This page provides an independent statistical analysis and educational interpretation of publicly reported results. ClinicalTrials.gov provides the official trial registry record. Numerical trial results on this page are restricted to the results posted in the ClinicalTrials.gov record; calculations added by Clinical Biostats are labelled as such.
1. Trial at a Glance
This page covers the registry results for Putative Investigational Therapeutics in the Treatment of Patients With Known Ebola Infection (NCT02363322), a randomized phase 1, phase 2 study. The primary outcome is Mortality.
| Feature | Registry value |
|---|---|
| ClinicalTrials.gov identifier | NCT02363322 |
| Phase | Phase 1, Phase 2 |
| Condition | Ebola Virus Infection |
| Allocation | Randomized |
| Design model | Parallel |
| Masking | None (open label) |
| Enrollment | 72 |
| Arms in the primary outcome | 2 |
| Lead sponsor | National Institute of Allergy and Infectious Diseases (NIAID) |
| Results posted | Yes |
2. Clinical Question
Population
People recently diagnosed with Ebola infection and hospitalized in an isolation unit for treatment were eligible according to the registry summary. Diagnosis was usually established by PCR. The condition listed for the trial is Ebola Virus Infection. The registry reports enrollment of 72, but the outcome entries separately list 35 participants in the standard-care-alone arm and 36 in the standard-care-plus-ZMapp arm. The registry record does not explain the relationship between those enrollment and outcome figures.
Intervention
Participants assigned to the intervention arm received ZMapp with optimized standard care. The arm description specifies ZMapp at 50mg/kg intravenously every third day for 3 infusions. Optimized care included aggressive fluid resuscitation, hemodynamic support, and other interventions available in an optimized care setting.
Comparator
The comparison arm received optimized standard care alone, including aggressive fluid resuscitation, hemodynamic support, and other interventions available in an optimized care setting. The trial was randomized, parallel-group, and unmasked, so participants and care teams were not described as blinded.
Primary question
The primary endpoint was mortality at 28 days. In statistical terms, the comparison asks whether the recorded frequency of death differed between the two randomized groups over that time frame. The posted counts were 13 of 35 in the standard-care-alone arm and 8 of 36 in the ZMapp-plus-standard-care arm. Those counts describe the outcome entries, but by themselves do not establish the size or precision of a treatment effect. The registry also lists ZMapp infusion-related adverse events and plasma viral load as secondary outcomes.
3. Trial Design
This was a randomized, parallel-group phase 1/phase 2 study sponsored by the National Institute of Allergy and Infectious Diseases (NIAID). The registry lists a start date of 2015-03-13, a primary completion date of 2017-12-31, and a completed status. Enrollment is recorded as 72. The registry outcome entries list 35 participants for current standard of care alone and 36 for current standard of care plus ZMapp; the record does not explain the difference between the enrollment figure and those outcome denominators.
The two groups received optimized standard care. One group also received ZMapp, described as 50mg/kg intravenously every third day for 3 infusions. The study was unmasked, meaning the registry does not describe masking of participants or investigators. Random allocation can help balance measured and unmeasured baseline factors on average, while lack of masking can affect care, outcome assessment, and reporting in ways that depend on the setting. The registry record does not report details about allocation concealment or outcome-assessor masking.
The primary outcome was death at day 28. The registry’s brief summary describes follow-up for up to 60 days, while the primary endpoint uses the 28-day time frame. These are different descriptions: the longer follow-up does not change the stated primary endpoint. Secondary outcomes listed include the number of participants with ZMapp infusion-related adverse events and plasma viral load. The record lists three outcome measures overall and two posted secondary outcomes.
The study took place in the context of an Ebola outbreak and evaluated an investigational treatment added to advanced care. The registry record does not report the trial’s original sample-size justification, detailed analysis plan, or operational details beyond the design and intervention descriptions quoted above. Those omissions limit what can be inferred about planned analyses and how the recorded results were generated.
