Randomized Trial of In-Home Cervical Cancer Screening in Underscreened Women: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Randomized Trial of In-Home Cervical Cancer Screening in Underscreened Women (NCT02005510), a randomized na study. The primary outcome is Number of Participants Diagnosed With Cervical Epithelial Neoplasia Grade 2 or Worse.

2. Clinical Question

The trial’s broader stated purpose was to determine whether mailing in-home HPV screening kits increased uptake of cervical cancer screening and early detection and treatment of cervical neoplasia. The primary outcome addresses a diagnosis, not screening uptake itself. Uptake and abnormal screening results are listed as secondary outcomes, so they describe related but distinct steps in the screening process.

The intervention was added to usual care rather than compared with no screening services. The contrast therefore concerns offering a mailed kit within the context of the usual-care services described in the registry record. The record does not report detailed eligibility criteria, participant characteristics, or how those services were delivered at each clinic.

3. Trial Design

The registry record describes a completed, randomized, single-masked, parallel-group trial sponsored by the University of Washington. The enrollment entry is 19851. The record lists the trial start as 2014-02 and primary completion as 2018-02. The phase entry is NA. The registry record does not identify which parties were masked.

One group received usual care plus a mailed in-home high-risk HPV testing kit; the comparator group received usual care. Usual care is described as including patient-, provider-, clinic- and systems-level services intended to promote adherence to Pap screening. The entry gives examples of reminders and outreach, but the descriptions of usual care are abbreviated in the registry record. More detail about how care was implemented is not reported in the registry record.

The primary outcome is a count of participants diagnosed with cervical epithelial neoplasia grade 2 or worse, assessed for up to 12 months post-randomization. The posted group counts are 12.0 in the in-home HPV screening group, with 9960.0 participants, and 8.0 in the usual-care group, with 9891.0 participants. These are the registry’s posted outcome counts and group sizes; the record does not provide a participant-flow account or explain the relationship between enrollment and the outcome denominators.

Secondary outcomes include completion of cervical cancer screening uptake and abnormal screening results, each assessed for up to 6 months post-randomization, as well as experiences and attitudes related to uptake and follow-up of positive in-home HPV results. The registry record lists six outcome measures, while detailed numerical results are posted for two secondary outcomes. Details of the randomization procedure, allocation concealment, the masking arrangements, and the analysis population are not reported in the registry record.

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.

Randomized (Round 1)

Rerandomized (Round 2)

Rerandomized (Round 3)

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: Baseline characteristics are not available for 117 participants in the intervention arm who opted out of electronic medical record review.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants Diagnosed With Cervical Epithelial Neoplasia Grade 2 or Worse, measured over Assessed for up to 12 months post-randomization.

The primary endpoint counts participants with a histologic diagnosis of cervical intraepithelial neoplasia grade 2 or worse. The record describes the endpoint as the number of participants diagnosed with cervical epithelial neoplasia grade 2 or worse and sets the assessment period at up to 12 months post-randomization. It is a binary event outcome at the participant level: a participant either had a qualifying diagnosis recorded during the assessment period or did not.

This endpoint captures a clinically defined diagnosis rather than the act of screening, the result of an initial screening test, or the completion of follow-up. That distinction matters for interpretation. A kit could affect whether screening is completed, whether an abnormal result is identified, and whether a qualifying diagnosis is ultimately recorded; those are related stages, not interchangeable outcomes. The registry lists screening uptake and abnormal screening results separately as secondary outcomes.

Using a histologic diagnosis provides an outcome definition based on tissue diagnosis, as described in the record. The endpoint’s interpretation nevertheless depends on how diagnoses were sought, confirmed, and recorded, and on the completeness of follow-up. Those operational details are not reported in the registry record. The listed assessment period also does not establish that every participant had the same duration of observation; the record says assessed for up to 12 months.

7. Results Posted in the Registry

• In-home HPV Screening: 0.1% (12/9960) versus 0.1% (8/9891) on control; risk difference 0.0 percentage points (95% CI -0.0 to 0.1), risk ratio 1.49 (0.61–3.64); unadjusted two-proportion z-test p = 0.379.

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.

