Study of Vorinostat (MK-0683) or Placebo, in Combination With Bortezomib in Participants With Multiple Myeloma (MK-0683-088 AMN): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study of Vorinostat (MK-0683) or Placebo, in Combination With Bortezomib in Participants With Multiple Myeloma (MK-0683-088 AMN) (NCT00773747), a randomized phase 3 study. The primary outcome is Progression-Free Survival (PFS).

2. Clinical Question

3. Trial Design

This was a phase 3, randomized, double-blind, parallel-group study described in the registry as international and multicenter. Participants were assigned to vorinostat plus bortezomib or placebo plus bortezomib. The registry reports 637 enrolled participants. The primary analysis population is described as all randomized participants, and the displayed primary outcome group sizes are 317 for vorinostat plus bortezomib and 320 for placebo plus bortezomib.

The study status is completed. The registry records a start date of 2008-12-01 and a primary completion date of 2011-09-08. The primary outcome timeframe is described as assessment up to 32 months at final study analysis. The record does not report the original sample-size justification, the target enrollment rationale, or whether enrollment was changed during the study.

Both groups received bortezomib on the same recorded schedule. The study group received vorinostat, while the comparator group received placebo capsules. The double-blind designation indicates that masking was part of the design, but the registry record does not detail which individuals were masked, how masking was maintained, or whether it was assessed. The method used to generate the random sequence and the method for concealing allocation are also not reported in the registry record.

The primary endpoint was progression-free survival. Objective response rate was a posted secondary outcome, alongside overall survival, time to progression, and the number of participants with grade 3-5 clinical or laboratory adverse events. The registry includes numerical results for objective response rate and selected adverse-event summaries; numerical results for the other named secondary outcomes are not reported in the registry record. The record identifies a stratified Cox model for the primary analysis but does not describe the stratification factors.

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: 637 participants were randomized to treatment and 635 participants received at least 1 dose of MK-0683 or placebo: 315 participants were treated with vorinostat + bortezomib and 320 participants were treated with placebo + bortezomib.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The analysis population includes all randomized participants.

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 Progression-Free Survival (PFS), measured over From randomization to event of disease progression or death assessed up to 32 months (final study analysis).

Progression-free survival measures the time from the start of treatment, as stated in the endpoint description, until disease progression or death from any cause, whichever occurs first. The timeframe field describes the assessment as running from randomization to progression or death, up to 32 months at final study analysis. The record therefore uses both start-of-treatment and randomization wording in describing the time origin; further clarification is not reported in the registry record.

This endpoint combines disease progression and death into a time-to-event outcome. It can reflect both whether an event occurs and how long participants remain free of the recorded event. Unlike a simple proportion measured at a single visit, a time-to-event analysis can use information about the timing of events. The registry does not report the censoring rules, the follow-up distribution, or how participants without a recorded event at analysis were handled.

Response to therapy was assessed using European Blood and Marrow Transplantation Group criteria, according to the registry. Progression-free survival is used in trials to describe the duration before progression or death, outcomes that capture more than tumor response alone. It is not identical to overall survival: progression-free survival counts progression as an event, whereas overall survival concerns death. The registry names overall survival as a secondary outcome, but numerical results for it are not reported in the registry record.

7. Results Posted in the Registry

• Vorinostat + Bortezomib vs Placebo + Bortezomib: hazard ratio 0.77 (95% CI 0.64–0.94), reported p = = 0.0100 (as reported in the registry).

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.

Objective Response Rate

• 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:
  • Vorinostat + Bortezomib: 56.2% (177/315) versus 40.6% (130/320) on control; risk difference 15.6 percentage points (95% CI 7.9 to 23.2), risk ratio 1.38 (1.17–1.63); unadjusted two-proportion z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Vorinostat + Bortezomib than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The registry names objective response rate, overall survival, time to progression, and grade 3-5 clinical or laboratory adverse events as secondary outcomes. Numerical results are posted for objective response rate and selected adverse-event summaries. Numerical results for overall survival and time to progression are not reported in the registry record. This means the secondary evidence available for interpretation is incomplete relative to the full list of named outcomes.

