achieved at Least 5*10^6 Cluster of Differentiation 34+ (CD34+) Cells Per Kilogram (Cells/kg).

2. Clinical Question

3. Trial Design

This was a phase 4, multicenter, randomized, comparator trial of two plerixafor dosing approaches in patients with non-Hodgkin's lymphoma weighing no more than 70 kg. The registry record lists 61 enrolled participants. The design was parallel-group and unmasked, with 30 participants in the fixed-dose arm and 31 in the weight-based arm in the primary outcome results.

Both groups received G-CSF as part of the mobilization regimen. The fixed-dose group received 20 mg plerixafor, while the weight-based group received 0.24 mg/kg. The arm descriptions place plerixafor in the evening of Day 4 after G-CSF during the mobilization period. The registry record describes the fixed-dose administration as 10 to 11 hours before first apheresis; the weight-based description also places it before first apheresis. The full administration wording is not reported in the registry record.

The primary endpoint was the proportion reaching the collection target of at least 5*10^6 CD34+ cells/kg, assessed from Day 5 up to Day 8. The FAS included randomized participants who signed informed consent and received at least one dose of plerixafor. The record also lists secondary outcomes concerning a lower collection threshold, apheresis duration, total cell collection, peripheral blood CD34+ cell change, and pharmacokinetic measures.

The study is marked completed. Its start is listed as 2010-10 and primary completion as 2013-02. The registry record does not report the original sample-size justification, a detailed randomization procedure, or the trial's original statistical analysis plan. It also does not report masking beyond the stated absence of masking.

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: A total of 71 patients were screened of which 10 patients were screen failures. A total of 61 patients were randomized.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: FAS included all randomized patients who signed informed consent form and received at least one dose of plerixafor.

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.

Population: Full analysis set (FAS) included all randomized patients who signed informed consent form and received at least one dose of plerixafor.

6. Primary Endpoint

The registry lists the primary outcome as Proportion of Patients Who Achieved at Least 5*10^6 Cluster of Differentiation 34+ (CD34+) Cells Per Kilogram (Cells/kg), measured over Day 5 up to Day 8.

The primary endpoint is the proportion of participants who collected at least 5*10^6 CD34+ cells/kg over a maximum of four apheresis sessions, within four days of apheresis. The collection window is described as Day 5 up to Day 8. CD34+ cells are the cell type counted for the stated collection target, which the registry describes as the optimum number required for transplantation.

Expressing the endpoint as a proportion makes the result clinically interpretable as the share of participants in each group who reached the prespecified collection threshold within the stated window. It does not show how far above or below the target each participant was, nor does it capture the full distribution of collected cell counts. It also does not, by itself, describe subsequent transplantation or patient outcomes.

The reported arm proportions were 60.0% for fixed-dose plerixafor and 54.8% for weight-based plerixafor. These are observed results in the FAS, rather than estimates of what would occur in a larger population with certainty. The uncertainty around the between-group comparison matters: the posted unadjusted interval for the risk difference extends across no difference. The endpoint therefore supports a comparison of observed target attainment in this trial, while leaving substantial uncertainty about the size and direction of any underlying difference.

7. Results Posted in the Registry

• Weight-Based Plerixafor: 54.8% (17/31) versus 60.0% (18/30) on control; risk difference -5.2 percentage points (95% CI -29.9 to 19.6), risk ratio 0.91 (0.59–1.41); unadjusted two-proportion z-test p = 0.684.

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.

Proportion of Patients Who Achieved at Least 2*10^6 CD34+ Cells/kg in Less Than or Equal to 4 Days of Apheresis

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Weight-Based Plerixafor: 90.3% (28/31) versus 93.3% (28/30) on control; risk difference -3.0 percentage points (95% CI -16.7 to 10.7), risk ratio 0.97 (0.83–1.12); unadjusted two-proportion z-test p = 0.668.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Weight-Based Plerixafor and the control. The interval gives the range of effects that remain compatible with the data.

Mean Fold Increase in Peripheral Blood CD34+ Cell Count Following Plerixafor

• 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 deviations.
• Result:
  • Weight-Based Plerixafor: mean 5.09 versus 5.43 on control; difference -0.34 (95% CI -2.09 to 1.41), standardized effect d = -0.10; z-test p = 0.703.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Weight-Based Plerixafor and the control. The interval gives the range of effects that remain compatible with the data.

