Immediate-Release Oxycodone Capsules Study in Cancer Pain: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Immediate-Release Oxycodone Capsules Study in Cancer Pain (NCT01675622), a randomized phase 3 study. The primary outcome is Numerical Rating Scale (NRS).

2. Clinical Question

3. Trial Design

The registry record describes a phase 3, randomized, quadruple-masked, parallel-group study comparing immediate-release oxycodone capsules with immediate-release morphine tablets for cancer pain. The sponsor was Mundipharma (China) Pharmaceutical Co. Ltd. Enrollment was 242. The recorded study status is completed, with a start date of 2011-01 and a primary completion date of 2012-06.

A parallel design assigns participants to distinct treatment groups and compares outcomes across those groups. Randomization is intended to reduce systematic differences between groups at assignment, though the registry record does not specify the randomization method, allocation ratio, or whether any stratification was used. Quadruple masking indicates that the registry labels the study as masked at multiple roles; which roles were masked and how masking was maintained are not reported in the registry record.

The primary outcome was Numerical Rating Scale score, described as the average change from baseline after double-blind treatment, compared between groups. The stated timeframe is baseline up to 5-8 days. The record also lists secondary outcomes concerning medication dose, pain measures, breakthrough pain, satisfaction, titrations, and pain relief. The full protocol and a complete statistical analysis plan are not reported in the registry record.

The registry record lists 10 outcome measures and reports no posted analyses. It gives outcome summaries for the primary NRS measure and selected secondary measures, but does not report the analysis populations, participant flow through each period, or treatment adherence. The open-label period is described in connection with some secondary outcomes, with a timeframe of baseline up to 19-22 days for the posted open-label measure. Details of how participants entered or continued into that period are not reported in the registry record.

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: Patients with moderate to severe cancer pain requiring oral opioid therapy were screened. All the patients who meets the inclusion/exclusion criteria were enrolled to double blind treatment phase. No wash our or run-in period required by protocol.

Overall Study

Reasons for not completing this period:

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Numerical Rating Scale (NRS), measured over baseline up to 5-8 days (double blind period).

The primary endpoint is the Numerical Rating Scale (NRS), a numerical measure of pain intensity. The registry describes a scale from 0 to 10: 0 means not painful and 10 means extremely painful. Scores from 1 to 3 are described as light pain, 4-6 as moderate pain, and 7 to 10 as severe pain. No NRS subscales are reported.

The primary outcome is described as the average change in NRS score from baseline after double-blind treatment, compared between the treatment groups. A change measure focuses on how the recorded score differs from the participant's baseline rather than only on a score at one time point. Comparing average changes between randomized groups can summarize the relative pattern over the stated treatment period. This is a general description of change-score outcomes; the registry does not provide participant-level scores or details of the analysis model.

Pain intensity is a patient-reported outcome: it captures a person's rating rather than an objective measurement of a physical sign. Using the same defined scale in both groups gives a common metric for the comparison. The registry lists mean scores and standard deviations for each group, and a mean difference with a confidence interval for the comparison. It does not report additional details about questionnaire administration, missing-score handling, or a prespecified threshold for a clinically important difference.

7. Results Posted in the Registry

• Morphine Tablets for Cancer Pain: mean 3.87 versus 3.91 on control; difference -0.04 (95% CI -0.62 to 0.54), standardized effect d = -0.02; z-test p = 0.892.

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.

Average Number of Titrations

• 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:
  • Morphine Tablets for Cancer Pain: mean 7.89 versus 8.25 on control; difference -0.36 (95% CI -1.38 to 0.66), standardized effect d = -0.09; z-test p = 0.488.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Morphine Tablets for Cancer Pain and the control. The interval gives the range of effects that remain compatible with the data.