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
| Stage | A/Current Standard of Care Alone | B/Current Standard of Care Plus ZMapp |
|---|---|---|
| STARTED | 36 | 36 |
| COMPLETED | 35 | 36 |
| NOT COMPLETED | 1 | 0 |
Reasons for not completing this period:
| Reason | A/Current Standard of Care Alone | B/Current Standard of Care Plus ZMapp |
|---|---|---|
| Lost to Follow-up | 1 | 0 |
Analysis population for the primary outcome, as defined in the registry: Seven of the eight deaths recorded in ZMapp recipients occurred before day 4, before the second of three planned infusions of ZMapp. The exception was one patient who received a second infusion on day 4 and died later that day. In the group that received the current standard of care alone, all 13 deaths occurred during the first 8 days of follow-up
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.
| Characteristic | Unit | A/Current Standard of Care Alone | B/Current Standard of Care Plus ZMapp | Total |
|---|---|---|---|---|
| Participants analysed | 36 | 36 | 72 | |
| Age, Continuous | years | 27.9 (SD 16.4) | 24.3 (SD 18.3) | 26.1 (SD 17.4) |
| Sex: Female, Male: Female | Participants | 17 | 23 | 40 |
| Sex: Female, Male: Male | Participants | 19 | 13 | 32 |
| Race (NIH/OMB): American Indian or Alaska Native | Participants | 0 | 0 | 0 |
| Race (NIH/OMB): Asian | Participants | 0 | 0 | 0 |
| Race (NIH/OMB): Native Hawaiian or Other Pacific Islander | Participants | 0 | 0 | 0 |
| Race (NIH/OMB): Black or African American | Participants | 31 | 29 | 60 |
| Race (NIH/OMB): White | Participants | 1 | 0 | 1 |
| Race (NIH/OMB): More than one race | Participants | 0 | 0 | 0 |
| Race (NIH/OMB): Unknown or Not Reported | Participants | 4 | 7 | 11 |
| Region of Enrollment: Liberia | participants | 2 | 3 | 5 |
| Region of Enrollment: United States | participants | 1 | 0 | 1 |
| Region of Enrollment: Guinea | participants | 5 | 7 | 12 |
| Region of Enrollment: Sierra Leone | participants | 28 | 26 | 54 |
6. Primary Endpoint
The registry lists the primary outcome as Mortality, measured over 28 days.
| Element | Registry entry |
|---|---|
| Result type | Count Of Participants |
| Measure of spread | not applicable |
| Unit | Participants |
| Endpoint classification | Binary Endpoint |
The primary endpoint measures whether a participant died by day 28. The registry describes it as mortality, with the unit recorded as participants and the timeframe recorded as 28 days. The posted outcome counts are 13 of 35 in the current-standard-care-alone group and 8 of 36 in the group receiving current standard care plus ZMapp.
Death is a clinically important, clearly defined outcome. In general, a fixed-time binary endpoint makes it possible to compare the proportion of participants with the event in each randomized group over a common period. This can be more directly interpretable than a laboratory measure, although a binary endpoint does not represent the timing of an event within the follow-up period. A time-to-event analysis can use event timing, but the registry record does not report such an analysis for this primary outcome.
The endpoint is specifically mortality at day 28; it should not be read as a measure of all health outcomes, longer-term survival, or recovery. The summary describes follow-up for up to 60 days, but the primary result is tied to the stated 28-day endpoint. The posted result does not provide a fuller account of outcome ascertainment or missing endpoint data. Those details are not reported in the registry record.
Because the outcome is a count of participants with an event, the comparison is a binary-outcome comparison. Its interpretation depends not only on the two counts but also on the uncertainty around the between-group estimate. The reported confidence interval is broad and includes values on both sides of no difference, so the observed counts alone should not be treated as a precise estimate of the underlying group difference.
7. Results Posted in the Registry
- B/Current Standard of Care Plus ZMapp: 22.2% (8/36) versus 37.1% (13/35) on control; risk difference -14.9 percentage points (95% CI -35.9 to 6.1), risk ratio 0.60 (0.28–1.26); unadjusted two-proportion z-test p = 0.168.
Risk difference: B/Current Standard of Care Plus ZMapp
95% CI: -35.9 to 6.1 percentage points
Recalculated from the posted summary statistics
8. Statistical Interpretation
The observed counts were 13 deaths among 35 participants assigned to current standard care alone and 8 deaths among 36 assigned to current standard care plus ZMapp. The posted unadjusted risk difference is negative, indicating fewer recorded deaths in the ZMapp group in this comparison. The registry-reported confidence interval for that risk difference extends across no difference, and the unadjusted p-value is 0.168. Taken together, these results do not provide a precise estimate of the direction or size of the group difference.