Maximum Observed Plasma Concentration (Cmax)

• 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 deviations.
• Result:
  • Weight-Based Plerixafor: mean 711.00 versus 957.00 on control; difference -246.00 (95% CI -336.92 to -155.08), standardized effect d = -1.37; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Weight-Based Plerixafor than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes cover several related but distinct questions: attainment of a lower collection threshold, apheresis duration and total cell collection, peripheral blood CD34+ cell change, and pharmacokinetic measures. Collectively, they describe aspects of cell mobilization, collection, and exposure rather than a single substitute for the primary endpoint. The posted results include outcomes that are close between arms and an exposure measure with a clearer difference in the unadjusted comparison.

This mixed pattern does not invalidate the primary result. A difference in plasma concentration is not equivalent to a difference in reaching the collection target, and similarity on one secondary measure does not prove equivalence on another. Each endpoint has its own measurement scale, variability, and uncertainty. The secondary findings may provide context for the primary comparison, but they do not establish a consistent advantage across all aspects of treatment.

Unadjusted secondary analyses carry less weight when many outcomes are examined because the chance of finding a nominally unusual result increases as more tests are considered. The registry record lists multiple secondary outcomes but does not report a multiplicity adjustment or a prespecified hierarchy for interpreting them. Thus, isolated secondary p-values should be treated as exploratory evidence, not as independent confirmation of a primary conclusion. The registry record also does not report posted results for every listed secondary outcome in the registry record for this analysis.

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

• Proportion of Patients Who Achieved at Least 2*10^6 CD34+ Cells/kg in Less Than or Equal to 4 Days of Apheresis
• Median Number of Days of Apheresis to Collect at Least 2*10^6 CD34+ Cells/kg
• Median Number of Days of Apheresis to Collect at Least 5*10^6 CD34+ Cells/kg
• Total Number of CD34+ Cells/kg Collected Over up to 4 Aphereses
• Mean Fold Increase in Peripheral Blood CD34+ Cell Count Following Plerixafor
• Maximum Observed Plasma Concentration (Cmax)
• Time to Reach Maximum Plasma Concentration (Tmax)
• Terminal Elimination Half-life (T1/2)

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is binary: each participant either reached the collection threshold within the specified period or did not. A percentage summarizes the number reaching the target relative to the number analyzed in each arm. The comparison can then be expressed as a difference in proportions, or as a ratio-based measure such as a risk ratio or odds ratio. These measures answer related but distinct questions and have different scales.

What does a risk difference describe?

A risk difference subtracts the proportion in one group from the proportion in the other. Its reference value for no difference is zero. An interval that crosses zero includes results compatible with either group having the higher proportion, as well as no difference. The posted primary risk-difference interval crosses zero, so its direction is uncertain. The interval is more informative than the point estimate alone because it conveys the range of effects compatible with the data under the calculation's assumptions.

Why are p-values not measures of effect size?

The unadjusted primary p-value is 0.684. A p-value describes how unusual data at least as inconsistent with a specified null hypothesis would be if that hypothesis and the analysis assumptions held. It is not the probability that the null hypothesis is true, and it does not measure the size or importance of an effect. A large p-value does not demonstrate equivalence or prove that the treatments have identical results. Interpretation should consider the estimate and its interval, along with the study design and the amount of information available.

What does the logistic regression result measure?

Logistic regression models the odds of a binary outcome. The registry reports an odds ratio of 1.91, a 95% confidence interval from 0.44 to 9.17, and p = 0.395. For an odds ratio, the no-association reference is one. The wide interval includes values on either side of that reference. The registry record does not report the covariates, model details, or enough information to reconcile the odds-ratio orientation with the named arms. It is therefore appropriate to report the model result as registered, without assuming it is a direct restatement of the unadjusted risk difference.

Why can a small trial have wide intervals?

Estimates from limited numbers of participants are sensitive to the outcomes of a few individuals. This is especially relevant for proportions when each participant contributes one binary outcome. Limited information tends to leave a broad range of plausible effects, even when the observed arm percentages are close. A wide interval is not evidence that every value in the interval is equally likely; it indicates that the data do not estimate the contrast precisely.

