Comprehensive vs. Assisted Management of Mood and Pain Symptoms: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Comprehensive vs. Assisted Management of Mood and Pain Symptoms (NCT01757301), a randomized na study. The primary outcome is Composite Z-score of Pain-anxiety-depression Severity.

2. Clinical Question

3. Trial Design

CAMMPS was a randomized, parallel-group comparative effectiveness trial. The registry lists the masking as single; it does not identify which participants or study personnel were masked. The phase is recorded as NA. The sponsor was the VA Office of Research and Development. Enrollment was 296, and the study status is completed.

The registry describes the intervention contrast as a lower-resource versus higher-resource enhancement of usual primary care. ASM used automated symptom monitoring and self-management modules focused on pain and mood. CSM included those ASM elements and added care management by a nurse-physician team. Thus, the comparison concerns the added care-management component on top of the shared ASM approach, rather than a comparison with no symptom-management intervention.

The primary outcome was assessed at 12 months. The registry reports group means and standard deviations and describes the primary analysis as a mixed model for repeated measures (MMRM). Seven participants in each group had no follow-up assessments after baseline and were excluded from that primary MMRM analysis because at least one follow-up data point is required for MMRM. Further details about randomization procedures, the identity of those masked, the original sample-size justification, and the full analysis plan are not reported in the registry record.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Before assignment: Two participants were excluded from the study after enrollment. Both participants failed screening and were considered ineligible.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Seven participants in the CSM group and seven participants in the ASM group had no follow-up assessments after baseline and were therefore not included in the primary MMRM analysis since at least one follow-up data point is required for MMRM.

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 Composite Z-score of Pain-anxiety-depression Severity, measured over 12 months.

The primary endpoint was a composite z-score combining the Brief Pain Inventory (BPI), Generalized Anxiety Disorder 7-Item Anxiety Scale (GAD-7), and Patient Health Questionnaire 9-item Depression Scale (PHQ-9). A z-score expresses an individual scale score relative to the sample mean and standard deviation. The three standardized scores were averaged to create one measure representing the joint severity of pain, anxiety, and depression.

The registry defines zero as no change from baseline, negative values as improvement, and positive values as worsening. Each unit represents one standard deviation of change relative to the group at baseline; the described practical range is -2.0 to +2.0. Combining the three domains gives a single primary measure aligned with the trial’s focus on overlapping symptoms, rather than treating pain, anxiety, and depression as unrelated outcomes. It also means the composite is not a direct score on any one of the component scales. Interpretation should therefore consider both the direction of the composite and the separate secondary symptom measures, while recognizing that the registry does not report separate primary results for each component scale.

7. Results Posted in the Registry

• Comprehensive Symptom Management (CSM): mean -0.65 versus -0.52 on control; difference -0.13 (95% CI -0.36 to 0.10), standardized effect d = -0.13; z-test p = 0.275.

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.

Pain Average/Enjoyment of Life/General Activities Pain Scale (PEG)

• 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:
  • Comprehensive Symptom Management (CSM): mean 6.10 versus 6.00 on control; difference 0.10 (95% CI -0.36 to 0.56), standardized effect d = 0.05; z-test p = 0.668.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Comprehensive Symptom Management (CSM) and the control. The interval gives the range of effects that remain compatible with the data.

Patient Health Questionnaire 9-item Depression Scale (PHQ-9)

• 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:
  • Comprehensive Symptom Management (CSM): mean 10.30 versus 11.40 on control; difference -1.10 (95% CI -2.41 to 0.21), standardized effect d = -0.20; z-test p = 0.101.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Comprehensive Symptom Management (CSM) and the control. The interval gives the range of effects that remain compatible with the data.

Generalized Anxiety Disorder 7-Item Anxiety Scale (GAD-7)

• 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:
  • Comprehensive Symptom Management (CSM): mean 7.50 versus 8.40 on control; difference -0.90 (95% CI -2.26 to 0.46), standardized effect d = -0.15; z-test p = 0.195.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Comprehensive Symptom Management (CSM) and the control. The interval gives the range of effects that remain compatible with the data.