A confidence interval that includes no difference is compatible with a range of possibilities: a reduction in mortality in the ZMapp group, little or no difference, or an increase. This is general statistical interpretation, not a claim that each possibility is equally likely. The interval is wide, reflecting substantial uncertainty in the estimated contrast. The posted p-value likewise does not establish that the groups were equivalent; it indicates that the observed data do not cross a conventional statistical-significance threshold under the unadjusted comparison.
The posted comparison is unadjusted. It does not account for any covariates, and the registry record does not report an adjusted primary analysis. Randomization supports comparison of groups, but in a trial with a limited number of outcome observations, chance differences in participant characteristics can remain. Without baseline information and details of the analysis population, the result cannot be examined for sensitivity to such differences.
The brief outcome description notes that seven of the eight deaths recorded among ZMapp recipients occurred before day 4 and before the second planned infusion. It states that the remaining participant received a second infusion on day 4 and died later that day. This timing description is relevant context, but it does not substitute for a prespecified analysis of event timing or treatment exposure. The corresponding control-group sentence is incomplete in the registry record, so no further timing comparison can be drawn from it.
The observed results should therefore be read as an uncertain comparison of recorded day-28 mortality in these two trial groups, not as a definitive estimate for other populations or care settings. The record does not provide enough detail to establish whether missing outcome data, protocol deviations, or other analytic choices affected the posted estimate. Nor does the primary mortality result alone describe the full balance of benefits and harms. The secondary outcomes and adverse-event entries add context, but their definitions and analysis details are limited.
In general, a p-value is a measure of how compatible observed data are with a specified statistical model under a null hypothesis; it is not the probability that the null hypothesis is true. A non-small p-value does not prove no effect, and a numerical difference between groups does not by itself show a reliable treatment effect. Here, the interval’s breadth is central: the data leave substantial uncertainty about the size and even the direction of the underlying difference.
9. Statistical Methods Explained
The primary outcome is binary: each participant either had a recorded death by day 28 or did not. The registry reports the outcome as counts of participants, not as a time-to-event estimate. The posted comparison is an unadjusted risk difference for ZMapp plus standard care relative to standard care alone. A risk difference expresses the contrast between the groups’ event risks in absolute terms. The registry also includes relative measures, but the central interpretation is the reported risk difference and its confidence interval.
What does the risk difference describe?
In general, a risk difference compares the proportion experiencing an event in one group with the proportion in another. A negative value in the stated comparison direction means the recorded event proportion is lower in the ZMapp group; a positive value would mean it is higher. The observed estimate is negative. This is a description of the trial’s recorded data, not a statement that the treatment caused the difference. Causal interpretation relies on the trial design and on assumptions about outcome ascertainment, missing data, adherence, and analysis populations.
The registry also reports group risks and relative measures, but they are not needed to understand the basic direction of the contrast. The counts and the risk-difference estimate describe different aspects of the same binary outcome: counts show the observed events and denominators, while the risk difference places the groups on an absolute scale. The denominators are the outcome entries listed in the record; the record does not explain the relationship of those entries to the overall enrollment figure.
How should the confidence interval be read?
In general, a confidence interval describes a range of estimates compatible with the observed data under a specified method and its assumptions. It conveys uncertainty about the underlying contrast; it is not a range containing a fixed proportion of individual participants’ outcomes. The reported interval for the risk difference crosses zero, the value corresponding to no absolute difference. Thus, it includes estimates favoring either group as well as the possibility of little or no difference. Its breadth indicates limited precision.
Confidence intervals are especially useful because a single estimate can conceal how much uncertainty is present. Two studies can produce similar point estimates but differ greatly in precision. Here, the interval is broad enough that the point estimate should not be interpreted in isolation. The registry record does not report the interval-construction method, so additional assumptions about that calculation should not be inferred.
What does the p-value contribute?
The posted p-value is unadjusted and equals 0.168. In general, a p-value assesses the compatibility of observed data with a null model, given the model’s assumptions. It is not the probability that a treatment is ineffective, nor is it a measure of clinical importance. The result does not meet a conventional threshold for statistical significance, but that does not establish equivalence or prove the absence of a difference. The confidence interval and the observed estimate should be considered together with the p-value.
The registry record does not report whether another, sponsor-designated analysis was used for the primary result. It lists no posted analyses. No covariate adjustment, stratification, or alternative analysis should be assumed from the registry information. The reported comparison is therefore best described as the posted unadjusted comparison.