How should the continuous outcomes be read?

For continuous outcomes, the posted arm results are means with standard deviations. A mean difference compares the average values, while the standard deviation describes variability among observations within an arm. The peripheral blood CD34+ fold-increase means were 5.43 and 5.09, with standard deviations of 4.02 and 2.81. The posted unadjusted mean difference is -0.34, with an interval from -2.086 to 1.406 and p = 0.703. That interval crosses zero, so the data do not precisely distinguish the arm means for this outcome.

For maximum observed plasma concentration, the posted means were 957.0 ng/mL and 711.0 ng/mL, with standard deviations of 216.0 and 136.0. The unadjusted mean difference is -246.0, with an interval from -336.9 to -155.1 and p < 0.001. This is evidence of a difference in this measured concentration outcome under the posted unadjusted comparison. It does not, on its own, establish a difference in the primary cell-collection endpoint or in later clinical outcomes.

Why can over-dispersion matter?

In general, over-dispersion means that observed variability is greater than a model assumes. When a model underestimates variability, its standard errors and intervals may be too small and its tests too optimistic. This is a general statistical consideration, not a reported finding about this trial. The registry record does not report an over-dispersion assessment or a model for the binary primary endpoint beyond the named logistic regression analysis.

The recalculated comparisons are simple, unadjusted calculations from the posted summary statistics. They do not substitute for a fully specified trial analysis. The posted record does not report the original statistical analysis plan, planned covariate adjustment, or a detailed procedure for handling missing data. These omissions limit how far the calculations can be taken beyond descriptive comparison.

11. Confidence Intervals and Precision

Precision concerns how narrowly the available data estimate a group contrast. The primary arm percentages are 60.0% for fixed-dose plerixafor and 54.8% for weight-based plerixafor. The unadjusted confidence interval for their risk difference spans zero and includes effects in either direction. Its breadth reflects substantial uncertainty; the point estimate alone should not be read as a settled difference.

A confidence interval is a range produced by a statistical procedure that, under its assumptions, would contain the true parameter at the stated rate over repeated use of that procedure. It is not a probability statement about the fixed true value after observing this particular interval. For the sponsor's logistic analysis, the 95% interval for the odds ratio runs from 0.44 to 9.17. That wide span includes the odds-ratio value associated with no difference, as well as values on either side.

Precision also differs by outcome. The peripheral blood cell-count fold-increase comparison has an interval that crosses zero, whereas the maximum plasma concentration comparison has an interval from -336.9 to -155.1 and p < 0.001. The latter result is comparatively more clearly separated from no mean difference in the posted analysis. Its precision applies to plasma concentration, not automatically to cell collection or other outcomes.

The primary comparison is based on 30 and 31 participants, so the observed proportions are informed by modest group sizes. The intervals make the resulting uncertainty visible. The trial's findings are compatible with a range of possible differences, and the registry record does not establish a narrow equivalence margin or report a formal equivalence analysis.

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 planning illustrations based on the observed effects, not the trial's original design calculations. For these non-time-to-event comparisons, the figures are participants per arm. The planning assumptions are a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect. The original trial's sample-size assumptions and justification are not reported in the registry record.

The 80% power column represents the planned number of participants per arm under those assumptions for a design with an 80% chance of detecting the selected effect if that effect were the true one. The 90% power column uses a higher target probability of detection, and therefore generally requires more participants per arm for the same assumed effect. These are design-planning quantities, not evidence that the completed trial had a particular probability of finding a difference.

Rows that plan for 75% or 50% of the observed effect ask what sample size would be needed if the effect of interest were smaller than the observed estimate. Smaller effects are harder to distinguish from random variation, so they require more participants to achieve the same planned power. The estimates based on the observed effect itself are especially dependent on the trial's observed result and should not be treated as reliable forecasts of a future effect.

This is not observed power. It is a set of hypothetical planning calculations that uses stated assumptions and the observed effect as an input. It does not explain the enrollment target for this trial, establish that its design was adequate, or show that a future study would reproduce the observed effect.