The posted secondary comparisons cover pain measured by PEG, depressive symptoms measured by PHQ-9, and anxiety symptoms measured by GAD-7. Their estimates do not all point in the same direction: the pain estimate is positive, while the depression and anxiety estimates are negative for CSM compared with ASM. Each reported interval includes zero. This lack of a uniform direction across measures is relevant context for a primary endpoint that combines pain, anxiety, and depression into one score.

The secondary results do not overturn or independently confirm the primary comparison. They give separate views of symptom domains that contribute to the broader clinical question, but they are not the primary composite. The registry does not report multiplicity-adjusted analyses for the secondary comparisons. When several outcomes are tested, the chance of at least one apparently notable result can increase; general statistical practice therefore treats unadjusted secondary findings as less confirmatory than a prespecified primary result. These outcomes are best read as additional, exploratory context unless a more complete analysis plan establishes otherwise.

The registry names the BPI among the scales used to construct the primary composite, but does not report a separate BPI comparison among the posted secondary outcome results. The available secondary summaries are group means, standard deviations, estimates, and intervals. The registry does not report adjusted secondary models or an explanation of how the secondary outcomes were prioritized. Consequently, the overall pattern is informative about the range of posted domain-specific estimates, but it does not establish a consistent advantage for either management approach across all symptoms.

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

• Pain Average/Enjoyment of Life/General Activities Pain Scale (PEG)
• Patient Health Questionnaire 9-item Depression Scale (PHQ-9)
• Generalized Anxiety Disorder 7-Item Anxiety Scale (GAD-7)
• Brief Pain Inventory (BPI)

9. Statistical Interpretation

10. Statistical Methods Explained

What does a mean difference represent?

The primary outcome is continuous, so the posted group summaries are means and standard deviations. A mean describes the average score in a group, while a standard deviation describes how spread out participant scores are around that average. The comparison is expressed as the CSM mean minus the ASM mean. For this endpoint, a negative difference points toward a more negative average composite score in CSM, which the registry associates with improvement. The sign has meaning only in relation to the outcome’s stated direction; it is not, by itself, a judgment about clinical importance.

A mean difference compresses the group contrast into one estimate. It does not show the full distribution of individual outcomes, and participants within either group may have scores above or below the group mean. For a composite score, it also does not reveal whether any observed pattern is driven more by pain, anxiety, or depression. Separate component results would be needed for that, and separate primary component comparisons are not reported in the registry record.

Why use a composite z-score?

General statistical explanation: standardizing component measures can place scores from different scales onto a common relative scale before combining them. A z-score is formed by subtracting a reference mean and dividing by a standard deviation. Averaging standardized measures gives a single summary that can represent several related domains. This can be useful when the scientific question concerns a group of co-occurring symptoms rather than only one symptom domain.

That summary comes with interpretive trade-offs. A composite may be easier to use as one primary outcome, but it can hide differences among its components. The registry’s definition gives the composite a direction: negative values mean improvement, positive values mean worsening, and one unit corresponds to one standard deviation change from the group at baseline. It describes a practical scale range of -2.0 to +2.0. The registry does not report component-specific estimates as part of the primary comparison.

What does the repeated-measures analysis address?

The registry identifies the primary analysis as MMRM, or a mixed model for repeated measures. General statistical explanation: repeated-measures models are designed for outcomes assessed at multiple occasions on the same participants. They can use available follow-up measurements to estimate group patterns over time while accounting for the fact that observations from one person are related to one another. The exact model specification, covariance structure, covariates, and missing-data assumptions are not reported in the registry record, so they should not be inferred from the MMRM label alone.

The registry explicitly says that seven CSM participants and seven ASM participants had no follow-up assessments after baseline and were not included in the primary MMRM analysis, because at least one follow-up data point is required. This explains a stated analysis-population exclusion, but it does not describe every form of missingness or show how missing measurements among participants with some follow-up were handled. The reported group sample sizes are 140 per arm for the primary outcome summary. Further details on the relationship between those summaries and all randomized participants are not reported in the registry record.

How should the unadjusted test be read?