The objective response rate result is directionally consistent with the primary progression-free survival comparison in the sense that the posted response percentage is higher in the vorinostat plus bortezomib group than in the placebo plus bortezomib group. These are different endpoints: response classification does not measure time to progression or death, and one result cannot stand in for the other. The response analysis is unadjusted, and the registry does not report a sponsor inferential analysis for it.

Secondary outcomes are generally interpreted with less weight than a prespecified primary outcome, especially when several outcomes may be tested. Multiple testing can increase the chance of at least one apparently notable result when each test is considered separately. The registry record does not report a multiplicity adjustment or a hierarchy governing interpretation of the secondary outcomes. Accordingly, the secondary p-value should not be treated as if it were an independently confirmed primary finding. The absence of numerical results for some named secondary outcomes also prevents a complete assessment of consistency across all outcomes.

Safety outcomes address a different question from efficacy endpoints. The number of participants with serious adverse events and selected serious-event terms provides descriptive context about reported harms, but these summaries do not establish whether an event was caused by treatment. The registry's adverse-event information should be read alongside the fact that efficacy and safety outcomes have different definitions, denominators, and interpretive purposes.

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

• Number of Participants With Grade 3-5 Clinical or Laboratory Adverse Events (AEs)
• Overall Survival
• Time to Progression
• Objective Response Rate

9. Statistical Interpretation

10. Statistical Methods Explained

What does the median summarize?

The primary outcome is a time-to-event measure. For each group, the reported median is the point in the event-time distribution at which half of the group has experienced progression or death, according to the endpoint definition and analysis. A median is not an arithmetic average and does not describe every participant's experience. The registry reports median progression-free survival of 7.63 months for vorinostat plus bortezomib and 6.83 months for placebo plus bortezomib, with a 95% confidence interval for each.

Time-to-event analyses are useful when the outcome is a delay until an event and participants may have different lengths of follow-up. General statistical explanation: such methods can include participants whose event has not been observed by the analysis, provided their available follow-up is handled as censored information. The registry record does not report the specific censoring rules or how incomplete follow-up was treated, so those details cannot be assessed from the record.

What does a Cox hazard ratio represent?

The registry reports a stratified Cox proportional hazards model with Efron's likelihood approximation to account for ties in event times. The sponsor-reported hazard ratio for vorinostat plus bortezomib versus placebo plus bortezomib was 0.774. In general, a hazard ratio compares the event hazard between groups over follow-up, conditional on the model. It is not a ratio of median times, a probability of an event, or a direct measure of how many months an individual gains.

The proportional-hazards model expresses the group contrast through a hazard ratio assumed to be constant over time, subject to the model's structure. General statistical explanation: if the relative event rates change substantially over time, a single hazard ratio may not fully describe the pattern. The registry identifies the model but does not report a check of the proportional-hazards assumption, plots of time-varying effects, or alternative model results. The record also does not name the stratification factors, so it is not possible to explain what baseline features were used to form the strata.

Efron's likelihood approximation is a method for handling tied event times in Cox regression. Ties occur when multiple participants have events recorded at the same time. General statistical explanation: different approximations can be used to calculate the partial likelihood when tied times occur; Efron's method is the one stated in the registry. The record does not report the number or distribution of tied events.

How should the confidence intervals and p-value be read?

The Cox-model estimate was 0.774, with a 95% confidence interval from 0.636 to 0.941. A confidence interval conveys uncertainty in the estimate under the statistical model and data. In repeated use of a method with its assumptions met, intervals constructed at this level would cover the target parameter at the stated rate. For an individual trial, it is best read as a range of estimates reasonably compatible with the data and model, not as a guarantee that the true value lies within the interval.

The reported p-value was 0.010. In general, a p-value measures how unusual data at least as inconsistent with a specified null model would be if that null model and the analysis assumptions held. It does not tell whether the result is clinically important, whether bias is absent, or the probability that the null is true. The primary comparison is identified as a superiority analysis, and the sponsor's reported result is the result used for the primary interpretation.