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, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.600; treatment proportion p₁ = 0.548; average p̄ = 0.574.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6993 = 1.3706.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6983 = 0.5877.
4. n = (1.3706 + 0.5877)² / (-0.0516)² = 1,439.6, rounded up to 1,440 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
p0 <- 0.6                          # control proportion
p1 <- 0.548387096774194                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^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 (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(1164475)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 1,440 (80% power), 1,927 (90% power)
 75% of observed effect: n per arm = 2,550 (80% power), 3,413 (90% power)
 50% of observed effect: n per arm = 5,713 (80% power), 7,648 (90% power)
power.prop.test: 1439.6 
Simulated power at n = 1,440 per arm: 0.805 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-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 the sponsor's primary comparison as logistic regression, with an odds ratio of 1.91, a 95% confidence interval from 0.44 to 9.17, and p = 0.395. This is the trial's reported model-based analysis. The registry record does not provide the model specification or enough detail to determine the exact coding and orientation of the odds ratio.

The simple recalculation is an unadjusted comparison based on the posted arm summaries. For the primary endpoint, it reports an unadjusted p-value of 0.684 and a risk-difference interval that crosses zero. Those statistics use a different effect measure and calculation from logistic regression, so the odds ratio and risk difference should not be compared as though they were the same quantity. Their p-values also need not match.

The record does not flag a discrepancy between the sponsor analysis and the recalculation. The recalculation is useful as a transparent comparison of the posted proportions, but it does not supersede the sponsor's model-based analysis or reproduce an analysis plan that is not reported. Both results indicate uncertainty rather than a clear separation between groups on the primary endpoint.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when several hypotheses are tested. Even if each test uses a conventional significance threshold, examining many outcomes can increase the chance that at least one result appears statistically notable by chance. This is why a trial may specify a primary endpoint and a testing hierarchy or adjust for multiple comparisons. The registry identifies a primary endpoint and lists secondary outcomes, but a multiplicity procedure or testing hierarchy is not reported in the registry record.

The primary endpoint should therefore remain the central result for the principal comparison. Secondary analyses can help describe other dimensions of the intervention, but unadjusted findings—especially an isolated small p-value—should be interpreted with caution. The registry record does not say whether any secondary outcome was intended to support a formal confirmatory claim.

The primary analysis population is described as randomized participants who signed informed consent and received at least one dose of plerixafor. This is the stated FAS definition; it is not a complete account of every analysis population used for every outcome. The registry record does not report the number of participants excluded from any analysis, the amount or pattern of missing outcome data, or an imputation method.

Other details needed to assess analysis choices are also not reported in the registry record. These include the original statistical analysis plan, planned handling of protocol deviations, prespecified covariates, and whether any interim analyses were conducted. The absence of these details does not demonstrate that such procedures were or were not used. It limits the ability to evaluate whether the posted analyses followed prespecified methods or how sensitive results may be to missingness and analysis-population choices.

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 0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: cellulitis (3.2%), diffuse large b-cell lymphoma (3.2%), non-hodgkin's lymphoma (3.2%), pleural effusion (3.2%).

The serious adverse event figures are counts of affected participants, not counts of every event, and they should be read separately from the efficacy outcomes. The registry lists zero participants with a serious adverse event in the fixed-dose group and three in the weight-based group. The numbers at risk were 30 and 31, respectively. These figures are descriptive; the record does not report a comparative statistical test for serious adverse events.

For other adverse events, the registry lists 26 affected participants in the fixed-dose group and 25 in the weight-based group. These counts do not establish that the groups had the same safety experience, because the trial involved relatively small groups and the counts do not show event severity, duration, or recurrence. The listed serious-event terms include cellulitis, diffuse large B-cell lymphoma, non-Hodgkin's lymphoma, and pleural effusion, each reported as 3.2%.

Deaths are not reported in the registry record. These safety summaries do not support a definitive comparison of safety between regimens, and they should not be interpreted as medical advice.

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

The posted primary results show that 60.0% of participants in the fixed-dose group and 54.8% in the weight-based group reached the specified CD34+ cell collection target. The unadjusted comparison is imprecise: its confidence interval includes no difference and possible effects in either direction, and the unadjusted p-value is 0.684. The sponsor's logistic regression result is also uncertain, with a 95% confidence interval from 0.44 to 9.17 and p = 0.395.

These findings do not establish a clear difference between the dosing strategies on the primary endpoint. They also do not prove the strategies equivalent, show that one is superior, or rule out effects that the trial could not estimate precisely. A conclusion of equivalence would require an appropriate design and a prespecified equivalence margin; neither is reported in the registry record.

