Immunomodulatory Drugs (Lenalidomide With or Without Pomalidomide) in Combination With a Corticosteroid Drug (Dexamethasone) for the Treatment of Multiple Myeloma: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Immunomodulatory Drugs (Lenalidomide With or Without Pomalidomide) in Combination With a Corticosteroid Drug (Dexamethasone) for the Treatment of Multiple Myeloma (NCT05288062), a non-randomized phase 2 study. The primary outcome is Response Rates (RR) at First Assessment.

2. Clinical Question

3. Trial Design

This phase II study, sponsored by Mayo Clinic, is titled “Evaluating Mechanisms of Immunomodulator Sensitivity and Resistance in Multiple Myeloma.” Its listed enrollment is 17. The study began on 2022-06-15, had a primary completion date of 2024-02-25, and is recorded as terminated. The reason for termination is not reported in the registry record.

The design is non-randomized, unmasked, and parallel. The registry describes four cohorts rather than assigning patients randomly to a common treatment comparison. Cohort A covers patients with smoldering multiple myeloma and lenalidomide, with or without dexamethasone. Cohort B covers newly diagnosed multiple myeloma and follows treatment as in Cohort A. Cohort C covers relapsed or refractory multiple myeloma and describes lenalidomide with dexamethasone or pomalidomide with dexamethasone. Cohort D covers relapsed multiple myeloma after lenalidomide maintenance and follows treatment as in Cohort C. The descriptions do not establish randomized assignment between the regimen alternatives.

The primary endpoint is response at first assessment, with a 21-day timeframe. The analysis population is described as patients who completed the study. Although the registry lists enrollment, it does not report the number of completers or the number included in the primary endpoint analysis. It also does not report a detailed statistical plan, a sample-size justification, or the reason the study was terminated. The design is suited to describing response and biomarker patterns within the specified cohorts, but it does not support treating the cohorts as interchangeable randomized arms.

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:

Analysis population for the primary outcome, as defined in the registry: Only patients that completed the study were included in analysis

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: Only patients that completed the study were included in analysis

6. Primary Endpoint

The registry lists the primary outcome as Response Rates (RR) at First Assessment, measured over 21 days.

The primary endpoint counts participants who achieved a partial response or better at first assessment, using International Myeloma Working Group criteria. Response is described as a binary outcome: a participant either meets the response definition or does not. The assessment timeframe is 21 days.

A response endpoint offers a clinically interpretable way to describe early disease response. In this study, the registry also links response assessment to baseline and post-treatment biospecimens, with the aim of identifying biomarkers and estimating response within biomarker groups. Such an approach can describe whether response patterns differ across biologically defined groups. It does not, by itself, show that a biomarker causes a response difference or that it can reliably predict response in other patients.

The registry says each cohort was to be evaluated separately and independently. That makes the endpoint a within-cohort description rather than a single randomized treatment contrast across the study. The primary response counts or estimates are not reported in the registry record. Consequently, the endpoint definition and analysis intent are available, but the observed response findings and their precision are not.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The registry describes a binary primary endpoint and a cohort-specific analysis. It does not report the statistical methods used to produce a primary response estimate, a confidence interval, or a hypothesis test. The following concepts explain how such results are generally read; they should not be taken as a claim that a particular unreported method was used in this study.

What does a binary response endpoint mean?

In general, a binary outcome places each participant into one of two categories according to a defined rule. Here, the stated success rule is achieving partial response or better under International Myeloma Working Group criteria. A count of participants meeting that rule is not the same as a response rate: a rate also needs a clearly stated denominator. The record identifies the analysis population as study completers but does not give the number of completers or the primary response count. Thus, a reader cannot recover a response rate from the information recorded.

Binary outcomes can be presented as counts, proportions, or contrasts between groups. Each representation answers a somewhat different question. A count says how many observed participants met the definition; a proportion relates that count to the number assessed; a contrast compares outcomes between groups. A contrast needs care when the groups were not formed by random assignment. In this study, each cohort is to be evaluated separately and independently, and the record explicitly notes that the arms are not a like-for-like control comparison.

