Ibuprofen With or Without Acetaminophen for Low Back Pain: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Ibuprofen With or Without Acetaminophen for Low Back Pain (NCT03554018), a randomized phase 3 study. The primary outcome is Change in Functional Impairment as Measured by the Roland Morris Disability Questionnaire.

2. Clinical Question

The key statistical question is whether the observed difference in average RMDQ change is sufficiently precise to distinguish a group difference from the range of differences compatible with sampling variability. The posted estimate is close to zero, while its confidence interval spans values on both sides of zero. That uncertainty matters: an estimate near zero is not, by itself, proof that the groups are equivalent or that any possible difference is clinically negligible.

3. Trial Design

This was a randomized, parallel-group, phase 3 trial sponsored by Montefiore Medical Center. The registry record gives the study status as completed and records enrollment of 120 participants. The recorded start date is 2018-10-16, and the primary completion date is 2019-09-30. The trial used quadruple masking; the registry record does not specify which trial roles were masked.

The randomized comparison assigned participants to ibuprofen with acetaminophen or ibuprofen with placebo. Both groups also received an educational intervention. The intended contrast is therefore the addition of acetaminophen to a common ibuprofen and education regimen, rather than a comparison of ibuprofen with no medication. The placebo arm helps maintain masking of the added medication, although further details about allocation procedures and masking implementation are not reported in the registry record.

Medication was dispensed at emergency department discharge, and the described treatment period was 7 days. The registry summary says data were collected from participants by telephone for 1 week. The primary outcome timeframe is baseline and one week after discharge. Secondary outcomes also refer to 7 days after discharge, with one measuring moderate or severe pain and the other whether analgesic medication was required within the previous 24 hours.

There were 57 participants in the acetaminophen arm and 53 in the placebo arm for the posted primary outcome. The different denominators across outcomes indicate that the available counts were not identical for every reported measure; the reasons for missing outcome data are not reported in the registry record. The safety summary lists 60 participants at risk in each group, which is a separate denominator from the primary-outcome counts.

The registry record does not report the original sample-size justification, the intended statistical analysis plan, or details of how randomization was generated or concealed. It also does not report participant demographic characteristics or the exact eligibility criteria. Those omissions limit how fully the design can be reconstructed from the registry record, even though the principal treatment comparison and outcome timeframes are described.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

Reasons for not completing this period:

5. Baseline Characteristics

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

6. Primary Endpoint

The registry lists the primary outcome as Change in Functional Impairment as Measured by the Roland Morris Disability Questionnaire, measured over Baseline and one week after discharge from emergency department.

The primary endpoint is change in functional impairment measured with the Roland Morris Disability Questionnaire. The RMDQ is a 24 item instrument about the impact of low back pain on daily life. Each item is answered yes or no, and the total score ranges from 0 to 24; higher scores indicate greater impairment. The registry describes the instrument as most sensitive for patients with mild to moderate disability due to acute, sub-acute or chronic low back pain.

Change was calculated by subtracting the one-week score from the baseline score. Under that definition, a positive change indicates that the score decreased over follow-up, while a negative change indicates that it increased. Comparing mean change between randomized groups summarizes the average difference in score movement during the first week after discharge. It does not describe every participant's response, and group averages can conceal substantial variation among individuals.

Functional impairment is relevant to this trial's question because the RMDQ focuses on the effect of back pain on daily activities, rather than pain intensity alone. The registry record reports the mean and standard deviation for each group and a confidence interval for the between-group mean difference. It does not report a threshold for a clinically important RMDQ change, so statistical estimates alone cannot establish whether a particular difference would be meaningful to patients.

7. Results Posted in the Registry

• Ibuprofen and Acetaminophen: mean 11.10 versus 11.90 on control; difference -0.80 (95% CI -4.61 to 3.01), standardized effect d = -0.08; z-test p = 0.681.

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.

