Efficacy and Safety of KAF156 in Combination With LUM-SDF in Adults and Children With Uncomplicated Plasmodium Falciparum Malaria: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Efficacy and Safety of KAF156 in Combination With LUM-SDF in Adults and Children With Uncomplicated Plasmodium Falciparum Malaria (NCT03167242), a randomized phase 2 study. The primary outcome is Part A and Part B: Number of Participants With Polymerase Chain Reaction (PCR)-Corrected Adequate Clinical and Parasitological Response (ACPR) at Day 29.

2. Clinical Question

The study aimed to identify an effective and tolerable dose using the shortest dosing regimen. The registry describes a need for antimalarial treatments with a new mechanism of action and for regimens shorter than 3 days or with reduced pill burden. Those aims explain the range of KAF156 and LUM-SDF doses and treatment durations; they do not, on their own, establish that any regimen is preferable.

The main contrast is between the reported response counts under each regimen and the reference cohort. The record also includes a Coartem arm and outcomes addressing recrudescence, reinfection and fever clearance. Because the study tested several dose and duration combinations, its results are best read as regimen-specific observations rather than as a single comparison of KAF156 with all other treatment. The posted comparisons are unadjusted recalculations, and the registry record does not report sponsor statistical analyses for these results.

3. Trial Design

This was a randomized, multicenter, parallel-group phase 2 interventional study. The registry status is completed, and enrollment is listed as 524. The study description calls it open label. The start date is 2017-08-02 and primary completion is listed as 2021-06-14.

The trial was organized into a PK run-in cohort and Parts A and B. Part A tested multiple KAF156 and LUM-SDF dose combinations and durations, as well as Coartem. Part B tested KAF 400 mg and LUM 960 mg once daily for 1, 2 or 3 days, alongside a Coartem arm. The registry describes oral administration; Coartem was given twice daily for 3 days. The KAF156 and LUM-SDF regimens were once daily for their stated treatment durations.

The reported primary endpoint results use the Per-protocol Set. That is the population specified for the endpoint, and it is not interchangeable with the overall enrollment figure. The registry record does not report the detailed criteria used to enter or remain in that set, or how its size relates to all randomized participants.

Although the trial was randomized, the posted comparisons use Part A Cohort 1 as their reference, including for comparisons involving Part B. Part B also had its own Coartem arm, but the comparison calculations displayed for it use the same Part A reference. The registry record does not report further details about the randomization procedure or the statistical handling of comparisons across parts. Those details matter when interpreting estimates as direct treatment contrasts.

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: Before being enrolled in the study, participants underwent a prescreening evaluation to ascertain the Plasmodium falciparum parasitemia count.

Only the first 6 of 12 groups are shown.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: All participants comprised in Per-protocol Set (PPS)

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.

Only the first 6 of 13 groups are shown.

6. Primary Endpoint

The registry lists the primary outcome as Part A and Part B: Number of Participants With Polymerase Chain Reaction (PCR)-Corrected Adequate Clinical and Parasitological Response (ACPR) at Day 29, measured over 28 days post first dose.

The primary endpoint is the number of participants with PCR-corrected adequate clinical and parasitological response (ACPR) at Day 29, described as 28 days after the first dose. The endpoint is based on absence of parasitaemia at the assessment, with PCR genotyping used to distinguish recrudescence from reinfection. A participant was counted as having PCR-corrected ACPR if they did not meet criteria for early treatment failure, late clinical failure or late parasitological failure and had no parasitaemia at Day 29. Parasitaemia after 7 days could be treated as reinfection under the stated PCR-based criteria.

This endpoint combines clinical and parasitological outcome criteria and addresses whether parasitaemia is present at the specified follow-up. PCR correction is used because recurrent parasitaemia can reflect either a return of the original infection or a new infection; the distinction affects how the response is classified. The registry notes that the Day 29 assessment was chosen in light of the short half-life of the study drugs.

ACPR is a binary participant outcome: each person either meets the endpoint definition or does not. The reported counts therefore describe participants meeting the definition within the stated analysis population, not the duration of response or an adjusted probability of response. The registry record does not report a time-to-event primary analysis.