Why can over-dispersion matter in other settings?
In general, over-dispersion occurs when observed variation is greater than a statistical model expects. It matters because standard errors can then be too small if the model assumes less variation than the data contain, which can make intervals look overly narrow and p-values overly favorable. This is a general statistical concept; the primary outcome is a binary participant count, and the registry record does not report an over-dispersion analysis or a model that would require one. It should not be presented as a finding from this trial.
What is not available about the analysis?
The registry record does not report a full statistical analysis plan, the original sample-size justification, interim analyses, a missing-data approach, or the analysis populations used. It also does not report adjustment for multiple outcomes or comparisons. These omissions matter because the chosen population, handling of incomplete observations, and multiplicity strategy can influence statistical interpretation. The presence of a posted unadjusted comparison does not fill in those missing methodological details.
The study was randomized and parallel-group, which describes how the comparison was organized. Randomization is intended, in general, to reduce systematic differences between groups at assignment. It does not guarantee identical groups, especially when the number of outcome observations is limited. The study was unmasked, so knowledge of group assignment could potentially affect co-interventions or assessment; the registry record does not quantify any such influence. These are considerations for interpretation, not evidence that bias occurred.
10. Confidence Intervals and Precision
The reported risk-difference confidence interval is wide and crosses zero. This means that the estimate is not precise enough to settle whether the underlying mortality difference favors ZMapp plus standard care, favors standard care alone, or is close to no difference. The observed point estimate is negative, but uncertainty around that estimate is substantial. A point estimate gives one summary of the observed contrast; the interval shows how much compatible variation remains under the analysis method.
In general, precision depends on the amount of information in the data, the number of observed events, and the variability of the outcome. Binary outcomes with relatively few events can yield uncertain estimates, particularly when groups are not large. This is a general explanation, not a new calculation about this trial. The registry provides group denominators and event counts, but it does not give a separate precision analysis or a reported confidence interval for each arm’s risk.
The unadjusted p-value of 0.168 is consistent with the uncertainty reflected in the interval. It should not be read as evidence that the groups are the same. Equivalence or non-inferiority conclusions would require an appropriate design, prespecified margins, and analyses; those are not reported in the registry record. Similarly, the confidence interval does not establish that either direction of effect is more probable.
The uncertainty also limits generalization. The registry record does not provide enough detail about the analysis population, incomplete outcomes, or participant characteristics to assess how those factors might influence precision or applicability. Readers should distinguish the recorded result from a precise estimate for other settings or populations.
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.
| Effect to detect | Participants per arm, 80% power | Participants per arm, 90% power |
|---|---|---|
| 100% of the observed effect | 146 | 195 |
| 75% of the observed effect | 270 | 361 |
| 50% of the observed effect | 627 | 838 |
The sample-size figures are planning illustrations based on the observed effect, not the trial’s original design justification. They are stated as participants per arm for 80% power and participants per arm for 90% power. The listed planning assumptions are a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation; the effect to detect is the stated fraction of the observed effect. The trial’s own original design assumptions are not reported in the registry record.
For planning at 100% of the observed effect, the figures are 146 participants per arm for 80% power and 195 participants per arm for 90% power. For planning at 75% of the observed effect, they are 270 participants per arm for 80% power and 361 participants per arm for 90% power. For planning at 50% of the observed effect, they are 627 participants per arm for 80% power and 838 participants per arm for 90% power.
In general, power is the chance that a study will detect an effect of a specified size if that effect is truly present, under the planning assumptions. The 80% and 90% columns show planning targets with different desired chances of detection; the higher target generally requires more participants for the same assumed effect. Smaller effects also need more participants to detect reliably, which is why the figures rise as the planned fraction of the observed effect becomes smaller. The curve represents this same planning relationship rather than additional trial outcome evidence.
These are not observed power. They do not describe what the completed trial achieved, and they should not be used to reinterpret its p-value. They are illustrations based on the observed effect and stated assumptions, not a substitute for the unreported original sample-size rationale.
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 z1−α/2 = 1.960) and the desired power (z1−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
- Control proportion p0 = 0.371; treatment proportion p1 = 0.222; average p̄ = 0.297.
- First term: z1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6461 = 1.2663.