Degree of Pain Relief Within 24hrs After Treatment

• 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:
  • Morphine Tablets for Cancer Pain: mean 34.19 versus 35.23 on control; difference -1.04 (95% CI -8.56 to 6.48), standardized effect d = -0.04; z-test p = 0.786.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Morphine Tablets for Cancer Pain and the control. The interval gives the range of effects that remain compatible with the data.

Brief Pain Inventory (BPI) Change From Baseline to Open Label Treatment

• 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:
  • Morphine Tablets for Cancer Pain: mean 31.64 versus 32.31 on control; difference -0.67 (95% CI -8.36 to 7.02), standardized effect d = -0.02; z-test p = 0.864.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Morphine Tablets for Cancer Pain and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists a range of secondary outcomes, including medication use, pain inventory measures, breakthrough pain, satisfaction, titrations, and pain relief. The posted numerical secondary results include average titrations, degree of pain relief within 24 hours, and a measure titled Brief Pain Inventory change from baseline to open-label treatment. Their estimated group differences are small in relation to the uncertainty intervals reported for those comparisons, and each interval includes zero. This broad pattern is directionally consistent with the primary comparison's limited separation in posted group averages, but it does not independently establish the primary result.

Secondary outcomes can add context because they assess different aspects of pain management and treatment experience. They are not interchangeable with the primary endpoint: they may use different scales, timeframes, or concepts, and some relate to the open-label period rather than the double-blind period. Their relevance depends on their definitions, measurement timing, completeness, and analysis populations, details that are not fully reported in the registry record.

Multiple outcomes create a multiplicity concern. When many outcomes are examined, the chance of at least one apparently notable finding can rise even if all null hypotheses are true. General statistical approaches include prespecifying a hierarchy, adjusting significance thresholds, or treating secondary results as exploratory. The registry record does not report which approach, if any, was used. The posted secondary comparisons are unadjusted recalculations and should therefore carry less inferential weight than a prespecified, adequately documented analysis. They are best read as descriptive context rather than separate confirmatory tests.

The record lists 9 posted secondary outcomes, but the available detailed numerical summaries do not cover every listed outcome. Results not included in the registry record are not reported in the registry record. In particular, a list of intended secondary measures should not be mistaken for a complete set of analyzable results. The secondary pattern can be described cautiously, but it cannot resolve uncertainties about the primary analysis, multiplicity, missing data, or clinical importance.

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

• The Average Dose of Study Medicine Used During Double Blind Treatment Period
• Brief Pain Inventory (BPI) Change From Baseline to After Double Blind Period
• Times of Breakthrough Pain Occurrence
• Patient Assessments of Satisfaction for Pain Management
• Average Number of Titrations
• Brief Pain Inventory (BPI) Change From Baseline to Open Label Treatment
• the Total Dose of Rescue Medicine for Breakthrough Pain.
• Degree of Pain Relief Within 24hrs After Treatment

9. Statistical Interpretation

10. Statistical Methods Explained

What does the mean difference represent?

For a continuous outcome, a group mean is the average of the recorded values. A mean difference compares the averages in two groups. The primary comparison is expressed as morphine minus oxycodone: a negative estimate means the posted mean for morphine is lower than the posted mean for oxycodone, while a positive estimate would mean it is higher. In this record, the estimate is -0.04. The calculation is an unadjusted comparison of group summaries, rather than a result from a reported sponsor analysis.

The mean is a useful summary when the research question concerns average outcome levels or changes. It does not show the full distribution. Participants can have scores far from their group average, and a mean alone cannot show whether the distribution is symmetric, contains outliers, or has clusters. The registry provides standard deviations alongside the means to convey variation, but it does not provide the underlying individual scores or distribution plots in the record.

What do standard deviation and standard error describe?

Standard deviation describes how dispersed observations are around their group mean. Standard error describes uncertainty in an estimated quantity, such as a mean, and depends on both the observed variability and the amount of information. They answer different questions: one is about variation among observations, the other about precision of an estimate. The posted values for the two NRS groups are standard deviations; the recalculation also reports standard errors for the group means. Those quantities should not be interchanged.