7. Results Posted in the Registry

• Part A - Cohort 2: KAF 800 mg and LUM 960 mg QD for 1 Day: 93.8% (45/48) versus 92.0% (46/50) on control; risk difference 1.7 percentage points (95% CI -8.4 to 11.9), risk ratio 1.02 (0.91–1.14); unadjusted two-proportion z-test p = 0.737.
• Part A - Cohort 3: KAF 400 mg and LUM 960 mg QD for 2 Days: 97.9% (47/48) versus 92.0% (46/50) on control; risk difference 5.9 percentage points (95% CI -2.6 to 14.5), risk ratio 1.06 (0.97–1.17); unadjusted two-proportion z-test p = 0.183.
• Part A - Cohort 4: KAF 200 mg and LUM 480 mg QD for 3 Days: 100.0% (47/47) versus 92.0% (46/50) on control; risk difference 8.0 percentage points (95% CI 0.5 to 15.5), risk ratio 1.09 (1.00–1.18); unadjusted two-proportion z-test p = 0.048.
• Part A - Cohort 5: KAF 400 mg and LUM 480 mg QD for 3 Days: 100.0% (44/44) versus 92.0% (46/50) on control; risk difference 8.0 percentage points (95% CI 0.5 to 15.5), risk ratio 1.09 (1.00–1.18); unadjusted two-proportion z-test p = 0.055.

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.

Part A and Part B: Number of Participants With Recrudescence Events

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Part A - Cohort 2: KAF 800 mg and LUM 960 mg QD for 1 Day: 5.9% (3/51) versus 7.8% (4/51) on control; risk difference -2.0 percentage points (95% CI -11.8 to 7.8), risk ratio 0.75 (0.18–3.18); unadjusted two-proportion z-test p = 0.695.
  • Part A - Cohort 3: KAF 400 mg and LUM 960 mg QD for 2 Days: 2.0% (1/51) versus 7.8% (4/51) on control; risk difference -5.9 percentage points (95% CI -14.2 to 2.4), risk ratio 0.25 (0.03–2.16); unadjusted two-proportion z-test p = 0.169.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Part A - Cohort 2: KAF 800 mg and LUM 960 mg QD for 1 Day 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 Part A - Cohort 3: KAF 400 mg and LUM 960 mg QD for 2 Days and the control. The interval gives the range of effects that remain compatible with the data.

Part A and Part B: Number of Participants With Reinfection Events

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Part A - Cohort 2: KAF 800 mg and LUM 960 mg QD for 1 Day: 13.7% (7/51) versus 5.9% (3/51) on control; risk difference 7.8 percentage points (95% CI -3.6 to 19.3), risk ratio 2.33 (0.64–8.52); unadjusted two-proportion z-test p = 0.183.
  • Part A - Cohort 3: KAF 400 mg and LUM 960 mg QD for 2 Days: 7.8% (4/51) versus 5.9% (3/51) on control; risk difference 2.0 percentage points (95% CI -7.8 to 11.8), risk ratio 1.33 (0.31–5.66); unadjusted two-proportion z-test p = 0.695.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Part A - Cohort 2: KAF 800 mg and LUM 960 mg QD for 1 Day 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 Part A - Cohort 3: KAF 400 mg and LUM 960 mg QD for 2 Days and the control. The interval gives the range of effects that remain compatible with the data.

Part A and Part B: Fever Clearance Time (FCT)

• 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 errors.
• Result:
  • Part A - Cohort 4: KAF 200 mg and LUM 480 mg QD for 3 Days: mean 16.60 versus 18.70 on control; difference -2.10 (95% CI -11.22 to 7.02), standardized effect d = -0.16; z-test p = 0.652.
  • Part A - Cohort 5: KAF 400 mg and LUM 480 mg QD for 3 Days: mean 17.50 versus 18.70 on control; difference -1.20 (95% CI -9.18 to 6.78), standardized effect d = -0.11; z-test p = 0.768.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Part A - Cohort 4: KAF 200 mg and LUM 480 mg QD for 3 Days 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 Part A - Cohort 5: KAF 400 mg and LUM 480 mg QD for 3 Days and the control. The interval gives the range of effects that remain compatible with the data.

