Application of HBV Rapid Tests as a Tool for Wide-Use Screening: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Application of HBV Rapid Tests as a Tool for Wide-Use Screening (NCT01767597), a randomized na study. The primary outcome is Percentage of Patients Appropriately Seeking Care.

2. Clinical Question

The study title and summary frame the work as an evaluation of rapid tests as a screening tool for improving hepatitis B diagnosis, care and prevention. The posted primary outcome narrows that broad aim to appropriate care-seeking among participants identified as needing further medical intervention. It therefore combines two different care pathways: vaccination initiation for participants who are not immunized and specialist assessment for those who are infected. The registry record does not report separate primary results for those pathways.

3. Trial Design

The registry identifies this as a randomized, parallel-group trial with no masking. Participants at risk of hepatitis B infection were assigned to ELISA testing or rapid testing. In the ELISA group, infection status was determined by enzyme-linked immuno-assay. In the rapid-testing group, status was determined initially by a rapid test and then confirmed by ELISA. The design therefore compares a rapid initial screening approach with ELISA testing, while both groups have ELISA involved in the described testing process.

The registry lists enrollment as 1000. For the posted primary outcome, the result records 211 participants in the ELISA Testing group and 198 in the Rapid Testing group. Those outcome denominators are distinct from the safety denominators, which are 496 and 499, respectively. The registry record does not explain the difference among these counts, including how many participants were randomized, met the primary outcome eligibility definition, had outcome data available, or were included in each analysis population.

The primary outcome was assessed at 6 months. The outcome measure is the percentage of participants considered to have achieved appropriate care, among those who needed intervention. The registry lists one primary outcome measure and one reported analysis. The reported statistical method is Chi-squared. The study is marked completed, and the phase is listed as NA. The registry record does not report the trial's original sample-size assumptions, allocation ratio details beyond randomization, masking procedures, or a full statistical analysis plan.

The study summary describes the French context of hepatitis B screening and prevention, including concerns about awareness of infection status and access to care. The trial's comparison is practical: it asks whether introducing a rapid test as the initial test changes the proportion of eligible participants who take the specified next step in care. It does not compare rapid testing with no screening, and the posted outcome does not directly measure long-term liver outcomes or disease progression.

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: 2061 participants were initially screened for eligibility. Of them, 625 did not meet inclusion criteria and 436 declined to participate. In total, 1000 participants were randomized.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Only participants needing further medical intervention were included in analysis: non-immunized (HBsAg negative, anti-HBc antibody negative, anti-HBs antibody negative) or infected (HBsAg positive).

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: All participants completing their intervention.

6. Primary Endpoint

The registry lists the primary outcome as Percentage of Patients Appropriately Seeking Care, measured over 6 months.

The primary endpoint is the percentage of participants appropriately seeking care by 6 months. The analysis population is restricted to participants who needed further medical intervention: those classified as non-immunized or infected. The registry defines appropriate care differently for those groups. For non-immunized participants, it means initiating the hepatitis B vaccination sequence. For infected participants, it means seeking care at a specialized center so the severity of liver-related disease can be assessed.

The endpoint is used to assess whether the screening strategy is followed by an appropriate next step, rather than evaluating test performance alone. It combines prevention and linkage to specialist care in one measure. The registry describes the calculation as the number of non-immunized participants who initiated vaccination plus infected participants who sought care, divided by the number of non-immunized and infected participants, expressed as a percentage.

This outcome is meaningful as a care-process measure, but it is not a direct measure of the number of infections detected, the accuracy of either test, completion of vaccination, treatment received, or later health outcomes. Those outcomes are not presented as primary results in the registry record. Because the measure combines different care pathways, the overall percentage can also conceal differences between vaccination initiation and specialist attendance; separate results by pathway are not reported in the registry record.

7. Results Posted in the Registry

• Rapid Testing: 4.0% (8/198) versus 5.7% (12/211) on control; risk difference -1.6 percentage points (95% CI -5.8 to 2.5), risk ratio 0.71 (0.30–1.70); unadjusted two-proportion z-test p = 0.440.