Number of Participants That Completed Uptake of Cervical Cancer Screening

• 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:
  • In-home HPV Screening: 26.3% (2618/9960) versus 17.4% (1719/9891) on control; risk difference 8.9 percentage points (95% CI 7.8 to 10.0), risk ratio 1.51 (1.43–1.60); unadjusted two-proportion z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for In-home HPV Screening than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Number of Participants With an Abnormal Screening Result

• 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:
  • In-home HPV Screening: 2.3% (225/9960) versus 1.2% (114/9891) on control; risk difference 1.1 percentage points (95% CI 0.7 to 1.5), risk ratio 1.96 (1.57–2.45); unadjusted two-proportion z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for In-home HPV Screening than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The numerical secondary results describe two different stages of screening: completion of cervical cancer screening and receipt of an abnormal screening result. In both posted comparisons, the estimated event risk is higher in the in-home HPV screening group than in usual care. The registry also lists experiences and attitudes related to uptake and follow-up of positive in-home HPV results, but numerical results for those outcomes are not reported in the registry record.

These outcomes help place the primary diagnosis result in context, but they do not answer the same question. Screening uptake records completion of screening; an abnormal result is not the same as a histologic diagnosis of cervical intraepithelial neoplasia grade 2 or worse. The primary diagnosis counts are sparse and the primary risk-difference interval includes zero. The observed pattern across screening-related outcomes therefore should not be treated as proof of a difference in the primary diagnosis endpoint or as a substitute for it.

The secondary comparisons are unadjusted. When several outcomes are examined, the chance of seeing at least one apparently notable result can increase, even if no corresponding effect exists. A result with an unadjusted p-value should consequently be interpreted cautiously, especially when the registry record does not specify which outcomes were designated for formal hypothesis testing or how multiplicity was handled.

The posted results do not include reported analyses for the secondary outcomes, and the registry record does not describe a hierarchy, multiplicity adjustment, or confirmatory testing strategy. The associations are useful descriptive evidence about the recorded outcomes, but they carry less inferential weight than a prespecified, fully described analysis that accounts for the set of questions being tested. They should be read as related outcome signals, not as independent confirmation of the primary result.

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

• Number of Participants That Completed Uptake of Cervical Cancer Screening
• Number of Participants With an Abnormal Screening Result
• Experiences and Attitudes Associated With In-home HPV Testing Uptake
• Experiences and Attitudes Associated With Follow-up of Positive In-home HPV Testing Results

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is a binary participant-level event expressed as a count: the number of participants with a histologic diagnosis of cervical intraepithelial neoplasia grade 2 or worse. For such an outcome, a group risk is the proportion of participants in that group who experienced the event. The registry reports risks of 0.001 for in-home HPV screening and 0.001 for usual care. The risk difference is the intervention-group risk minus the comparator-group risk; the reported estimate is < 0.001.

What does the risk difference describe?

The risk difference expresses the absolute contrast on the risk scale. A positive estimate indicates a higher estimated risk in the in-home HPV screening group; a negative estimate would indicate a lower estimated risk. The estimate of < 0.001 is close to zero on this scale. Its confidence interval runs from -0.001 to 0.001, so the data do not narrowly pinpoint the absolute contrast. The interval includes zero, the value corresponding to no risk difference.

A risk difference is often useful when the question concerns the absolute change in event risk between groups. Its numerical size depends on the event’s underlying frequency. With few events, small changes in counts can materially affect the estimated contrast, and uncertainty can remain substantial even when group sizes are large. General statistical point: the amount of information about an outcome depends not only on the number of participants but also on how often the outcome occurs.

How should the ratio measures be understood?

The relative risk compares the event risk in one group with the event risk in the other. The posted relative-risk estimate is 1.49, with a confidence interval from 0.609 to 3.643. The odds ratio compares the odds of the event between groups; the posted estimate is 1.49, with a confidence interval from 0.609 to 3.647. For both ratio measures, the no-association value is one. Both intervals include that value and span estimates below and above it, so the ratio measures are also imprecise.

Risk differences and ratio measures answer related but different questions. A risk difference describes an absolute contrast; relative risk and odds ratio describe relative contrasts. The odds ratio is not generally identical to the relative risk, although the posted point estimates happen to be the same after rounding. The registry record does not report a model specification or adjusted estimates for the primary outcome. These values should therefore be understood as unadjusted summary comparisons rather than as evidence of a model-based adjustment.

What does the p-value add?