How should uncertainty be understood?

In general, a confidence interval describes the range of values reasonably compatible with the observed data under a specified statistical model. It communicates precision as well as the point estimate: a wider interval indicates less precision, while a narrower interval indicates more precision. A confidence interval is not a guarantee that the true value lies within its limits, and it does not correct for selection, confounding, or an inappropriate analysis population. The registry record does not report a confidence interval for the primary endpoint.

For a binary outcome, precision depends in part on how many participants are assessed and how the outcomes are distributed. Small or sparse groups generally yield less precise estimates. That general principle is relevant to interpreting cohort-specific response estimates, but the record does not provide the analyzed group sizes or primary outcome counts needed to quantify precision in this study.

Why does the cohort structure matter?

In general, random allocation can help balance known and unknown characteristics between treatment groups. Non-randomized cohorts do not have that protection. When cohorts represent different disease settings or treatment histories, their outcomes may differ even if treatment itself has no effect. The study descriptions distinguish smoldering, newly diagnosed, relapsed, and refractory settings, as well as relapsed disease after lenalidomide maintenance. Consequently, comparing cohort outcomes as though they arose from exchangeable groups would not be justified by the design information in the registry.

The biomarker plan also requires cautious interpretation. The registry says biomarkers will be categorized into clinically relevant groups using baseline and post-treatment biospecimens, and response will be estimated within each biomarker. In general, categorizing a continuous or complex biological measure can simplify presentation, but the choice of categories can affect observed patterns. The specific biomarkers, classification rules, and corresponding estimates are not reported in the registry record. Association between a biomarker group and response would not alone establish that the biomarker predicts response beyond other characteristics or causes a difference in response.

What do the planning assumptions mean?

In general, a sample-size calculation asks how many participants would be needed under stated assumptions to detect a specified effect with a chosen significance level and power. The registry's planning description refers to a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. It also says the effect to detect is a stated fraction of the observed effect. These are planning assumptions, not evidence that the study was designed or conducted with those conditions. The numerical planning estimates are not reported in the registry record.

Any sample-size illustrations based on an observed effect are hypothetical planning aids, not observed power. Observed power is not a substitute for interpreting the estimate and its uncertainty after a study. Moreover, the registry's description of equal allocation between two arms does not make this non-randomized, multi-cohort study a randomized two-arm comparison. The stated assumptions should therefore be understood as the basis for planning illustrations, not as a description of the actual cohort allocation.

What can be concluded from the posted methods?

The record identifies the endpoint definition, timeframe, analysis population, biomarker intent, and separate cohort evaluation. It does not report a detailed statistical analysis plan, the method for calculating response estimates, how uncertainty was quantified, how missing endpoint data were handled, or how multiplicity was addressed. General methods can explain what those choices mean, but they cannot fill in the choices absent from the record. For this study, the available design information and the absence of primary response results limit interpretation to the stated analytic intent rather than an estimate of treatment effect.

10. Exact Estimates for Each Arm

No two-arm comparison is shown for this trial, but each arm's result can still be summarized with exact interval estimates computed from the posted counts. The Clopper-Pearson interval is exact and conservative; the Wilson interval is a common closer-to-nominal alternative; the Bayesian credible interval uses a uniform Beta(1, 1) prior. For small groups the three can differ noticeably.

R code and output

arm    <- c("Cohort B (Lenalidomide, Dexamethasone)", "Cohort C (Lenalidomide, Dexamethasone, Pomalidomid")
n      <- c(5, 10)
events <- c(1, 4)
for (i in seq_along(n)) {
  ci <- binom.test(events[i], n[i])$conf.int          # Clopper-Pearson exact interval
  cr <- qbeta(c(0.025, 0.975), 1 + events[i], 1 + n[i] - events[i])   # Bayesian, uniform Beta(1,1) prior
  wi <- (function(x, n) { p <- x / n; z <- qnorm(0.975); d <- 1 + z^2 / n
    c((p + z^2 / (2 * n) - z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d, (p + z^2 / (2 * n) + z * sqrt(p * (1 - p) / n + z^2 / (4 * n^2))) / d) })(events[i], n[i])
  cat(sprintf("ARM|%s|%d|%d|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f|%.1f\n", arm[i], n[i], events[i], 100 * events[i] / n[i],
              100 * ci[1], 100 * ci[2], 100 * wi[1], 100 * wi[2], 100 * cr[1], 100 * cr[2]))
}