For a difference between two independent group means, a simple unadjusted calculation combines information about variability in both groups and the numbers in each group. Its confidence interval is centered on the estimated difference and extends in both directions to represent statistical uncertainty. The registry record does not report whether the trial's original analysis used this simple approach, a repeated-measures model, baseline adjustment, or another method. The recalculated comparison should therefore be read as a transparent summary-based calculation, not as a reconstruction of an undocumented analysis plan.

How should the p-value be understood?

A p-value measures how unusual an observed result, or a more extreme result, would be under a specified null hypothesis and statistical model. A small p-value can be evidence against that null model, but it is not the probability that the null hypothesis is true. It also does not express the probability that a treatment is effective, the importance of a difference, or the probability that the result will replicate. The primary p-value of 0.892 is unadjusted and recalculated from the posted summaries; the registry record lists no reported analyses. It should be interpreted together with the point estimate, confidence interval, endpoint definition, and study design, not on its own.

Why does the confidence interval matter?

A confidence interval gives a range of values compatible with the data and calculation method at a stated confidence level. In repeated use of the same procedure under its assumptions, intervals constructed this way have a specified long-run coverage property. It is not correct to interpret one interval as assigning a probability to the fixed true value after the data are observed. In practical reading, the interval helps show which directions and magnitudes of difference remain consistent with the posted information. A wide interval indicates less precision than a narrow one, but whether the range is clinically important requires context and a threshold that is not reported in the registry record.

Here, the primary interval extends from -0.616 to 0.536 around the mean difference of -0.04. It spans zero, so the summary-based comparison does not rule out zero difference at the interval's confidence level. It also allows values on either side of zero. That is different from proving that the groups are identical. Demonstrating equivalence or noninferiority generally requires a prespecified margin and a design and analysis suited to that question; such a margin and plan are not reported in the registry record.

What does randomization add?

In general, random assignment aims to make treatment groups comparable on average with respect to measured and unmeasured baseline characteristics. It supports causal interpretation when the randomization process is implemented appropriately and subsequent conduct and analysis preserve the comparison. The registry identifies the study as randomized, but the sequence-generation and allocation-concealment procedures are not reported. Nor does the registry provide baseline characteristics in the registry record described for this outcome. These missing details limit assessment of the implementation and balance, though they do not change the meaning of the posted summary statistics.

Masking can reduce the influence of treatment knowledge on participants' reports, care decisions, outcome assessment, and analysis. The study is labeled quadruple-masked, but the roles covered by that label and the masking procedures are not reported. Since NRS is a patient-reported measure, masking is relevant in general to how expectations may influence reported pain. The record does not permit an assessment of whether masking was maintained.

Why can over-dispersion matter?

General statistical explanation: a simple mean-based model often relies on assumptions about the distribution and variability of observations. If the observed variability is greater than the model allows, standard errors can be too small and confidence intervals too narrow, making evidence appear more precise than it is. This is one reason to examine the standard deviations, study design, and analysis assumptions together. The registry record does not report a formal assessment of distributional assumptions or over-dispersion, and the posted summary data alone cannot diagnose every model issue.

The NRS is bounded from 0 to 10, as described in the record, whereas a normal approximation treats a continuous outcome through a model that may not reflect every feature of a bounded scale. The summary-based recalculation is therefore a simple unadjusted way to compare reported means, not a substitute for a complete analysis plan. The registry does not report whether the trial's sponsor used a model tailored to the scale, nor whether outcomes were analyzed as changes, repeated observations, or endpoint scores in the final analysis.

What does the recalculation leave out?

The recalculated difference uses the posted group means, standard deviations, and group sizes. It does not incorporate participant-level covariates, correlations among repeated measurements, imputation for missing observations, stratification, or any adjustment for multiple outcomes unless those features are explicitly encoded in the posted summary calculation; such details are not reported. A sponsor analysis, if available, could use a different model and take precedence when there is a discrepancy. The registry comparison does not indicate a discrepancy, but no sponsor analysis is reported in the registry record.