The unadjusted p-value for the primary comparison is 0.379. A p-value describes how unusual data at least as inconsistent with a specified null hypothesis would be under the assumptions of the statistical test, if that null hypothesis were true. It is not the probability that the null is true, nor a measure of the probability that the observed estimate will reproduce. The record does not report the test used, its assumptions, or a sponsor-reported analysis. The p-value should be read alongside the effect estimate and confidence interval, rather than as a stand-alone verdict.

General statistical explanation: confidence intervals display a range of values reasonably compatible with the data under the interval method’s assumptions. A wide interval signals limited precision; an interval containing the no-difference value does not prove no effect. The exact method used to calculate the posted intervals is not reported in the registry record.

Why does event frequency matter?

The primary outcome occurred infrequently in the posted results: the counts are 12.0 and 8.0. When an outcome is uncommon, information about the group contrast is driven by a relatively small number of observed events, even when the participant groups are large. Consequently, uncertainty around the contrast can be substantial. General statistical explanation: additional participants can improve precision, but the degree of improvement depends on the event frequency and on the size of the effect being estimated.

Over-dispersion is a concern in some count-data settings when variability exceeds what a chosen model expects. Here, the registry classifies the primary outcome as a binary participant count, not as a rate or repeated-event count, and does not report a count model. Over-dispersion diagnostics or a model designed to address it are not reported in the registry record; it would not be appropriate to assume that such a method was used.

The registry also does not describe missing-outcome handling, imputation, adherence-based analyses, or an intention-to-treat analysis. These details affect how a comparison is interpreted, especially when the outcome depends on screening, follow-up, or diagnosis recording. The posted estimates summarize the recorded group counts, while the underlying analysis procedures and the completeness of outcome ascertainment are not reported in the registry record.

11. Confidence Intervals and Precision

The primary risk-difference estimate is < 0.001, with a confidence interval from -0.001 to 0.001. The interval includes zero and permits estimates on either side of no difference. Its width indicates that the observed estimate does not locate the absolute group contrast precisely. The point estimate alone would hide this uncertainty; the interval is essential to understanding what the data can and cannot distinguish.

The reported relative risk is 1.49, with an interval from 0.609 to 3.643. The odds ratio is also 1.49, with an interval from 0.609 to 3.647. Each ratio interval includes the no-association value and allows a broad range of relative effects. The different scales give complementary descriptions, but neither ratio estimate is precise enough to settle the direction of the association.

General statistical explanation: a confidence interval is a procedure for quantifying uncertainty in an estimate. Under the method’s assumptions, intervals constructed repeatedly in comparable studies would cover the underlying quantity at the method’s stated rate. An interval is not a range containing a fixed proportion of individual participant outcomes, and it is not a probability statement about the particular fixed effect. The interval method used for the posted estimates is not reported in the registry record.

The small number of primary events is relevant to precision. Large participant group sizes do not automatically produce narrow intervals when the event itself is uncommon. A further limitation is that the record does not describe the completeness of follow-up or outcome ascertainment. If some diagnoses were not captured, the posted counts and their uncertainty would not by themselves describe that source of uncertainty.

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 estimates are illustrations based on the observed effect, not a reconstruction of the trial’s original design. The figures are participants per arm for 80% power and participants per arm for 90% power. The stated planning assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is specified as a stated fraction of the observed effect. These estimates are not observed power.

For each endpoint, the rows consider planning for 100%, 75%, and 50% of the observed effect. A row based on a smaller fraction represents a smaller effect to detect. Smaller effects require more participants to achieve the same planned power, so the corresponding participant requirements increase. The primary outcome’s planning figures are especially large relative to the secondary examples because the observed primary event contrast is small and the event is uncommon. These are illustrations under the listed assumptions, not predictions of what a future trial would observe.

The 80% power column describes the number of participants per arm that would be planned so that, under the stated assumptions and if the specified effect were real, the test would have an 80% chance of rejecting the null hypothesis. The 90% column describes the corresponding planning target for a 90% chance. Power is a design property for a specified effect, test, and assumptions; it does not describe the probability that the trial’s result is correct.

The registry record does not report the original trial’s sample-size justification, target effect, planned power, significance level, or other design assumptions. In particular, the illustration based on the observed effect should not be mistaken for the trial’s prospective calculation. For non-time-to-event outcomes, the displayed planning counts are participants per arm; the assumptions state that time-to-event displays, if present, give total events instead.

