PROMIS Measures in Primary Care Practice: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for PROMIS Measures in Primary Care Practice (NCT02383862), a randomized na study. The primary outcome is Change From Baseline in PROMIS Composite T-Score at 3-Month Follow-up.

2. Clinical Question

3. Trial Design

The registry record describes a randomized, single-masked, parallel-group study titled PROMIS Measures in Primary Care Practice. Indiana University is listed as the sponsor. The study was marked completed, with enrollment of 300 and a study period from 2015-03 to primary completion in 2016-08. The phase is listed as NA. The identity of the person or group masked is not reported in the registry record.

The two groups differed in whether clinicians received baseline PROMIS symptom scores at the clinic visit. Patients in the Feedback Group had scores shared with their clinician; patients in the Control Group did not. The intervention is classified as OTHER in the registry record. The record does not specify a mandated clinician response, decision algorithm, or additional treatment associated with receiving scores.

The primary endpoint was change in PROMIS composite T-score at 3-month follow-up. The posted group summaries include 151 participants in the Feedback Group and 149 in the Control Group. The endpoint description says the questionnaire was administered at baseline and follow-up, and that follow-up scores for nonrespondents were determined using multiple imputation.

The registry lists 16 outcome measures, 15 posted secondary outcomes, and 6 analyses. It names additional symptom and patient-reported outcomes, including treatment satisfaction and measures of sleep and pain. The registry record does not report the original sample-size justification, the randomization procedure, the details of masking, or a full statistical analysis plan. Those aspects therefore cannot be reconstructed from the posted information.

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: In clinic, patients who had 1≤ SPADE (sleep, pain, anxiety, depression low energy/fatigue) symptoms, consented and provided authorization, completed PROMIS (Patient-Reported Outcome Measurement Information System), and then were randomized to a feedback or control group. Patients unable to complete enrollment prior to the encounter were excluded.

Baseline

3 Month Follow up

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: Multiple imputation was used to determine follow-up scores for nonrespondents.

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: Patients with 1 or more SPADE symptoms who completed enrollment (e.g., consent, authorization, baseline questionnaire, randomization)

6. Primary Endpoint

The registry lists the primary outcome as Change From Baseline in PROMIS Composite T-Score at 3-Month Follow-up, measured over baseline and 3 month follow up.

The primary endpoint is change from baseline in the PROMIS composite T-score at 3-month follow-up. The measure is based on a 20-item questionnaire, with 4-item scales for each of the 5 SPADE symptoms: sleep, pain, anxiety, depression, and energy or fatigue. Participants reported the extent of problems over the past 7 days using a 5-point Likert scale. Higher scores reflect greater symptom severity.

The registry defines change as baseline PROMIS T-score minus the 3-month PROMIS T-score. Under that direction, a positive value means the follow-up score is lower than the baseline score and is interpreted as symptom improvement. A negative value means the follow-up score is higher than baseline under the same calculation. The group contrast is intended to assess whether the average change differed between patients whose clinicians received scores and those whose clinicians did not.

A composite can summarize the set of SPADE symptoms in a single endpoint, rather than treating each symptom scale as the primary question. That can make the primary comparison more focused, while secondary symptom-specific outcomes provide additional detail. The registry record does not explain how the composite was constructed beyond describing the questionnaire and its component scales, nor does it report a threshold for a clinically important difference. The posted endpoint should therefore be interpreted as a continuous score contrast, not as a count of patients who improved or as evidence that any individual experienced a meaningful change.

7. Results Posted in the Registry

• Feedback Group: mean 3.48 versus 2.38 on control; difference 1.10 (95% CI -0.41 to 2.61), standardized effect d = 0.16; z-test p = 0.154.

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.

Change From Baseline in PROMIS Sleep T-score at 3-Month Follow up

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • Feedback Group: mean 4.88 versus 4.04 on control; difference 0.84 (95% CI -1.27 to 2.95), standardized effect d = 0.09; z-test p = 0.434.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Feedback Group and the control. The interval gives the range of effects that remain compatible with the data.

Change From Baseline in PROMIS Pain T-score at 3-Month Follow up

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • Feedback Group: mean 2.77 versus 2.12 on control; difference 0.65 (95% CI -1.38 to 2.68), standardized effect d = 0.07; z-test p = 0.530.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Feedback Group and the control. The interval gives the range of effects that remain compatible with the data.