8. Statistical Interpretation

9. Statistical Methods Explained

The primary outcome is binary at the participant level: each eligible participant either met the registry definition of appropriate care or did not. Results are then presented as percentages within the analyzed groups. This type of endpoint is common when the question concerns whether an event or action occurred during a defined follow-up period. Here, the action depends on the participant's status: vaccination initiation for a non-immunized participant, or attendance at a specialized center for an infected participant.

What does a risk difference describe?

In general, a risk difference subtracts the event proportion in one group from the event proportion in the other. It expresses the contrast on the same percentage scale as the outcome. The recalculated comparison is oriented as Rapid Testing relative to ELISA Testing. Its interval extends across no difference, so the summary estimates are compatible with a lower appropriate-care percentage in the rapid-testing group, no difference, or a higher percentage in that group. The exact recalculated estimate and interval bounds are not repeated in this explanation because the registry percentages and interval provide the main interpretive information.

A risk difference is an absolute measure. It is not the same as a risk ratio, which compares proportions multiplicatively, or an odds ratio, which compares odds. The registry record includes recalculated risk-ratio and odds-ratio summaries as well as the risk difference. Each measure uses a different scale, and none should be read as a count of participants. For clinical and service questions, an absolute difference is often directly interpretable, while relative measures can offer a complementary view. These measures remain estimates with uncertainty, not guaranteed effects.

What does the Chi-squared test assess?

The sponsor-reported analysis uses a Chi-squared test to compare the categorical outcome between the two groups. In general, this test evaluates whether the distribution of event and non-event observations differs across groups, under assumptions appropriate to the data. The registry reports a p-value of 0.5 for that analysis. The unadjusted recalculation reports a p-value of 0.44. A p-value is a measure of compatibility between observed data and a specified null model; it is not a measure of the probability that a treatment is effective, nor does it say how important a difference would be.

The posted statistical description does not give the full test specification, any continuity correction, or a detailed analysis plan. The registry also does not describe adjustments for covariates. The recalculated statistics are explicitly unadjusted summaries based on the posted group-level results. They should not be mistaken for estimates from a model that accounts for participant characteristics or the study's randomization process.

Why is an interval important?

In general, a confidence interval conveys the range of effect estimates that are reasonably compatible with the observed data under the method used. Its width reflects precision: a narrower interval indicates more precise estimation, while a wider interval indicates less precision. An interval that spans no difference does not rule out a meaningful effect in either direction. The confidence level and construction method for the posted comparison interval are not reported in the registry record, so the interval should be interpreted without assigning it an unreported confidence level.

The event counts are small relative to the group denominators, which contributes to uncertainty in a binary outcome comparison. In general, sparse event data can make estimates sensitive to individual observations and can affect the performance of methods based on large-sample approximations. The registry's reported Chi-squared result and the unadjusted recalculation offer a statistical comparison, but the available summary does not describe whether alternative methods for sparse data were considered. No additional analysis should be inferred from the reported results.

The analysis population also matters. The outcome does not apply to every participant indiscriminately: its denominator includes those designated as non-immunized or infected and thus in need of further intervention. The registry does not report a detailed flow of participants from randomization to eligibility, follow-up and analysis. Without that information, readers cannot establish how exclusions, unavailable outcomes or deviations were handled. This limits assessment of how fully the reported group comparison preserves the randomized allocation.

Finally, statistical significance and practical relevance are different questions. A p-value alone does not describe the magnitude of the observed difference, the range of plausible effects, or the implications for a screening pathway. Those questions require reading the group percentages and interval together with the endpoint definition, event counts, analysis population and limits of reporting.

10. Confidence Intervals and Precision

The primary outcome percentages are 5.7% in the ELISA Testing group and 4.0% in the Rapid Testing group. The recalculated risk-difference interval crosses no difference and includes possible contrasts in both directions. This indicates that the observed group percentages do not estimate the comparison precisely enough to exclude either a lower or higher appropriate-care percentage with rapid testing. The result is not evidence that the strategies are identical; it is an uncertain estimate.