- Second term: z1−β × √[p0(1−p0) + p1(1−p1)] = 0.842 × 0.6374 = 0.5365.
- n = (1.2663 + 0.5365)2 / (-0.1492)2 = 146.0, rounded up to 146 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 <- 0.371428571428571 # control proportion
p1 <- 0.222222222222222 # 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(2363322)
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 = 146 (80% power), 195 (90% power)
75% of observed effect: n per arm = 270 (80% power), 361 (90% power)
50% of observed effect: n per arm = 627 (80% power), 838 (90% power)
power.prop.test: 146
Simulated power at n = 146 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.
13. Multiplicity, Missing Data and Analysis Populations
The registry lists a primary mortality endpoint and two posted secondary outcomes: the number of participants with ZMapp infusion-related adverse events and plasma viral load. It also records three outcome measures overall. When a study examines several outcomes or comparisons, the chance of at least one apparently unusual result can increase if no adjustment or hierarchy is used. In general, multiplicity methods can control that issue, but the appropriate method depends on the trial’s prespecified objectives and analysis plan.
The registry record does not report a multiplicity adjustment, a hierarchy among outcomes, or a detailed analysis plan. It also lists zero posted analyses. Therefore, it is not possible to determine from the record whether multiplicity was addressed in a sponsor analysis or how secondary results should be treated inferentially. The posted primary comparison is unadjusted, and no claim about adjusted significance should be made.
Missing-data methods and analysis populations are also not reported in the registry record. The entries provide outcome denominators for the two arms, but do not state whether those denominators represent all randomized participants, participants with available endpoint data, or another analysis population. No imputation method, sensitivity analysis, or account of withdrawals is given. Consequently, the completeness of outcome ascertainment and the possible influence of missing outcomes cannot be assessed from the registry record.
In general, missing outcome data can affect both the estimate and its uncertainty, particularly if the chance of missingness is related to prognosis or assigned treatment. Different assumptions about unobserved outcomes can produce different conclusions. This is a general concern, not evidence that data were missing in this trial. The record does not report enough detail to establish whether missingness occurred or how it was handled.
These reporting gaps do not invalidate the posted counts, but they restrict the conclusions that can be drawn about how the analysis was planned and whether the displayed comparison was the prespecified primary analysis. The most defensible reading is to describe the posted unadjusted result and keep the unreported multiplicity, missing-data, and population details explicit.
14. Safety Results
The registry reports serious adverse events as affected participants divided by participants at risk.
| Arm | Participants with serious adverse events | Participants at risk | Percentage |
|---|---|---|---|
| A/Current Standard of Care Alone | 13 | 35 | 37.1% |
| B/Current Standard of Care Plus ZMapp | 11 | 36 | 30.6% |
Deaths
| Arm | Deaths (participants affected of at risk) |
|---|---|
| A/Current Standard of Care Alone | 13 of 35 |
| B/Current Standard of Care Plus ZMapp | 8 of 36 |
Other (non-serious) adverse events
Participants with at least one non-serious event at or above the registry's 0% reporting threshold.
| Arm | Participants affected of at risk |
|---|---|
| A/Current Standard of Care Alone | 0 of 35 |
| B/Current Standard of Care Plus ZMapp | 32 of 36 |
Most frequent serious adverse event terms
| Event term | Organ system | A/Current Standard of Care Alone | B/Current Standard of Care Plus ZMapp |
|---|---|---|---|
| Death due to EVD | Infections and infestations | 10 of 35 | 2 of 36 |
| Multi-organ failure due to EVD | Infections and infestations | 2 of 35 | 3 of 36 |
| Worsened renal insufficiency | Renal and urinary disorders | 1 of 35 | 0 of 36 |
| Syncope | Nervous system disorders | 1 of 35 | 0 of 36 |
| Death due to Hypotensive Shock | Vascular disorders | 1 of 35 | 0 of 36 |
| Head Injury | Nervous system disorders | 1 of 35 | 0 of 36 |
| Death due to sepsis | Infections and infestations | 0 of 35 | 1 of 36 |
| Generalized seizure | Nervous system disorders | 0 of 35 | 1 of 36 |
| Hypovolemic shock due to acute hemorrhage | Vascular disorders | 0 of 35 | 1 of 36 |
| Severe diarrhea | Gastrointestinal disorders | 0 of 35 | 1 of 36 |
Most frequent non-serious adverse event terms
| Event term | Organ system | A/Current Standard of Care Alone | B/Current Standard of Care Plus ZMapp |
|---|---|---|---|
| Elevation in Fever | Infections and infestations | n/a of 35 | 8 of 36 |
| Hypotension | Vascular disorders | n/a of 35 | 7 of 36 |
| Tachycardia | Vascular disorders | n/a of 35 | 4 of 36 |
| Tachypnea | Respiratory, thoracic and mediastinal disorders | n/a of 35 | 3 of 36 |
| Hypertension | Vascular disorders | n/a of 35 | 3 of 36 |
| Confusion | Nervous system disorders | n/a of 35 | 2 of 36 |
| Seizure | Nervous system disorders | n/a of 35 | 1 of 36 |
| Difficulty Breathing | Respiratory, thoracic and mediastinal disorders | n/a of 35 | 1 of 36 |
| Chills | Infections and infestations | n/a of 35 | 1 of 36 |
| Vomiting | Gastrointestinal disorders | n/a of 35 | 1 of 36 |
Serious events with the highest arm-level rate: death due to evd (28.6%), multi-organ failure due to evd (8.3%), worsened renal insufficiency (2.9%), syncope (2.9%), death due to hypotensive shock (2.9%).
