Study to Investigate the Clinical and Parasiticidal Activity and Pharmacokinetics of Different Doses of Artefenomel and Ferroquine in Patients With Uncomplicated Plasmodium Falciparum Malaria: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Study to Investigate the Clinical and Parasiticidal Activity and Pharmacokinetics of Different Doses of Artefenomel and Ferroquine in Patients With Uncomplicated Plasmodium Falciparum Malaria (NCT03660839), a randomized phase 2 study. The primary outcome is Percentage of Participants With Polymerase Chain Reaction (PCR)-Corrected Adequate Clinical and Parasitological Response (ACPR) at Day 28 (ACPR28).

2. Clinical Question

The comparison is about response after the assigned regimens in this trial population, not a direct test of every possible dose or treatment schedule. The registry describes a randomized, open-label, parallel-group study. Random allocation supports a comparison between assigned groups, while open-label conduct means participants and study staff were not masked to treatment assignment. Whether outcome assessors were masked is not reported in the registry record.

The primary question is framed around an exposure-response relationship, with response defined using PCR-corrected ACPR at Day 28. The posted primary results give the percentage meeting this response definition in each arm and comparisons with ferroquine alone. They do not provide the exposure-response model or an estimate of the relationship between area under the curve and response. That analysis is not reported in the registry record.

3. Trial Design

The registry identifies this as a randomized, open-label, parallel-group Phase 2a study. The study enrolled 140 participants. Its status is completed. The recorded start date is 2018-09-11 and the primary completion date is 2019-11-06. The sponsor is Sanofi.

Participants were assigned to ferroquine 400 mg alone or ferroquine 400 mg combined with artefenomel at one of three dose levels. Each regimen was given orally as a single dose on Day 0. For the combination regimens, the record describes ferroquine given in fasted condition followed by an artefenomel oral suspension. There was no masking. The allocation ratio and the method used to generate or conceal the random sequence are not reported in the registry record.

The study’s stated purpose was to investigate clinical and parasiticidal activity and pharmacokinetics. The primary objective was to evaluate artefenomel’s contribution to the combination’s clinical and parasiticidal effect through an exposure-response analysis using PCR-corrected Day 28 ACPR, with artefenomel area under the curve as the pharmacokinetic predictor. Secondary objectives included crude Day 28 ACPR, dose-response for selected outcomes, safety and tolerability, and pharmacokinetic characterization of artefenomel, ferroquine, and an active ferroquine metabolite.

The primary endpoint results are reported for a PK/PD efficacy population with stated eligibility requirements, rather than simply describing everyone enrolled. The arm-specific denominators for the posted primary result differ from the enrollment figure, and the registry record does not explain the flow from enrollment to the primary endpoint population. The original sample-size rationale, planned allocation, and detailed protocol are not reported in the registry record.

Randomization makes the assigned arms the basis for the treatment comparison. However, the open-label design may affect care, reporting, or assessment, depending on how outcomes were collected. The endpoint uses parasite testing and a defined response rule, but the record does not report whether laboratory assessments or endpoint adjudication were masked.

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: All eligible participants were randomized via a centralized randomization system using interactive response technology to 1 of the 4 arms in 1:1:1:1 ratio. Day 0 (drug administration day, per protocol) was considered as Day 1 for all analysis using Safety population as per Clinical Data Interchange Standards Consortium convention.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Pharmacokinetic/Pharmacodynamic (PK/PD) efficacy population: who received at least 1 dose of OZ439/FQ with parasitologically confirmed Plasmodium falciparum at baseline with data post-randomization, 1 evaluable PK blood sample (OZ439/FQ) post dose, adequate documentation of dosing \& sampling date, without any major protocol deviation related to drug administration (e.g. vomiting after drug intake). Here,"overall number of participants analyzed"=participants evaluable for this outcome measure.

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.

Population: Analysis was performed on all randomized participants.

6. Primary Endpoint

The registry lists the primary outcome as Percentage of Participants With Polymerase Chain Reaction (PCR)-Corrected Adequate Clinical and Parasitological Response (ACPR) at Day 28 (ACPR28), measured over Day 28.

