Risk Stratification to Promote Effective Shared Decision-Making for Colorectal Cancer Screening: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Risk Stratification to Promote Effective Shared Decision-Making for Colorectal Cancer Screening (NCT01596582), a randomized na study. The primary outcome is Concordance Between Patient Preference and Test Ordered.

2. Clinical Question

The trial focused on decision-making around screening rather than on cancer diagnoses or other clinical outcomes. Its central comparison was whether providing a risk assessment in addition to a decision aid was associated with a different frequency of preference-concordant test orders. The registry describes screening test completion, satisfaction, screening intentions, and provider satisfaction as additional outcomes. The posted primary result compares Standard Care with Risk Assessment. The registry record also reports a secondary comparison of concordance by high versus low risk, and additional secondary results grouped by concordance versus discordance. Those secondary groupings address different questions from the randomized comparison and should not be treated as though they were randomized treatment arms.

3. Trial Design

The study is recorded as a randomized, parallel-group trial with no masking. Its enrollment is listed as 352. The trial status is completed; the recorded start was 2012-04 and primary completion was 2016-02. The sponsor is Boston Medical Center. The phase is listed as NA.

Participants were assigned to one of two behavioral interventions. Standard Care consisted of reviewing a web-based colorectal cancer screening decision aid just before a scheduled provider visit. Risk Assessment consisted of reviewing the same decision aid and then completing the Advanced Colorectal Neoplasia Index risk assessment before the visit. The intended distinction between the groups was therefore the addition of the risk assessment, not the presence or absence of the decision aid.

The primary outcome was preference concordance: the count of participants whose preferred screening test was the test ordered. The registry gives a timeframe of 3 months for this measure. The primary endpoint counts were 148 among 168 participants in Standard Care and 147 among 173 participants in Risk Assessment. The outcome denominators are not the same as the total enrollment, and the reasons for the denominators are not reported in the registry record.

The registry describes secondary outcomes including concordance by risk group, satisfaction with the decision-making process, screening intentions, screening test completion, and provider satisfaction. The posted results cover only a subset of the listed secondary outcome topics. The exact randomization procedure, allocation concealment, trial protocol, and original design assumptions are not reported in the registry record. No masking was used, so participants and providers were not described as blinded to the intervention assignment.

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.

Overall Study

Reasons for not completing this period:

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 Concordance Between Patient Preference and Test Ordered, measured over 3 months.

The primary endpoint measures whether the screening test ordered for a participant matched the test that participant preferred. The registry defines concordance as the number of participants who had their preferred test ordered. It is a count-based measure of alignment between a participant’s stated preference and the clinical decision documented as an order; it is not a measure of whether the participant later completed screening.

This endpoint is relevant to the trial’s shared decision-making question because the study sought to assess whether risk information affected clinical decisions about screening test selection. Preference concordance captures one concrete part of that process: whether the final order reflected the participant’s preference. It does not, by itself, establish how much the participant understood, whether the discussion was satisfactory, why a particular test was selected, or whether the ordered test was completed.

The reported timeframe is 3 months. The registry lists 148 concordant orders among 168 Standard Care participants and 147 among 173 Risk Assessment participants. These counts describe the endpoint as posted. They do not provide information about the particular screening tests preferred or ordered, nor do they explain how preferences were elicited. Those details are not reported in the registry record.

7. Results Posted in the Registry

• Risk Assessment: 85.0% (147/173) versus 88.1% (148/168) on control; risk difference -3.1 percentage points (95% CI -10.4 to 4.1), risk ratio 0.96 (0.89–1.05); unadjusted two-proportion z-test p = 0.399.

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.

Concordance Between Patient Preference and Test Ordered for High vs. Low Risk Patients

• 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:
  • Low Risk: 87.1% (61/70) versus 83.5% (86/103) on control; risk difference 3.6 percentage points (95% CI -7.0 to 14.3), risk ratio 1.04 (0.92–1.18); unadjusted two-proportion z-test p = 0.510.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Low Risk and the control. The interval gives the range of effects that remain compatible with the data.