The registry posts an unadjusted p-value for the primary comparison. General statistical explanation: a p-value assesses how compatible the observed data are with a specified null hypothesis under the test’s assumptions. It is not the probability that the null hypothesis is true, and it does not quantify the probability that the observed estimate will replicate. An unadjusted p-value does not account for testing multiple outcomes or comparisons. The registry record does not report a multiplicity adjustment for the posted results.

The p-value should be read alongside the estimated mean difference and its interval. The estimate conveys direction and magnitude on the composite scale; the interval conveys uncertainty around that estimate; and the p-value is a test summary. None of these alone establishes equivalence, clinical importance, or a causal mechanism. Randomization supports a comparison of assigned groups, but interpretation still depends on the outcome definition, analysis population, missing-data handling, and reported analysis details.

Why does over-dispersion matter?

General statistical explanation: over-dispersion arises when the observed variability is greater than a statistical model expects. It is especially relevant to count or binary outcomes when a model assumes a particular variance structure. The primary endpoint is continuous and is reported with means and standard deviations; the registry does not identify an over-dispersion adjustment for it. The adverse-event summaries are counts of affected participants and are not accompanied by a model-based comparative analysis in the registry record. No additional model or correction should be presumed.

11. Confidence Intervals and Precision

The primary estimate is a mean difference of -0.13 for CSM compared with ASM. Its reported interval extends from -0.363 to 0.103. The interval includes zero and spans negative and positive values, so the posted estimate does not pin down the direction of the between-group difference with certainty. It is compatible with a more negative mean in CSM, a more positive mean in CSM, and values near no mean difference.

A confidence interval is generally a way to express the statistical uncertainty around an estimate: narrower intervals indicate greater precision, while wider intervals indicate less precision, given the method used. The registry record does not state the confidence level or all details of the interval method. The interval should therefore be quoted as reported without assigning a confidence level that is not documented. It is also not a range containing a known proportion of individual participant scores; it concerns uncertainty about the estimated group contrast.

The primary group standard deviations were 1.05 for ASM and 0.94 for CSM, reflecting variability in participant composite scores within each arm. The standard deviations describe spread among scores, not uncertainty in the estimated difference itself. The interval and the point estimate address the between-group comparison; the group standard deviations describe within-group dispersion.

The unadjusted p-value for the primary comparison was 0.275. It is consistent with the interval’s inclusion of zero, but it should not be used as a substitute for examining the estimate and its uncertainty. The registry does not report a threshold for a clinically meaningful difference, so statistical precision cannot by itself determine whether any particular value in the interval would matter in practice.

12. Planning a Similar Trial: Sample Size

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

The planning figures are participants per arm, not total events. They are illustrative calculations based on the observed effect, not the original trial’s design assumptions. The stated calculation assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, a normal approximation, and an effect to detect equal to the stated fraction of the observed effect. The trial’s own original sample-size assumptions and justification are not reported in the registry record.

The 80% power column describes the number of participants per arm estimated by the planning calculation to give an 80% chance of detecting the specified effect under those assumptions, if that effect is the one being tested. The 90% power column uses a higher probability of detecting that effect, and therefore gives a larger planned number of participants per arm. These are design-planning quantities, not descriptions of how likely the completed study was to obtain a statistically significant result.

Each row changes the fraction of the observed effect used for planning. For example, the primary-outcome illustration for 100% of the observed effect gives 923 participants per arm for 80% power and 1,235 for 90% power; planning for 50% of the observed effect gives 3,690 per arm for 80% power and 4,940 for 90% power. Smaller effects require more participants to detect under the same assumptions. These figures are not observed power: they are prospective planning illustrations calculated from the posted effect estimate, not a measure of the trial’s achieved power or a substitute for interpreting the estimate and its interval.