Confidence intervals are useful because they show the range of estimates compatible with the observed data under a statistical method. In general, narrower intervals indicate greater precision, while wider intervals indicate less precision. Here, relatively few events contribute to the outcome comparison, and the interval is broad enough to include no difference. The interval's confidence level and construction method are not reported in the registry record, so a specific coverage interpretation should not be assigned.

The registry also provides a sponsor-reported Chi-squared p-value of 0.5 and an unadjusted recalculated p-value of 0.44. Neither p-value conveys precision in the way an interval does. A p-value cannot tell readers which effect sizes remain plausible, and a value that does not indicate a clear difference is not proof of equivalence. Interpretation should therefore focus on the observed percentages, the uncertainty interval and the limited event information, rather than treating either p-value as a verdict.

The primary outcome group sizes are 211 and 198, while the safety denominators are 496 and 499. Because the registry record does not explain this difference, the outcome precision should be understood in relation to the outcome analysis denominators, not the larger safety counts.

11. Planning a Similar Trial: Sample Size

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

The planning illustrations are expressed as participants per arm, not total events. They use two-sided significance level 0.05, equal allocation between the two arms and a normal approximation. The effect to detect is set at the observed effect or at a stated smaller share of it. The trial's own original sample-size assumptions are not reported in the registry record, so these figures should not be treated as the enrollment target or as evidence about the trial's intended power.

Planning for 100% of the observed effect gives 2,678 participants per arm for 80% power and 3,584 participants per arm for 90% power. Planning for 75% of the observed effect gives 4,952 participants per arm for 80% power and 6,628 participants per arm for 90% power. Planning for 50% of the observed effect gives 11,570 participants per arm for 80% power and 15,488 participants per arm for 90% power.

In plain language, 80% power means that, under the assumptions used for planning and if the specified effect were the true effect, the design would have an 80% chance of detecting a difference according to the chosen test and threshold. The 90% column expresses the same idea with a higher chance of detection under those assumptions. These are prospective planning illustrations based on the observed effect, not observed power. Smaller effects require more participants to detect reliably, which is why the illustrations increase as the assumed effect gets smaller.

The registry record does not report the original design assumptions behind enrollment, and the illustrations do not establish whether the completed study was adequately sized for its intended purpose. The observed outcome analysis includes 211 participants in the ELISA Testing group and 198 in the Rapid Testing group, but those figures do not change the assumptions used in the planning illustrations.

12. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.057; treatment proportion p₁ = 0.040; average p̄ = 0.049.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.3042 = 0.5962.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.3040 = 0.2558.
4. n = (0.5962 + 0.2558)² / (-0.0165)² = 2,677.2, rounded up to 2,678 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 <- 0.0568720379146919                          # control proportion
p1 <- 0.0404040404040404                          # 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(1767597)
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 = 2,678 (80% power), 3,584 (90% power)
 75% of observed effect: n per arm = 4,952 (80% power), 6,628 (90% power)
 50% of observed effect: n per arm = 11,570 (80% power), 15,488 (90% power)
power.prop.test: 2677.2 
Simulated power at n = 2,678 per arm: 0.802 (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. Analyses Reported by the Sponsor

The registry's own reported comparison is a Chi-squared analysis with p=0.5. A separate unadjusted recalculation from the posted summary statistics gives p=0.44 and also supplies an interval for the risk difference. These are distinct results: the sponsor-reported analysis is the trial's posted analysis, while the recalculation is a simple comparison derived from the group summaries and should not be presented as the sponsor's analysis.

The p-values are close in interpretation: neither indicates strong evidence of a group difference. They should not be treated as interchangeable, and the recalculated result does not replace the registry-reported result. The registry record does not give enough detail to determine why the p-values differ, including whether the test implementations or analysis details were identical. No claim about an error or substantive conflict follows from the difference alone.

The group percentages remain the posted primary outcome results: 5.7% for ELISA Testing and 4.0% for Rapid Testing. Both the sponsor's analysis and the recalculation should be considered alongside the limited number of recorded events and the uncertainty in the risk-difference interval. Neither p-value establishes equivalence or identifies which screening strategy should be used.