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 = 0.001; treatment proportion p₁ = 0.001; average p̄ = 0.001.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.0449 = 0.0879.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.0449 = 0.0377.
4. n = (0.0879 + 0.0377)² / (0.0004)² = 100,681.2, rounded up to 100,682 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 <- 0.000808816095440299                          # control proportion
p1 <- 0.00120481927710843                          # 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(2005510)
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 = 100,682 (80% power), 134,784 (90% power)
 75% of observed effect: n per arm = 170,199 (80% power), 227,847 (90% power)
 50% of observed effect: n per arm = 363,164 (80% power), 486,173 (90% power)
power.prop.test: 100681.2 
Simulated power at n = 100,682 per arm: 0.800 (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 registry record lists several outcomes, including the primary diagnosis endpoint, screening uptake, abnormal screening results, and experiences and attitudes associated with in-home testing and follow-up. It does not report a multiplicity plan, such as a hierarchy among outcomes or an adjustment to control the overall chance of false-positive findings. The secondary comparisons are unadjusted, so their p-values should be treated as exploratory rather than as a familywise-confirmatory set of tests.

The record lists no reported analyses for the secondary outcomes, and no primary analysis description is posted. The statistical test, any covariate adjustment, the model used, and the handling of departures from assumptions are not reported in the registry record. The registry does not identify a prespecified analysis population, such as an intention-to-treat population, nor does it describe per-protocol or other analysis sets. Randomized allocation is reported, but the analysis approach cannot be inferred from that design information alone.

Missing outcome data and participant flow are not described. The group sizes attached to the primary outcome are 9960.0 and 9891.0, while the registry’s overall enrollment entry is 19851. The record does not explain whether all randomized participants contributed to the primary outcome analysis, how missing diagnoses were handled, or whether the listed denominators reflect exclusions or incomplete follow-up. It also does not report imputation, sensitivity analyses, or outcome-ascertainment rates.

These omissions matter because missing outcome information can affect the estimated group contrast, and a complete-case comparison may not represent all randomized participants if missingness is related to outcome or group. General statistical explanation: multiplicity concerns arise because repeated tests create more opportunities for chance findings; missing-data concerns arise because the observed participants may not fully represent the intended analysis population. The registry record does not provide enough detail to evaluate either issue for this trial beyond noting that no adjustment or missing-data method is reported.

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 0% reporting threshold.

Most frequent non-serious adverse event terms

The registry reports zero serious adverse events among the 9960 participants at risk in the in-home HPV screening group and zero among the 9891 participants at risk in usual care. It lists zero deaths in each group. No serious adverse event terms are listed. These figures describe the safety entries in the registry record during the reported period; the record does not give further detail about the safety collection window or ascertainment procedures.

For other adverse events, the registry reports 5 affected participants in the in-home HPV screening group and 0 in usual care, with the same listed group sizes at risk. The record does not supply event descriptions for those other adverse events in the posted safety summary. These counts should not be conflated with serious adverse events, which were recorded as zero in both groups.

Zero reported serious events does not establish that no events occurred outside the collection or reporting process, and the registry record does not describe how completely adverse events were sought. The counts are descriptive and should be interpreted with the scope of the registry’s safety reporting in mind. They do not, on their own, establish comparative safety.

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

The primary posted comparison shows a small positive risk-difference estimate for cervical epithelial neoplasia grade 2 or worse, but the confidence interval includes zero and extends in both directions. The unadjusted p-value is 0.379. The available primary data therefore do not precisely determine whether the event risk differed between groups, nor do they establish that the groups had identical risks. The ratio estimates are similarly uncertain.

The result applies to the randomized comparison described in the record: usual care plus a mailed in-home high-risk HPV kit versus usual care. It does not compare the kit with an absence of screening support. The registry’s summary describes the population as underscreened women, but detailed eligibility and participant characteristics are not reported in the registry record. The result should not be generalized beyond the population and care setting represented by the trial without additional evidence.

The secondary results address screening completion and abnormal screening results, not the primary histologic diagnosis. Their pattern can inform understanding of the screening pathway, but it cannot be used to infer an effect on the primary outcome. The registry does not provide numerical results for the listed experiences and attitudes outcomes, nor does it report a multiplicity plan for the secondary comparisons.