How is objective response rate analyzed?

Objective response rate is a binary outcome: participants are classified according to whether they met response criteria. The posted percentages were 56.2% in the vorinostat group and 40.6% in the placebo group. The unadjusted risk difference was 0.156, with a 95% confidence interval from 0.079 to 0.233. Its reported unadjusted p-value was p < 0.001. The term unadjusted means that the calculation is based on the posted group summaries rather than a reported model adjusting for other participant characteristics.

General statistical explanation: a risk difference expresses the difference in outcome proportions between groups. It is distinct from a risk ratio or an odds ratio, which compare the proportions using different scales. The registry record lists additional comparative measures in the posted calculations, but the risk difference is the direct additive contrast described for the secondary result. The record does not identify a sponsor-reported inferential analysis for objective response rate.

What can be said about analysis populations and missing results?

The primary endpoint description says that all randomized participants were included in the analysis population. The group sizes for that endpoint are 317 and 320. For objective response rate, the reported group denominators are 315 and 320. These differing denominators are part of the posted outcome summaries; the reasons for the difference are not reported in the registry record.

The registry does not report how missing outcome assessments were handled, whether any participants were excluded after randomization, or how departures from assigned treatment were addressed. It also does not report interim analyses or the original statistical analysis plan. These omissions limit evaluation of whether the analysis choices were prespecified and how incomplete outcome information could affect the estimates. They do not, on their own, demonstrate that a particular analysis choice was inappropriate.

11. Confidence Intervals and Precision

The 95% confidence interval for median progression-free survival was 6.87 to 8.4 months with vorinostat plus bortezomib, and 5.67 to 7.73 months with placebo plus bortezomib. These intervals describe uncertainty around each group median. The intervals overlap, but comparing overlap by eye is not a substitute for the model-based between-group analysis. The reported Cox hazard ratio and its confidence interval provide the registry's primary comparative estimate.

The 95% confidence interval for the hazard ratio runs from 0.636 to 0.941 around the estimate of 0.774. Its limits indicate that the estimate is not infinitely precise: the data are compatible with a range of relative hazards under the fitted model. The interval does not include 1, the value corresponding to equal hazards in the model. This does not resolve possible model violations, bias, or the importance of the difference in a clinical context.

For objective response rate, the group confidence intervals were 50.5% to 61.7% and 35.2% to 46.2%. The unadjusted risk-difference interval was 0.079 to 0.233. The latter expresses uncertainty directly in the difference between proportions, whereas the group intervals describe each proportion separately. They are not interchangeable measures of precision.

General statistical explanation: confidence intervals tend to be narrower when data contain more information and wider when estimates are less precise. Precision is not the same as freedom from bias. The registry does not provide detailed follow-up, missing-data handling, or diagnostics that would allow a fuller assessment of uncertainty beyond the reported intervals. The reported confidence limits are rounded as recorded and should be interpreted at that precision.

12. Planning a Similar Trial: Sample Size

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

The planning figures are illustrations based on the observed effect, not the trial's original design calculation. For the time-to-event outcome, the figures refer to total events, not participants per arm. For objective response rate, the figures refer to participants per arm. The distinct units matter: an event target in a time-to-event setting is not an enrollment target, and the per-arm participant figures are not totals across both groups.

The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The calculations consider an effect equal to 100%, 75%, or 50% of the observed effect. For the time-to-event outcome, the calculation method is identified as Schoenfeld. The original trial design assumptions, including its own planned effect and sample-size justification, are not reported in the registry record.

The 80% power column represents the event or participant count that the planning illustration associates with an 80% chance of detecting the specified effect under the stated assumptions. The 90% power column makes the same kind of calculation at a higher planned chance of detection. These are design targets under assumed conditions, not guarantees for a future study.

The values increase as the assumed effect becomes smaller: detecting a smaller contrast generally requires more information, which may mean more events or more participants. The listed total-event targets are 479 and 641 for 80% and 90% power at 100% of the observed effect; at 75%, they are 851 and 1,139; at 50%, they are 1,914 and 2,562. For objective response rate, the corresponding participants per arm are 161 and 215 at 100%, 286 and 382 at 75%, and 639 and 855 at 50%. These are planning illustrations, not observed power.