Change From Baseline in PROMIS Anxiety T-score at 3-Month Follow up

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard errors.
• Result:
  • Feedback Group: mean 2.96 versus 2.13 on control; difference 0.83 (95% CI -1.40 to 3.06), standardized effect d = 0.08; z-test p = 0.466.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Feedback Group and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists secondary measures covering PROMIS sleep, pain, anxiety, depression, and fatigue, as well as treatment satisfaction and other sleep and pain measures. The numerical secondary results detailed in the record include PROMIS sleep, pain, and anxiety change scores. Their estimated differences are positive in the improvement direction, but each reported 95% confidence interval includes zero. This pattern is broadly consistent with the primary result in that the point estimates favor the Feedback Group while the uncertainty does not establish a group difference.

These secondary outcomes add symptom-specific context to the composite question, but they should not be treated as independent confirmation of the primary result. Symptom scales may capture related aspects of the same overall experience, and multiple outcomes create multiple opportunities to observe apparently notable results by chance. The registry record does not report a multiplicity adjustment or a hierarchy specifying which secondary outcomes would be treated as confirmatory.

The registry reports 15 posted secondary outcomes, but detailed numerical comparisons for all of them are not included in the record details available for this analysis. In particular, the reported data do not permit a complete numerical synthesis of every listed secondary measure. Individual results for the remaining secondary outcomes are not reported in the registry record. Conclusions should therefore be limited to the available numerical results rather than generalized across the entire secondary outcome set.

Unadjusted secondary results carry less weight than the prespecified primary endpoint because repeated testing can increase the chance of at least one apparently unusual result even when there is no underlying effect. Without a reported multiplicity plan, secondary estimates are best read as exploratory context. They neither replace the primary comparison nor establish a broad effect across all symptom domains.

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

• Change From Baseline in PROMIS Sleep T-score at 3-Month Follow up
• Change From Baseline in PROMIS Pain T-score at 3-Month Follow up
• Change From Baseline in PROMIS Anxiety T-score at 3-Month Follow up
• Change From Baseline in PROMIS Depression T-score at 3-Month Follow up
• Change From Baseline in PROMIS Fatigue T-score at 3-Month Follow up
• Treatment Satisfaction at 3-Month Follow-up
• Sleep at 3-month Follow up, as Measured by the Pittsburgh Insomnia Rating Scale (PIRS-2)
• Pain at 3 Month Follow up, as Measured by PEG

9. Statistical Interpretation

10. Statistical Methods Explained

The primary analysis is reported as a two-sided t-test comparing the groups. A t-test evaluates whether the observed difference in group means is large relative to the variability and uncertainty in the data, under the assumptions of the method. A two-sided test allows evidence in either direction: the Feedback Group could have a higher or lower mean change than the Control Group. The registry’s reported analysis gives a mean difference, a 95% confidence interval, and a p-value.

What does the mean difference represent?

The mean difference is the contrast between the group averages for the continuous endpoint. For this study, the change score is defined as baseline T-score minus follow-up T-score, so a positive change indicates improvement in the direction of lower symptom severity. The posted primary mean difference of 1.10 is in that positive direction. It is an average contrast, not a description of every participant’s experience; participants’ individual changes can vary around their group mean.

The registry’s primary outcome description concerns change from baseline, while the reported analysis labels its parameter Mean Difference (Final Values). The posted record does not clarify the relationship between that label and the endpoint’s stated change-score definition. That is a reporting detail to keep in mind when interpreting the analysis; it does not justify inferring an unreported model or analysis procedure.

How should the p-value be read?

A p-value describes how compatible the observed data are with a specified null hypothesis under the assumptions of the test. For a two-sided t-test, the null hypothesis is generally a zero mean difference. A p-value is not the probability that the null hypothesis is true, the probability that the result happened by chance, or a measure of the size or importance of an effect. The primary reported p-value is 0.165. It does not meet the conventional 0.05 threshold used in the planning illustration, but the registry record does not report the trial’s own prespecified significance threshold or full testing plan. The p-value should be interpreted together with the estimated difference and confidence interval.

What does the confidence interval add?

A confidence interval expresses uncertainty about the group difference. In repeated use of a method under its assumptions, intervals at a stated confidence level would cover the underlying parameter at the stated rate. For this study, the sponsor reports a 95% interval from -0.45 to 2.64. Because that interval includes zero, the data do not rule out no average difference under the reported analysis. Its values on both sides of zero also show that the direction of the true group contrast remains uncertain. A confidence interval is not a range containing a specified proportion of individual participants’ changes.

What is the role of the re-calculation?

