Engaging and Activating Cancer Survivors in Genetic Services Study: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Engaging and Activating Cancer Survivors in Genetic Services Study (NCT04455698), a randomized na study. The primary outcome is Number of Participants Who Received Genetic Services.

2. Clinical Question

3. Trial Design

This was a randomized, parallel-group study with no masking recorded. The registry lists the phase as NA and the status as completed. The study began on 2021-08-16, and the primary completion date is 2025-03-05. The sponsor is the University of Chicago.

The registry describes three approaches: remote telegenetic counseling by telephone, remote telegenetic counseling by videoconferencing, and usual care. The remote services included pre-test and disclosure counseling with a genetic counselor. Usual care involved referrals to genetic counseling providers, with participants initiating services themselves. The usual-care description also says that participants who had not sought and received counseling within six months would be offered randomization to one of the remote approaches.

The primary outcome was assessed at six months for the three arms. The posted primary results identify the video group as ARM A, the phone group as ARM B, and usual care as ARM C. However, the narrative arm descriptions assign the phone and video modalities to the opposite A/B labels. This inconsistency makes the modality names more dependable than the letter labels when reading the results.

The registry does not report the method used to generate or conceal random assignments, detailed eligibility criteria, or the original rationale for the planned enrollment. Those aspects of trial conduct and design cannot be evaluated from 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.

Before assignment: 511 participants were consented and enrolled.

Completed Baseline (T0) and Randomized

T1 Survey Following Pre-test Counseling

T2 Survey Post Genetic Testing

T3 Survey 6 Months Post Genetic Testing

Analysis population for the primary outcome, as defined in the registry: The number of participants who received genetic services

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.

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants Who Received Genetic Services, measured over Assessed at 6 Months for ARMS A/B/C.

The primary endpoint counts participants who received genetic services, assessed at six months. It is described as a composite outcome collected through remote-services records and recorded as yes or no. The registry defines the population-level measure as the number of participants who received genetic services, but it does not specify the component services or operational rules used to classify receipt.

This endpoint addresses the study’s stated objective: evaluating remote delivery as a way to increase uptake of recommended genetic assessment and testing among childhood cancer survivors. A service-uptake measure is relevant to that access question because it captures whether participants reached genetic services during the follow-up period. It is not a measure of a cancer outcome, a genetic test result, or a change in health status.

Because the outcome is binary for each participant, the posted counts can be compared as group proportions, and the registry reports risk differences, risk ratios, and odds ratios for the remote approaches versus usual care. These summaries describe service receipt in the study groups. The registry record does not report further detail about the timing of service receipt within the six-month period or how missing service records were handled.

7. Results Posted in the Registry

• Remote Telehealth Service: Video (ARM A): 44.1% (83/188) versus 14.7% (19/129) on control; risk difference 29.4 percentage points (95% CI 20.1 to 38.8), risk ratio 3.00 (1.92–4.68); unadjusted two-proportion z-test p = <0.001.
• Remote Telehealth Service: Phone (ARM B): 47.5% (94/198) versus 14.7% (19/129) on control; risk difference 32.7 percentage points (95% CI 23.5 to 42.0), risk ratio 3.22 (2.08–5.01); unadjusted two-proportion z-test p = <0.001.

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.

Patient Reported Outcomes Measurement Information Systems (PROMIS) Anxiety

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Remote Telehealth Service: Phone (ARM B): mean -1.77 versus -2.00 on control; difference 0.23 (95% CI -1.02 to 1.48), standardized effect d = 0.09; z-test p = 0.719.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Remote Telehealth Service: Phone (ARM B) and the control. The interval gives the range of effects that remain compatible with the data.