Interpretation also depends on who was included in each outcome analysis. The registry gives arm-level sample sizes for the posted outcome, but it does not identify whether these are all randomized participants, participants with available endpoint data, or another analysis population. It does not report exclusions, missing observations, or a missing-data method. Accordingly, the numerical comparison is best understood as a summary-statistic result for the groups as posted, with the limits of the analysis population not fully documented.

11. Confidence Intervals and Precision

The primary mean difference is -0.04, with a 95% confidence interval from -0.616 to 0.536. The interval includes zero and spans values favoring either group under the stated subtraction order of morphine minus oxycodone. Its width indicates that the point estimate is not precise enough to pin down a single small difference. The result is consistent with little separation in the group averages, but it also permits differences in either direction within the interval.

A confidence interval is a measure of uncertainty in an estimated group difference under the calculation's assumptions. It is not a range containing a specified proportion of individual participants' scores. The group standard deviations, 2.31 for oxycodone and 2.22 for morphine, describe within-group spread, while the confidence interval describes uncertainty about the mean difference. These summaries serve different purposes.

The interval alone does not determine clinical importance. A clinically meaningful margin for NRS change is not reported in the registry record. Without such a margin and the trial's prespecified analysis details, the interval cannot establish equivalence, noninferiority, or the absence of an important effect. A result whose interval crosses zero is not proof that the groups are identical; it means the posted comparison does not exclude zero under the calculation used.

Precision is also conditional on the completeness and analysis of the data. The registry record does not report missing-data handling, the exact analysis population, or a sponsor-reported model-based interval. Thus, the interval should be read as the uncertainty attached to the summary-based recalculation, not as a complete account of every uncertainty in study conduct or 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 effect, not the trial's original design assumptions. For these continuous outcomes, the figures are participants per arm, not total events. The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. Each planning row uses the stated fraction of the observed effect as the effect to detect. The trial's own original sample-size justification is not reported in the registry record.

The 80% power column gives the approximate number of participants per arm for a design with an 80% chance of detecting the specified effect at the stated significance level, if the planning assumptions and statistical model hold. The 90% power column gives the corresponding planning number for a 90% chance. These are prospective design calculations: they describe what a future study might plan under the assumptions, not what probability the completed study had of finding a result.

Rows using a smaller fraction of the observed effect describe smaller target differences. Smaller effects are harder to distinguish from random variation, so they require more participants under the same assumptions. The posted observed mean difference is very close to zero, which makes calculations based on fractions of that estimate especially large; those numbers should not be mistaken for a recommendation or evidence that the trial was underpowered. The figures are planning illustrations, not observed power.

The registry does not report the original design effect, target power, or sample-size calculation used to plan enrollment. The planning numbers attached to the posted effect are separate from the completed study's reported enrollment of 242 participants. They can illustrate how sample-size needs change with target effect and desired power, but they cannot establish what the investigators planned or whether their original design assumptions were met.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = -0.040; pooled standard deviation σ = 2.266.
2. n = 2 × (1.96 + 0.842)² × 2.266² / -0.040² = 50,370.0, rounded up to 50,370 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
delta <- -0.04                      # observed difference in means
sigma <- 2.26582822437467                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(1675622)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 50,370 (80% power), 67,432 (90% power)
 75% of observed effect: n per arm = 89,547 (80% power), 119,878 (90% power)
 50% of observed effect: n per arm = 201,480 (80% power), 269,725 (90% power)
power.t.test: 50370.9 
Simulated power at n = 50,370 per arm: 0.797 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists multiple secondary outcomes in addition to the primary endpoint. Testing many outcomes can increase the chance that one or more results appear statistically notable by chance. A multiplicity plan can help manage that problem, for example by specifying a hierarchy of outcomes or an adjustment method. The registry record does not report whether such a plan was prespecified or applied. The posted secondary comparisons are unadjusted recalculations, so their p-values should not be read as if they controlled the overall false-positive risk across the outcome set.