The unadjusted re-calculation uses posted group summaries to obtain a simple mean contrast and associated uncertainty. It is useful as a consistency check, but it is not a reconstruction of any unreported adjusted or imputed analysis. The calculated p-value is 0.154, close to the sponsor’s reported p-value of 0.165, and both analyses give the same broad reading: the interval includes zero. The registry record marks no discrepancy, and the sponsor’s result remains the reported trial analysis.

The primary endpoint’s follow-up scores for nonrespondents were determined using multiple imputation, according to the registry description. Multiple imputation is a general statistical approach for handling missing values by creating plausible replacements based on observed information and combining analyses across imputed datasets. Its validity depends on assumptions about why values are missing and on the variables and model used. The imputation model, assumptions, number of imputations, and sensitivity analyses are not reported in the registry record, so their adequacy cannot be assessed from the posted description.

General statistical context: continuous symptom outcomes can vary more than a normal distribution would imply, a feature often called over-dispersion in settings where it applies. Methods that account for such variation can help avoid understating uncertainty. The registry reports a t-test for the primary comparison and does not report additional diagnostics or alternative models. No specific over-dispersion issue is described for this endpoint, so it should not be assumed to have occurred.

The registry says the study was randomized, which supports interpreting the group contrast as a randomized comparison, but randomization alone does not answer every analysis question. The allocation sequence, concealment procedures, analysis population, and any covariate adjustment are not reported in the registry record. Those missing details limit the ability to assess the analysis beyond the stated method and posted results.

11. Confidence Intervals and Precision

The primary estimate is a mean difference of 1.10 T-score points, with a sponsor-reported 95% confidence interval from -0.45 to 2.64. That interval is wide enough to include no difference and values in either direction. It is therefore important not to focus only on the positive point estimate: the interval conveys substantial uncertainty about the magnitude and direction of the group contrast.

The confidence interval is an estimate of uncertainty about the average group difference, not a range for individual responses. It does not say that most participants had changes between its limits. The posted group means are 3.48 for the Feedback Group and 2.38 for the Control Group, but the estimate’s uncertainty means these summaries should not be interpreted as a precise treatment effect.

The interval also cannot determine clinical importance on its own. The registry record does not report a threshold for a clinically important change in the composite T-score. Without such a benchmark, the values in the interval cannot be classified as clinically meaningful or unimportant on the basis of the registry record.

The re-calculated analysis produces a similar broad picture, with p = 0.154, while the sponsor reports p = 0.165. The reported and re-calculated estimates are close, and both intervals include zero. This consistency in the broad statistical reading does not eliminate the uncertainty in the estimated difference. A larger or more precise study could yield a narrower interval, but the posted results do not establish what such a study would find.

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 fractions of the observed primary effect. The entries are participants per arm, not total participants and not total events. They assume two-sided significance level 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is the stated fraction of the observed effect. These are planning assumptions for the illustrations; the original trial’s design assumptions and sample-size justification are not reported in the registry record.

The 80% power column describes the planned number of participants per arm for a design that would have an 80% chance of detecting the specified effect under the listed assumptions, if that effect were the true effect and the assumptions held. The 90% power column describes a higher chance of detection under the same conditions. These are design targets, not guarantees for a particular study or a measure of the probability that the study’s conclusion is correct.

Rows that plan for a smaller fraction of the observed effect require more participants per arm, because smaller differences are harder to distinguish from random variation. The figures are illustrations based on the observed result, not a record of the sample size chosen for this trial. They are not observed power: observed power is not a useful substitute for interpreting the estimated effect and its confidence interval after results are known. The uncertainty in the primary estimate also means that using the observed effect as a planning anchor should not be mistaken for a reliable forecast of a future effect.

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, Δ is the difference in means to detect and σ is the common standard deviation.

Worked calculation for this trial

1. Observed difference Δ = 1.100; pooled standard deviation σ = 6.674.
2. n = 2 × (1.96 + 0.842)² × 6.674² / 1.100² = 577.9, rounded up to 578 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
delta <- 1.1                      # observed difference in means
sigma <- 6.67447054431884                     # pooled standard deviation
n_per_arm <- function(power, frac = 1) {
  ceiling(round(2 * (z_a + qnorm(power))^2 * sigma^2 / (delta * frac)^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 (t-based, so very slightly larger)
cat("power.t.test:", round(power.t.test(delta = delta, sd = sigma, power = 0.80)$n, 1), "\n")

# Simulation: exact two-sample t-test using simulated means and variances
set.seed(2383862)
n    <- n_per_arm(0.80)
reps <- 20000
m_diff <- rnorm(reps, delta, sigma * sqrt(2 / n))             # difference in sample means
s2     <- sigma^2 * rchisq(reps, 2 * (n - 1)) / (2 * (n - 1))   # pooled sample variance
tstat  <- m_diff / sqrt(s2 * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(tstat) > qt(0.975, 2 * (n - 1))), reps))