Multi-dimensional Impact of Cancer Risk Assessment Questionnaire (MICRA) Uncertainty

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Remote Telehealth Service: Phone (ARM B): mean 4.97 versus 2.06 on control; difference 2.91 (95% CI 0.57 to 5.25), standardized effect d = 0.63; z-test p = 0.015.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Remote Telehealth Service: Phone (ARM B) than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Change in Health Behaviors: Change in Number of Wine/Beer/Mixed Drinks Per Day Among Those With Genetic Testing

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Remote Telehealth Service: Phone (ARM B): mean -0.04 versus 0.00 on control; difference -0.04 (95% CI -0.68 to 0.60), standardized effect d = -0.03; z-test p = 0.902.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Remote Telehealth Service: Phone (ARM B) and the control. The interval gives the range of effects that remain compatible with the data.

The registered secondary outcomes cover several domains: uptake of genetic counseling and testing, anxiety, uncertainty related to cancer risk assessment, and health behaviors. The listed behavior measures include alcohol consumption, exercise, and screening procedures. This range provides context around the primary service-uptake question, but the secondary measures address different questions and should not be treated as direct substitutes for the primary endpoint.

Numerical summaries are posted for anxiety, MICRA uncertainty, and change in drinks per day among participants with genetic testing. The comparisons for these outcomes are between phone and video, rather than between either remote approach and usual care. The reported anxiety and drinks-per-day intervals include zero, whereas the MICRA uncertainty interval is above zero. The registry lists eight secondary outcomes, but detailed numerical comparisons for every listed outcome are not present in the record. Reported analyses are not listed for the posted secondary summaries.

The primary result concerns whether genetic services were received by six months. Secondary scores and behavior changes can help describe other aspects of participants’ experience, but they do not explain the primary difference or establish a pathway connecting service receipt to later outcomes. The secondary comparisons also involve different measures, subsets, and time descriptions, so their results should not be combined into a single overall judgment.

Unadjusted secondary results carry less weight because multiple outcomes and comparisons create more opportunities for apparently notable results to occur by chance. The registry record does not report a multiplicity procedure or a prespecified hierarchy for interpreting secondary outcomes. The secondary findings are therefore best treated as exploratory descriptions rather than definitive evidence across all measured domains.

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

• Uptake of Genetic Counseling and Testing
• Patient Reported Outcomes Measurement Information Systems (PROMIS) Anxiety
• Multi-dimensional Impact of Cancer Risk Assessment Questionnaire (MICRA) Uncertainty
• Change in Health Behaviors: Change in Number of Wine/Beer/Mixed Drinks Per Day Among Those With Genetic Testing
• Change in Health Behaviors: Change in Minutes of Vigorous Exercise Per Week Among Those With Genetic Testing
• Change in Health Behaviors: Change in Minutes of Moderate Exercise Per Week Among Those With Genetic Testing
• Change in Health Behaviors: New Sigmoidoscopy or Colonoscopy Among Those Who Did Not Have One Within a Year of the Baseline Visit
• Change in Health Behaviors: New Mammogram Within One Year at 6 Months Among Those Who Did Not Have One Within a Year at Baseline

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is binary at the participant level: a participant either was recorded as having received genetic services or was not. The registry reports counts by group and compares each remote approach with usual care. The principal comparison measure is the risk difference, which expresses the difference between the two group proportions. A positive risk difference means the event proportion is higher in the remote group than in the comparator group. The posted risk differences are positive for both remote-versus-usual-care comparisons.

What do the relative measures add?

A risk ratio divides one group’s event proportion by the other group’s event proportion. An odds ratio instead compares the odds of the event between groups. These relative measures can make the size of a contrast easier to describe on a proportional scale, while the risk difference describes the absolute contrast. They are not interchangeable, and the odds ratio is not the same as a risk ratio. In this study, the reported risk ratios and odds ratios both favor more recorded service receipt in each remote group relative to usual care, consistent in direction with the risk differences.

How should the p-values be read?

The unadjusted p-value describes how compatible the observed data are with a specified no-difference hypothesis under the assumptions of the comparison. A small p-value is not the probability that the no-difference hypothesis is true, and it does not measure the size or practical importance of an effect. The registry reports p <0.001 for each primary comparison. Those values are unadjusted, and the registry record does not report whether multiplicity was addressed in a prespecified analysis plan.