The primary endpoint is the percentage of participants with PCR-corrected adequate clinical and parasitological response at Day 28. ACPR requires absence of parasitemia at Day 28 and excludes participants meeting specified definitions of early therapy failure, late clinical failure, or late parasitological failure. The criteria include parasite findings and, for some failure categories, temperature and clinical signs. PCR correction distinguishes recrudescence of the original infection from reinfection; participants classified as having reinfection are excluded from the PCR-corrected response calculation.

This endpoint combines clinical and parasitological information into a binary outcome: each participant either meets the response definition or does not. Reporting the percentage gives a group-level description of how often the defined response was observed. It is useful for comparing regimens at a specified follow-up point, while the confidence interval indicates how uncertain the estimated percentage is.

The endpoint is relevant to the trial’s stated aim of evaluating clinical and parasiticidal activity. The PCR correction is intended to separate recurrence of the original infection from a new infection, which matters when interpreting response after treatment. The definition is also important to the meaning of the result: response is not simply a negative parasite test on Day 28, because the protocol definition incorporates earlier failure criteria and rescue therapy conditions.

The primary analysis population required treatment exposure, confirmed infection, post-randomization data, an evaluable post-dose PK sample, and adequate dosing and sampling documentation. The registry record does not report how missing endpoint observations were handled or whether the endpoint definition was applied by blinded assessors.

7. Results Posted in the Registry

• Ferroquine 400 mg + Artefenomel 300 mg: 90.3% (28/31) versus 80.8% (21/26) on control; risk difference 9.6 percentage points (95% CI -8.8 to 27.9), risk ratio 1.12 (0.90–1.39); unadjusted two-proportion z-test p = 0.301.
• Ferroquine 400 mg + Artefenomel 600 mg: 90.9% (30/33) versus 80.8% (21/26) on control; risk difference 10.1 percentage points (95% CI -7.9 to 28.2), risk ratio 1.13 (0.91–1.40); unadjusted two-proportion z-test p = 0.259.
• Ferroquine 400 mg + Artefenomel 1000 mg: 87.1% (27/31) versus 80.8% (21/26) on control; risk difference 6.3 percentage points (95% CI -12.9 to 25.5), risk ratio 1.08 (0.86–1.36); unadjusted two-proportion z-test p = 0.514.

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.

Percentage of Participants With Crude Adequate Clinical and Parasitological Response at Day 28

• Endpoint type: Binary: the percentage of participants with the event (counts rebuilt from the posted percentages and group sizes).
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Ferroquine 400 mg + Artefenomel 300 mg: 81.8% (27/33) versus 64.5% (20/31) on control; risk difference 17.3 percentage points (95% CI -4.1 to 38.7), risk ratio 1.27 (0.93–1.72); unadjusted two-proportion z-test p = 0.117.
  • Ferroquine 400 mg + Artefenomel 600 mg: 77.8% (28/36) versus 64.5% (20/31) on control; risk difference 13.3 percentage points (95% CI -8.4 to 34.9), risk ratio 1.21 (0.88–1.65); unadjusted two-proportion z-test p = 0.230.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Ferroquine 400 mg + Artefenomel 300 mg and the control. The interval gives the range of effects that remain compatible with the data.
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Ferroquine 400 mg + Artefenomel 600 mg and the control. The interval gives the range of effects that remain compatible with the data.

Parasite Clearance Rate

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Ferroquine 400 mg + Artefenomel 300 mg: mean 0.36 versus 0.20 on control; difference 0.17 (95% CI 0.12 to 0.21), standardized effect d = 1.83; z-test p = <0.001.
  • Ferroquine 400 mg + Artefenomel 600 mg: mean 0.40 versus 0.20 on control; difference 0.20 (95% CI 0.15 to 0.26), standardized effect d = 1.94; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Ferroquine 400 mg + Artefenomel 300 mg than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Ferroquine 400 mg + Artefenomel 600 mg than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary results cover distinct aspects of response and parasite dynamics. The crude Day 28 ACPR percentages are directionally higher in the combination groups than with ferroquine alone, while the parasite clearance rate means are higher in the reported combination groups. These outcomes complement the primary PCR-corrected ACPR by describing a response definition without reinfection correction and a continuous measure of clearance. They address related but not identical questions.