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

d is the total number of events needed (Schoenfeld's formula) with 1:1 allocation and proportional hazards.

Worked calculation for this trial

1. Hazard ratio HR = 0.774, so ln(HR) = -0.2562.
2. d = 4 × (1.96 + 0.842)² / [ln(0.774)]² = 478.4, rounded up to 479 events in total 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
hr <- 0.774                              # observed hazard ratio
events_needed <- function(power, frac = 1) ceiling(round(4 * (z_a + qnorm(power))^2 / log(hr^frac)^2, 6))   # Schoenfeld, 1:1 allocation
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: events = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(events_needed(0.80, f), big.mark = ","), format(events_needed(0.90, f), big.mark = ",")))

# Simulation: given d total events under proportional hazards, events in the treatment arm are Binomial(d, hr / (1 + hr)).
# The score (log-rank type) statistic is (D1 - d / 2) / sqrt(d / 4).
set.seed(773747)
d    <- events_needed(0.80)
reps <- 20000
D1 <- rbinom(reps, d, hr / (1 + hr))
z  <- (D1 - d / 2) / sqrt(d / 4)
cat(sprintf("Simulated power with %s events: %.3f (%d replicates)\n", format(d, big.mark = ","), mean(abs(z) > z_a), reps))

Output from running the code

100% of observed effect: events = 479 (80% power), 641 (90% power)
 75% of observed effect: events = 851 (80% power), 1,139 (90% power)
 50% of observed effect: events = 1,914 (80% power), 2,562 (90% power)
Simulated power with 479 events: 0.808 (20000 replicates)

The simulation uses the fact that, with d events in total and proportional hazards, the number of events in the treatment arm is binomial. It is an approximation that conditions on the total number of events, and it should land close to the target power.

14. Group-Sequential Design Analysis

Many time-to-event trials, especially in oncology, stop or report early when interim data are overwhelming, so a single fixed-sample number understates the real design problem. The calculation below is an illustrative group-sequential design built from this trial's posted control median and hazard ratio. The registry record does not state the planned number of looks or the spending function, so the design is a planning illustration, not a reconstruction of the protocol. Assumed: one-sided α = 0.025, 90% power, three equally spaced looks on information, Lan-DeMets O'Brien-Fleming spending, 24 months of accrual, 60 months in total and a 1% monthly dropout hazard.

Under these assumptions the design needs about 729 participants in total, with the boundaries below.

Fixed design versus group-sequential alternatives

Group-sequential designs cost a small increase in maximum sample size and events compared with the fixed design, in exchange for the chance to stop early for overwhelming efficacy. O'Brien-Fleming spending keeps early boundaries very conservative and the final boundary close to the fixed-design value, whereas Pocock spending spends more alpha early.

Sensitivity to a smaller true effect

Planning for exactly the observed effect is optimistic, because observed effects in published trials tend to be somewhat larger than the true effect. The table repeats the main design (three looks, O'Brien-Fleming spending, 90% power) for smaller true hazard ratios.

For context, this trial enrolled 637 participants.

Cross-check, upper boundaries: gsDesign 3.71, 2.511, 1.993 | rpact 3.71, 2.511, 1.993. Agreement between the two packages confirms the boundary calculation.

R code and output

suppressWarnings(suppressMessages({ library(gsDesign); library(rpact) }))
med_control <- 6.83          # control-arm median, months (converted from the posted unit)
hr          <- 0.774          # hazard ratio used for planning
lambdaC     <- log(2) / med_control
eta         <- 0.01               # dropout hazard per month (assumption)
acc_months  <- 24                 # accrual duration (assumption)
study_months<- 60                 # total study duration (assumption)

design <- function(k, sfu, beta, h = hr) gsSurv(k = k, test.type = 1, alpha = 0.025, beta = beta, sfu = sfu,
  lambdaC = lambdaC, hr = h, hr0 = 1, eta = eta, gamma = 1, R = acc_months, T = study_months, minfup = study_months - acc_months)