The registry reports serious adverse events in both groups. In the current-standard-care-alone arm, 13 of 35 participants were recorded as having a serious adverse event, and 13 deaths were listed. In the ZMapp-plus-standard-care arm, 11 of 36 participants were recorded as having a serious adverse event, and 8 deaths were listed. The record also reports other adverse events for 0 of 35 participants in the standard-care-alone arm and 32 of 36 in the ZMapp arm. These are registry entries, not adjusted comparisons.
The listed serious-event terms include Death due to EVD at 28.6%, Multi-organ failure due to EVD at 8.3%, Worsened renal insufficiency at 2.9%, Syncope at 2.9%, Death due to Hypotensive Shock at 2.9%, and Head Injury at 2.9%. The record does not explain the denominator or coding rules for these term percentages, so they should be read as reported rather than reinterpreted as participant-level risks. Terms can also describe events associated with the underlying illness, not necessarily events caused by study treatment.
Serious adverse event counts and mortality counts overlap conceptually because death can be a serious event. They should not be added together. The registry record does not provide detailed causality assessments, event timing for all serious events, or a full adverse-event analysis plan. The figures describe recorded safety events and do not, on their own, establish attribution.
15. What the Result Does, and Does Not, Mean
The result describes day-28 mortality in a randomized comparison of optimized standard care alone with optimized standard care plus ZMapp. The observed counts were 13 of 35 and 8 of 36, respectively. The posted risk-difference estimate favors the ZMapp group in direction, but its confidence interval crosses no difference and the unadjusted p-value is 0.168. The evidence is therefore uncertain about the size and direction of the underlying group difference.
This result does not show that the groups are equivalent, and it does not prove that there is no effect. A failure to meet a conventional statistical-significance threshold is not a demonstration of no difference. Conversely, the lower observed death count in the ZMapp arm is not sufficient to establish that ZMapp caused lower mortality. The estimate is imprecise, and the registry record does not report important analytic details such as missing-data handling, analysis populations, or the original statistical plan.
The result applies to the recorded trial comparison and its stated endpoint. It does not by itself answer questions about longer-term outcomes, other populations, other treatment regimens, or care settings. The brief summary describes follow-up for up to 60 days, but the primary endpoint reported is mortality at day 28. The listed secondary outcomes and adverse-event entries offer additional information, but the registry provides limited detail on their analysis and interpretation.
The intervention was an investigational regimen of ZMapp added to optimized care, compared with optimized care alone. The trial was unmasked and conducted in a specific clinical context. Generalizing beyond that context requires evidence not contained in this comparison. Statistical uncertainty is only one limitation; incomplete reporting about outcome ascertainment, treatment exposure, and analysis procedures further constrains interpretation.
The appropriate statistical conclusion is narrow: the posted data show fewer recorded day-28 deaths in the ZMapp group, but the estimated difference is not precise enough to determine whether the underlying mortality difference is meaningfully in either direction. The registry result should be read as an uncertain estimate rather than a definitive verdict about treatment effect.