The secondary outcomes add information about recurrence and symptom clearance, but they do not replace the primary Day 29 endpoint. Recrudescence and reinfection are listed through 42 days after the first dose. Fever clearance time provides a measure of symptom resolution, while the registry also identifies parasite clearance, parasitaemia and pharmacokinetic outcomes among the secondary measures.

The posted recrudescence counts vary across regimens and between Parts A and B. For example, Part B Cohort 1 reports 12 participants with recrudescence, compared with 3 in its 3-day KAF regimen and 2 in the Part B Coartem arm. In Part A, the counts range from no reported events in the 400 mg/480 mg 3-day and Coartem cohorts to 4 in the reference cohort. Reinfection counts are also variable: Part B reports 11, 10 and 9 in the 1-day, 2-day and 3-day KAF cohorts, respectively, and 10 in its Coartem arm. These are descriptive counts, not adjusted comparisons.

Fever clearance time means and standard errors are posted for each cohort, with relatively small outcome-specific denominators. The reported means vary across groups, but the registry record does not report sponsor analyses for these comparisons. The observed mean differences therefore should not be treated as evidence of a reliable regimen effect on fever clearance.

These outcomes help characterize the trial beyond a single Day 29 assessment. Recrudescence and reinfection give different information from PCR-corrected ACPR, and fever clearance reflects a different clinical feature. A favorable pattern in one secondary measure would not automatically confirm the primary result, and a differing pattern does not by itself invalidate it. Secondary analyses generally carry less weight when many outcomes or contrasts are examined without a reported multiplicity plan. The registry record does not report such an adjustment, so these findings are most useful as descriptive context and for generating questions for further study.

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

• Part A and Part B: Number of Participants With Polymerase Chain Reaction (PCR)-Uncorrected Adequate Clinical and Parasitological Response (ACPR)
• Part A and Part B: Number of Participants With Polymerase Chain Reaction (PCR)-Corrected Adequate Clinical and Parasitological Response (ACPR)
• Part A and Part B: Number of Participants With Recrudescence Events
• Part A and Part B: Number of Participants With Reinfection Events
• Part A and Part B: Fever Clearance Time (FCT)
• PK Run-in, Part A and Part B: Parasite Clearance Time (PCT)
• PK Run-in, Part A and Part B: Number of Participants With Parasitaemia
• Part A and Part B: Area Under the Blood Concentration-time Curve Over the Last 24 Hours After Last Treatment Dose (AUC0-24h) of KAF156

9. Statistical Interpretation

10. Statistical Methods Explained

What does a risk difference describe?

General explanation: a risk difference subtracts the event proportion in a reference group from the event proportion in another group. For this endpoint, the event is meeting the PCR-corrected ACPR definition. A positive difference means the observed proportion meeting the definition is higher in the compared cohort; a negative difference means it is lower. It is an absolute contrast, not a relative increase or a measure of how many additional people would benefit in another population.

The posted risk differences are simple unadjusted recalculations from the reported counts and denominators. They are not adjusted for participant characteristics, trial part, or other factors. The registry record does not report an adjusted analysis to compare with them. Since there is no discrepancy flag, the recalculations are not marked as conflicting with a sponsor result; nonetheless, no sponsor inferential analysis is reported in the registry record.

What do risk ratios and odds ratios add?

General explanation: a risk ratio compares the event proportions as a ratio, while an odds ratio compares event odds. They express the same binary outcome on different scales, so their numeric values are not directly interchangeable. Both can be difficult to estimate precisely when group sizes are limited or when nearly all participants experience the event. The posted comparisons include risk ratios and, for many contrasts, odds ratios. They should be read with their confidence intervals rather than as stand-alone measures.

Why do confidence intervals matter?

