Prevention of Malaria in HIV-uninfected Pregnant Women and Infants: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Prevention of Malaria in HIV-uninfected Pregnant Women and Infants (NCT02793622), a randomized phase 3 study. The primary outcome is Number of Participants Who Deliver With a Composite Adverse Birth Outcome.

2. Clinical Question

The study concerns prevention of malaria in pregnancy and in infants, while the primary endpoint is a composite of adverse birth outcomes. Secondary outcomes address placental malaria, maternal malaria, anemia, asymptomatic parasitemia, and adverse events. The registry record does not report the location of the study or describe a particular malaria-transmission setting.

3. Trial Design

This was a randomized, parallel-group, phase 3 trial. The registry lists enrollment of 782 and a quadruple masking designation. Its brief summary describes a double-blinded randomized controlled trial; the record does not explain how the double-blind description relates to the quadruple masking label. The sponsor was the University of California, San Francisco. The study is listed as completed, with a start date of 2016-09 and primary completion date of 2018-12-04.

Participants were assigned to monthly SP or monthly DP during pregnancy. The brief summary says allocation was in equal proportions. Both groups also received placebo treatment to support blinding. The arm descriptions give the intended dosing schedules, but their text is incomplete in the registry record, so the full dosing and placebo-matching details are not reported in the registry record.

Women entered at 12-20 weeks of gestation. The summary describes follow-up to approximately 6 weeks after delivery for women and follow-up from birth until 12 months of age for children born to enrolled women. The primary endpoint is assessed at delivery. Other outcomes use different follow-up periods, including maternal malaria from study entry to delivery and anemia follow-up extending to one month after delivery.

The registry reports an enrollment figure, but the primary outcome has its own arm-specific denominators. Those denominators should be read with that endpoint rather than treated as a universal number of participants contributing to every analysis. The registry record does not report the original sample-size justification, the planned statistical analysis, interim analyses, or a detailed analysis population definition.

4. Participant Flow and Accounting

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

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Number of livebirths reported here. SP: 338 women followed through delivery resulting in 348 infants (10 twin sets). 9 mothers/infants excluded (4 spontaneous abortions, 5 stillbirths). DP: 349 women followed through delivery resulting in 352 infants (3 twin sets). 12 mothers and 13 infants excluded (10 spontaneous abortions, 3 stillbirths).

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 Number of Participants Who Deliver With a Composite Adverse Birth Outcome, measured over Delivery.

The primary endpoint counts participants who deliver with a composite adverse birth outcome. A participant meets the composite definition if any one of the listed conditions occurs: low birth weight (< 2500 gm), preterm delivery (< 37 weeks gestational age), or small for gestational age (< 10th percentile relative to an external growth reference). The endpoint is recorded at delivery and combines events that represent different aspects of birth outcome.

A composite can capture whether at least one of several clinically relevant events occurred, rather than focusing on only one event type. It can therefore provide a broad summary of adverse birth outcomes. At the same time, the combined result does not show which component contributes most to the overall count. The registry record does not provide component-specific primary outcome counts, so the separate contributions of low birth weight, preterm delivery, and small for gestational age are not reported in the registry record.

The result is a count of participants with an event, not a count of all event episodes. The primary comparison uses the outcome-specific denominators recorded for the two groups. Its risk difference expresses the difference in the proportion with the composite outcome, with DP compared against SP. The endpoint should be interpreted as a measure of the listed birth outcomes, not as a direct measure of every aspect of maternal or infant health.

7. Results Posted in the Registry

• Monthly Dihydroartemisinin-Piperaquine (DP) During Pregnancy: 16.0% (54/337) versus 18.2% (60/329) on control; risk difference -2.2 percentage points (95% CI -7.9 to 3.5), risk ratio 0.88 (0.63–1.23); unadjusted two-proportion z-test p = 0.448.

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.