ARM  Cohort B (Lenalidomide, Dexamethasone)  5  1  20.0  0.5  71.6  3.6  62.4  4.3  64.1
ARM  Cohort C (Lenalidomide, Dexamethasone, Pomalidomid  10  4  40.0  12.2  73.8  16.8  68.7  16.7  69.2

11. Multiplicity, Missing Data and Analysis Populations

The registry lists secondary outcomes concerning response rates among African American and White patients and depth of hematological responses. It also records four outcome measures and one analysis. Those entries indicate more than one outcome or subgroup question, but the registry record does not report a multiplicity procedure or explain how confirmatory and exploratory analyses were distinguished.

In general, testing or estimating many outcomes and subgroups creates more opportunities for apparently notable patterns to arise by chance. Multiplicity methods can address some of this concern, but the appropriate approach depends on the questions and analysis plan. No correction method, hierarchy of endpoints, or prespecified subgroup strategy is reported in the registry record. The listed subgroup outcome should therefore be interpreted descriptively unless further analysis details are available.

The primary analysis population is described as patients who completed the study. The record does not state how many patients completed, how many had an assessable response, or what happened to missing or unevaluable response data. It does not report imputation, sensitivity analyses, or a missing-data assumption. These omissions matter because a completer-only analysis can differ from an analysis that includes all enrolled participants, especially if completion is associated with outcome.

The record also does not report a detailed statistical plan, sample-size justification, or interim-analysis plan. None should be inferred from the endpoint description or the planning assumptions. With no reported primary response estimates and limited analysis detail, neither multiplicity control nor the effects of missing data can be evaluated.

12. Safety Results

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

Deaths

Other (non-serious) adverse events

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

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: anemia (9.1%), non-cardiac chest pain (9.1%), pulmonary edema (9.1%), thromboembolic event (9.1%).

The registry reports serious adverse-event counts for Cohort B and Cohort C. In Cohort B, 5 were at risk for serious events and 0 were affected; 5 were at risk for other events and 3 were affected. In Cohort C, 11 were at risk for serious events and 2 were affected; 11 were at risk for other events and 10 were affected. Deaths were recorded as 0 in each cohort.

These are descriptive counts, not randomized comparisons. Cohorts differ in their clinical descriptions and treatment options, so the counts do not establish that one regimen is safer than another. The registry lists Anemia, Non-cardiac chest pain, Pulmonary edema, and Thromboembolic event among the serious adverse-event terms, each at 9.1%. The record does not give further context for interpreting these term percentages in the information.

Event counts do not establish that treatment caused an event, and the absence of a recorded death in a cohort does not establish absence of other risks. The registry record does not provide enough detail about event timing, severity grading, or attribution to treatment to support stronger conclusions.

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

The study record describes an investigation of immunomodulatory drug sensitivity and resistance in multiple myeloma. Its primary endpoint is response at first assessment, defined as partial response or better under International Myeloma Working Group criteria, with a 21-day timeframe. The stated analysis was intended to evaluate cohorts separately and estimate response within biomarker groups.

What the record does not provide is the observed primary response count or estimate. Without those results, readers cannot determine the response pattern, quantify its uncertainty, or assess whether it differs across biomarker groups. The study's stated enrollment does not fill that gap: the primary analysis included patients who completed the study, and the number of completers is not reported in the registry record.

The non-randomized structure also limits what comparisons could mean. Cohorts cover different disease settings and treatment histories, and some descriptions include alternative regimens. They are not a like-for-like randomized control comparison. Any differences across cohorts would be descriptive and could reflect underlying population differences as well as treatment.