Several details needed for a fuller assessment are not reported in the registry record: the original sample-size justification, a complete statistical analysis plan, the analysis population, participant flow, missing-data handling, and the precise procedures for outcome ascertainment. The posted estimates should therefore be read as evidence about recorded outcomes and their statistical uncertainty, rather than as a comprehensive account of all trial analyses or follow-up.

These results are not a recommendation about screening or treatment. They describe the outcomes posted for this trial and the precision with which the group contrast is estimated. The evidence for the primary endpoint remains uncertain, and the observed screening-related outcomes are distinct from a diagnosis of cervical neoplasia.

17. Why This Trial Matters Statistically

This trial illustrates why a large participant count does not guarantee a precise estimate for every endpoint. The primary outcome is uncommon in the posted results, with counts of 12.0 and 8.0, and the confidence interval for the risk difference spans zero. For a rare binary outcome, the number of events can be more informative about precision than the overall size of the randomized groups alone. The contrast must therefore be interpreted with its uncertainty rather than by looking only at group sizes or the point estimate.

It also illustrates the importance of separating stages in a clinical pathway. Screening uptake, abnormal screening results, and a histologic diagnosis are related outcomes but measure different events. A trial can show a different pattern for screening behavior than for a later clinical diagnosis, particularly when the outcome definitions and assessment periods differ. Treating these outcomes as interchangeable would obscure what was actually measured.

The planning illustrations make the effect-size issue visible: planning to detect a smaller effect requires more participants per arm under the stated assumptions. This is a forward-looking design concept, not a measure of the trial’s success or a retrospective assessment of its power. The original design assumptions are not reported in the registry record, so the illustrations cannot be taken as the actual basis for the trial’s enrollment.

Finally, the record demonstrates how incomplete reporting limits statistical appraisal. Without a reported analysis plan, analysis population, missing-data procedures, and multiplicity strategy, readers cannot fully assess how the estimates were produced or how robust they are to alternative choices. Transparent reporting of these details is essential for distinguishing the observed estimates from the broader claims that may be made about a trial.

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.

The registry record contains limited detail about who was eligible and the characteristics of participants. The title and summary describe underscreened women, but further demographic, clinical, and setting information is not reported in the registry record. This restricts assessment of how representative the enrolled population was and how directly results apply to other groups or service settings.

The descriptions of usual care are truncated. The entry mentions reminders, telephone outreach, and electronic medical record alerts, but does not fully specify which services were available, how consistently they were delivered, or whether use varied across participants. Because the intervention was added to usual care, variation in the comparator services could influence how the contrast should be understood.

The record does not report the randomization sequence method, allocation concealment, or which parties were masked under the single-masked designation. It also does not describe participant flow, missing diagnoses, the completeness of follow-up, or the procedures used to ascertain and confirm histologic outcomes. The assessment period is stated as up to 12 months, but the distribution of follow-up time is not reported.

Although several outcomes are listed, the record does not provide a full analysis plan, a multiplicity approach, or the analysis population. Detailed numerical results are posted for only two secondary outcomes; results for the listed experiences and attitudes outcomes are not reported in the registry record. These limitations do not change the posted estimates, but they constrain assessment of their completeness, prespecification, and generalizability.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Randomized Trial of In-Home Cervical Cancer Screening in Underscreened Women — NCT02005510.
• Registry record last updated 2020-09-16; status last verified 2020-08.
• Results first posted 2020-09-16.
• 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

The registry record describes a completed randomized, single-masked, parallel-group trial sponsored by the University of Washington, with enrollment of 19851. It compared usual care plus a mailed in-home high-risk HPV testing kit with usual care for underscreened women. The primary endpoint was the number of participants diagnosed with cervical epithelial neoplasia grade 2 or worse, assessed for up to 12 months post-randomization.

The posted primary counts were 12.0 in the in-home HPV screening group and 8.0 in usual care. The risk difference was < 0.001, with a confidence interval from -0.001 to 0.001 and an unadjusted p-value of 0.379. The interval includes zero, so the primary comparison is imprecise. Secondary results concern screening uptake and abnormal screening results, distinct outcomes from the primary diagnosis. The registry record does not report the original sample-size justification, a full analysis plan, missing-data handling, or a multiplicity strategy.