An Intervention Study To Improve Human PapillomaVirus ( HPV) Immunization in Haitian and African American Girls: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for An Intervention Study To Improve Human PapillomaVirus ( HPV) Immunization in Haitian and African American Girls (NCT01254669), a randomized na study. The primary outcome is The Receipt of the First HPV Vaccination.

2. Clinical Question

3. Trial Design

The registry describes a randomized, parallel-group clinical trial with no masking. The two groups were assigned to BNI or standard of care. The record lists Boston Medical Center as sponsor, an enrollment of 200, a start date of 2011-01, primary completion in 2013-10, and a completed status. The phase is recorded as NA.

In the standard-of-care group, mothers received a low-literacy, standard-practice HPV-vaccine information sheet. In the BNI group, the interview addressed mothers’ beliefs, values, and concerns about HPV prevention and considered their priorities for health and well-being. The registry’s brief summary frames the study around HPV immunization among Haitian and African American adolescent girls and maternal acceptance and knowledge.

The primary outcome concerns receipt of a daughter’s first HPV vaccination within 1 month of randomization. The posted arm summaries list 97.0 participants for standard of care and 96.0 for BNI. The primary outcome description says the analysis population was determined by enrollment and by answering questions of interest. The registry does not report detailed eligibility criteria, the original allocation procedure, or further information about how the analysis population was selected.

A secondary outcome assessed maternal knowledge about the HPV vaccine 1 hour after intervention. The registry record does not report the trial’s original sample-size assumptions or a detailed statistical analysis plan. The planning calculations associated with the posted effects are illustrations, not evidence of the assumptions used to design or conduct the trial.

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: Following participant enrollment, but prior to group assignment, no significant event occurred. However, in our study after being randomized, participants provided demographic data. During data collection, one participants was excluded/self-withdrew from the trial for fear that demographic data may affect her immigration status/not documented.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: The number of participants for analysis was determined based on number of participants enrolled and who answered questions of interest.

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 The Receipt of the First HPV Vaccination, measured over within 1 month of randomization.

The primary endpoint is the percentage of participants whose adolescent daughters received a first HPV vaccination within 1 month of randomization. It captures a vaccination event in a defined period after group assignment. The endpoint therefore concerns vaccination receipt, not just a mother’s stated intention, consent, or knowledge.

This outcome is relevant to the study’s stated objective of increasing HPV immunization rates. In general, measuring an observed event can help distinguish a change in knowledge or attitudes from a change in the behavior the study is trying to influence. The registry’s stated primary endpoint is specifically the daughter’s receipt of the first vaccination; the record does not define the endpoint as completion of a vaccine schedule.

The posted outcome summaries give percentages for each arm, while the comparison information also gives event counts and analysis denominators. These figures describe the posted analysis, not necessarily every participant enrolled. The outcome description notes that inclusion in the analysis depended on enrollment and answering questions of interest. The registry record does not report further detail about missing outcome responses, how the analysis population was finalized, or how any missing values were handled.

The endpoint is time-bounded: vaccination receipt was assessed within 1 month of randomization. It should not be read as a measure of later doses, long-term immunization, HPV infection, or cervical cancer. Those are different outcomes from the one specified as primary.

7. Results Posted in the Registry

• BNI/Intervention: 56.2% (54/96) versus 50.5% (49/97) on control; risk difference 5.7 percentage points (95% CI -8.3 to 19.8), risk ratio 1.11 (0.85–1.45); unadjusted two-proportion z-test p = 0.425.

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.

The Secondary Outcome Will be Maternal Knowledge About HPV Vaccine.

• 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:
  • BNI Post-educational Intervention Group: mean 10.00 versus 5.00 on control; difference 5.00 (95% CI 4.44 to 5.56), standardized effect d = 2.50; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for BNI Post-educational Intervention Group than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcome is maternal knowledge about the HPV vaccine, measured 1 hour after intervention. Its posted statistical pattern is more distinct between groups than the primary vaccination outcome. The secondary result concerns an immediate knowledge measure, whereas the primary outcome concerns whether a daughter received a first vaccination within 1 month. They therefore address related but different stages of the study’s proposed pathway.

Knowledge may be relevant to understanding how an educational or behavioral intervention could operate, but a knowledge score is not itself vaccination receipt. A difference in knowledge does not show that consent was given, that vaccination occurred, or that any later health outcome changed. The registry’s brief summary describes a hypothesis linking BNI, maternal consent, vaccination, and knowledge; the posted outcomes do not establish every link in that proposed sequence.

The record lists one secondary outcome and no reported analyses. It does not report whether secondary outcomes were prespecified in a detailed analysis plan, how many statistical tests were considered, or whether any multiplicity adjustment was used. When several outcomes or comparisons are examined, the chance of at least one apparently unusual result can increase. In general, adjustment methods or a prespecified hierarchy can help address that issue, but the record does not document such an approach.