Satisfaction With Decision-making Process (SDMP)

• 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:
  • Discordance: mean 48.90 versus 52.00 on control; difference -3.10 (95% CI -5.09 to -1.11), standardized effect d = -0.57; z-test p = 0.002.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Discordance than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Screening Intentions

• 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:
  • Discordance: mean 4.00 versus 4.60 on control; difference -0.60 (95% CI -0.95 to -0.25), standardized effect d = -0.79; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically lower for Discordance than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary results extend the study beyond the primary randomized comparison, but they do not all preserve that comparison’s interpretation. The posted secondary outcomes include concordance by high versus low risk, satisfaction with decision-making, and screening intentions, alongside listed topics such as screening test completion and provider satisfaction. The outcomes should be read according to the groups and measures actually reported; a topic named in the study record is not, by itself, evidence that its result is available.

The high- versus low-risk analysis describes concordance across risk categories. It is not a direct comparison of the randomized Standard Care and Risk Assessment groups. The satisfaction and screening-intention results use Concordance and Discordance groups. Those comparisons show how outcomes differ across categories defined by preference concordance, but do not establish that concordance caused the differences. The primary randomized result remains the direct evidence about assignment to the risk assessment intervention versus decision aid alone.

The reported secondary tests include chi-squared testing for the binary concordance comparison and Wilcoxon (Mann-Whitney) testing for satisfaction and intentions. The posted p-values for the secondary comparisons are 0.51 for high versus low risk, <0.001 for satisfaction, and <0.001 for screening intentions. These results should be considered in the context of several secondary outcomes and comparisons. No multiplicity adjustment or prespecified hierarchy for secondary testing is reported in the registry record. When multiple tests are conducted, the chance of at least one apparently notable result can increase; unadjusted results therefore carry less weight than a clearly specified primary analysis. The secondary patterns can inform questions for further evaluation, but they do not overturn or replace the primary randomized comparison.

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

• Concordance Between Patient Preference and Test Ordered for High vs. Low Risk Patients
• Satisfaction With Decision-making Process (SDMP)
• Screening Intentions
• Screening Test Completion
• Provider Satisfaction

9. Statistical Interpretation

10. Statistical Methods Explained

The registry reports a chi-squared test for the primary comparison. The recalculated risk difference is an unadjusted comparison of the two observed proportions, derived from the posted counts and denominators. These methods summarize the same binary endpoint but express the comparison differently: the chi-squared test assesses evidence of association between randomized group and concordance, while the risk difference estimates the absolute contrast in the observed proportions.

What does the risk difference describe?

In general, a risk difference is the difference between the proportion with an event in one group and the proportion with an event in the comparison group. Here, the event is a participant having the preferred test ordered, and the comparison is Risk Assessment relative to Standard Care. A negative estimate means the observed proportion was lower in Risk Assessment. The estimate is unadjusted, meaning it does not account for covariates in a model. No adjusted primary estimate is reported in the registry record.

What does a p-value tell the reader?

In general, a p-value describes how compatible the observed data are with a specified null hypothesis under the assumptions of the test. A small p-value can indicate that the observed data would be unusual under that null model; it is not the probability that the null hypothesis is true. The registry’s primary p-value is 0.40. The unadjusted recalculation is 0.399. Neither value alone quantifies the size or practical importance of a difference, which is why the estimate and confidence interval also matter.

How do the secondary tests differ?

The registry reports Wilcoxon (Mann-Whitney) tests for satisfaction with the decision-making process and screening intentions. In general, this rank-based test compares the distributions of observations in two groups and does not require the comparison to be framed only as a difference between arithmetic means. The posted group summaries give means and standard deviations, while the registry’s reported test is rank-based. These summaries and tests answer related, but not identical, questions about the data. The registry record does not report a model-based adjusted analysis for these outcomes.

The satisfaction and intention groups are Concordance and Discordance, not the randomized intervention groups. Thus, the reported tests assess whether outcomes differ between participants whose preferred test was ordered and those whose preferred test was not ordered. They do not isolate an effect of the risk assessment. A difference may be associated with concordance while also reflecting other characteristics or experiences that distinguish participants in those groups.