The primary endpoint concerns target cell collection over a defined apheresis period. It does not itself report whether transplantation occurred or describe later health outcomes. The secondary pharmacokinetic result concerns plasma concentration and should not be used as a replacement for the cell-collection result. Likewise, the descriptive adverse-event counts are not a definitive comparative safety assessment.

Interpretation is bounded by the group sizes, the width of the primary interval, and the lack of detail about the original statistical plan, missing data, and multiplicity. The results describe this completed trial and do not guarantee that another population or study would yield the same estimates. They provide a comparison of observed outcomes, not a basis for medical advice.

18. Why This Trial Matters Statistically

This trial illustrates why a treatment comparison should not be reduced to the difference between two percentages or to a p-value. The primary arm percentages are separated by a modest observed amount, but the uncertainty interval crosses no difference. Reporting both the estimate and its uncertainty prevents the observed ordering from being mistaken for a reliable conclusion about the underlying groups.

It also demonstrates that different effect measures can tell the same broad story while looking numerically different. The unadjusted risk difference and the sponsor's logistic odds ratio use distinct scales and analysis methods. A reader needs the measure, interval, and model context before interpreting either estimate. The registry record's limited description of the model is an important boundary on interpretation.

The secondary outcomes show why endpoints should not be collapsed into one overall claim. A pharmacokinetic contrast can be statistically clear while the primary collection endpoint remains uncertain. Such differences may help characterize the trial, but multiplicity and endpoint relevance matter when weighing secondary findings.

Finally, planning calculations based on an observed effect are not evidence of the trial's original design adequacy or of observed power. Separating planning illustrations from the completed trial's observed estimates helps avoid a common interpretive error. This record is therefore useful for understanding uncertainty, endpoint distinctions, and the limits of what a small randomized comparison can establish.

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.
• Participant counts were reconstructed from posted percentages and arm sizes, so small rounding differences are possible.

The trial enrolled 61 participants, with 30 and 31 in the primary outcome arms. This limits the amount of information available for estimating the primary difference and leaves its interval broad. The study was unmasked, as recorded in the registry. The registry record does not report details about allocation concealment, the randomization procedure, or safeguards against bias in outcome assessment.

The primary endpoint is a threshold-based measure. It records whether participants reached the target within the specified collection period, but does not convey how far each participant was from the target or the distribution of total cell counts. The registry record also does not report individual participant data, so the recalculation is limited to posted summaries.

The sponsor's logistic regression is reported without model details sufficient to assess covariate selection, coding, or the orientation of the odds ratio. The original statistical analysis plan, sample-size justification, missing-data handling, and interim analyses are not reported in the registry record. Multiplicity control for the secondary outcomes is also not reported.

The safety information is descriptive, with no comparative test reported, and deaths are not reported in the registry record. Several listed secondary outcomes do not have results in the registry record for this analysis. These limitations restrict conclusions about the full outcome profile and about how robust the findings are to alternative analysis choices.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Evaluation of Approved Weight-Based Dose Compared to Fixed Dose of Plerixafor in Patients With Non-Hodgkin's Lymphoma (NHL) Weighing Less Than 70 Kilograms — NCT01164475.
• Registry record last updated 2014-02-25; status last verified 2014-02.
• Results first posted 2014-01-31.
• 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

This completed, randomized, unmasked phase 4 trial compared fixed-dose plerixafor at 20 mg with weight-based plerixafor at 0.24 mg/kg, both used with G-CSF, in patients with non-Hodgkin's lymphoma weighing no more than 70 kg. The registry lists 61 enrolled participants.

The primary outcome was reaching at least 5*10^6 CD34+ cells/kg within four days of apheresis. The posted proportions were 60.0% for fixed-dose and 54.8% for weight-based plerixafor. The unadjusted comparison and the reported logistic regression both leave substantial uncertainty about the between-group difference. The results do not establish superiority or equivalence.

Secondary measures address cell collection, mobilization, and drug exposure. Serious adverse events affected zero participants in the fixed-dose group and three in the weight-based group; comparative safety conclusions are limited. Important details, including the original sample-size justification, missing-data methods, and multiplicity approach, are not reported in the registry record.