General explanation: a confidence interval represents a range of values compatible with the observed data under the statistical method used. Wider intervals indicate less precision. For a risk difference, an interval spanning zero is compatible with no difference as well as with effects in either direction. An interval that does not span zero provides stronger evidence against a zero difference under that method, but it does not address bias, multiplicity, or whether the contrast was planned as confirmatory. The posted intervals are unadjusted recalculations.

What does an unadjusted p-value tell a reader?

General explanation: a p-value measures how unusual the data would be under a specified null model, subject to the assumptions of the test. It does not give the probability that a treatment is effective, the probability that the null hypothesis is true, or the size of a clinically important effect. The p-values in these comparisons are unadjusted. With multiple regimen contrasts and outcomes, isolated low p-values can occur by chance, and their interpretation depends on the prespecified analysis plan. The registry record does not report that plan or any multiplicity procedure.

Why is the analysis population important?

The primary endpoint population is the Per-protocol Set, not the overall enrollment. General explanation: a per-protocol analysis generally focuses on participants who meet protocol-defined requirements, but the exact membership rules must be known to understand possible selection effects. The registry record does not report detailed Per-protocol Set criteria or a missing-data method. Thus, the reported proportions describe the posted analysis population and cannot be assumed to represent every randomized participant.

The reference cohort is Part A Cohort 1. This matters because the calculated comparisons for Part B also use that reference, rather than the Part B Coartem arm. General explanation: a randomized design can support fair comparisons when allocation and analysis align with the intended contrast, but a contrast across study parts may also reflect differences in conduct, timing, or participant composition. The registry record does not give enough detail to assess these possibilities or to identify an adjustment for them.

11. Confidence Intervals and Precision

Precision is limited by the size of the individual cohorts and by the observed number of participants who did not meet the primary endpoint. For example, several groups have nearly all reported participants meeting the endpoint, while the Part B 1-day cohort has a lower count. When outcomes are very common, a small number of outcome differences can materially affect a risk difference or ratio. The confidence intervals communicate that uncertainty more fully than the point estimates alone.

The recalculated intervals are broad for many comparisons and include zero. That means the data are compatible with no risk difference as well as with differences in either direction, under the calculation used. The Part A 3-day 200 mg/480 mg comparison and the Part A 3-day 400 mg/480 mg comparison have intervals above zero; the Part B 1-day comparison has an interval below zero. These unadjusted intervals do not account for testing multiple regimens and outcomes, and they do not establish that the corresponding contrasts are confirmatory.

Precision also depends on the reference group and analysis population. The primary outcome is reported for the Per-protocol Set, while some secondary outcome denominators differ from the primary denominators. The registry record does not explain these differences in detail. For the Part B comparisons, the reference is a Part A cohort, which adds a design-context consideration beyond the width of a confidence interval.

General explanation: confidence intervals describe sampling uncertainty under a specified method; they do not capture every source of uncertainty. They cannot by themselves account for possible selection, missing outcomes, outcome classification issues, or analysis choices not reported in the registry. The posted precision estimates should therefore be considered together with the study design and the lack of reported sponsor analyses.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures for the displayed binary and continuous comparisons are participants per arm. In time-to-event planning, the stated convention is to report the total number of events; these comparisons are not presented as time-to-event calculations. The figures are planning illustrations based on the observed effect, not the trial's original design calculation.

The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The calculations consider detecting the full observed effect, 75% of the observed effect, or 50% of the observed effect. For each assumed effect, the 80% power column gives the participants per arm estimated to provide an 80% chance of detecting that effect under the assumptions if it is real. The 90% power column gives the corresponding estimate for a 90% chance.

Smaller effects require more participants because they are harder to distinguish from random variation. This is why the planning estimates rise as the assumed effect is reduced. When the observed effect is close to zero, the resulting estimates can become very large; such figures reflect the input effect and assumptions, not a recommended trial size or evidence that the present study had adequate or inadequate power. These are planning illustrations, not observed power. The registry record does not report the original sample-size justification or the assumptions used to design the trial.