For the high-versus-low-risk concordance outcome, the registry reports a chi-squared test. This comparison uses risk categories and is distinct from the randomized primary analysis. The methods used to define the risk categories are not reported in the outcome entry, beyond the category labels. The registry does not provide an adjusted estimate for this analysis.

Why can over-dispersion matter?

General explanation: for count outcomes, a statistical model may assume that the variation in counts follows a specified distribution. Over-dispersion occurs when the observed variability is greater than the model assumes. If it is ignored, standard errors can be too small and intervals or tests can appear more decisive than warranted. The primary outcome is reported as participant counts with a binary event definition, not as a count rate with a dispersion estimate. The registry record does not report an over-dispersion assessment or a count-model analysis, so that issue is not part of the posted primary method.

All reported comparisons should be read alongside their outcome definitions, denominators, and group formation. The randomized comparison can support an assessment of the assigned intervention contrast, subject to the unreported details of allocation and outcome handling. The other posted comparisons are descriptive or observational with respect to the groupings used. The registry record does not report the full statistical analysis plan, missing-data methods, or details of any covariate adjustment.

11. Confidence Intervals and Precision

The recalculated risk difference for the primary outcome is -0.031, with a confidence interval from -0.104 to 0.041. In general, a confidence interval represents a range of estimates compatible with the data and the method used to construct the interval. Its width conveys precision: a wider interval leaves more uncertainty about the size and direction of the contrast. The confidence level for this interval is not reported in the registry record.

The interval includes zero, the value corresponding to no difference on the risk-difference scale. It also extends to values on either side of zero, so the posted estimate does not precisely distinguish a lower concordance proportion from a higher one in the Risk Assessment group. This is consistent with the registry’s chi-squared p-value of 0.40 and the unadjusted recalculated p-value of 0.399. The interval should be read as uncertainty around the estimated contrast, rather than as a range of outcomes that each have a separate probability of being true.

The interval does not establish that the interventions have equivalent effects. Such a conclusion would require a prespecified equivalence margin and an analysis designed for that purpose; neither is reported in the registry record. The endpoint counts also do not resolve whether the assessment might affect other outcomes, such as test completion or satisfaction. Precision is specific to the outcome and comparison being estimated, and cannot be carried over automatically to the other outcomes.

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 illustrations are planning calculations based on the observed effect, not the original trial design. The original sample-size assumptions and justification are not reported in the registry record. The figures for these non-time-to-event outcomes are participants per arm, rather than total events. The stated assumptions are a two-sided significance level of 0.05, equal allocation between two arms, a normal approximation, and an effect to detect set to the stated fraction of the observed effect. Time-to-event calculations, if present, would instead report total events, but no such calculation applies to these posted outcomes.

The 80% power column describes the number of participants per arm estimated to give an 80% chance of detecting the specified effect under the planning assumptions, if that effect is the true one. The 90% power column uses a higher chance of detection and therefore calls for a larger planned sample for the same effect. These are prospective planning illustrations, not statements about what the completed trial achieved. This is not observed power.

The rows consider planning for 100%, 75%, and 50% of the observed effect. A smaller effect is harder to distinguish from ordinary sampling variation, so detecting a smaller effect requires more participants. These figures should not be interpreted as evidence that the trial was designed around the observed result or that the displayed sample sizes are appropriate for a future study without additional design decisions. The original assumptions, including any allowance for loss to follow-up or other design features, are not reported in the registry record.

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 = 0.881; treatment proportion p₁ = 0.850; average p̄ = 0.865.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.4828 = 0.9462.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.4823 = 0.4059.
4. n = (0.9462 + 0.4059)² / (-0.0312)² = 1,873.1, rounded up to 1,874 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 <- 0.880952380952381                          # control proportion
p1 <- 0.84971098265896                          # 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(1596582)
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 = 1,874 (80% power), 2,507 (90% power)
 75% of observed effect: n per arm = 3,249 (80% power), 4,349 (90% power)
 50% of observed effect: n per arm = 7,125 (80% power), 9,538 (90% power)
power.prop.test: 1873.1 
Simulated power at n = 1,874 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.