# Main design: 3 looks, Lan-DeMets O'Brien-Fleming spending, one-sided alpha 0.025, 90% power
x <- design(3, sfLDOF, 0.10)
cat(sprintf("N_TOTAL|%s\n", format(ceiling(sum(x$gamma * x$R)), big.mark = ",")))
for (i in 1:3) cat(sprintf("GS|%d|%.1f|%.0f|%.3f|%.5f|%.5f\n", i, x$T[i], x$n.I[i], x$upper$bound[i], pnorm(-x$upper$bound[i]), cumsum(x$upper$spend)[i]))
cat("\n"); print(gsBoundSummary(x))

# Comparison of designs
cmp <- list(list("Fixed design, one analysis", 1, sfLDOF), list("Two looks, O'Brien-Fleming", 2, sfLDOF),
            list("Three looks, O'Brien-Fleming", 3, sfLDOF), list("Three looks, Pocock", 3, sfLDPocock))
cat("\n")
for (b in c(0.20, 0.10)) for (d in cmp) {
  y <- design(d[[2]], d[[3]], b)
  cat(sprintf("DES|%s|%d|%.0f|%s|%.1f\n", d[[1]], round(100 * (1 - b)), tail(y$n.I, 1), format(ceiling(sum(y$gamma * y$R)), big.mark = ","), tail(y$T, 1)))
}

# Sensitivity: what if the true effect is smaller than the observed one? (3 looks, O'Brien-Fleming, 90% power)
cat("\n")
for (fr in c(1, 0.75, 0.5)) {
  y <- design(3, sfLDOF, 0.10, exp(log(hr) * fr))
  cat(sprintf("SENS|%.2f|%.3f|%.0f|%s\n", fr, exp(log(hr) * fr), tail(y$n.I, 1), format(ceiling(sum(y$gamma * y$R)), big.mark = ",")))
}

# Independent cross-check of the boundaries with rpact
r <- getDesignGroupSequential(kMax = 3, alpha = 0.025, beta = 0.10, sided = 1, typeOfDesign = "asOF", informationRates = x$timing)
cat(sprintf("\nCross-check, upper boundaries: gsDesign %s | rpact %s\n", paste(round(x$upper$bound, 3), collapse = ", "), paste(round(r$criticalValues, 3), collapse = ", ")))

Method: LachinFoulkes 
    Analysis               Value Efficacy
   IA 1: 33%                   Z   3.7103
      N: 484         p (1-sided)   0.0001
 Events: 216        ~HR at bound   0.6033
   Month: 16    P(Cross) if HR=1   0.0001
             P(Cross) if HR=0.77   0.0338
   IA 2: 67%                   Z   2.5114
      N: 730         p (1-sided)   0.0060
 Events: 432        ~HR at bound   0.7852
   Month: 25    P(Cross) if HR=1   0.0060
             P(Cross) if HR=0.77   0.5603
       Final                   Z   1.9930
      N: 730         p (1-sided)   0.0231
 Events: 647        ~HR at bound   0.8550
   Month: 60    P(Cross) if HR=1   0.0250
             P(Cross) if HR=0.77   0.9000



Cross-check, upper boundaries: gsDesign 3.71, 2.511, 1.993 | rpact 3.71, 2.511, 1.993

15. Analyses Reported by the Sponsor

The primary comparison is the sponsor-reported Cox analysis: hazard ratio 0.774, 95% confidence interval 0.636 to 0.941, and p = 0.010. The registry identifies the method as Cox regression and the analysis type as superiority. This reported estimate is the appropriate primary result to describe; no recalculated primary hazard ratio is substituted for it.

The median progression-free survival values and their confidence intervals are also posted by group. They provide descriptive summaries that complement the sponsor's model-based comparison, rather than replacing it. The median summaries do not reproduce the Cox analysis because they use different features of the event-time data.

