Safety, Immunogenicity, and Protective Efficacy of Radiation Attenuated Plasmodium Falciparum NF54 Sporozoites (PfSPZ Vaccine) During Malaria Transmission Season in Healthy African Adult Women of Childbearing Potential in Mali: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Safety, Immunogenicity, and Protective Efficacy of Radiation Attenuated Plasmodium Falciparum NF54 Sporozoites (PfSPZ Vaccine) During Malaria Transmission Season in Healthy African Adult Women of Childbearing Potential in Mali (NCT03989102), a randomized phase 2 study. The primary outcome is Number of Participants With Adverse Events Within 7 Days After Each Vaccine Administration.

2. Clinical Question

3. Trial Design

This was a Phase 2, randomized, double-blind, parallel-group, placebo-controlled trial in Mali. The registry lists an enrollment of 324 and describes three groups: two PfSPZ Vaccine dose groups and one normal saline placebo group. The arm descriptions specify 100 participants in each group, and the primary outcome results report 100 participants per arm. The relationship between the listed enrollment and the outcome denominators is not reported in the registry record.

Participants in the two vaccine groups were scheduled to receive three doses by direct venous inoculation. Arm 1 received 9 x10(5) and Arm 2 received 1.8 x10(6), with administrations on days 1, 8, and 29. The placebo group received normal saline using the same stated schedule and route. The study summary says participants would receive treatment to prevent malaria about 2 weeks before the first and third injections. The specific preventive treatment is not reported in the registry record.

The stated study objective was to assess safety and tolerability in healthy Malian women of childbearing potential. The record also describes assessment of immunogenicity and protective efficacy during malaria transmission season, but the posted primary outcome is a safety count. Screening was described as including physical examination, medical history, blood and urine testing, heart tests, and a multiple-choice malaria knowledge test. The summary describes follow-up for about 1 year after the third injection. The trial is listed as completed, with a start date of 2019-07-03 and a primary completion date of 2022-04-05.

Details such as the allocation ratio, sequence-generation procedure, concealment method, and exact follow-up schedule are not reported in the registry record. Although the study is described as double-blind, the identities of the masked parties are not specified there.

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: 324 participants were enrolled, but 24 participants were not assigned to any treatment arms due to withdrawn consent; thus 300 total participants were assigned to treatment arms.

Year 1

Reasons for not completing this period:

Year 2

Reasons for not completing this period:

Post-Year 3 (up to 3 Years, 8 Months)

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 Number of Participants With Adverse Events Within 7 Days After Each Vaccine Administration, measured over 7 days after each vaccination at days 1, 8, and 29.

The primary endpoint is the number of participants with adverse events within 7 days after each vaccine administration. The stated assessment window follows each of the three scheduled vaccinations on days 1, 8, and 29. The outcome is reported as a participant count, rather than as the number of separate adverse-event episodes or an event rate over person-time. A participant who experienced more than one event may still contribute once to a count of participants, but the exact event-counting rules are not reported in the registry record.

This kind of endpoint is used to describe short-term safety and tolerability around dosing. Counting participants with an event can help readers understand how many people in each group had at least one qualifying event during the specified window. It does not, on its own, describe event severity, duration, or clinical importance. The posted primary outcome does not specify event categories or a severity threshold, and those details are not reported in the registry record.

The results list 51 participants in Arm 1, 43 in Arm 2, and 43 in Arm 3, with 100 participants represented in each arm. These figures concern the posted primary outcome; they do not establish the number of distinct events or provide a measure of malaria infection, immune response, or protection. No secondary outcomes are posted in the registry record.

7. Results Posted in the Registry

• Arm 2: 43.0% (43/100) versus 51.0% (51/100) on control; risk difference -8.0 percentage points (95% CI -21.8 to 5.8), risk ratio 0.84 (0.63–1.13); unadjusted two-proportion z-test p = 0.257.
• Arm 3: 43.0% (43/100) versus 51.0% (51/100) on control; risk difference -8.0 percentage points (95% CI -21.8 to 5.8), risk ratio 0.84 (0.63–1.13); unadjusted two-proportion z-test p = 0.257.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is a binary participant-level measure: a participant either had a qualifying adverse event within the stated window or did not. The registry presents the result as counts of participants. General statistical explanation: a count is easier to interpret alongside its denominator, because the denominator indicates how many participants contribute to that group’s result. The posted results list 100 participants in each arm, alongside counts of 51, 43, and 43.

What does a risk difference express?

General explanation: a risk difference compares the proportion with an outcome in one group with the proportion in another group by subtraction. A value of zero corresponds to equal observed proportions; a negative value means the first group’s reported proportion is lower when the comparison is expressed in that direction. The registry reports risk differences of -0.08 for both Arm 2 versus Arm 1 and Arm 3 versus Arm 1. This is a comparison of group proportions, not a count of events and not a measure of the time until an event.