14. Analyses Reported by the Sponsor

The registry’s primary analysis is a chi-squared test and reports p = 0.40. The unadjusted recalculation from the posted counts gives a risk difference of -0.031, a confidence interval from -0.104 to 0.041, and p = 0.399. The two p-values are close, and both indicate that the posted primary comparison does not provide strong statistical evidence of a difference.

The recalculation expresses the contrast as an absolute difference in proportions and adds an interval around that estimate. It is not a replacement for the sponsor’s reported analysis, and it is not described as an adjusted result. The registry record does not report a discrepancy between the recalculation and the sponsor’s analysis. The sponsor’s chi-squared result remains the posted analysis, while the unadjusted estimate and interval help describe the magnitude and precision of the same primary comparison.

The methods are not identical: a chi-squared test evaluates evidence for an association, whereas the recalculation presents an unadjusted risk difference. Small differences in p-value can arise from different statistical formulations. Neither result should be read as proof of no effect, and neither establishes equivalence. The registry record does not report a prespecified equivalence margin or a non-inferiority analysis.

15. Multiplicity, Missing Data and Analysis Populations

The registry record lists multiple secondary outcomes and reports more than one statistical comparison. It does not report whether secondary hypotheses were prespecified in a hierarchy, whether any multiplicity adjustment was used, or how the primary outcome was protected from the effects of multiple testing. In general, testing many hypotheses can increase the chance that at least one result appears statistically notable even when there is no corresponding underlying difference. Unadjusted secondary p-values should therefore be interpreted cautiously and in conjunction with effect estimates, outcome definitions, and study context.

Missing-data methods are not reported in the registry record. The total enrollment is 352, while the primary endpoint denominators are 168 and 173. The registry does not explain the relationship between enrollment and those denominators, state whether any participants lacked outcome data, or describe how missing observations were handled. The reasons for any difference between enrolled and analyzed counts cannot be inferred from the posted results.

The analysis populations are also not specified. The record does not say whether the primary analysis followed an intention-to-treat approach, whether participants were analyzed according to assignment, or whether other analysis sets were used. Randomization is recorded, but the method of sequence generation, allocation concealment, and details of deviations from assignment are not reported in the registry record. These omissions limit assessment of how the posted analysis relates to the original allocation and how representative the outcome denominators are of all randomized participants.

For the secondary comparisons, the record does not explain how risk categories were assigned or how the concordance and discordance groupings were handled when outcome data were unavailable. No imputation, sensitivity analysis, or missingness assessment is reported. These details matter because the interpretation of an estimate can depend on who contributed data and how unavailable outcomes were treated.

16. 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 registry reports zero serious adverse events among 168 participants at risk in Standard Care and among 173 participants at risk in Risk Assessment. It also records zero other adverse events and zero deaths in both groups. These figures describe the safety entries in the registry record for the listed at-risk groups.

Zero recorded events in these entries means that no events were recorded in the reported categories; it does not establish that the interventions are free of risk or that all possible events were measured. The registry record does not provide event definitions, collection procedures, follow-up duration for safety outcomes, or an account of how adverse events were adjudicated. The safety figures should be interpreted within those limits and do not change the interpretation of the primary preference-concordance endpoint.

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

The primary result describes the frequency with which a participant’s preferred screening test was the test ordered. The posted counts were similar across the randomized groups, and the unadjusted risk-difference interval includes zero. The sponsor’s reported chi-squared p-value and the recalculated p-value are also close. Taken together, these statistics do not show a clear difference in the primary endpoint between the decision aid alone and decision aid plus risk assessment groups.

This finding does not prove that the groups were equivalent. The confidence interval still allows differences in either direction, and the registry does not report an equivalence margin or an equivalence analysis. Nor does the result establish that risk assessment has no effect on other elements of decision-making. Preference concordance is one specific outcome, not a complete measure of the quality of a shared decision-making conversation.

The endpoint is also distinct from screening completion. An order that matches a participant’s preference does not establish that the test was completed, and the primary result does not answer whether screening rates changed. Although the study description names test completion, satisfaction, intentions, and provider satisfaction as outcomes, the primary comparison should not be used to infer their results. Secondary findings use other groups and comparisons, and some are observational rather than comparisons by randomized assignment.