The general direction of the crude response results is consistent with the primary percentages, but the secondary crude-response comparison intervals include zero. The reported parasite clearance rate comparisons have unadjusted p-values below 0.001 and positive mean-difference intervals. That pattern is evidence of a difference in the posted clearance-rate summaries under the unadjusted comparisons, but it does not prove a difference in the primary endpoint or establish the exposure-response relationship that motivated the primary objective. Different outcomes measure different features of treatment response, and one cannot be treated as a substitute for another.

The registry lists additional secondary outcomes, including parasite counts at several follow-up times, parasite reduction measures, clearance times, time to re-emergence, and time to recrudescence. Results for every listed outcome are not reported in the registry record. The available results therefore do not support a complete synthesis of all secondary endpoints or a judgment about whether their overall pattern is consistent.

Secondary findings generally carry less weight when there are many outcomes and comparisons, especially when the registry does not report a testing hierarchy or multiplicity correction. An unadjusted result can be useful for generating hypotheses, but it may overstate the strength of evidence if many comparisons were examined. These secondary results should be read as complementary and exploratory, alongside the primary estimate and its uncertainty, rather than as independent confirmation of efficacy.

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

• Percentage of Participants With Crude Adequate Clinical and Parasitological Response at Day 28
• Parasitemia: Change From Baseline in Number of Parasites Per Microliter of Blood at 6, 12, 18, 24, 30, 36, 48, 72, 96, 120, 144 and 168 Hours
• Observed Parasite Reduction Ratio (PRR) at 24 Hours, 48 Hours, and 72 Hours
• Time to 50% and 99% Parasite Reduction
• Parasite Clearance Time (PCT)
• Parasite Clearance Rate
• Time to Re-emergence
• Time to Recrudescence

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is binary: each eligible participant either met the PCR-corrected Day 28 ACPR definition or did not. The reported percentages estimate the proportion meeting that definition within each arm. A binary outcome is often summarized by a proportion, and arm comparisons can be expressed as a risk difference. The risk difference describes the contrast between the two proportions on the probability scale. It is not an adjusted estimate unless an adjustment procedure is explicitly reported; no such adjusted procedure is described for these comparisons.

What does a confidence interval describe?

In general, a confidence interval describes the statistical uncertainty around an estimate under the assumptions of the method used to calculate it. For an arm-specific percentage, the interval indicates a range of values compatible with the observed data and that calculation method. For a risk difference, an interval spanning zero includes no difference as one value compatible with the data. A wide interval indicates less precision than a narrow interval, although neither width nor inclusion of zero alone establishes whether a clinically important effect is present.

The registry posts arm-specific 95% confidence intervals for the primary percentages and comparison intervals for the risk differences. The comparison intervals span zero for each combination-versus-ferroquine contrast. This means the data are not sufficiently precise to rule out no difference using those intervals. The intervals also permit differences in either direction, so they do not establish equivalence or show that the regimens have the same effect.

How should the p-values be read?

The posted p-values for the primary risk-difference comparisons are unadjusted. In general, a p-value describes how incompatible the observed data are with a specified null hypothesis under the statistical model; it is not the probability that the null hypothesis is true, nor a measure of effect size. These values should be read alongside the point estimates and confidence intervals, not in isolation. Because no multiplicity adjustment is reported, the p-values do not account for the set of outcomes and comparisons that may have been examined.

The registry does not report the precise statistical tests, model specification, covariates, or handling of incomplete observations used for the primary comparisons. Therefore, the displayed comparison statistics should not be assumed to be adjusted for baseline characteristics, stratification factors, or other design features. The randomization process is reported, but details of the randomization method and any planned analysis procedures are not reported in the registry record.

What is different about the exposure-response objective?

The study’s stated primary objective involved relating artefenomel exposure, with area under the curve as the pharmacokinetic predictor, to PCR-corrected response. Such an analysis would ordinarily require a specified model and exposure data. Neither the exposure-response estimate nor the model is reported in the registry record. The arm-level dose comparisons are not an exposure-response analysis: assigned dose and measured exposure are related concepts but are not interchangeable. The posted results allow description of response percentages by assigned regimen, but not conclusions about the shape or strength of a relationship between measured exposure and response.

For the continuous secondary outcome, parasite clearance rate is reported as a mean with a standard deviation. In general, a mean describes the central average on the measurement scale, while a standard deviation describes the spread of individual observations around that average. The posted comparisons are mean differences with confidence intervals and unadjusted p-values. These summaries answer a different question from the binary response outcome and use a different scale. The registry does not report the detailed model or assumptions used for those comparisons.