Prevalence of Placental Malaria by Histology

• 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:
  • Monthly Dihydroartemisinin-Piperaquine (DP) During Pregnancy: 28.4% (94/331) versus 61.2% (197/322) on control; risk difference -32.8 percentage points (95% CI -40.0 to -25.6), risk ratio 0.46 (0.38–0.56); unadjusted two-proportion z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically lower for Monthly Dihydroartemisinin-Piperaquine (DP) During Pregnancy than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Prevalence of Maternal Malaria

• 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:
  • Monthly Dihydroartemisinin-Piperaquine (DP) During Pregnancy: 0.3% (1/342) versus 8.3% (28/336) on control; risk difference -8.0 percentage points (95% CI -11.1 to -5.0), risk ratio 0.04 (0.00–0.26); unadjusted two-proportion z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically lower for Monthly Dihydroartemisinin-Piperaquine (DP) During Pregnancy than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Prevalence of Anemia in Pregnant Women

• 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:
  • Monthly Dihydroartemisinin-Piperaquine (DP) During Pregnancy: 2.1% (8/373) versus 7.5% (28/375) on control; risk difference -5.3 percentage points (95% CI -8.4 to -2.3), risk ratio 0.29 (0.13–0.62); unadjusted two-proportion z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically lower for Monthly Dihydroartemisinin-Piperaquine (DP) During Pregnancy than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The posted secondary outcomes span placental infection, maternal malaria, anemia, asymptomatic parasitemia, infant anemia, and adverse events. The displayed comparative results cover some of these outcomes, while the registry record lists a broader set of secondary outcome measures. The overall pattern among the posted comparisons with estimates is that the DP group has lower unadjusted event proportions for placental malaria by histology, maternal malaria, and anemia in pregnant women. The full pattern should be assessed outcome by outcome, because these measures differ in definition, population, and follow-up period.

These results complement the primary birth-outcome question but do not answer it. Malaria and anemia outcomes are biologically and clinically distinct from the composite of low birth weight, preterm delivery, or small for gestational age. An apparent difference in one type of outcome does not establish a difference in another, and the secondary findings do not resolve the uncertainty in the primary estimate. Nor do the registry results establish whether changes in one outcome mediated any change in another.

Unadjusted secondary results carry less weight when many outcomes are examined because the chance of observing apparently notable results can increase across multiple comparisons. A prespecified hierarchy or multiplicity adjustment can help control that issue, but the registry record does not report such a plan. The record also does not provide reported analyses for the secondary outcomes. The posted comparison statistics should therefore be treated as exploratory evidence unless supported by a prespecified analysis plan not reported in the registry record.

Differences in denominators across outcomes may reflect outcome-specific availability or definitions, but the registry record does not give a complete account of why denominators differ or how missing observations were handled. The overall pattern is informative as a set of reported comparisons, not a substitute for full trial reporting or a single summary of treatment effect.

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

• Prevalence of Placental Malaria by Histology
• Prevalence of Placental Parasitemia
• Prevalence of Maternal Malaria
• Number of Participants With Adverse Events
• Prevalence of Anemia in Pregnant Women
• Prevalence of Anemia in Infants
• Prevalence of Asymptomatic Parasitemia in Pregnant Women
• Prevalence of Asymptomatic Parasitemia in Infants

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is binary: each participant is counted as having or not having the composite adverse birth outcome. A risk is the proportion of participants in a group who experienced the outcome. The posted risk difference compares those risks, subtracting the SP-group risk from the DP-group risk. A negative value therefore indicates a lower observed risk in the DP group, while a positive value indicates a higher observed risk. These are unadjusted comparisons based on the posted group counts.

For the primary endpoint, the reported risks are 0.182 for SP and 0.160 for DP. The risk difference is -0.022. The 95% confidence interval runs from -0.079 to 0.035. The interval is expressed on the risk-difference scale, so its values describe plausible differences in risk under the method used to construct it. Because it includes zero, the data do not clearly distinguish a risk decrease from no difference or a risk increase at the usual two-sided significance threshold. The unadjusted p-value is 0.448.

A p-value describes how unusual data at least as incompatible with a specified no-difference model would be, if that model and the analysis assumptions held. 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 p-value is unadjusted; the registry record does not report a multiplicity adjustment or the planned testing hierarchy. A p-value should therefore be read together with the effect estimate, confidence interval, outcome definition, and design details.

Other effect measures are also posted for comparisons, including risk ratios and odds ratios. A risk ratio compares the two group risks as a ratio; an odds ratio compares the group odds. These measures answer related but not identical questions and use different scales. The risk difference is especially direct when the question concerns the absolute difference in the proportion with an outcome. No single measure replaces examination of the underlying counts and uncertainty.