Number of Participants With Moderate or Severe Pain, as Measured on an Ordinal Scale

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Ibuprofen and Acetaminophen: 28.1% (16/57) versus 28.3% (15/53) on control; risk difference -0.2 percentage points (95% CI -17.1 to 16.6), risk ratio 0.99 (0.55–1.80); unadjusted two-proportion z-test p = 0.978.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Ibuprofen and Acetaminophen and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants Who Required Analgesic Medication for Low Back Pain Within the Previous 24 Hours.

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Ibuprofen and Acetaminophen: 63.2% (36/57) versus 61.5% (32/52) on control; risk difference 1.6 percentage points (95% CI -16.6 to 19.8), risk ratio 1.03 (0.77–1.37); unadjusted two-proportion z-test p = 0.862.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Ibuprofen and Acetaminophen and the control. The interval gives the range of effects that remain compatible with the data.

The two secondary outcomes concern different aspects of the first week after discharge: whether participants had moderate or severe pain, and whether they required analgesic medication for low back pain within the previous 24 hours. Across these outcomes, the posted comparisons do not show a consistent, precisely estimated advantage for either randomized group. The uncertainty intervals for both risk differences include zero, and the unadjusted p-values are 0.978 and 0.862.

This broad pattern is compatible with the primary result, which is also centered near no between-group difference and has an interval spanning zero. Taken together, the posted summaries do not identify a clear separation between the regimens across the measured functional and symptom-related outcomes. That pattern should not be mistaken for proof of equivalence: the intervals indicate uncertainty, and the registry record does not report a clinically important threshold for these endpoints.

Secondary outcomes usually carry less evidential weight than a prespecified primary outcome because they may be among several outcomes examined. When multiple comparisons are made, the chance of at least one apparently unusual result can increase unless the analysis plan accounts for multiplicity. The registry record does not report a multiplicity adjustment, a hierarchy for the secondary outcomes, or the intended analysis plan. The posted secondary p-values are unadjusted, so they should be treated as descriptive rather than as independent confirmatory evidence.

Denominators also differ between the outcome summaries. The analgesic-use outcome has 57 participants in the acetaminophen group and 52 in the placebo group, whereas the moderate-or-severe-pain outcome has 57 and 53. Reasons for the differing available counts are not reported in the registry record. Without information about why outcome data are absent, it is difficult to assess whether the missing observations could have influenced the comparisons.

The secondary results can contextualize the primary functional measure, but they do not replace it. They measure related yet distinct experiences, and no composite or joint analysis is reported in the registry record. Their overall pattern is consistent with uncertainty around small between-group contrasts, not a definitive conclusion that the regimens are identical.

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

• Number of Participants With Moderate or Severe Pain, as Measured on an Ordinal Scale
• Number of Participants Who Required Analgesic Medication for Low Back Pain Within the Previous 24 Hours.

9. Statistical Interpretation

10. Statistical Methods Explained

What does the mean difference represent?

The primary outcome is continuous: each participant has a numerical change score, and the reported group summary is the mean of those scores. The comparison subtracts the control-group mean from the intervention-group mean. Here, the mean change was 11.1 in the ibuprofen and acetaminophen group and 11.9 in the ibuprofen and placebo group, producing a mean difference of -0.8 units. The sign depends on the order of subtraction and on the change-score definition. Since change is baseline score minus follow-up score, a positive group mean represents an average decrease in impairment score.

A mean difference keeps the result in the original RMDQ units, which can be easier to relate to the scale than a standardized measure. The reported standard deviations describe the spread of individual change scores around each group's mean; they are not confidence intervals for the means. The primary group standard deviations were 10.7 and 9.7. A mean is a useful summary, but it does not show the distribution of individual responses or whether changes were similar across participants.

How should a confidence interval be read?