16. Why This Trial Matters Statistically
This trial illustrates why observed group counts and statistical uncertainty need to be read together. The recorded deaths were fewer in the ZMapp-plus-standard-care arm than in the standard-care-alone arm, yet the risk-difference interval crosses no difference and remains broad. The point estimate communicates the observed direction; the interval communicates that the data leave substantial uncertainty around that estimate.
The example also shows the limits of interpreting a p-value in isolation. The unadjusted p-value of 0.168 does not establish equality, and it does not quantify the probability that the treatment has no effect. Statistical significance, effect size, precision, and clinical importance are different concepts. In general, an estimate can be directionally notable but too uncertain to support a firm conclusion.
Trial context matters. Randomization provides a structured basis for comparing groups, but the registry record does not report all the details needed to assess allocation procedures, missing outcomes, analysis populations, or multiplicity. The unmasked design is also relevant to how outcomes and care may have been recorded, although the record does not show that this altered the result. Recognizing what is reported and what is absent is part of sound statistical interpretation.
The sample-size illustrations make a further general point: smaller effects require larger planned groups to detect with a specified power under stated assumptions. Those planning figures are not evidence about the completed trial’s observed power and do not repair uncertainty in the posted estimate. They help explain why the amount of information in a study matters, while also emphasizing that planning assumptions and observed results answer different questions.
For clinical researchers and biostatisticians, the trial is a useful case in separating description from inference. Counts describe what happened in the recorded groups; estimates quantify a contrast; confidence intervals describe precision; and design and reporting limitations shape how far those results can be interpreted.
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 registry record gives limited detail about how the primary outcome was ascertained, whether all randomized participants were included in the posted analysis, and how any incomplete outcomes were handled. It reports enrollment of 72 while the outcome entries list denominators of 35 and 36. The record does not explain this relationship, so those figures should not be reconciled by assumption.
The primary outcome description includes a timing detail for deaths among ZMapp recipients: seven of the eight recorded deaths occurred before day 4 and before the second of three planned infusions, with one participant receiving a second infusion on day 4 and dying later that day. The control-group description ends mid-sentence in the registry record. This prevents a complete comparison of the reported death timing from that description. The timing information also does not establish an exposure-adjusted effect or a causal explanation.
The registry identifies an unmasked trial but does not report whether outcome assessment was independently blinded, or whether allocation was concealed. It does not describe baseline characteristics in the registry record for this analysis, nor does it report covariate adjustment. The posted effect is unadjusted. These omissions make it difficult to evaluate the influence of chance baseline imbalance or ascertainment procedures.
Safety reporting is also limited. Serious-event counts and selected terms are listed, but the record does not provide detailed definitions, attribution methods, event timing for all terms, or the denominator underlying the term percentages. As a result, the listed events should not be interpreted as proof of treatment causation.
The registry record does not report the original sample-size rationale, interim analyses, a complete statistical analysis plan, multiplicity handling, or analysis populations. The trial’s completion status and posted results do not resolve these reporting gaps. These limitations constrain interpretation of both the primary comparison and the broader safety and secondary-outcome evidence.
18. Related Tutorials
19. Related Statistical Calculators
20. Sources
- ClinicalTrials.gov: Putative Investigational Therapeutics in the Treatment of Patients With Known Ebola Infection — NCT02363322.
- Registry record last updated 2019-06-05; status last verified 2018-06.
- Results first posted 2019-05-14.
- 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.
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21. Record Summary
NCT02363322, titled Putative Investigational Therapeutics in the Treatment of Patients With Known Ebola Infection, was a randomized, unmasked, parallel-group phase 1/phase 2 study sponsored by the National Institute of Allergy and Infectious Diseases (NIAID). The registry lists a start date of 2015-03-13, primary completion on 2017-12-31, and completed status. Enrollment is recorded as 72.
The study compared optimized standard care alone with optimized standard care plus ZMapp. The primary endpoint was mortality at day 28. Outcome entries list 13 deaths among 35 participants in the standard-care-alone group and 8 among 36 in the ZMapp group. The posted unadjusted comparison has a confidence interval that crosses no difference and a p-value of 0.168, leaving substantial uncertainty about the underlying difference.
Secondary outcomes listed include ZMapp infusion-related adverse events and plasma viral load. The record does not report the original sample-size justification, a full statistical analysis plan, missing-data methods, or analysis populations.