The registry record reports 10 outcome measures and no reported analyses. It provides selected outcome summaries, but does not report the full statistical analysis plan, analysis populations, or whether the analyses followed prespecified methods. It is not possible from the registry information to determine whether the primary outcome was analyzed exactly as originally planned, whether any outcomes or timepoints were changed, or whether other analyses were conducted but not posted. Those details are not reported in the registry record.

Missing-data handling is also not reported. This matters in general because missing outcome values can affect both the number of observations contributing to a comparison and the interpretation of the result. Methods may rely on assumptions about why data are missing; different assumptions can lead to different estimates. The registry does not provide the number of missing NRS values, reasons for missingness, imputation methods, or sensitivity analyses. The posted arm sizes alone do not establish whether every enrolled participant contributed to the primary endpoint.

The record does not identify the analysis population, such as all randomized participants or those with available endpoint data, nor does it report participant disposition by treatment period. Consequently, the posted comparison cannot be fully evaluated for exclusions after randomization, deviations from assigned treatment, or loss to follow-up. These are reporting gaps, not evidence that any particular problem occurred. A complete interpretation would require the protocol, analysis plan, and participant-level flow information, none of which is reported in the registry record.

15. 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 0.0% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: respiratory and circulatory failure (1.7%), ileus (0.8%), brain metastases (0.8%).

The registry reports serious adverse events affecting 4 participants in the oxycodone group and 2 in the morphine group. Other adverse events affected 76 and 75 participants, respectively. The registry also reports 2 deaths in each group. These are counts, with the at-risk group sizes reported as 120 for oxycodone and 118 for morphine. They should be read as descriptive safety summaries, not as adjusted comparisons.

The serious adverse event terms listed among the top terms are respiratory and circulatory failure at 1.7%, ileus at 0.8%, and brain metastases at 0.8%. These entries describe reported event terms and percentages in the registry record; they do not by themselves establish whether an event was caused by study treatment. The record does not provide detailed event-level timing, seriousness criteria, relatedness assessments, or the complete safety analysis method.

Differences in raw counts do not account for exposure duration, participant characteristics, or missing safety follow-up. The double-blind period and open-label period are described, but treatment exposure and safety ascertainment details are not reported. These figures therefore support a descriptive account of the recorded events only and should not be used alone to compare overall safety or attribute causation.

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

The posted primary result describes a near-zero difference between the average NRS values in the two randomized groups during the stated double-blind timeframe. The 95% confidence interval includes zero and allows a range of differences on either side of it. The result therefore does not show a clear separation in the posted group averages, while leaving uncertainty about the size and direction of any underlying difference.

This finding is not proof that the treatments are equivalent. Equivalence requires a prespecified margin defining what differences count as sufficiently small, along with an analysis designed to test that question. A noninferiority claim likewise needs a prespecified margin and appropriate methods. Neither such margin nor a corresponding trial analysis is reported in the registry record. A non-significant result or an interval crossing zero is not, by itself, evidence that two treatments have the same effect.

The result also does not establish that either treatment works or does not work. The posted comparison is between two active treatment groups and the registry does not provide a no-treatment comparison. The group means and their difference address a particular pain measure over a particular timeframe; they do not directly answer every question about pain control, longer-term outcomes, individual response, or other treatment effects.

Clinical importance cannot be inferred from statistical summaries alone. The registry defines the NRS scale but does not report a threshold for a clinically important change or a prespecified decision rule. The analysis population, missing-data method, and sponsor's full statistical analysis are also not reported. These gaps limit what can be concluded beyond the descriptive comparison.