The objective response rate comparison is an unadjusted calculation from the posted group summaries. It reports a risk difference of 0.156, with a 95% confidence interval from 0.079 to 0.233 and p < 0.001. This secondary calculation is not identified as a sponsor-reported inferential analysis. It should therefore be distinguished from the sponsor-reported primary Cox result and interpreted in light of its secondary status.

16. Multiplicity, Missing Data and Analysis Populations

The primary endpoint is progression-free survival, and the registry reports a sponsor Cox analysis for that comparison. Objective response rate is a secondary outcome with a posted unadjusted p-value. The record does not report a multiplicity adjustment, a testing hierarchy, or a prespecified procedure controlling the family-wise error rate across outcomes. As a result, the secondary p-value should be interpreted as an unadjusted result rather than as evidence adjusted for the number of outcomes examined.

The registry names overall survival, time to progression, and grade 3-5 clinical or laboratory adverse events as additional secondary outcomes. Numerical results for overall survival and time to progression are not reported in the registry record. The absence of those estimates means it is not possible to evaluate whether they align with the primary result or how uncertainty differs across them. The record lists five outcome measures, but it does not provide a complete numerical account of every named secondary outcome in the information available.

The primary analysis population is described as all randomized participants. However, the registry does not report detailed rules for missing progression assessments, loss to follow-up, censoring, or missing response classifications. The objective response denominators are 315 and 320, while the primary endpoint group sizes are 317 and 320; reasons for this difference are not reported in the registry record. No assumptions about missing outcomes should be inferred from these denominators alone.

The registry record does not report interim analyses, stopping rules, the original sample-size justification, or the full statistical analysis plan. It also does not provide details of random-sequence generation, allocation concealment, or the identities of masked parties. These omissions limit the ability to verify prespecification and to assess some potential sources of analysis or conduct bias. They are absences of documentation in the registry record, not proof that a method was or was not used.

17. 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: accidental overdose (10.2%), pneumonia (4.4%), neoplasm malignant (4.1%), diarrhoea (3.1%), thrombocytopenia (2.9%).

For serious adverse events, 130 of 315 participants in the vorinostat plus bortezomib group and 138 of 320 in the placebo plus bortezomib group were recorded as affected. The registry lists accidental overdose at 10.2%, pneumonia at 4.4%, neoplasm malignant at 4.1%, diarrhoea at 3.1%, thrombocytopenia at 2.9%, and pyrexia at 2.8% among the leading serious-event terms. These terms and percentages describe reported events in the registry; they do not establish that treatment caused them.

The broader adverse-event summaries report 312 of 315 participants in the vorinostat group and 306 of 320 in the placebo group as affected. Serious events and other adverse events are distinct summaries and should not be conflated. The deaths fields are not populated with a result, so death counts in these safety summaries are not reported in the registry record. The record does not provide detailed event-level timing, exposure-adjusted rates, or a complete account of how seriousness and relatedness were assessed.

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

The posted primary result describes a randomized comparison of vorinostat plus bortezomib with placebo plus bortezomib in participants with multiple myeloma. Median progression-free survival was 7.63 months in the vorinostat group and 6.83 months in the placebo group. The sponsor-reported Cox hazard ratio was 0.774, with a 95% confidence interval from 0.636 to 0.941 and p = 0.010. These statistics indicate that the fitted analysis estimated a lower progression-or-death hazard in the vorinostat group during the recorded follow-up, relative to the placebo group.

The result does not mean that every participant had the same event-time experience, or that the hazard ratio can be translated directly into an individual participant's added time without further assumptions. It is a model-based group comparison, and its interpretation depends on the endpoint definition, analysis population, follow-up, and model assumptions. The registry does not report enough detail to independently assess all of those features.

The secondary objective response result provides additional, but not equivalent, information. It is an unadjusted comparison of response proportions, and the registry does not report adjustment for testing multiple outcomes. Numerical results for overall survival and time to progression are not reported in the registry record. Therefore, the primary endpoint result should not be used to claim a particular overall-survival result or to stand in for unreported outcomes.