Why does multiplicity matter?

When many outcomes, doses, or pairwise comparisons are considered, the chance of observing apparently notable results by chance can increase. Multiplicity methods can control error rates across a defined family of tests, but the chosen family and procedure need to be specified. They are not reported in the registry record. Consequently, the unadjusted secondary comparisons should be treated as exploratory, and even the primary comparisons should be interpreted in light of the study’s multiple objectives and outcomes rather than as isolated tests.

These methods explain how the posted summaries are usually interpreted; they do not fill gaps in the analysis record. The statistical analysis plan, prespecified testing hierarchy, missing-data methods, and treatment of protocol deviations are not reported in the registry record. Those omissions limit the ability to assess whether the posted comparisons follow a prespecified plan or how sensitive the findings might be to alternative analysis choices.

11. Confidence Intervals and Precision

The arm-specific primary response estimates have 95% confidence intervals: 62.1% to 91.5% for ferroquine 400 mg; 75.1% to 96.7% for ferroquine 400 mg plus artefenomel 300 mg; 76.4% to 96.9% for ferroquine 400 mg plus artefenomel 600 mg; and 71.1% to 94.9% for ferroquine 400 mg plus artefenomel 1000 mg. Each interval covers a range of plausible underlying response percentages under the method used to calculate it. The broad intervals show that the arm-level percentages are not estimated with high precision.

For the comparisons with ferroquine alone, every risk-difference interval includes zero. The interval for the 300 mg combination ranges from -0.088 to 0.279; for the 600 mg combination, from -0.079 to 0.282; and for the 1000 mg combination, from -0.129 to 0.255. These ranges include the possibility of no difference, as well as differences in either direction. Their width means the data leave substantial uncertainty about the size and direction of the contrast.

Confidence intervals do not show the probability that the true value lies within a particular interval, and overlap between arm-specific intervals is not itself a formal test of the difference. The comparison intervals are the more direct summaries for the between-arm contrasts. They do not establish equivalence: demonstrating equivalence requires a prespecified margin and an analysis designed for that question, neither of which is reported in the registry record.

Precision depends partly on how much information is available for each endpoint. The primary analysis population has smaller arm denominators than the overall enrollment figure, and the registry record does not explain exclusions or missing measurements. This contributes to uncertainty in interpreting the endpoint estimates, but the record does not provide enough information to attribute interval width to any single cause.

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, not a record of the trial’s original design calculation. For the binary outcomes, the listed figures are participants per arm. They assume a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation. The effect used for each illustration is the stated fraction of the observed effect. The original trial’s own sample-size assumptions and justification are not reported in the registry record.

The 80% power column describes a planning scenario in which a study using that many participants per arm would have an 80% probability of detecting the specified effect under the stated assumptions, if that effect were the true one. The 90% power column uses a higher target probability of detection under the same type of assumptions. These are prospective design calculations, not guarantees about what a future study will find.

The rows use the full observed effect, 75% of the observed effect, and 50% of the observed effect. The smaller the effect targeted for detection, the more participants are generally needed to distinguish it from random variation under otherwise similar assumptions. That is why the planning figures rise as the assumed fraction of the observed effect becomes smaller. The observed effect is estimated from a small trial sample and may not be a stable estimate for planning a future study.

These calculations are not observed power. Observed power would not provide a useful substitute for examining the estimates and their confidence intervals after the trial; the planning figures instead illustrate how design requirements depend on the chosen effect size and assumptions. The curve reflects this relationship between target effect and required sample size. It should be read as an illustration based on the stated assumptions, not as evidence that the trial was designed or powered according to those figures.

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 = 0.808; treatment proportion p₁ = 0.903; average p̄ = 0.855.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.4973 = 0.9747.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4927 = 0.4147.
4. n = (0.9747 + 0.4147)² / (0.0955)² = 211.5, rounded up to 212 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 <- 0.807692307692308                          # control proportion
p1 <- 0.903225806451613                          # 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(3660839)
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 = 212 (80% power), 283 (90% power)
 75% of observed effect: n per arm = 403 (80% power), 539 (90% power)
 50% of observed effect: n per arm = 963 (80% power), 1,288 (90% power)
power.prop.test: 211.5 
Simulated power at n = 212 per arm: 0.806 (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 study has a primary exposure-response objective and multiple secondary objectives and outcomes. The listed secondary outcomes cover response, parasite reduction, clearance, recurrence, safety, and pharmacokinetics. Considering multiple outcomes or making multiple comparisons creates a multiplicity issue: even when there is no underlying effect, some results may appear notable by chance. Statistical plans commonly address this by defining which tests are confirmatory, specifying a testing order, or adjusting inference across a family of comparisons.