The confidence intervals for both reported risk differences span zero. General explanation: a confidence interval describes a range of values compatible with the observed data under the method used to calculate it. An interval that includes zero does not rule out no difference, and it also allows differences in either direction. Its width reflects uncertainty: wider intervals indicate less precision than narrower intervals, all else equal. The confidence interval calculation method is not reported in the registry record.

How should the p-value be read?

The unadjusted p-value is 0.257 for each comparison. General explanation: a p-value describes how compatible the observed data, or more extreme data, are with a specified no-difference model, under assumptions of the test. It is not the probability that the null hypothesis is true, nor is it a measure of the chance that a treatment works. The record does not report the test used to obtain the p-value, whether it was prespecified, or whether other analyses were considered alongside it. The label unadjusted indicates that the posted value is not presented as adjusted for multiple comparisons.

Because the outcome is binary and the posted comparison uses risk differences, the result is naturally interpreted in terms of the proportion of participants with an event. General explanation: binary outcomes can also be compared using measures such as risk ratios or odds ratios, but these use different scales and have different interpretations. The registry displays risk-ratio and odds-ratio intervals as comparison statistics, but the primary comparison is identified as a risk difference. No adjusted model is described in the registry record.

Why can event counts differ from participant counts?

General explanation: one participant can experience more than one adverse event. A count of participants with at least one event is therefore not interchangeable with a total count of event episodes. The primary outcome explicitly counts participants. The registry’s adverse-event summary separately reports participants with serious events, participants with other adverse events, and deaths. The detailed event terms and rules for assigning events to categories are not reported in the registry record.

Over-dispersion is a general concern when analyzing event counts, particularly when the variability in the number of events is greater than a model assumes. It is not the central issue for the posted primary endpoint because the endpoint is a participant count with a binary status, not a total event count. The registry does not report an event-count model or a dispersion estimate. No inference about repeated-event modeling can therefore be drawn from the posted result.

What does randomization contribute?

General explanation: random assignment is intended to make treatment groups comparable on average, including with respect to characteristics that may not be measured. It does not guarantee identical groups in a particular trial, especially when group sizes are limited, and it does not remove uncertainty from the results. The record identifies the study as randomized but does not report the sequence-generation or allocation-concealment procedures.

Blinding can reduce the influence of treatment knowledge on behavior, reporting, and assessment. The study is described as double-blind, but the registry does not specify who was blinded or how blinding was maintained. The statistical analysis plan, analysis population definitions, handling of missing data, and methods for controlling multiplicity are not reported in the registry record. Those missing details matter when judging how the numerical results were generated and how robust they are to alternative analysis choices.

10. Confidence Intervals and Precision

Precision concerns how narrowly the result estimates the underlying group difference. The posted risk difference is -0.08 in each comparison, and the confidence interval for each comparison spans zero. This means the estimates are not precise enough to exclude no difference using the reported intervals. The intervals also allow values on either side of zero, so the data do not pin down the direction of the underlying difference.

The reported unadjusted p-value is 0.257 for each comparison. This is consistent with the uncertainty reflected by the confidence intervals, but the two statistics answer different questions: the interval describes a range of estimates compatible with the data under its method, while the p-value measures compatibility with a particular null model. Neither statistic demonstrates equivalence or establishes that the groups have identical risks.

The registry supplies interval limits to four decimal places, while the reporting limit for this analysis permits no more than three decimal places. To avoid changing the posted values, the limits are not reproduced numerically. The qualitative conclusion is that both intervals include zero. The interval method and any adjustments are not reported in the registry record.

The outcome denominators are 100 participants per arm. These group sizes and the observed counts help contextualize the estimates, but the precision depends on the data and method, not simply on the point estimate. The registry reports enrollment of 324, but the reason the primary outcome results list 100 participants in each arm is not reported in the registry record. The available precision statements apply to the posted primary comparisons and do not automatically apply to other outcomes or follow-up periods.

11. 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 events. They are illustrations based on the observed effect, rather than the trial’s original design assumptions. The stated 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 set to the stated fraction of the observed effect. The original trial’s own sample-size assumptions and justification are not reported in the registry record.

For planning for 100% of the observed effect, the figures are 610 participants per arm for 80% power and 816 participants per arm for 90% power. For planning for 75% of the observed effect, they are 1,088 participants per arm for 80% power and 1,455 participants per arm for 90% power. For planning for 50% of the observed effect, they are 2,451 participants per arm for 80% power and 3,281 participants per arm for 90% power.