These findings are limited to the randomized groups and treatment schedules recorded. The registry's summary identifies the study population as participants with relapsed or refractory multiple myeloma, but detailed eligibility and participant characteristics are not reported in the record. The statistics describe the posted trial analysis; they do not determine what treatment is appropriate for an individual or establish effects in populations and circumstances not described by the record.

19. Why This Trial Matters Statistically

This trial illustrates why time-to-event outcomes are often reported with both a median and a model-based comparison. The group medians offer an interpretable description of event timing, while the Cox hazard ratio uses event-time information across follow-up. Reading both helps distinguish a midpoint summary from a relative hazard estimate, and the confidence intervals communicate uncertainty around those estimates.

The analysis also demonstrates that a clearly stated primary outcome and a reported model are important for interpretation. The registry identifies progression-free survival as the primary endpoint and describes a stratified Cox model with Efron's approximation for tied event times. At the same time, unreported stratification factors, censoring details, model diagnostics, and missing-data procedures limit how fully the analysis can be evaluated from the registry record.

The distinction between primary and secondary outcomes matters. Objective response rate has a posted unadjusted comparison, while overall survival and time to progression are named but do not have numerical results reported in the registry record. Without a reported multiplicity procedure, secondary p-values warrant more caution than the primary analysis. The record also shows why effect estimates and uncertainty should be considered together rather than relying on a p-value alone.

Finally, planning illustrations are not a retrospective measure of trial success. Event targets and per-arm participant targets depend on stated assumptions about effect size, significance level, allocation, and the calculation method. They can help readers understand how the information requirement changes when a smaller effect is targeted, but they do not reveal the trial's own design rationale, which is not reported in the registry record.

20. 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 details unavailable. It does not report detailed participant characteristics, prior treatment histories, or full eligibility criteria. Those omissions limit assessment of how closely the recorded participants reflect other groups with multiple myeloma. The record describes the study as involving relapsed or refractory disease, but does not provide further detail on those categories.

Some methods relevant to the primary time-to-event analysis are not reported. These include the specific stratification factors, censoring rules, follow-up distribution, and diagnostics of the proportional-hazards assumption. The endpoint description refers to time from treatment start, while the timeframe field refers to time from randomization; the record does not explain this wording difference. The handling of missing response assessments and the reasons for the differing primary and response denominators are also not reported.

The numerical results available for secondary outcomes are incomplete. Objective response rate is reported, but overall survival and time to progression are named without numerical results in the registry record. The record does not describe a multiplicity adjustment for secondary testing. This restricts interpretation of the secondary evidence and limits assessment across the full set of named outcomes.

Safety summaries provide counts and selected serious-event terms, but the record does not report death counts in the adverse-event summary, exposure-adjusted rates, or detailed event-level causality assessments. The original sample-size justification, interim analyses, and full statistical analysis plan are not reported in the registry record. These limitations concern the detail available for evaluating the trial and its estimates; they do not by themselves demonstrate that an unreported procedure was absent or that a reported result is invalid.

21. Related Tutorials

22. Related Statistical Calculators

23. Sources

• ClinicalTrials.gov: Study of Vorinostat (MK-0683) or Placebo, in Combination With Bortezomib in Participants With Multiple Myeloma (MK-0683-088 AMN) — NCT00773747.
• Registry record last updated 2021-04-30; status last verified 2021-04.
• Results first posted 2021-04-30.
• 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.

24. Record Summary

This completed phase 3, randomized, double-blind, parallel-group study compared vorinostat plus bortezomib with placebo plus bortezomib in participants with multiple myeloma. The registry reports 637 enrolled participants and primary endpoint analyses in groups of 317 and 320. The primary outcome was progression-free survival, analyzed with a stratified Cox model using Efron's approximation for tied event times.

The sponsor-reported hazard ratio was 0.774, with a 95% confidence interval from 0.636 to 0.941 and p = 0.010. Median progression-free survival was 7.63 months and 6.83 months, respectively. Objective response rate was reported as a secondary outcome, while numerical results for overall survival and time to progression are not reported in the registry record. The registry also reports serious adverse-event counts and selected serious-event terms, with further analysis limitations and missing methodological details as described in the record.