The registry record does not report a multiplicity procedure, a prespecified testing hierarchy, or which secondary comparisons were intended to be confirmatory. The posted p-values are unadjusted. They should therefore not be interpreted as if they account for all outcomes, doses, and contrasts considered. This is particularly relevant when interpreting isolated secondary results; the parasite clearance rate comparisons, for example, are a different endpoint from the primary Day 28 response and do not resolve its uncertainty.

The registry does not report a complete statistical analysis plan, the analysis model for each endpoint, or the handling of missing observations. It also does not report whether participants were analyzed according to randomized assignment, how protocol deviations were handled, or whether sensitivity analyses were conducted. These details are important because different analytic choices can affect estimates and their precision.

The primary endpoint population is described using treatment, infection confirmation, post-randomization, pharmacokinetic sampling, and documentation requirements. The record does not provide a participant flow explaining how those requirements affected inclusion or how missing primary outcomes were treated. It also does not explain whether reinfections, rescue therapy, or other post-baseline events were handled consistently across groups beyond the endpoint definition itself.

Without these details, readers cannot verify the prespecified status of individual analyses, assess the impact of missing data, or determine whether results are robust to alternative assumptions. The posted results remain informative as reported estimates, but the missing analysis information limits the strength of confirmatory interpretation.

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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: malaria (2.8%).

The registry reports serious adverse events among participants at risk in each group. No serious adverse events are reported for ferroquine 400 mg alone, the 300 mg combination, or the 1000 mg combination. One participant is reported as affected in the 600 mg combination group. Malaria is listed as a serious adverse event term at 2.8%. No deaths are reported in any group.

Other adverse events are reported separately from serious adverse events. The number affected is 13 with ferroquine alone, 17 with the 300 mg combination, 17 with the 600 mg combination, and 22 with the 1000 mg combination. These counts are descriptive; they do not establish that a regimen caused an event or that groups differ in safety. The registry record does not provide event-level detail, severity distributions for these other events, exposure-adjusted rates, or statistical comparisons.

Safety counts should be interpreted in light of the numbers at risk and the duration and method of follow-up. They are not a complete comparative safety analysis, and the small group sizes limit the ability to characterize uncommon events. The record reports no deaths, but that does not demonstrate that serious or rare risks are absent.

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

The posted primary results describe PCR-corrected Day 28 response after ferroquine alone and ferroquine combined with different artefenomel doses. The combination arms have higher observed response percentages than the ferroquine-alone arm. However, the comparison intervals are wide and include zero, and the unadjusted p-values do not provide strong evidence of between-arm differences in this sample. The data therefore suggest a pattern in the observed percentages but leave substantial uncertainty about the size and direction of the underlying contrasts.

This does not establish that a combination is better, worse, or equivalent to ferroquine alone. A non-significant comparison is not proof that groups have the same response, while a numerical difference is not proof that the regimen caused that difference. Equivalence or non-inferiority would require a suitable design, prespecified margin, and corresponding analysis; these are not reported in the registry record.

The primary objective also concerned the relationship between measured artefenomel exposure and response. The posted arm percentages do not answer that question. The exposure-response analysis and its result are not reported in the registry record, so the results cannot establish whether a particular exposure level predicts response or how response changes across exposure.

The secondary outcomes add information about crude response and parasite clearance, but they do not remove uncertainty in the primary endpoint. Secondary comparisons are unadjusted, and the registry does not report multiplicity control or a testing hierarchy. The remaining listed secondary outcomes are not all accompanied by result summaries in the registry record.

These results apply to the study population, regimens, endpoint definitions, and follow-up reported in the record. The trial was open-label and involved a PK/PD efficacy population with specific analysis requirements. Generalizing beyond these conditions requires caution. The results are statistical descriptions of the posted data, not individual treatment guidance and not a guarantee of outcomes in other settings.