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 = 0.920; treatment proportion p₁ = 0.938; average p̄ = 0.929.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.3638 = 0.7130.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.3636 = 0.3060.
4. n = (0.7130 + 0.3060)² / (0.0175)² = 3,390.7, rounded up to 3,391 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 <- 0.92                          # control proportion
p1 <- 0.9375                          # 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(3167242)
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 = 3,391 (80% power), 4,539 (90% power)
 75% of observed effect: n per arm = 6,200 (80% power), 8,299 (90% power)
 50% of observed effect: n per arm = 14,332 (80% power), 19,186 (90% power)
power.prop.test: 3390.7 
Simulated power at n = 3,391 per arm: 0.803 (20000 replicates)

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

14. Multiplicity, Missing Data and Analysis Populations

The study compares several KAF156 and LUM-SDF dose-duration regimens, includes Coartem arms, and lists multiple secondary outcomes. Each additional comparison creates another opportunity for a chance finding. The recalculated p-values are unadjusted, and the registry record does not report a multiplicity strategy, a hierarchy of hypotheses, or which contrasts were intended to be confirmatory. Accordingly, a nominally small p-value should not be interpreted in isolation as definitive evidence.

The registry record lists no reported statistical analyses for the outcomes discussed. It does not report the original analysis plan, the tests used by the sponsor, covariate adjustments, interim analyses, or a sample-size justification. These elements are not available in the registry record, so the unadjusted recalculations cannot be assumed to reproduce the sponsor's intended inferential approach.

The primary outcome is based on the Per-protocol Set. Although the endpoint definition is described, detailed inclusion and exclusion rules for that set are not reported. The posted data do not specify how participants with missing Day 29 assessments were handled, whether any outcomes were imputed, or whether sensitivity analyses were conducted. The relationship between enrollment, randomization, and the endpoint denominators is therefore not fully explained.

Missingness can affect a binary endpoint if the probability of an unavailable assessment is related to treatment or outcome. General explanation: complete-case results describe participants with usable observations, and their interpretation depends on how missing outcomes arose. Without the missing-data method and reasons for missingness, the direction and size of any effect on the reported estimates cannot be determined.

Finally, Part B comparisons are recalculated against the Part A Cohort 1 reference. The record does not explain how the study parts were incorporated into an analysis or whether any cross-part adjustment was planned. These gaps do not erase the descriptive counts, but they limit what can be concluded from the unadjusted contrasts.

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: blood alkaline phosphatase increased (5.9%), blood bilirubin increased (3.9%), anaemia (2.0%), plasmodium falciparum infection (2.0%), alanine aminotransferase increased (2.0%).

The registry reports serious adverse event counts by safety group. The counts include 0 of 12 in the PK run-in group; 1 of 51 for Part A KAF 800 mg and LUM 960 mg for 1 day; 2 of 54 for Part A KAF 200 mg and LUM 480 mg for 3 days; and 1 of 51 for Part A KAF 400 mg and LUM 480 mg for 3 days. For combined Part A and Part B groups, serious adverse events were reported in 7 of 103 for KAF 400 mg and LUM 960 mg for 1 day, 5 of 104 for the 2-day schedule, 2 of 97 for the 3-day schedule, and 3 of 51 for Coartem. Deaths are reported as 0 in each listed group.

These are counts, not evidence that an event was caused by a study drug. The combined safety groups and individual Part A groups have different definitions and denominators; they should not be added or treated as independent comparisons. The record also lists other adverse events and serious-event terms, but the counts above alone do not summarize their severity, timing or relationship to treatment. The registry record does not report a comparative statistical analysis of safety.

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

The primary results describe the number of participants in each Per-protocol Set cohort who met the registry's PCR-corrected ACPR definition at Day 29. The counts show that many participants met the endpoint in the posted cohorts. They also show variation across regimens and between Parts A and B. The estimates and intervals provide a way to describe those observed differences, but they do not establish that one regimen is better or worse.

This distinction matters because the trial included multiple dose and duration combinations, and the posted comparisons are unadjusted recalculations. Several confidence intervals include zero, while a small number do not. Without a reported multiplicity plan, sponsor analysis, and detailed information about comparisons across study parts, isolated inferential results should be treated cautiously. The results are not a substitute for a prespecified analysis or a larger confirmatory comparison.