Accordingly, the secondary finding can inform interpretation of the intervention’s short-term association with knowledge, but it should carry less weight than a clearly prespecified primary result when making claims about the trial’s main objective. It also should not be used to resolve the uncertainty in the primary vaccination comparison. The outcomes differ in meaning, timing, and direct relevance to the stated objective.

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

• The Secondary Outcome Will be Maternal Knowledge About HPV Vaccine.

9. Statistical Interpretation

10. Statistical Methods Explained

What does a risk difference describe?

In general, a risk difference subtracts the event proportion in one group from the event proportion in the other. It is an absolute measure: it expresses how far apart the group proportions are on the probability scale. The posted risk difference is 0.057 for BNI compared with standard of care. Its confidence interval runs from -0.083 to 0.198. A value of zero would mean equal proportions on this scale. Because the interval includes zero, the data are compatible with no absolute difference, as well as with differences favoring either group.

How do relative measures differ?

In general, a risk ratio compares event probabilities by division, while an odds ratio compares the odds of an event. A value of one represents no relative contrast for either measure. The posted risk ratio is 1.114, with an interval from 0.855 to 1.451; the posted odds ratio is 1.259, with an interval from 0.715 to 2.22. Both intervals include one. Relative measures answer a different question from an absolute risk difference, so their numerical values should not be compared directly with the risk difference.

What does a confidence interval communicate?

In general, a confidence interval describes the uncertainty around an estimate under a specified statistical procedure. Narrower intervals indicate greater precision, while wider intervals indicate less precision. A confidence interval is not a guarantee that the true effect lies within its endpoints, and it is not a direct probability statement about the effect. The registry record does not state the method used to calculate the posted primary interval.

What does the p-value say?

In general, a p-value measures how unusual data at least as incompatible with a specified null hypothesis would be if that hypothesis and the analysis assumptions were true. It is not the probability that the null hypothesis is true, and it does not measure the size or importance of an effect. The primary comparison reports an unadjusted p-value of 0.425. This value does not establish either a difference or equivalence. The registry does not report the test used to obtain it.

Why distinguish the analysis summaries?

The primary arm summaries report 51.0 for standard of care and 56.0 for BNI, while the comparison information lists 49 events among 97.0 and 54 among 96.0, respectively. The registry record does not explain the difference between these reported summaries. It states that the analyzed participant count depended on enrollment and responses to questions of interest. The comparison should therefore be read using its own reported counts and denominators rather than by reconstructing or substituting values from the arm summaries.

What is the role of randomization?

In general, random assignment is intended to make groups comparable at the point of assignment, on average, reducing the risk that known or unknown baseline factors systematically determine group membership. It does not ensure identical groups in a particular trial, and it does not remove uncertainty from a finite dataset. The record identifies the trial as randomized, but does not report the sequence-generation or allocation-concealment procedures. The trial was unmasked, so participants and study staff were not masked according to the registry entry. The record does not describe whether outcome assessment was masked.

What can be said about the knowledge outcome?

The secondary knowledge outcome is reported as a mean score with a standard deviation. The posted comparison gives a mean difference of 5.0, with a confidence interval from 4.439 to 5.561, and an unadjusted p-value of <0.001. In general, a mean difference compares average scores on the scale used, while a standard deviation describes variation among observations within a group. The registry record does not give further detail about the scale’s interpretation, validation, or analysis method. This outcome was measured 1 hour after intervention, which is a different time and construct from the primary vaccination outcome.

What analyses are not documented?

The registry record does not report a detailed statistical analysis plan, the specific tests or models used, adjusted analyses, or a multiplicity procedure. It lists no reported analyses. No assumptions about covariate adjustment, interim analyses, or alternative analysis populations should be inferred from the posted summary statistics. General explanations of statistical measures do not establish which exact procedures were used for this trial.

11. Confidence Intervals and Precision

Precision is most directly assessed by the width of the confidence interval around an estimate. The primary risk-difference estimate is 0.057, and its interval extends from -0.083 to 0.198. Because the interval crosses zero and covers values on both sides, the direction and size of the underlying group difference remain uncertain. The interval does not support a narrow conclusion about the size of the primary effect.

The relative estimates also have intervals that include the no-difference value: 0.855 to 1.451 for the risk ratio and 0.715 to 2.22 for the odds ratio. They likewise leave room for different magnitudes and directions of the group contrast. These intervals should be interpreted on their own scales rather than as absolute percentage-point differences.

For the secondary knowledge outcome, the posted mean-difference interval is 4.439 to 5.561. This is narrower relative to its estimate than the primary interval, but it concerns a separate outcome measured 1 hour after intervention. Greater precision for knowledge does not imply greater precision for vaccination receipt or establish that knowledge changes led to vaccination.