Output from running the code

100% of observed effect: n per arm = 578 (80% power), 774 (90% power)
 75% of observed effect: n per arm = 1,028 (80% power), 1,376 (90% power)
 50% of observed effect: n per arm = 2,312 (80% power), 3,095 (90% power)
power.t.test: 578.9 
Simulated power at n = 578 per arm: 0.796 (20000 replicates)

The simulation draws many sets of group means and variances at the planned sample size and counts how often the two-sample t-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 sponsor’s reported primary analysis is a two-sided t-test of the mean difference. It gives an estimated difference of 1.10, a 95% confidence interval from -0.45 to 2.64, and p = 0.165. This is the trial analysis recorded by the sponsor and should be distinguished from the simple unadjusted re-calculation based on the posted group summaries.

The re-calculation gives a mean difference of 1.1 and p = 0.154. These results are close to the sponsor’s estimate and p-value and lead to the same broad interpretation: the estimated difference is positive under the endpoint’s improvement direction, while the confidence interval includes zero. The registry record marks no discrepancy. The re-calculation is a check of the posted summary statistics, not an independent analysis with access to participant-level data, and it cannot verify unreported modeling or imputation choices.

The registry labels the sponsor’s analysis parameter Mean Difference (Final Values), whereas the endpoint description defines a change from baseline. The record does not explain that wording difference. The reported sponsor analysis remains the appropriate result to quote, while the parameter label is a point of interpretive caution rather than a basis for substituting a different analysis.

15. Multiplicity, Missing Data and Analysis Populations

The registry record lists 16 outcome measures, 15 posted secondary outcomes, and 6 analyses. Testing multiple outcomes can increase the chance of finding at least one result that appears statistically notable by chance. This general concern is called multiplicity. It matters especially when many symptom scales, time points, or patient-reported measures are examined and then interpreted together.

The primary endpoint is identified, which gives the study a central outcome for interpretation. However, the registry record does not report whether secondary tests were adjusted for multiplicity, whether a hierarchy or gatekeeping plan was used, or which analyses were prespecified as confirmatory. The reported secondary p-values are therefore unadjusted in the re-calculation, and their evidence should be treated cautiously. No multiplicity correction should be assumed.

Missing data also affect interpretation. The primary endpoint description states that multiple imputation was used to determine follow-up scores for nonrespondents. The record does not report the amount or pattern of missingness, the variables used in the imputation model, the assumptions about missingness, or sensitivity analyses under alternative assumptions. Those omissions make it impossible to judge from the registry record whether the imputation results are robust to departures from the model’s assumptions.

The posted arm summaries give the group counts used in the outcome reporting, but the record does not fully describe the analysis population or how participants with missing baseline or follow-up data were handled outside the stated imputation approach. It also does not report a detailed intention-to-treat statement or a per-protocol analysis. Such information can affect how closely the analysis reflects the randomized comparison. The trial’s original statistical analysis plan, interim analyses, and sample-size justification are not reported in the registry record, so those procedures should not be inferred.

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 in the Feedback Group, with 151 at risk, and zero in the Control Group, with 149 at risk. It also reports zero other adverse events in each group and zero deaths in each group. No serious adverse event terms are listed.

These are reported event counts, not proof that no adverse events occurred beyond the categories and reporting captured in the registry. The record does not provide further detail on how adverse events were defined, collected, attributed, or followed. The figures should therefore be read as the posted safety counts for this study, not as a complete assessment of every possible harm or as a comparison that establishes safety equivalence between groups.

The trial’s primary question concerned symptom-score feedback and change in PROMIS measures. The adverse-event figures are separate from that efficacy-related endpoint and do not establish whether sharing scores altered clinical management or patient outcomes. No medical conclusion should be drawn from the zero counts alone.

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

The primary result is an estimated mean difference in composite change that favors the Feedback Group according to the registry’s positive-change definition. The sponsor-reported confidence interval includes zero, and the reported p-value is 0.165. Taken together, these results do not establish a clear average difference between groups, while also leaving uncertainty about the size and direction of the underlying difference.

This does not show that the groups were identical. A confidence interval that includes zero is compatible with no average difference, but it also contains nonzero values. Nor does the positive point estimate establish that providing scores caused symptom improvement. The randomized design is relevant to causal interpretation, but the estimate remains uncertain and the registry does not report enough detail to assess every analysis choice.