17. Why This Trial Matters Statistically

This study is statistically interesting because its main objective links pharmacokinetic exposure to a clinical and parasitological endpoint. Such questions require more than comparing assigned dose groups: they depend on measured drug exposure and a defined exposure-response analysis. The registry states that area under the curve was to serve as the predictor, but the exposure-response result is not reported. The gap between the stated objective and the available result highlights why a registry’s posted endpoint estimates may not fully answer the scientific question posed.

The study also illustrates the distinction between an observed difference and a precise estimate. The combination groups have higher posted primary response percentages, but their comparison intervals include zero and span a range of possible effects. Reporting the percentages alone could make the pattern seem more conclusive than the uncertainty permits. Reading estimates together with intervals and unadjusted p-values gives a more balanced account.

Using a PCR-corrected endpoint adds an important definitional layer. It distinguishes recrudescence from reinfection, while crude ACPR uses a different response measure. The comparison between these endpoints demonstrates that statistical conclusions depend on how the outcome is defined, not only on the treatment groups being compared.

Finally, the record includes multiple secondary outcomes and comparisons but does not report a multiplicity plan, detailed analysis methods, or complete results for all listed outcomes. This makes the study a useful example of why prespecification, transparent analysis reporting, and clear separation of confirmatory from exploratory findings matter. The information available supports careful description, while leaving important questions about the planned analyses unresolved.

18. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.
• Participant counts were reconstructed from posted percentages and arm sizes, so small rounding differences are possible.

Several limitations are specific to interpreting this trial’s posted results. The study was open-label, so participants and study staff were not masked to assigned regimen. The record does not state whether laboratory staff or outcome assessors were masked. Because response includes clinical and parasitological criteria, the absence of reported assessment procedures makes it difficult to judge how much open-label conduct could have influenced outcome ascertainment or other aspects of care.

The primary objective concerned exposure-response, yet the registry does not report the exposure-response model, its estimate, or its uncertainty. The dose-arm percentages therefore cannot stand in for the primary pharmacokinetic analysis. This leaves the stated central question only partly addressed by the posted results.

The primary endpoint analysis uses a defined PK/PD efficacy population rather than all enrolled participants. The record gives eligibility conditions but does not report a flow of participants into each analysis, reasons for exclusion, or handling of missing data. This limits assessment of whether the analyzed groups remained comparable after randomization.

The registry does not report the original sample-size rationale, detailed statistical analysis plan, multiplicity adjustment, or testing hierarchy. The posted primary comparisons have broad intervals, and secondary comparisons are unadjusted. Results for all listed secondary outcomes are not reported. Together, these omissions limit confirmatory interpretation and prevent a full assessment of the outcome pattern.

Finally, the study evaluates single-dose regimens in the described population. The registry record does not establish how the results generalize to other populations, dosing schedules, settings, or follow-up periods. The available summaries should be interpreted within the trial’s stated scope.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Study to Investigate the Clinical and Parasiticidal Activity and Pharmacokinetics of Different Doses of Artefenomel and Ferroquine in Patients With Uncomplicated Plasmodium Falciparum Malaria — NCT03660839.
• Registry record last updated 2022-03-21; status last verified 2022-03.
• Results first posted 2020-12-02.
• 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

NCT03660839 is a completed, randomized, open-label, parallel-group Phase 2a study sponsored by Sanofi. It enrolled 140 participants and compared a single oral dose of ferroquine 400 mg alone with ferroquine 400 mg combined with artefenomel 300 mg, 600 mg, or 1000 mg in African patients with uncomplicated Plasmodium falciparum malaria.

The primary endpoint was PCR-corrected ACPR at Day 28 in a defined PK/PD efficacy population. Posted response percentages were higher in the combination arms than in the ferroquine-alone arm, but the unadjusted risk-difference intervals include zero. The registry record does not report the exposure-response analysis central to the stated primary objective, a detailed analysis plan, missing-data handling, or multiplicity procedures.

Secondary results include crude Day 28 response and parasite clearance rate, while results for all listed secondary outcomes are not reported in the registry record. Safety summaries report no deaths and one participant with a serious adverse event in the 600 mg combination group. The posted findings are descriptive and leave uncertainty about the comparative primary effect.