In general, confidence intervals reflect both the observed data and the analysis procedure. The registry record does not report the precise interval-calculation method or a detailed analysis plan. The intervals describe uncertainty in the posted estimates; they do not account for every possible source of bias, such as missing outcome data or limitations in measurement.

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 participants per arm, not total event counts. The associated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is specified as a fraction of the observed effect. The registry record does not report the trial’s own original design assumptions, so these figures should not be read as the sample-size rationale used for the trial.

The 80% power column gives the number of participants per arm that the planning calculation indicates would be needed to have an 80% chance of detecting the specified effect if that effect were the true one and the planning assumptions held. The 90% power column gives the corresponding number for a 90% chance. These are prospective planning concepts, not guarantees about the outcome of a study.

The rows represent planning for 100%, 75%, and 50% of the observed effect. The figures rise as the assumed effect becomes smaller: a smaller contrast is harder to distinguish from random variation and generally requires more participants. The calculations are based on the observed effect, so they are illustrations of possible future planning needs rather than independent evidence about the true effect. They are not observed power.

The table and curve should be read as planning aids under the stated assumptions, not as reconstructions of the trial’s design or as evidence that the trial was adequately or inadequately powered. The registry record does not report the assumptions used when the study was originally planned.

13. How the Sample Size Is Derived

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

Formula

n is the number of participants in each arm, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.505; treatment proportion p₁ = 0.562; average p̄ = 0.534.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.7055 = 1.3827.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.7043 = 0.5928.
4. n = (1.3827 + 0.5928)² / (0.0573)² = 1,186.7, rounded up to 1,187 participants per arm for 80% power.

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

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
p0 <- 0.505154639175258                          # control proportion
p1 <- 0.5625                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(1254669)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 1,187 (80% power), 1,589 (90% power)
 75% of observed effect: n per arm = 2,115 (80% power), 2,831 (90% power)
 50% of observed effect: n per arm = 4,766 (80% power), 6,379 (90% power)
power.prop.test: 1186.7 
Simulated power at n = 1,187 per arm: 0.803 (20000 replicates)

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

14. Multiplicity, Missing Data and Analysis Populations

The registry identifies receipt of a first HPV vaccination as the primary outcome and maternal knowledge about the HPV vaccine as a secondary outcome. It does not report a detailed statistical analysis plan, a prespecified hierarchy for interpreting outcomes, or a multiplicity adjustment. The record lists no reported analyses. It is therefore not possible to determine from the registry record whether other analyses were planned or performed, or how their results were handled.

In general, testing multiple outcomes or comparisons can increase the chance of obtaining a small p-value by chance alone. Adjustment procedures or a clearly specified hierarchy can help control how results are interpreted. Without information about such procedures, the posted unadjusted secondary result should be treated as exploratory or supportive rather than as stand-alone confirmation. The primary result is also posted as unadjusted, and the registry record does not provide further details on the testing strategy.

The primary outcome description says the analysis population was determined based on enrollment and answering questions of interest. The primary comparison lists 97.0 participants in standard of care and 96.0 in BNI, with event counts of 49 and 54. The registry record does not report the number of missing primary outcome responses, reasons for missingness, an imputation method, or whether participants were analyzed according to their randomized assignment. It also does not explain the relationship between the arm-level percentages and the comparison counts.

For the secondary knowledge outcome, the posted arm summaries list 99.0 and 96.0 participants. The record does not explain whether the analysis population differed by outcome because of missing data or other criteria. It does not report sensitivity analyses addressing missingness. These omissions limit assessment of how missing outcome information could affect the estimates.

Further details about allocation concealment, baseline adjustment, interim analyses, and analysis populations are not reported in the registry record. Their absence from the record should not be taken as evidence that any particular method was or was not used.

15. Safety Results

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

Other (non-serious) adverse events

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

The serious adverse event figures list 100 at risk in each group and 0 affected in each group. The other adverse event figures likewise list 100 at risk in each group and 0 affected in each group. These are the registry’s posted counts for the reported categories. No serious adverse event terms are listed.

These figures should be read as the events recorded in the registry, not as proof that no adverse events of any kind occurred. The record does not provide further detail about event definitions, collection procedures, follow-up duration, or whether the at-risk group shown for safety was the same as the analysis population for the primary outcome. Death counts are not reported in the registry record.

In general, safety summaries depend on how events are defined, monitored, and recorded, as well as on the period of observation. The posted information alone does not establish the completeness of surveillance or allow comparisons beyond the figures listed. It is descriptive reporting, not a basis for a broader claim about safety.

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

The primary result is a comparison of the proportion of participants whose daughters received a first HPV vaccination within 1 month of randomization. The point estimate is higher in the BNI arm, but the confidence interval includes no difference and allows for contrasts in either direction. The data therefore leave substantial uncertainty about the magnitude and direction of the primary group contrast.