In plain language, the 80% power column gives the illustrative number per arm under the stated assumptions for a design intended to have an 80% chance of detecting the selected effect if that effect were present. The 90% column uses a higher target chance of detection under those assumptions. Smaller effects require more participants to detect, which is why the planning figures rise as the assumed fraction of the observed effect gets smaller.

These figures are planning illustrations, not observed power. They do not describe the probability that the completed trial’s results are correct, and they do not change the uncertainty in the posted comparisons. The assumed equal allocation is for a two-arm planning comparison; it should not be mistaken for a report of how the original three-group trial was designed or powered.

12. 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 = 0.510; treatment proportion p₁ = 0.430; average p̄ = 0.470.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.7058 = 1.3834.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.7036 = 0.5921.
4. n = (1.3834 + 0.5921)² / (-0.0800)² = 609.8, rounded up to 610 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 <- 0.51                          # control proportion
p1 <- 0.43                          # 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(3989102)
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 = 610 (80% power), 816 (90% power)
 75% of observed effect: n per arm = 1,088 (80% power), 1,455 (90% power)
 50% of observed effect: n per arm = 2,451 (80% power), 3,281 (90% power)
power.prop.test: 609.8 
Simulated power at n = 610 per arm: 0.796 (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.

13. Multiplicity, Missing Data and Analysis Populations

The registry record lists two pairwise primary-outcome comparisons: Arm 2 versus Arm 1 and Arm 3 versus Arm 1. Both are reported with the same risk difference, confidence interval, and unadjusted p-value. No method for adjusting for multiple comparisons is reported. When several hypotheses are tested, multiplicity can increase the chance of at least one false-positive finding across the set of tests. General explanation: adjustment methods can address that issue, but they may change the threshold or interpretation for individual comparisons. It is not reported whether a multiplicity strategy was planned for this trial.

The record identifies the primary outcome but does not provide a statistical analysis plan or specify whether the comparisons were prespecified, whether other comparisons were conducted, or how the primary outcome was analyzed beyond the posted statistics. The unadjusted p-value should therefore be understood as reported, without assuming that it accounts for the number of comparisons or other analyses.

Missing-data handling is not reported in the registry record. The posted outcome results show 100 participants per arm, but do not say whether that represents all participants assigned, all participants who received an injection, or those with an available outcome assessment. The record does not describe withdrawals, exclusions, missed visits, or the treatment of participants with incomplete adverse-event information. It also does not state whether any imputation or sensitivity analysis was used.

Analysis populations are not specified. The registry does not say whether results were analyzed according to randomized assignment, receipt of treatment, or another defined population. These distinctions can matter if participants do not follow their assigned regimen or lack outcome data. The record also does not report covariate adjustment or subgroup analysis methods. Without those details, the posted counts and pairwise estimates can be described, but the exact analysis framework and its handling of incomplete or nonstandard observations remain unclear.

No secondary outcomes are posted, and no analyses are listed in the record. The absence of those results should not be interpreted as evidence that no additional analyses were conducted; rather, those details are not reported in the registry record.

14. 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 1% reporting threshold.

Most frequent non-serious adverse event terms

The serious adverse-event summary lists zero affected participants in Arm 1, zero in Arm 2, and zero in Arm 3. Each group has 100 participants at risk in that summary. The death counts are zero in Arm 1, one in Arm 2, and zero in Arm 3. These figures describe the posted serious-event and death categories; they do not establish whether a death was related to study treatment, because causality is not reported in the registry record.

The registry also lists 51 participants with other adverse events in Arm 1, 43 in Arm 2, and 43 in Arm 3, with 100 at risk in each group. These counts should be read separately from the serious adverse-event counts and from the primary outcome’s specified 7-day window. The detailed timing and terms for these other events are not reported in the registry record.

The serious-event term list is empty. Zero recorded serious events in the posted summary does not show that the underlying risk is zero; it describes the observed records in these groups. The counts do not by themselves establish comparative safety, event severity, or causation. The registry does not provide further clinical detail about the death or event categories.

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

The posted results show that adverse events within 7 days after vaccination were counted in 51 participants in Arm 1, 43 in Arm 2, and 43 in Arm 3. Each group’s outcome results include 100 participants. The reported risk differences are -0.08 for each vaccine-dose comparison with Arm 1, with confidence intervals that span no difference and unadjusted p-values of 0.257. These findings describe the recorded short-window counts and the uncertainty around the pairwise estimates.

The results do not establish that the groups are equivalent. An interval that includes no difference can reflect uncertainty, and equivalence requires a defined margin and an analysis designed to assess it; neither is reported in the registry record. The results also do not prove that a difference exists. The posted data do not provide a basis for a definite claim about the direction or size of an underlying difference.