A confidence interval expresses uncertainty around an estimated effect. In general, a 95% confidence interval is produced by a method that, under its assumptions, would cover the target effect in 95% of repeated samples. It is not a probability statement that the particular interval contains the effect, and it does not mean that every value inside is equally plausible. The primary interval, -4.613 to 3.013, crosses zero. Zero represents no mean difference between groups under the comparison's subtraction convention. Because the interval crosses zero, the data are compatible with a range of effects that include no difference as well as differences in either direction.

The interval's width is important in addition to whether it crosses zero. A wide interval indicates less precision about the size of the effect. Precision depends on factors such as sample size and the variability of the outcome. The primary outcome has 57 and 53 participants in the two arms, and the standard deviations are substantial relative to the estimated mean difference. These features help explain why the estimate remains uncertain. The interval alone does not determine whether an effect would be important in practice; that judgment would require a meaningful-change threshold, which is not reported in the registry record.

What does the p-value add?

The unadjusted p-value for the primary mean comparison was 0.681. In general, a p-value is calculated under a null model, commonly one that assumes no difference, and measures how inconsistent the observed data are with that model. It is not a measure of the probability that the treatment effect is exactly zero. Nor does a larger p-value prove that the groups are equivalent. The p-value and confidence interval address related questions: the p-value summarizes evidence against a null value, while the interval presents a range of effect sizes compatible with the data under the interval method.

The p-value is unadjusted, meaning it is not reported as corrected for multiple outcomes or comparisons. The registry record does not provide a formal analysis plan or an adjustment procedure. The result should therefore not be treated as a fully documented confirmatory analysis with known handling of all planned comparisons.

Why do binary outcomes use different summaries?

The secondary outcomes count participants meeting a condition: moderate or severe pain, or reporting analgesic use within the previous 24 hours. Such outcomes are binary at the participant level, even though the registry posts counts. A risk difference compares the proportion meeting the outcome in one group with the corresponding proportion in the other group. In general, a risk difference of zero corresponds to equal proportions. Confidence intervals for risk differences express uncertainty in that absolute contrast.

Counts and denominators both matter. A count by itself does not show how frequent an outcome was unless the denominator is also considered. Denominators may differ across outcomes if outcome data are unavailable for some participants. The posted secondary summaries use different group counts for the analgesic-use outcome than for the primary measure, and the reason for this difference is not reported in the registry record. The registry record also lists no reported analyses for the secondary outcomes, so the posted comparisons should be read as unadjusted summaries rather than as a documented model-based analysis.

What does over-dispersion mean in general?

For count or binary outcomes, statistical methods rely on assumptions about how much variation is expected. Over-dispersion means the observed variability is greater than a model assumes. When over-dispersion is present and not accounted for, uncertainty may be understated, making intervals too narrow and tests too optimistic. The registry record does not report an over-dispersion assessment or a model for the secondary outcomes, so no conclusion about whether it affected these results can be drawn.

For the continuous primary outcome, the posted summaries give means and standard deviations, but do not document distributional checks, covariate adjustment, or a formal model specification. The record says staff statisticians verified the calculated mean and associated confidence interval values. Verification of those values does not supply the missing analysis-plan details or establish which assumptions were checked.

11. Confidence Intervals and Precision

The primary mean difference is -0.8 units, with a 95% confidence interval from -4.613 to 3.013. The interval includes zero and extends in both directions. This means the observed data do not pin down the size or direction of the between-group difference with high precision. The point estimate is one summary of the data; the interval makes clear that estimates differing substantially from that point remain compatible with the sampling uncertainty.

Precision is not the same as whether a result is statistically significant. A narrow interval could precisely estimate a small difference, while a wide interval could include both negligible and important differences. Here, the registry record does not give a clinically important threshold for RMDQ change, so it is not possible to determine from the posted information which parts of the interval would matter clinically. The interval should be read as statistical uncertainty about the mean contrast, not as a range of individual participant outcomes.