General statistical explanation: random allocation is intended to make treatment groups comparable, on average, with respect to factors measured and unmeasured at baseline. It does not guarantee that every realized group is identical, nor does it resolve problems from missing outcomes, departures from assigned treatment, or selective reporting. The registry record lists randomized allocation but does not report the detailed allocation procedure or the analysis population rules.

General statistical explanation: confidence intervals express uncertainty around an estimate under a statistical model and method. Wider intervals indicate less precision, while narrower intervals indicate greater precision. An interval that crosses zero for a risk difference includes values on both sides of no difference; it should not be summarized only by whether it crosses a significance threshold. The interval does not account automatically for unreported sources of bias or uncertainty in outcome measurement.

The secondary results use the same broad binary-outcome framework for the posted counts. For placental malaria by histology, the displayed risk difference is -0.328 with a 95% confidence interval from -0.400 to -0.256 and p < 0.001. For maternal malaria, the risk difference is -0.080 with a 95% confidence interval from -0.111 to -0.050 and p < 0.001. For anemia in pregnant women, the risk difference is -0.053 with a 95% confidence interval from -0.084 to -0.023 and p < 0.001. Each is an unadjusted comparison of the posted group counts, and none should be confused with the primary composite outcome.

General statistical explanation: when event rates or data structures are more variable than a model assumes, standard errors and confidence intervals can be too optimistic if that extra variability is ignored. This is often described as over-dispersion. The posted outcomes are participant counts for binary endpoints, and the registry record does not report an over-dispersion model or a detailed analysis method. It is therefore not possible to assess from the record whether the analyses used additional adjustment for features of the data.

The record lists no reported secondary analyses, and it does not provide a detailed statistical analysis plan. Methods for adjustment, covariate inclusion, missing data, and handling of multiple outcomes are not reported in the registry record. The comparative estimates should consequently be read as the posted unadjusted results, not as evidence that every protocol-specified analysis or sensitivity analysis has been reported.

11. Confidence Intervals and Precision

The primary risk difference is -0.022, with a 95% confidence interval from -0.079 to 0.035. This interval is broad enough to include differences in either direction. The point estimate favors a lower observed risk in the DP group, but the interval indicates that the estimate is imprecise: the data are also compatible with no difference and with a higher risk in the DP group. The unadjusted p-value of 0.448 is consistent with the interval's inclusion of zero.

A confidence interval is not a guarantee that the true effect lies within its limits, and it does not represent the range of outcomes for individual participants. It summarizes uncertainty about the estimated group difference under the statistical method used. It also does not account for limitations that are not represented in that method, such as possible bias from missing data or selective reporting.

The group counts and denominators are important to the precision of the estimate: the primary comparison is based on 60 events among 329 in the SP group and 54 among 337 in the DP group. The registry record does not report a prespecified clinically important difference, so statistical precision cannot be translated into a conclusion about clinical importance. It also does not report component-specific confidence intervals for the composite outcome.

In contrast, the posted secondary comparisons for placental malaria by histology, maternal malaria, and anemia in pregnant women have confidence intervals that lie below zero on the risk-difference scale. Those intervals describe greater precision for their respective unadjusted comparisons, but they concern different outcomes and do not narrow the uncertainty around the primary endpoint. Their interpretation is also subject to the unreported analysis and multiplicity plans.

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 record of the trial's original design calculations. For binary outcomes, the figures are participants per arm. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The planning exercise considers detecting the stated fraction of the observed effect: 100%, 75%, or 50%.

The 80% power column gives the participants per arm estimated to provide an 80% chance of detecting the specified effect under those assumptions if that effect is the true one. The 90% power column gives the corresponding estimate for a 90% chance. Power is a design property calculated under assumptions, not a guarantee about what a trial will find. The figures for the primary endpoint and the posted secondary outcomes are specific to each outcome's observed effect and event pattern; they are not interchangeable.

Smaller effects are harder to distinguish from random variation, so planning to detect a smaller fraction of an observed effect requires more participants per arm. The displayed curve should be read as a visual aid for this relationship, not as an additional result from the randomized comparison. For time-to-event outcomes, the stated convention is total number of events; for other outcomes, the convention is participants per arm. The outcomes discussed in the registry record are presented as participant counts, so their planning figures use participants per arm.