The most defensible reading is therefore narrow: the registry's summary statistics show similar group averages for the posted NRS outcome, with an unadjusted recalculated interval that remains compatible with differences in either direction. That is a statement about the reported comparison and its precision, not a treatment recommendation or a definitive judgment about clinical benefit.

17. Why This Trial Matters Statistically

This study is statistically informative as an example of why the point estimate, uncertainty interval, and design question should be considered together. The estimated primary difference is close to zero, but the confidence interval is the more complete guide to the range of differences compatible with the posted summary calculation. Treating a p-value alone as the result would conceal that uncertainty and could encourage an unwarranted conclusion of equivalence.

The record also illustrates the distinction between a randomized trial and a fully documented analysis. Randomization is an important design feature, but interpretation depends on the analysis population, handling of missing outcomes, prespecified endpoint definitions, and the statistical methods actually used. These details are not reported in the registry record. The available arm summaries allow a simple unadjusted comparison, yet they do not reproduce all the information a complete trial report would contain.

Multiple secondary measures broaden the descriptive picture, but they also raise the issue of multiplicity. Without a reported plan for how those outcomes were prioritized or adjusted, unadjusted secondary findings should not be treated as independent confirmations. The distinction between confirmatory and exploratory evidence matters when many measures are available.

Finally, planning calculations based on the observed effect are not retrospective evidence about a trial's power. They show how a future design's participant requirements depend on the target effect and desired power under stated assumptions. The original sample-size justification is not reported, so these illustrations cannot establish the investigators' planning rationale. Together, these issues make the record useful for learning how to read effect estimates cautiously while separating statistical uncertainty from clinical importance.

18. Limitations

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

The registry record does not report the original sample-size justification, the prespecified statistical analysis plan, or a sponsor-reported analysis for the primary outcome. The posted primary comparison is an unadjusted recalculation from group summaries. It cannot account for any adjustment, repeated-measures structure, or other modeling choices that may have been part of the trial's analysis.

The outcome population and missing-data handling are not reported. The arm counts associated with the posted outcome do not establish whether the analysis included all randomized participants or only participants with observed values. The record also does not give reasons for missing data, participant flow, or sensitivity analyses. These omissions limit evaluation of attrition and the robustness of the estimate.

The NRS is described as a bounded pain scale from 0 to 10, but the record does not report distributional checks, questionnaire administration details, or a threshold for clinically important change. The mean and standard deviation summarize the outcome but do not reveal its full distribution or participant-level variation.

Although the study is labeled randomized and quadruple-masked, the randomization method, allocation concealment, the roles masked, and the success of masking are not described. The registry gives selected secondary results but does not report a multiplicity strategy, and detailed results for every listed secondary outcome are not present. Safety summaries are descriptive and do not include enough event-level detail to attribute causation. These are limits of the registry information and do not establish that specific design or conduct problems occurred.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Immediate-Release Oxycodone Capsules Study in Cancer Pain — NCT01675622.
• Registry record last updated 2018-05-21; status last verified 2018-04.
• Results first posted 2018-05-21.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

The registry record describes a completed phase 3, randomized, quadruple-masked, parallel-group comparison of immediate-release oxycodone capsules and immediate-release morphine tablets for Chinese patients with cancer pain. Enrollment was 242. The primary outcome was the average change in Numerical Rating Scale score during the double-blind period, stated as baseline up to 5-8 days.

The posted primary group means are 3.91 for oxycodone and 3.87 for morphine. The unadjusted recalculated mean difference, expressed as morphine minus oxycodone, is -0.04, with a 95% confidence interval from -0.616 to 0.536 and p = 0.892. The interval includes zero, and the registry record does not report a clinical-importance threshold, sponsor analysis, missing-data method, or original sample-size justification.

Selected secondary and safety summaries are also recorded, but multiplicity handling and the full analysis populations are not reported. The posted results support a cautious descriptive interpretation of the measured outcomes rather than a definitive conclusion about equivalence or clinical effect.