What does a confidence interval communicate?

A confidence interval gives a range of effect values compatible with the observed data under the method used to construct it. For a risk difference, zero represents no difference in group proportions. The primary risk-difference intervals are entirely positive, so their reported ranges do not include zero. The interval also conveys uncertainty: a range that is more spread out permits a broader set of effect sizes than a narrower range. An interval should not be read as guaranteeing that the true effect lies within its endpoints, and it does not account for design or analysis limitations that are not represented in the calculation.

Why are there secondary mean comparisons?

Several posted secondary outcomes are scores or changes in behavior summarized by group means and standard deviations. A mean difference subtracts the comparison group’s mean from the other group’s mean. Its sign depends on the order of groups, and the meaning of a higher score depends on the outcome scale. A standard deviation describes variability among observations within a group; it is not the uncertainty in the group mean. The registry reports an unadjusted mean difference for phone versus video for the listed continuous outcomes, with no reported analyses listed for those outcomes.

The uncertainty interval for a mean difference is interpreted relative to zero in much the same way as an interval for a risk difference: an interval including zero is compatible with no mean difference under the calculation, while an interval entirely on one side of zero indicates a nonzero difference at the interval’s stated confidence level. The confidence level itself is not stated in the registry record for these comparisons. The unadjusted p-values likewise do not incorporate any multiplicity adjustment.

Group summaries and simple comparisons do not show whether participant characteristics, adherence, or missing observations influenced the results. The registry record does not report adjusted models, the handling of missing outcomes, or the analysis population for the posted summaries. It also does not report a detailed statistical analysis plan. These details matter because they determine how the trial’s design and available data are translated into estimates and uncertainty measures.

For binary outcomes, over-dispersion is not the central issue in interpreting the posted comparison in the way it can be for count models. In general, over-dispersion means that variation in count data exceeds what a model assumes; ignoring it can make uncertainty estimates too small. The primary outcome is reported as a participant count with a yes-or-no classification, and the registry record does not describe a count-model analysis or an over-dispersion assessment.

11. Confidence Intervals and Precision

Precision concerns how much uncertainty remains around an estimated contrast. The primary comparisons report confidence intervals for the risk differences, risk ratios, and odds ratios. For both remote-versus-usual-care risk differences, the interval lies above zero, and the corresponding intervals for the relative measures lie above one. Thus, the intervals do not include the respective no-difference values. Their widths still matter: a confidence interval covers a range of plausible effect sizes, not just the direction of the contrast.

The recorded group sizes differ, and the number of participants with the event is small in usual care relative to the remote groups. Such features affect how much information is available to estimate a group contrast. The primary results indicate a clear separation in the posted summaries, but an interval does not remove uncertainty about the magnitude, generalizability, or interpretation of that separation.

For the secondary continuous comparisons, the anxiety interval includes zero, while the MICRA uncertainty interval is entirely positive. The drinks-per-day interval includes zero. Those interval patterns describe uncertainty in the respective unadjusted mean differences; they do not establish that an outcome is unimportant or that a difference is absent. The registry record does not report confidence intervals for every secondary outcome listed, nor does it specify a confidence level for these comparisons.

Intervals quantify sampling uncertainty under the calculation used. They do not capture possible bias from missing data, outcome classification, deviations from assigned approaches, or selective reporting. Those issues cannot be evaluated fully because the registry record does not report the relevant analysis details.

12. Planning a Similar Trial: Sample Size

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

The sample-size display is a planning illustration based on the observed effect, not the trial’s original design calculation. Its entries are participants per arm for 80% power and participants per arm for 90% power. The 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 set to the stated fraction of the observed effect. These entries are planning quantities, not observed power.

For each comparison, the rows consider planning for 100%, 75%, and 50% of the observed effect. The columns describe two different target probabilities of detecting the specified effect under the planning assumptions, if that effect were present and the assumptions held. The 90% target is more demanding than the 80% target, so it generally requires more participants per arm. Smaller effects are harder to distinguish from random variation and therefore require more participants per arm than larger effects, under otherwise unchanged assumptions.