The primary outcome counts are 57 in the combination group and 53 in the placebo group. The change-score standard deviations are 10.7 and 9.7, while the group means are close together. Variation within groups relative to the observed mean separation contributes to uncertainty around the contrast. The sample sizes and dispersion therefore help explain why a near-zero estimate is not accompanied by a sharply defined effect size.

The secondary risk-difference intervals also include zero. Their presence reinforces that the posted secondary comparisons do not provide precise evidence of a directional difference. Those endpoints have different denominators and are measured as participant counts at a single follow-up time. Their uncertainty should not be inferred from the primary outcome interval, because each outcome has its own data and sampling variability.

Confidence intervals quantify sampling uncertainty under statistical assumptions. They do not capture every source of uncertainty, such as missing outcome data, limitations in the recorded eligibility information, or uncertainty about how the analysis was planned. The registry record does not report the missing-data approach or original analysis plan, leaving those aspects of precision difficult to assess.

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 a reconstruction of the trial's original design. For these outcomes, the reported figures are participants per arm, not total events. The planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect equal to the stated fraction of the observed effect. The original design assumptions and sample-size justification are not reported in the registry record.

The 80% power column describes the number of participants per arm estimated to give an 80% chance of detecting the specified effect under those assumptions, if that effect is real and the model assumptions hold. The 90% column uses a higher target chance of detecting that effect and consequently calls for more participants. Power is a design property for a specified effect and analysis; it is not a measure of how likely the observed result is to be true.

Rows for planning at 100%, 75%, and 50% of the observed effect illustrate how planning changes when the target effect is smaller than the observed estimate. Smaller effects require more participants because they are harder to distinguish from sampling variation. For the primary outcome, the planning figures rise from 2,568 participants per arm for 80% power at 100% of the observed effect to 10,270 at 50% of that effect. The 90% figures similarly rise from 3,437 to 13,748 participants per arm across those rows. These are illustrations from the observed estimate, not recommended trial sizes.

The binary-outcome planning figures are especially sensitive to the small observed risk differences. For example, the moderate-or-severe-pain figures at 100% of the observed effect are 591,814 participants per arm for 80% power and 792,271 for 90% power. Such large estimates reflect the planning calculation applied to the observed contrast; they should not be read as evidence about the trial's original enrollment target.

These calculations are not observed power. They do not tell whether the completed trial was adequately powered for a prespecified effect, because the original target effect and design assumptions are not reported in the registry record. A planning curve visualizes the relation between assumed effect size and required sample size under the same planning assumptions; it does not establish what sample size the investigators originally intended.

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 = -0.800; pooled standard deviation σ = 10.231.
2. n = 2 × (1.96 + 0.842)² × 10.231² / -0.800² = 2,567.3, rounded up to 2,568 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 <- -0.800000000000001                      # observed difference in means
sigma <- 10.2307271382721                     # 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(3554018)
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 = 2,568 (80% power), 3,437 (90% power)
 75% of observed effect: n per arm = 4,565 (80% power), 6,110 (90% power)
 50% of observed effect: n per arm = 10,270 (80% power), 13,748 (90% power)
power.t.test: 2568.2 
Simulated power at n = 2,568 per arm: 0.809 (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

Multiplicity arises when several outcomes, time points, subgroup analyses, or treatment comparisons are assessed. Even when each test uses the same nominal significance threshold, testing many hypotheses can increase the chance of at least one result appearing noteworthy by chance. A prespecified primary outcome helps focus interpretation, while secondary outcomes can provide supporting or exploratory information. The registry record lists one primary outcome and two secondary outcomes, but it does not report a multiplicity strategy, a testing hierarchy, or whether any additional analyses were planned.

The p-values posted for the comparisons are unadjusted. The registry record does not report a correction for multiple testing, so the secondary p-values should not be interpreted as if a family-wise or false-discovery procedure had been applied. This does not invalidate the descriptive estimates; it means their evidential role should be considered in light of the number of outcomes and the absence of a documented adjustment plan.