These figures are not observed power. The original trial's sample-size justification and design assumptions are not reported in the registry record, so the planning illustration cannot establish whether the trial was designed around the primary endpoint or any particular effect threshold.

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 = 0.182; treatment proportion p₁ = 0.160; average p̄ = 0.171.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.5328 = 1.0443.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.5326 = 0.4483.
4. n = (1.0443 + 0.4483)² / (-0.0221)² = 4,547.7, rounded up to 4,548 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 <- 0.182370820668693                          # control proportion
p1 <- 0.160237388724036                          # 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(2793622)
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 = 4,548 (80% power), 6,088 (90% power)
 75% of observed effect: n per arm = 8,189 (80% power), 10,963 (90% power)
 50% of observed effect: n per arm = 18,657 (80% power), 24,976 (90% power)
power.prop.test: 4547.7 
Simulated power at n = 4,548 per arm: 0.800 (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 lists multiple secondary outcomes, including placental malaria, maternal malaria, adverse events, anemia, and asymptomatic parasitemia in pregnant women and infants. When many outcomes are assessed, the chance of at least one apparently unusual result can increase, even if no underlying effect exists for any outcome. Statistical plans may address this through a defined hierarchy, adjustment for multiple testing, or interpretation that treats secondary analyses as exploratory. The registry record does not report a multiplicity strategy or a prespecified hierarchy of outcomes.

The posted comparisons are unadjusted. Their p-values do not account for the number of outcomes examined. This matters particularly when interpreting secondary findings: an unadjusted p-value describes an individual comparison under its assumptions, not the chance of a false positive across the full family of outcomes. The primary result should also be interpreted in the context of the unreported analysis plan, although it remains the designated primary endpoint in the registry record.

Missing-data methods are not reported in the registry record. The record gives different denominators for different outcomes, but does not explain all reasons for unavailable outcome data, the assumptions used about missingness, or whether any imputation or sensitivity analysis was conducted. The primary outcome description mentions exclusions, but the record does not provide a complete analysis of how exclusions and missing outcomes were handled in the comparison.

The analysis populations are not defined in sufficient detail in the registry record. It does not report whether the primary comparison followed an intention-to-treat, per-protocol, or other population definition, or how deviations from assigned treatment were handled. The registry lists randomized allocation, but randomization alone does not specify which participants were included in each analysis. These omissions limit assessment of whether the posted estimates follow the planned analysis and how robust they are to alternative handling of missing data and analysis populations.

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 serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: congenital anomaly (2.7%), thrombocytopenia (1.3%), anemia (1.1%), haemorrhage (0.5%), elevated alanine aminotransferase (0.3%).

The registry reports serious adverse events and other adverse events separately for each group. For serious adverse events, the at-risk counts are 375 in the SP group and 373 in the DP group; the counts affected are 11 and 19, respectively. The record reports 1 death in the SP group and 3 in the DP group. These are descriptive counts. The registry record does not provide a comparative statistical analysis of these safety results or enough detail to attribute events to a study drug.

For other adverse events, the at-risk count is 375 in the SP group and 373 in the DP group, with 341 affected in each group. The registry lists the most frequently reported serious-event terms as congenital anomaly at 2.7%, thrombocytopenia at 1.3%, anemia at 1.1%, haemorrhage at 0.5%, elevated alanine aminotransferase at 0.3%, and altered mental status at 0.3%. The record does not specify in the posted summary how these term percentages are distributed between treatment groups.

Event counts alone do not establish whether a treatment caused an event or whether groups differ in risk. Interpretation would require event definitions, timing, severity, relatedness assessments, and a planned comparative safety analysis. Those details are not reported in the registry record.

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

The primary result describes the observed frequency of a composite adverse birth outcome in the two randomized groups and the uncertainty around their estimated risk difference. The estimate is negative for DP relative to SP, but its confidence interval includes zero and values in both directions. The unadjusted comparison therefore does not establish a clear difference in this primary outcome. It also does not establish equivalence, non-inferiority, or absence of an effect.