The serious adverse-event figures offer limited descriptive information for Cohorts B and C, but they do not establish causation or a comparative safety effect. The registry record does not report enough detail to resolve the role of treatment or differences in the groups.

Accordingly, the record establishes the study's purpose, design, endpoint definition, and selected safety counts. It does not establish a treatment benefit, lack of benefit, or a definitive biomarker relationship. Those conclusions would require reported outcome estimates, uncertainty, and sufficient analysis detail.

14. Why This Trial Matters Statistically

This study is statistically interesting because it combines a clinical response endpoint with a biomarker-focused question. The registry proposes examining baseline and post-treatment biospecimens and estimating response within biomarker groups. That connects a patient-level outcome with a biological classification, but it also makes clear why the analysis plan and transparent reporting matter: the biomarker definitions, group sizes, response counts, and uncertainty are needed to judge whether observed patterns are informative.

The separate-cohort structure is another important feature. The cohorts represent distinct clinical settings and treatment histories rather than randomized groups intended for a direct comparison. This design can support cohort-specific description, but it does not remove confounding when readers compare outcomes across groups. The registry explicitly cautions that the arms are not a like-for-like control comparison.

The record also illustrates the difference between an endpoint being defined and an endpoint result being reported. The primary response definition and timeframe are stated, yet the response findings are not reported in the registry record. Without the observed estimates and their precision, readers cannot evaluate the central efficacy question or the planned biomarker relationships.

Finally, the analysis population is limited to study completers, while the number of completers and handling of missing outcomes are not stated. These details affect what an estimate represents. Clear reporting of participant flow, outcome availability, analysis choices, and uncertainty would be necessary to make the response and biomarker findings interpretable.

15. Limitations

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

The main limitation for interpreting this record is that the primary response results are not reported. The endpoint is defined, but response counts, estimates, and precision are absent. The record therefore does not support an assessment of the observed response pattern.

The study is non-randomized and unmasked, with parallel cohorts for different disease settings and treatment histories. The record warns that the arms are not a like-for-like control comparison. The cohort descriptions also include alternative drug regimens in some settings, without establishing randomized assignment. These features prevent a straightforward causal comparison across cohorts.

The analysis population is restricted to patients who completed the study. The number of completers, the number assessed for response, and the handling of participants with missing or unevaluable outcomes are not reported in the registry record. The record also does not give detailed biomarker definitions, biomarker group sizes, or the specific statistical methods used to estimate response.

Multiplicity handling, the detailed statistical plan, sample-size justification, and interim-analysis procedures are not reported in the registry record. The study is recorded as terminated, but the reason is not reported. The safety figures are limited to listed counts and terms and do not establish attribution or comparative risk. These gaps make it difficult to assess precision, selection, or the robustness of the intended findings.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Immunomodulatory Drugs (Lenalidomide With or Without Pomalidomide) in Combination With a Corticosteroid Drug (Dexamethasone) for the Treatment of Multiple Myeloma — NCT05288062.
• Registry record last updated 2026-09-28; status last verified 2026-09.
• Results first posted 2025-08-20.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

19. Record Summary

NCT05288062 is a Mayo Clinic phase II study titled “Evaluating Mechanisms of Immunomodulator Sensitivity and Resistance in Multiple Myeloma.” The registry describes a non-randomized, unmasked, parallel design, an enrollment of 17, and a terminated status. The study began on 2022-06-15, with primary completion on 2024-02-25.

The cohorts concern smoldering, newly diagnosed, relapsed, or refractory multiple myeloma and describe lenalidomide and/or pomalidomide with dexamethasone. The primary endpoint is response at first assessment, defined as partial response or better under International Myeloma Working Group criteria, within 21 days. The primary analysis population is described as study completers.

Primary response results and the number of completers are not reported in the registry record. The record includes selected adverse-event counts for Cohorts B and C, but the non-randomized design does not support a like-for-like comparison between them.