The results do not address colorectal cancer incidence, diagnosis, or survival. No such outcomes are reported in the posted primary result. They also do not support medical advice for individuals deciding whether or how to be screened. The statistical conclusion is limited to the registered study’s measured outcome and the analysis reported: the available primary comparison is not precise enough to establish a meaningful direction of difference, and it does not establish that the groups are identical.

18. Why This Trial Matters Statistically

This trial raises a statistical question about what counts as evidence of shared decision-making: the primary measure operationalizes one aspect of the process as agreement between stated preference and the test ordered. That makes the endpoint concrete and countable, but it also narrows the interpretation. It captures alignment at the ordering stage, not the entire discussion or the later completion of screening.

The randomized design is useful for comparing assignment to the added risk assessment with assignment to the decision aid alone. The posted primary analysis appropriately focuses on that contrast. Its interpretation is strengthened by considering both the group counts and the estimated risk difference with its interval, rather than relying on a p-value alone. The interval makes clear that the data do not precisely resolve the direction of the difference.

The study also illustrates why secondary analyses need careful framing. Comparisons across risk categories or across participants whose preferences were concordant or discordant do not have the same basis as the randomized comparison. They can describe patterns, but cannot automatically be given a causal interpretation. The absence of reported multiplicity procedures and analysis-population details further limits how much weight to place on isolated secondary results.

More broadly, the registry distinguishes a decision outcome from a screening outcome. Having a preferred test ordered is not the same as completing that test. Keeping those endpoints separate helps prevent a favorable result on one process measure from being mistaken for evidence about the whole screening pathway. The record offers a focused example of how endpoint definition, comparison structure, and precision shape the conclusions that can be drawn from a clinical trial.

19. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

Several details needed to assess the trial fully are not reported in the registry record. These include the precise eligibility criteria, participant characteristics, the randomization procedure, allocation concealment, and the original sample-size justification. The record indicates that the trial was unmasked, but does not describe how participants’ preferences were elicited or how providers’ test orders were captured and verified.

The primary outcome is a specific measure of preference concordance. The registry does not report which screening tests participants preferred or which tests were ordered, nor does it describe whether an order could be considered concordant under more than one preference. The endpoint does not directly indicate whether the test was completed. Its timeframe is listed as 3 months, but outcome ascertainment details are not provided.

The primary endpoint denominators are smaller than the total enrollment, and the record does not explain the difference. Missing-data handling and analysis populations are not reported. Without that information, it is not possible to determine from the registry record whether all randomized participants contributed to the primary analysis or how unavailable outcomes were treated.

The registry does not report a multiplicity strategy for the several secondary outcomes. Some secondary results compare participants based on risk category or observed concordance rather than randomized assignment, which limits causal interpretation. The record also does not provide adjusted estimates, subgroup analysis plans, or sensitivity analyses. These limitations do not negate the posted findings, but they restrict the scope and precision of conclusions that can be drawn from them.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Risk Stratification to Promote Effective Shared Decision-Making for Colorectal Cancer Screening — NCT01596582.
• Registry record last updated 2017-03-21; status last verified 2017-03.
• Results first posted 2017-03-21.
• 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.

23. Record Summary

NCT01596582 is a completed randomized, parallel-group study sponsored by Boston Medical Center. It compared a web-based colorectal cancer screening decision aid alone with the same decision aid followed by the Advanced Colorectal Neoplasia Index risk assessment before a scheduled provider visit. The registry lists enrollment of 352, no masking, and a primary completion date of 2016-02.

The posted primary outcome was concordance between a participant’s preferred screening test and the test ordered, measured at 3 months. Counts were 148 of 168 in Standard Care and 147 of 173 in Risk Assessment. The registry reports a chi-squared p-value of 0.40; the unadjusted recalculation gives a risk difference of -0.031 with a confidence interval from -0.104 to 0.041 and p = 0.399. The record also reports secondary comparisons and zero recorded serious adverse events in both groups. Details on missing data, analysis populations, the original design assumptions, and multiplicity handling are not reported in the registry record.