The endpoint is limited to adverse events within the stated 7-day periods after each vaccination. It does not capture every possible safety outcome across the entire follow-up described in the study summary. The serious adverse-event summary reports zero affected participants in each arm, while one death is listed in Arm 2. The record does not provide enough detail to draw conclusions about causality or the clinical circumstances of that death.

The title and summary describe broader aims that include immunogenicity and protective efficacy, but the posted primary result is a safety count and no secondary outcomes are posted. These data therefore do not answer whether vaccination changed malaria infection, immune response, or protection. They also do not establish safety for populations or settings beyond the study population described in the record. Interpretation should remain tied to the outcome, comparison, follow-up window, and participants represented in the posted results.

16. Why This Trial Matters Statistically

This trial raises a statistical question about how to compare short-term adverse-event experience across two vaccine-dose groups and a placebo group while keeping the outcome definition clear. The primary measure counts participants with an event, rather than episodes of events. That distinction matters because repeated events in one participant do not necessarily correspond to additional participants experiencing an event.

The registry’s comparison is expressed as a risk difference, which places the group contrast on the scale of the difference between participant proportions. This scale makes the direction of the comparison interpretable alongside the counts, while the confidence interval shows that the estimate remains uncertain. Here, both posted intervals span no difference, and both unadjusted p-values are 0.257. A careful reading keeps the observed counts distinct from claims about the underlying group risks.

The comparison also highlights the importance of analysis transparency. The record identifies randomization and double blinding, but does not report the allocation procedure, analysis populations, missing-data methods, or multiplicity plan. Those design and analysis details help readers understand how group comparisons were generated and what conclusions the results can support.

Finally, sample-size planning figures based on an observed effect are not a substitute for the original trial’s design justification. The record’s planning illustration uses stated assumptions and shows how required participants per arm increase when planning to detect smaller effects. Separating that illustration from the completed trial’s observed results helps prevent confusion between planning, precision, and evidence from the trial itself.

17. 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 primary endpoint is restricted to adverse events within 7 days after each vaccination. It does not summarize all events across the follow-up described in the study summary, and the registry does not report the detailed event definitions, severity grading, or adjudication procedures. The endpoint is a participant count, so it does not indicate the total number of adverse-event episodes or how often events recurred.

The posted outcome results list 100 participants per arm, while total enrollment is listed as 324. The reason for this difference is not reported in the registry record. The record does not clarify the analysis population, the number who completed each vaccination, or whether participants without complete follow-up were excluded. It also does not report missing-data methods, withdrawals, or sensitivity analyses.

The pairwise results have identical reported risk differences, confidence intervals, and unadjusted p-values for Arm 2 versus Arm 1 and Arm 3 versus Arm 1. The registry record does not explain this pattern. It also does not report a multiplicity adjustment, statistical analysis plan, or the method used to calculate the comparison statistics. These omissions make it difficult to assess the full analysis process from the posted record alone.

The study concerns healthy women of childbearing potential in Mali, including a described community setting. Results from this group should not automatically be generalized to other populations or settings. Although the registry summary mentions immunogenicity and protective efficacy, no secondary outcomes are posted. The primary safety results therefore cannot fill gaps in the posted evidence about those other aims.

18. Related Tutorials

19. Related Statistical Calculators

20. Sources

• ClinicalTrials.gov: Safety, Immunogenicity, and Protective Efficacy of Radiation Attenuated Plasmodium Falciparum NF54 Sporozoites (PfSPZ Vaccine) During Malaria Transmission Season in Healthy African Adult Women of Childbearing Potential in Mali — NCT03989102.
• Registry record last updated 2024-03-19; status last verified 2022-05.
• Results first posted 2024-03-19.
• 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.

21. Record Summary

The registry identifies a completed Phase 2 randomized, double-blind, placebo-controlled parallel-group trial in healthy Malian women of childbearing potential. Three groups were described: PfSPZ Vaccine at 9 x10(5), PfSPZ Vaccine at 1.8 x10(6), and normal saline placebo, each scheduled for three administrations on days 1, 8, and 29. Enrollment is listed as 324.

The posted primary outcome counts participants with adverse events within 7 days after each vaccination. Counts are 51 in Arm 1, 43 in Arm 2, and 43 in Arm 3, with 100 participants in each arm’s outcome results. The two reported risk-difference comparisons are -0.08, each with a confidence interval spanning zero and an unadjusted p-value of 0.257. Serious adverse-event counts are zero in each group; one death is listed in Arm 2.

No secondary outcomes are posted. Details on analysis populations, missing data, multiplicity, and the statistical analysis plan are not reported in the registry record.