The sample-size assumptions in the registry record do not describe the trial’s original enrollment planning. The original design assumptions and sample-size justification are not reported in the registry record. The planning values should not be interpreted as a retrospective assessment of whether the completed study was adequately powered, and they do not replace consideration of the actual design, allocation, outcome data, or uncertainty intervals. The outcomes discussed in these comparisons are not time-to-event outcomes, so the relevant entries are participants per arm rather than total event counts.

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 = 0.147; treatment proportion p₁ = 0.441; average p̄ = 0.294.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6446 = 1.2633.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6101 = 0.5134.
4. n = (1.2633 + 0.5134)² / (0.2942)² = 36.5, rounded up to 37 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 <- 0.147286821705426                          # control proportion
p1 <- 0.441489361702128                          # 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(4455698)
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 = 37 (80% power), 49 (90% power)
 75% of observed effect: n per arm = 61 (80% power), 81 (90% power)
 50% of observed effect: n per arm = 124 (80% power), 166 (90% power)
power.prop.test: 36.5 
Simulated power at n = 37 per arm: 0.813 (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

Multiplicity arises when several outcomes or comparisons are examined. Even when each individual test uses a conventional significance threshold, the chance of at least one apparently notable result can increase as the number of tests grows. The registry lists eight secondary outcomes and posts comparisons for multiple outcomes, in addition to the primary comparisons. The record does not report a multiplicity adjustment, a hierarchy of outcomes, or a prespecified strategy for deciding which results should be treated as confirmatory.

The primary comparisons are reported with unadjusted p-values. The secondary comparisons are also unadjusted, and reported analyses are not listed for them. Without an analysis plan, it is not possible to determine from the registry record whether these posted comparisons correspond to the planned primary and secondary analyses, or whether other analyses were conducted.

Missing-data handling is not reported in the registry record. The record does not say how participants without an outcome record were classified, whether any imputation was used, or whether analyses were restricted to participants with complete data. The analysis populations are also not reported in sufficient detail to determine whether the posted summaries follow an intention-to-treat, per-protocol, or other approach.

These omissions affect interpretation because the handling of missing observations and the selection of an analysis population can influence estimates and their uncertainty. Randomization is recorded, but the registry record does not provide enough information to assess how missingness, adherence, or exclusions were handled in the posted results. The original statistical plan, including any interim analyses or multiplicity strategy, is not reported in the registry record.

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.

The adverse-event record lists zero serious adverse events and zero other adverse events in the video, phone, and usual-care groups. It also lists zero deaths in each group. The numbers recorded as at risk are 188 in the video group, 198 in the phone group, and 129 in usual care.

These entries describe what was recorded in the registry. They do not, on their own, establish that no adverse events occurred outside the recorded definitions or collection process. The registry record does not provide serious adverse-event terms, and it lists no top serious-event terms. Details about adverse-event ascertainment, severity criteria, follow-up, and missing safety data are not reported in the registry record.

Zero recorded events should therefore be read as a feature of the posted safety data, not as proof that the approaches have no risks. The event counts also do not establish comparative safety, particularly when the record does not describe the methods used to collect and assess adverse events.

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

The primary endpoint indicates whether participants were recorded as having received genetic services by six months. In the posted results, service receipt was recorded more often in each remote group than in usual care, and both unadjusted comparisons have p-values reported as <0.001. The risk-difference intervals exclude zero, while the relative-measure intervals exclude one. These findings describe the observed group comparisons in this randomized study.

The result does not show whether video or phone is better than the other, because the posted primary comparisons are each against usual care rather than a direct comparison between the two remote modalities. It also does not establish that every participant received the same counseling content or level of service. The registry record does not report enough operational detail to assess those matters.

Service receipt is an access and uptake outcome, not a direct measure of health benefit. The primary result does not establish that genetic assessment or testing changed health outcomes, nor does it show the effects of genetic results on participants or their families. The secondary outcomes address selected reported scores and behaviors, but the available summaries do not establish a complete downstream account.