The endpoint is a continuous composite score, not a binary measure of response. A group average cannot tell whether every participant improved, whether improvement was concentrated in a subset, or whether a change mattered to patients. The record does not report a clinically important threshold for the composite. It is therefore not possible to classify the estimated difference as clinically meaningful based on the posted information alone.

The secondary results for sleep, pain, and anxiety have positive estimates but intervals that include zero, and the broader set of secondary results should be interpreted cautiously in the absence of a reported multiplicity plan. The findings concern the study’s measured outcomes and follow-up period; they do not establish effects beyond those outcomes or at other times.

In short, the posted data describe a positive but imprecise primary estimate, with no clear statistical evidence of a group difference under the sponsor’s reported analysis. This is a statement about the evidence and its precision, not a recommendation about clinical practice and not a conclusion that score feedback does or does not work.

18. Why This Trial Matters Statistically

This trial raises a practical measurement question with a clear statistical contrast: whether making baseline symptom scores available to clinicians is associated with a different subsequent change in patients’ reported symptoms. The randomized parallel-group design and a defined primary composite endpoint provide a structure for comparing the feedback approach with care in which clinicians did not receive those scores.

Statistically, the example illustrates why an estimated effect, its uncertainty, and the analysis plan must be considered together. The positive primary point estimate might attract attention on its own, but the sponsor’s confidence interval spans zero and the p-value is 0.165. The interval gives a more informative account of the range of group differences compatible with the analysis than the point estimate alone.

The study also highlights the interpretation challenges created by multiple symptom domains and secondary outcomes. A composite primary measure can focus the principal comparison, while the separate symptom scales can help describe the pattern. Yet a broad outcome set raises multiplicity concerns, particularly when the record does not state whether secondary tests were adjusted or arranged in a prespecified hierarchy.

Finally, the registry’s description of multiple imputation makes missing-data assumptions relevant to the interpretation. Reporting the imputation model, missingness patterns, and sensitivity analyses would help readers assess how dependent the results are on those assumptions. The record’s limits do not erase the value of the posted results; they define how far the statistical conclusions can reasonably extend.

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.

The registry record does not report the original sample-size justification or design assumptions, so the planning illustrations based on the observed effect cannot establish whether the trial was planned to detect a particular clinically important difference. The number of participants enrolled does not by itself resolve the uncertainty in the primary estimate.

The primary endpoint description and sponsor analysis label are not fully aligned in wording: the endpoint is described as change from baseline, while the analysis parameter is labeled Mean Difference (Final Values). The registry record does not explain whether this is a naming convention or reflects a distinction in the analysis. The result should be read using the sponsor’s reported analysis, without assuming an unreported model.

Important details about the randomized procedure, masking, analysis population, covariate adjustment, and the imputation model are not reported in the registry record. The identity of the party masked is also not reported. The primary endpoint description mentions multiple imputation for nonrespondents but does not give missingness patterns or sensitivity analyses, limiting assessment of robustness.

The registry lists many outcomes, but does not report a multiplicity strategy. Detailed numerical results for every secondary endpoint are not available in the record details for this analysis, so the pattern across all listed secondary outcomes cannot be fully evaluated. The lack of a reported clinically important difference threshold also limits interpretation of the magnitude of the T-score contrast in clinical terms.

Finally, the outcome is based on patient-reported symptom scores at baseline and 3-month follow-up. The posted results do not establish effects at other follow-up times, on outcomes not measured, or on clinical decisions and care processes beyond the described score feedback. These are limits on inference, not evidence that unreported effects occurred.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: PROMIS Measures in Primary Care Practice — NCT02383862.
• Registry record last updated 2017-06-16; status last verified 2017-04.
• Results first posted 2017-06-16.
• 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.

23. Record Summary

The registry describes a completed randomized, single-masked, parallel-group study sponsored by Indiana University, with enrollment of 300. Clinicians in the Feedback Group received patients’ baseline PROMIS symptom scores; clinicians in the Control Group did not. The primary endpoint was change in PROMIS composite T-score from baseline to 3-month follow-up, with positive change defined as improvement.

The sponsor reported a mean difference of 1.10, a 95% confidence interval from -0.45 to 2.64, and p = 0.165. The interval includes zero, so the posted primary analysis does not establish a clear average group difference. The unadjusted re-calculation is broadly consistent. Secondary results detailed for sleep, pain, and anxiety also have intervals that include zero. Multiple imputation is reported for follow-up scores of nonrespondents, while details of the imputation model, multiplicity handling, and original sample-size justification are not reported in the registry record.