14. Multiplicity, Missing Data and Analysis Populations

The registry lists one primary outcome measure and one reported analysis. It lists no posted secondary outcomes. This limits the visible multiplicity concern in the record, but it does not establish that no additional outcomes, subgroup analyses or interim looks were planned or conducted. Such details are not reported in the registry record. No multiplicity adjustment is described, and the registry record does not report a statistical analysis plan specifying how multiple tests would be handled.

Missing-data handling is also not reported in the registry record. The primary outcome denominators are 211 for ELISA Testing and 198 for Rapid Testing, while the safety denominators are 496 and 499. The record does not explain how the primary outcome analysis population was assembled from the randomized participants, whether all eligible participants had six-month outcome ascertainment, or how unavailable outcomes were treated. It would therefore be inappropriate to assume that missing observations were absent, excluded, imputed, or counted as failures.

The endpoint population is defined by need for further medical intervention: non-immunized participants or participants with infection. This definition makes the outcome conditional on that classification. The registry does not report a full participant flow, separate counts for these clinical categories, or whether eligibility was determined before or after assignment. Those omissions make it difficult to evaluate how the analyzed population relates to the randomized population and whether the group comparison retains the protection intended by randomization.

The record also does not report whether the analysis followed an intention-to-treat principle, whether any per-protocol analysis was performed, or how protocol deviations were addressed. An analysis restricted to participants with outcome data may differ from an analysis of everyone randomized, particularly if outcome availability is related to group assignment or care-seeking. The available summary is not enough to assess that possibility.

These omissions do not invalidate the posted result, but they constrain how broadly it can be interpreted. The clearest description is that the registry reports outcome percentages among the groups included in the primary analysis, using the stated eligibility definition. Further details about missingness, analysis populations, interim analyses and multiplicity are not reported in the registry record.

15. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

The registry reports no serious adverse events and no other adverse events in the safety groups listed. The serious-event and other-event denominators are 496 for ELISA Testing and 499 for Rapid Testing. These are safety denominators and should not be confused with the primary outcome analysis groups of 211 and 198 participants.

Zero reported events means that no events were recorded in the listed categories and denominators in the registry results. It does not establish that the risk of an event is zero, and it does not by itself establish that the two strategies have identical safety profiles. The record does not provide event-specific terms because no serious adverse event terms are listed. Death counts are not reported in the registry record.

Safety interpretation also depends on how events were defined, collected and followed. Those details, including definitions, observation periods and assessment procedures, are not reported in the registry record. The figures should therefore be read as a description of the events posted for these groups, not as a complete safety evaluation or a basis for comparing uncommon risks.

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

The primary result describes the proportion of eligible participants who met the registry's definition of appropriate care within 6 months. The observed percentages are 5.7% for ELISA Testing and 4.0% for Rapid Testing. The recalculated comparison is uncertain, with its interval spanning no difference and possible effects in either direction. The registry's Chi-squared analysis reports p=0.5, while the unadjusted recalculation reports p=0.44. Together, these results do not provide clear statistical evidence that one strategy led to a different percentage of appropriate care in the analyzed groups.

This does not establish that the strategies are equivalent. A nonsignificant comparison can reflect a small or absent difference, but it can also reflect limited information and imprecision. The registry record does not report an equivalence or non-inferiority framework, including a prespecified margin. The result should not be translated into a claim that rapid testing improves or worsens care-seeking, or that either approach is preferable.

The endpoint has a specific scope. It measures vaccination initiation among non-immunized participants and specialist attendance among infected participants. It does not report test sensitivity or specificity, the number of infections newly diagnosed, vaccine-series completion, clinical management after specialist attendance, or longer-term health outcomes. No separate outcome percentages for the vaccination and infected-participant pathways are reported in the registry record.

The results also apply to the primary outcome analysis population as defined in the record, not automatically to all enrolled participants. The record lists enrollment as 1000 but reports smaller primary outcome denominators. It does not explain the relationship between those numbers. Without a participant flow or missing-data description, the completeness and representativeness of the analyzed outcome cannot be fully assessed.