Randomization is an important design feature for comparing groups, but the record does not describe allocation procedures, missing-data handling, or analysis populations. The results should therefore be interpreted alongside those limitations. The posted data also cannot guarantee that the pattern applies to other populations or service settings. Generalizability depends on study eligibility and implementation details that are not fully reported in the registry record.

The most direct conclusion supported by the posted primary data is that recorded service receipt differed between each remote group and usual care during the stated follow-up period. That is narrower than concluding that a particular delivery method improves health or that it should be selected for an individual. The data are a comparison of group outcomes, not personal medical advice.

17. Why This Trial Matters Statistically

This trial raises a statistical question about how to evaluate an intervention whose immediate aim is access to services. The primary outcome is service receipt, which is a practical endpoint for a study addressing a gap in access to genetic services. Its interpretation is distinct from that of a clinical endpoint: the results describe whether participants reached services, not whether a later health outcome changed.

The three-arm design provides separate comparisons of two remote delivery approaches with usual care. That structure can answer whether each remote approach differs from the comparator in the posted data, but it does not supply a direct primary comparison of the two remote modalities. Keeping these questions separate prevents a common misreading: evidence of a difference from usual care in both groups does not show that the two remote groups are equivalent or different from one another.

The record also illustrates why effect measures and precision should be read together. Risk differences describe absolute contrasts, while risk ratios and odds ratios describe relative contrasts. Confidence intervals add information about the range of effect sizes compatible with the data under the calculation. P-values alone do not communicate effect magnitude, and the registry’s unadjusted secondary comparisons require caution given the range of outcomes.

Finally, statistical interpretation depends on more than the reported estimates. Missing-data methods, analysis populations, multiplicity handling, and the original sample-size rationale are not reported in the registry record. Their absence limits independent assessment of the planned analysis and the strength of conclusions that can be drawn from the posted summaries.

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 leaves several trial-specific uncertainties. The narrative descriptions and posted results use opposite A/B assignments for phone and video. Although the modality names identify the posted groups, the discrepancy makes arm-letter references potentially confusing and warrants care when matching descriptions to results.

The primary outcome is described as a composite yes-or-no measure, but the registry does not define its components or the rules for classifying receipt of genetic services. It also does not report how service records were checked, whether receipt from different providers was captured consistently, or how unavailable records were handled. These details bear directly on interpretation of an uptake endpoint.

The usual-care description includes an offer of randomization to remote counseling after six months for participants who had not sought and received genetic counseling. The registry does not describe how this later offer was handled in the analysis or whether it affected follow-up or outcome ascertainment. It also does not report detailed eligibility criteria, adherence information, or the analysis population.

For secondary outcomes, the record lists more outcomes than it provides numerical comparisons for, and does not list reported analyses. The time description for the posted secondary summaries reports an average time from baseline to disclosure of 152.3 days, with a standard deviation of 150.0 days, for arms A and B. The record does not explain how that timing relates to each individual secondary measurement. Generalizability and interpretation are also limited by the absence of detailed recruitment and implementation information.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Engaging and Activating Cancer Survivors in Genetic Services Study — NCT04455698.
• Registry record last updated 2026-08-12; status last verified 2026-07.
• Results first posted 2026-08-12.
• 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 Engaging and Activating Cancer Survivors in Genetic Services Study is a completed randomized, parallel-group study with no masking recorded. It evaluated remote genetic counseling by video or phone against usual care among childhood cancer survivors, with an enrollment of 511. The primary outcome was the number of participants recorded as receiving genetic services at six months.

The posted primary comparisons show higher service receipt in each remote group than in usual care, with unadjusted p-values reported as <0.001. The registry also lists secondary outcomes in anxiety, uncertainty, and health behaviors, but does not report analyses for those outcomes. Missing-data methods, analysis populations, multiplicity procedures, and the original sample-size rationale are not reported in the registry record.