Missing-data methods and analysis populations are also not reported in the registry record. The primary outcome summaries include 57 participants in the acetaminophen group and 53 in the placebo group. The moderate-or-severe-pain outcome uses those same group counts, while the analgesic-use summary includes 57 and 52. The safety figures list 60 participants at risk in each arm. These differing denominators may reflect outcome availability or reporting conventions, but the reason is not reported in the registry record.

Without a missing-data description, the record does not establish whether analyses used all randomized participants, only those with observed outcomes, or another defined population. It also does not say whether missing values were imputed, whether sensitivity analyses were performed, or whether the reasons for missing data differed between groups. If missingness is related to outcome experience, complete-case summaries could differ from the results that would have been observed with complete follow-up. This is a general concern, not a claim that such bias occurred in this trial.

The record reports zero listed analyses in its analysis summary and gives no detailed statistical plan. It therefore does not establish which inferential procedures were prespecified or whether the posted outcome summaries represent the complete planned analysis set. These documentation gaps limit assessment of selective reporting, multiplicity, and robustness to missing data.

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% reporting threshold.

Most frequent non-serious adverse event terms

The serious adverse event summary lists 0 affected participants among 60 at risk in each arm. Deaths are listed as 0 in both groups. The other adverse event counts are 5 among 60 participants at risk in the ibuprofen and acetaminophen group and 2 among 60 at risk in the ibuprofen and placebo group. These are counts in the registry record, not adjusted comparisons.

Zero serious adverse events recorded in these groups means none were listed as affecting participants in the posted safety summary. It does not show that serious events are impossible or that the groups have identical safety profiles. With a limited number of participants, uncommon events can be difficult to characterize, and the registry record does not provide a comparative safety analysis or confidence intervals for these counts.

The number at risk for safety is 60 in each arm, distinct from the primary outcome counts of 57 and 53. The registry record does not explain the denominator difference or define the other adverse events in detail. The serious-event terms list is empty. These summaries describe what was recorded for the trial and should not be used alone to draw broader safety conclusions.

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

The central result is an estimated mean difference of -0.8 RMDQ units between the two randomized groups, with a 95% confidence interval from -4.613 to 3.013. The point estimate is close to zero, and the interval includes zero. The unadjusted p-value is 0.681. Together, these statistics indicate that the registry results do not establish a clear difference in mean functional change between the assigned regimens during the one-week follow-up.

That conclusion is narrower than saying the regimens are equivalent. A non-significant result can occur when the true effect is small, but it can also occur when data are too imprecise to distinguish a meaningful difference from no difference. Equivalence requires a prespecified margin defining how large a difference can be while still counting as equivalent, along with an analysis tailored to that objective. Such a margin and analysis are not reported in the registry record.

The result also does not establish that either regimen works or does not work. Both arms received ibuprofen and an educational intervention, and there is no untreated or ibuprofen-free comparison in the described randomized contrast. The comparison addresses the added contribution of acetaminophen within this regimen, not the effect of the full treatment package relative to no treatment or another standard of care.

The findings apply to the described population and observation period: patients presenting to an emergency room for acute, non-radicular low back pain, with outcomes collected over one week after discharge. The registry record does not provide detailed participant characteristics, so applicability to other populations cannot be assessed fully. Nor do the posted outcomes resolve effects beyond the short follow-up period.

Statistical interpretation should account for the limited precision, the different outcome denominators, and the absence of a reported analysis plan and missing-data methods. The posted data are useful for describing the observed comparison, but they do not answer every clinical or methodological question about the interventions. No clinical decision should be based on the statistical summaries alone.

17. Why This Trial Matters Statistically

This trial illustrates why a point estimate and its uncertainty need to be read together. The primary estimate is close to zero, but the confidence interval is wide enough to include differences in either direction. Looking only at the estimate could suggest a firm absence of separation; looking at the interval shows that the size and direction of the underlying difference remain uncertain.