In general, trial results are most informative when the outcome definition, analysis population, effect estimate and uncertainty are considered together. In this trial, the outcome addresses a relevant step between screening and subsequent care, but the available summary gives limited precision and leaves important details about analysis and follow-up unreported. The appropriate conclusion is a description of the observed percentages and their uncertainty, not a recommendation about testing or care.

17. Why This Trial Matters Statistically

This trial illustrates why screening research needs outcomes beyond whether a test produces a result. A screening strategy can matter because of what happens next: whether people who need intervention begin vaccination or reach specialist care. The primary endpoint therefore links a testing approach to a care pathway. That connection is statistically important because a test may only influence health through subsequent actions, yet those actions can involve different processes and barriers.

The combined endpoint is also a useful reminder that a single percentage can bring together distinct clinical groups and events. Here, vaccination initiation and specialist attendance are counted as appropriate care for different participants. Without separate results, the overall comparison cannot show whether the two pathways behaved similarly or whether one contributed more to the observed percentage.

The posted comparison further demonstrates the difference between a point estimate and its precision. The group percentages differ, but the interval for the recalculated risk difference includes no difference and values in either direction. A p-value by itself cannot resolve that uncertainty. Reading the estimated contrast with the interval, event counts and endpoint definition gives a more complete statistical interpretation than relying on a threshold alone.

Finally, the gap between enrollment, primary-outcome denominators and safety denominators highlights the importance of participant-flow reporting. Randomization is central to a fair group comparison, but readers need to know who was eligible for each analysis and how missing outcomes were handled. The registry record does not provide those details, so the trial is informative about the structure of the question while leaving limits on how fully its result can be evaluated.

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.

The primary outcome combines two different care actions: beginning vaccination and seeking specialist care. The registry does not provide separate results for non-immunized and infected participants. As a result, the overall percentage cannot show whether any group contrast arose predominantly from one pathway, nor whether the pathways differed in how care was measured or achieved.

The record lists enrollment as 1000, but the primary outcome results include 211 participants in ELISA Testing and 198 in Rapid Testing. Safety denominators are larger, at 496 and 499. The registry does not explain these different analysis counts or provide a participant flow. It also does not report how missing outcomes or exclusions were handled. These omissions limit assessment of the completeness of the primary outcome comparison and its relationship to random assignment.

Detailed methods are limited. The record does not report the randomization sequence or concealment, the original sample-size calculation, the confidence level and method for the posted interval, or a complete statistical analysis plan. It does not state whether covariate adjustment, interim analyses or additional exploratory analyses were conducted. No secondary outcomes are posted, but that does not answer whether other analyses were planned.

The endpoint is a care-process measure at 6 months, not a direct measure of screening accuracy or long-term health outcomes. The registry does not report test-performance results, separate pathway results, or whether initiated vaccination was completed. Although the rapid-testing group used ELISA confirmation, further details of test administration and follow-up are not reported in the registry record. These limitations do not determine the direction of the results, but they narrow the questions that the posted statistics can answer.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Application of HBV Rapid Tests as a Tool for Wide-Use Screening — NCT01767597.
• Registry record last updated 2016-12-13; status last verified 2016-10.
• Results first posted 2016-12-13.
• 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

NCT01767597, titled “Application of HBV Rapid Tests as a Tool for Wide-Use Screening,” is listed as a completed, randomized, unmasked, parallel-group study with enrollment of 1000. It compares ELISA testing with an approach using an initial rapid test followed by ELISA confirmation. The primary outcome is the percentage of participants requiring further intervention who appropriately sought care by 6 months.

The posted primary outcome percentages are 5.7% for ELISA Testing and 4.0% for Rapid Testing. The registry reports a Chi-squared p-value of 0.5; the unadjusted recalculation reports p=0.44, with an interval spanning no difference. The record lists no secondary outcomes and reports zero serious and other adverse events in the safety denominators, while deaths are not reported in the registry record.

Interpretation is limited by uncertainty in the comparison and by unreported details about participant flow, missing data, analysis populations and original design assumptions. The result describes appropriate care-seeking in the analyzed groups; it does not establish equivalence, test accuracy, or a difference in longer-term health outcomes.