The secondary findings offer additional descriptive context. Recurrence counts, fever clearance summaries and other listed measures address different aspects of outcome; they should not be collapsed into a single judgment about efficacy or safety. The safety counts also describe reported events rather than proving causation. No deaths are reported in the listed safety groups, but that observation does not establish the absence of risk.

General explanation: a trial result is most informative when its outcome definition, analysis population, comparison, uncertainty and analysis plan are understood together. The record gives the primary endpoint definition and reported cohort results, but several analysis details are not reported in the registry record. The results therefore support a careful account of what was observed, not medical advice or a treatment recommendation.

17. Why This Trial Matters Statistically

Statistically, the study illustrates the challenge of dose and duration selection when several regimens are evaluated in relatively small phase 2 cohorts. The primary outcome is common in many groups, so estimates can be sensitive to a small number of participants who do not meet the endpoint. Point estimates alone conceal that sensitivity; confidence intervals provide essential context.

The study also highlights the difference between descriptive evidence and confirmatory inference. Its posted comparisons are unadjusted recalculations, while the registry record does not report sponsor analyses, the original statistical plan, or a multiplicity procedure. With several regimens and secondary outcomes, a small unadjusted p-value is not sufficient on its own to establish a dependable difference.

Another important statistical feature is the reference group: Part B estimates are compared with a Part A cohort. This makes it important to distinguish the numerical contrast from the interpretation of a direct randomized comparison. The registry does not report enough detail to assess how cross-part comparisons were intended to be interpreted.

Finally, the primary endpoint uses a Per-protocol Set, and the registry does not describe all membership or missing-data rules. That distinction helps readers avoid treating outcome denominators as if they automatically represented every enrolled participant. Together, these features make the study useful for understanding how endpoint definition, analysis population, precision and multiplicity shape the interpretation of trial results.

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.

Several limitations are specific to the posted record. First, the primary result is reported for the Per-protocol Set, but the criteria defining that set are not fully described. The registry record also does not explain the difference between the endpoint denominators and the overall enrollment or state how missing Day 29 data were handled.

Second, the trial includes multiple cohorts, doses and treatment durations. The registry record does not report a multiplicity adjustment or a hierarchy that would identify a limited set of confirmatory comparisons. The unadjusted recalculations therefore require caution, particularly when interpreting isolated p-values.

Third, Part B comparisons use the Part A Cohort 1 reference. The record does not provide enough detail to determine how differences between study parts were handled analytically. The recalculated contrast may not capture all design or conduct differences between those parts.

Fourth, the primary result is a participant count at a specified assessment, and the posted endpoint data do not provide a complete account of missing outcomes or sensitivity analyses. The secondary outcomes also have outcome-specific denominators, and the record does not explain all denominator differences.

Finally, the registry does not report sponsor statistical analyses, the original sample-size justification, or the statistical plan. The planning illustrations use observed effects and stated assumptions rather than the trial's original design assumptions. These gaps limit reconstruction of the intended analysis and the strength of conclusions that can be drawn from recalculated comparisons.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Efficacy and Safety of KAF156 in Combination With LUM-SDF in Adults and Children With Uncomplicated Plasmodium Falciparum Malaria — NCT03167242.
• Registry record last updated 2022-02-10; status last verified 2021-12.
• Results first posted 2022-02-10.
• 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

NCT03167242 is a completed randomized phase 2 study of KAF156 with LUM-SDF in adults and children with uncomplicated Plasmodium falciparum malaria. It tested several doses and once-daily treatment durations, with Coartem arms included in Parts A and B.

The primary outcome was PCR-corrected ACPR at Day 29, assessed in the Per-protocol Set. Posted counts are high in several cohorts but vary across regimens and study parts. The recalculated comparisons are unadjusted and use Part A Cohort 1 as the reference. Secondary recurrence and fever-clearance outcomes and safety counts add descriptive context. The registry record does not report sponsor statistical analyses, a multiplicity plan, or detailed missing-data methods, so the findings are best interpreted as cohort-level results with uncertainty rather than as definitive comparative conclusions.