It also demonstrates the distinction between failing to detect a difference and demonstrating equivalence. A p-value above a conventional threshold does not certify that two regimens have the same effect. Equivalence requires a defined margin and a design intended to test whether the difference is confined within that margin. The registry record does not report such a framework.

The trial's shared treatment components make the estimand specific and useful to understand: the randomized contrast is ibuprofen plus acetaminophen versus ibuprofen plus placebo, with education in both groups. This structure isolates the added medication contrast more directly than comparing two entirely different treatment packages. At the same time, it does not estimate the effects of ibuprofen itself or of the combined regimen against no treatment.

The outcomes also show why multiplicity and missingness matter. Several outcomes were recorded, and their p-values are unadjusted. Outcome denominators vary, while the registry record does not explain missing data or report analysis populations. These details affect how confidently results can be interpreted and reproduced.

Finally, the sample-size illustrations underline the dependence of planning on the effect one wants to detect. Smaller target effects require larger samples under the stated assumptions. Such calculations help explain planning tradeoffs, but because they use observed effects and are not the original design justification, they cannot retrospectively establish the trial's intended power. The registry record's incomplete methodological detail is itself an important statistical lesson: transparent reporting of plans, analysis populations, missingness, and clinically meaningful thresholds is needed to interpret estimates fully.

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 main limitation specific to this trial is the short observation period. The primary assessment was one week after emergency department discharge, and the secondary outcomes refer to 7 days after discharge. The registry record therefore does not describe longer-term functional status or symptoms.

The primary comparison includes 57 participants in one arm and 53 in the other, with a mean difference close to zero and a confidence interval spanning both directions. This limits the precision with which the between-group difference can be characterized. The registry record does not report a clinically important RMDQ threshold, so the clinical significance of values across the interval cannot be classified from the posted information.

The registry summary describes patients presenting to an emergency room with low back pain and identifies the trial as involving acute, non-radicular low back pain. However, detailed eligibility criteria and participant characteristics are not reported in the registry record. That makes it difficult to assess how closely the enrolled participants represent other patient groups or settings.

Outcome counts are not identical across all endpoints, and the safety denominator differs from the primary-outcome counts. The reasons for these differences, the amount and pattern of missing data, and any methods for addressing missing observations are not reported in the registry record. If missingness was related to outcomes or differed by group, the available-case summaries might not fully represent the randomized groups; the record does not permit that possibility to be evaluated.

Other limitations of interpretation include the absence of a reported original sample-size justification, statistical analysis plan, multiplicity strategy, analysis populations, or clinically important threshold. The record does not provide a formal comparative analysis of adverse events. These omissions do not change the posted estimates, but they constrain the assessment of how the analyses were selected and how robust the results are to alternative assumptions.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Ibuprofen With or Without Acetaminophen for Low Back Pain — NCT03554018.
• Registry record last updated 2024-02-28; status last verified 2024-02.
• Results first posted 2021-09-22.
• 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, randomized, parallel-group phase 3 trial sponsored by Montefiore Medical Center, with enrollment of 120. It compared ibuprofen 600 mg plus acetaminophen with ibuprofen 600 mg plus placebo; both arms also received an educational intervention. The primary outcome was change in RMDQ score from baseline to one week after emergency department discharge.

The primary mean difference was -0.8 units, with a 95% confidence interval from -4.613 to 3.013 and an unadjusted p-value of 0.681. The interval includes zero and indicates uncertainty about the size and direction of the between-group difference. Secondary comparisons likewise do not provide a clear, precise separation, and their results are unadjusted.

The registry record does not report the original sample-size justification, statistical analysis plan, missing-data methods, analysis populations, or multiplicity approach. The posted summaries describe a short-term randomized comparison, but those documentation gaps and the precision of the estimates should be considered when interpreting the results.