This does not prove that BNI had no effect, and it does not establish that BNI increased vaccination receipt. A non-significant unadjusted p-value is not evidence of equivalence. Demonstrating equivalence or non-inferiority would require a design and analysis framed around a prespecified margin, which the registry record does not report.

The secondary knowledge result concerns an immediate post-intervention measure. It is not a substitute for the primary behavioral outcome and does not establish that a change in knowledge led to vaccination. Nor do the posted outcomes establish effects on later vaccine doses, HPV infection, or cervical cancer. Those outcomes are not reported as trial results in the registry record.

The study was randomized and unmasked, according to the registry. Randomization is generally intended to reduce systematic differences between groups at assignment, but it does not eliminate uncertainty or all potential bias. The record does not give enough detail to assess allocation procedures, missing-data handling, or the full analysis strategy. The primary outcome description also indicates that analysis depended on participants answering questions of interest.

The most defensible reading is therefore limited: the registry reports a positive primary point estimate with an interval that is broad and includes no difference, alongside a secondary knowledge result that is more clearly separated between groups. These findings describe the posted data and do not establish a causal conclusion beyond the limits of the record.

17. Why This Trial Matters Statistically

This trial illustrates why the statistical interpretation of an intervention study should separate its primary behavioral outcome from intermediate measures. The stated objective was to increase HPV immunization, and the primary endpoint concerns vaccination receipt. Maternal knowledge is relevant to the intervention’s rationale, but it measures a different construct at a different time. A result on one outcome cannot automatically stand in for a result on the other.

It also illustrates the distinction between an estimated effect and its precision. The primary point estimate favors BNI, but its confidence interval includes no difference and spans a broad range of possible contrasts. Reading only the point estimate or only the p-value would miss the uncertainty expressed by the interval. Absolute and relative measures add different perspectives, but neither removes that uncertainty.

The record also shows why transparent reporting matters. The arm-level percentage summaries and the event counts used in the comparison are both posted, but their relationship is not explained. The analysis population is described in terms of enrollment and answering questions of interest, while missing-data procedures and the detailed analysis plan are not reported. Those details help readers assess how directly the reported estimates correspond to the randomized groups and how sensitive they may be to incomplete data.

Finally, sample-size planning based on an observed effect is not the same as the original design rationale or observed power. Treating planning illustrations as design evidence would overstate what the registry record establishes. Clear separation of trial findings, uncertainty, planning calculations, and unreported methods supports a more measured interpretation.

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

The registry record gives limited detail about participant eligibility and the daughters’ age range. It does not report the randomization sequence method, allocation concealment, or whether outcome assessment was masked. The trial itself is listed as unmasked. These reporting gaps limit assessment of how allocation and outcome ascertainment were conducted.

The primary outcome description states that the analysis population depended on enrollment and answers to questions of interest. The record does not report missingness counts, reasons for missing responses, or methods used to handle missing data. It also does not explain why the arm-level percentage summaries differ in presentation from the event counts and denominators listed for the comparison. This makes it harder to trace the primary result from the reported summaries.

The registry record does not provide the original sample-size justification, a detailed statistical analysis plan, or a reported-analysis list beyond the posted summary statistics. It does not describe whether analyses were adjusted, whether interim analyses occurred, or how multiple outcomes were handled. No conclusions about those procedures should be inferred from their absence.

The primary endpoint covers first vaccination receipt within 1 month of randomization. The registry record does not report later vaccination, schedule completion, or longer-term clinical outcomes as results. Maternal knowledge was assessed 1 hour after intervention, so that result does not establish persistence of knowledge or a behavioral pathway over time.

The safety record gives event counts but does not describe definitions or collection procedures, and death counts are not reported in the registry record. These limitations concern what can be assessed from the registry entry; they do not establish that unreported procedures or outcomes were absent from the conduct of the study.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: An Intervention Study To Improve Human PapillomaVirus ( HPV) Immunization in Haitian and African American Girls — NCT01254669.
• Registry record last updated 2017-05-19; status last verified 2017-04.
• Results first posted 2014-10-24.
• 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

NCT01254669 is a completed randomized, parallel-group, unmasked trial sponsored by Boston Medical Center. It compared a brief-negotiating interview with a low-literacy, standard-practice HPV-vaccine information sheet for mothers of Haitian and African American adolescent girls. The registry lists an enrollment of 200.

The primary outcome was receipt of a daughter’s first HPV vaccination within 1 month of randomization. The posted comparison has a positive point estimate for BNI, but its confidence interval includes no difference and is broad. Maternal knowledge was posted as a secondary outcome measured 1 hour after intervention. The registry record does not report a detailed analysis plan, missing-data procedures, or the original sample-size assumptions.