The endpoint combines three outcomes, and the registry does not report separate primary counts for its components. A reader cannot determine from the composite result which component accounts for the observed events or whether the components show different patterns. The primary result also does not summarize malaria, anemia, infant outcomes, or safety; those are separate questions with their own definitions and denominators.

The secondary comparisons provide additional information about outcomes recorded during the trial, but they are unadjusted and their multiplicity plan is not reported. Their results should not be used to replace the primary comparison or to infer that a difference in one outcome necessarily produces a difference in another. The record does not report a detailed analysis plan, missing-data approach, or analysis population definition, which limits a complete assessment of the estimates.

Randomized allocation and masking are features of the design that can support a fair comparison, but they do not by themselves guarantee complete reporting or eliminate all possible sources of bias. The registry describes both double-blinding and quadruple masking; the relationship between those descriptions is not explained. The posted statistics are best read as the reported comparative evidence for the defined outcomes, with uncertainty and limitations kept in view. They do not, on their own, establish a universal conclusion for populations or settings not described in the record.

17. Why This Trial Matters Statistically

This trial illustrates why a primary outcome and its uncertainty matter even when secondary outcomes show more striking comparisons. The primary endpoint combines low birth weight, preterm delivery, and small for gestational age, while the primary risk-difference interval includes both negative and positive values. Reporting the estimate together with its interval prevents the point estimate alone from being mistaken for a settled conclusion.

It also shows the importance of distinguishing outcomes that sound related but measure different things. Placental malaria, maternal malaria, anemia, and adverse birth outcomes are not interchangeable endpoints. Their separate definitions, denominators, and follow-up periods shape what each estimate can say. A result for one endpoint cannot simply be transferred to another.

The study is also a useful example of how design information and results reporting work together. Randomization and masking are recorded, but the analysis plan, missing-data methods, multiplicity strategy, and original sample-size justification are not reported in the registry record. Those details are needed to assess whether the reported comparisons match the planned analyses and how much confidence to place in secondary findings.

Finally, planning illustrations based on observed effects should not be confused with a trial's original design or with observed power. They show how planning requirements change with the effect one aims to detect under stated assumptions. Keeping planning calculations separate from trial results helps prevent retrospective calculations from being misread as evidence about the adequacy of the study design.

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 trial location or the malaria-transmission context. That limits assessment of how directly the results apply to other settings. The record identifies the population as HIV-uninfected pregnant women and their children, so conclusions should not be extended from these results to populations not described in the study without further evidence.

The primary outcome is composite, but component-specific primary results are not reported in the registry record. The record's primary population description is incomplete, and the details of exclusions and outcome availability are not fully reported. Denominators differ across outcomes, while a complete explanation of missing observations and analysis populations is not available.

The registry record does not report the original sample-size justification, the detailed statistical analysis plan, interim analyses, or a multiplicity approach. It also does not report the methods used to handle missing data or departures from assigned treatment. These omissions limit assessment of the planned-versus-reported analyses and of the reliability of secondary comparisons.

Safety reporting is descriptive in the available record. Comparative safety methods, event relatedness assessments, and a complete group-specific breakdown for the listed serious-event terms are not reported in the registry record. The registry describes double-blinding in its summary and quadruple masking in its design fields, without explaining the difference. These reporting limitations do not change the posted counts, but they constrain interpretation of how the trial was conducted and analyzed.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Prevention of Malaria in HIV-uninfected Pregnant Women and Infants — NCT02793622.
• Registry record last updated 2021-04-14; status last verified 2021-04.
• Results first posted 2021-04-14.
• 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

NCT02793622 is a completed randomized, parallel-group, phase 3 trial sponsored by the University of California, San Francisco. The registry lists enrollment of 782, quadruple masking, a start date of 2016-09, and primary completion on 2018-12-04. The comparison was monthly SP versus monthly DP during pregnancy among HIV-uninfected pregnant women, with follow-up also described for their children.

The primary endpoint was a composite adverse birth outcome assessed at delivery. The posted risk difference for DP relative to SP was -0.022, with a 95% confidence interval from -0.079 to 0.035 and an unadjusted p-value of 0.448. The interval includes zero, leaving uncertainty about the direction of the primary comparison. Secondary outcomes and safety counts provide additional descriptive evidence, but interpretation is limited by unreported analysis, multiplicity, and missing-data methods.