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 = -0.130; pooled standard deviation σ = 0.997.
2. n = 2 × (1.96 + 0.842)² × 0.997² / -0.130² = 922.4, rounded up to 923 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 <- -0.13                      # observed difference in means
sigma <- 0.996518941114518                     # 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(1757301)
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 = 923 (80% power), 1,235 (90% power)
 75% of observed effect: n per arm = 1,640 (80% power), 2,196 (90% power)
 50% of observed effect: n per arm = 3,690 (80% power), 4,940 (90% power)
power.t.test: 923.4 
Simulated power at n = 923 per arm: 0.797 (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. Multiplicity, Missing Data and Analysis Populations

Multiplicity concerns arise when a study evaluates more than one outcome or comparison. Each additional test creates another opportunity for a result to appear noteworthy by chance under its null hypothesis. General statistical explanation: adjustment procedures can control specified error rates across a defined family of tests, while a prespecified hierarchy can identify which findings are confirmatory and which are secondary. The registry record does not report a multiplicity adjustment or a complete hierarchy for interpreting the secondary endpoints. The secondary p-values are therefore unadjusted and should not be treated as if they account for all outcomes examined.

The primary outcome is identified as the composite z-score at 12 months. The registry provides a primary MMRM result and states that participants with no post-baseline follow-up were excluded from that analysis. It does not report the original sample-size justification, detailed model specification, covariates, missing-data assumptions, sensitivity analyses, or a full prespecified analysis plan. Those details matter for judging how robust the result is to modeling and data-handling choices.

For missing data, the record identifies one specific exclusion: seven participants in each group had no follow-up after baseline and were not included in the primary MMRM analysis. This is not enough to characterize all missing measurements or determine whether missingness differed in other ways between groups. The registry does not report a detailed accounting of missingness at each assessment, reasons for missing follow-up, or sensitivity analyses addressing alternative assumptions about missing outcomes. The reported primary summaries should therefore be interpreted in light of the stated exclusion, without assuming a particular mechanism for missing data.

The registry does not provide enough information to determine whether the primary analysis followed an intention-to-treat estimand in every respect, how protocol deviations were handled, or what populations were used for other analyses. These omissions do not invalidate the posted estimate, but they limit independent assessment of the analysis choices and the scope of the conclusions.

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 5% reporting threshold.

Most frequent serious adverse event terms

Most frequent non-serious adverse event terms

Serious events with the highest arm-level rate: hospitalization for suicidal behavior (2.7%), hospitalization for wound (2.0%), hospitalization for substance abuse (2.0%), hospitalization for pneumonia (1.4%), hospitalization for heart catheterization (1.4%).

The registry reports serious adverse events for 18 of 147 participants at risk in ASM and 30 of 147 participants at risk in CSM. Other adverse events were reported for 13 of 147 participants at risk in ASM and 72 of 147 participants at risk in CSM. The record also lists 1 death in ASM and 2 deaths in CSM. These are descriptive counts; the registry does not provide a comparative statistical analysis of these figures in the information.

The serious-event terms listed include hospitalization for suicidal behavior, wound, substance abuse, pneumonia, heart catheterization, and planned hernia repair, with the reported percentages ranging from 1.4% to 2.7% across those terms. The registry does not establish from these summaries whether events were caused by an intervention. Counts of participants affected are not interchangeable with the number of separate events, and the record does not give enough detail to infer event duration, severity beyond the serious classification, or relatedness. Differences in counts should be read descriptively, not as proof of a safety difference.

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

The primary comparison estimates the difference in the 12-month composite symptom score between two active approaches to enhancing usual primary care. The reported mean difference is -0.13 for CSM compared with ASM, and its interval includes zero. The estimate’s direction is toward a more negative average score in CSM, but uncertainty extends to values on either side of no difference. The posted result therefore does not precisely settle the direction or size of the group contrast.

This result does not show that the groups are equivalent. Equivalence requires a defined margin and an analysis designed to assess whether the difference falls within that margin; such a margin is not reported in the registry record. Nor does the result establish clinical importance, because no threshold for a meaningful between-group change is reported. It also does not indicate whether either management approach should be selected for an individual. The registry comparison concerns group-level estimates, not personalized treatment decisions.

The contrast is specific to the trial’s approaches: ASM included monitoring and self-management modules, while CSM added nurse-physician care management. It is not a comparison of comprehensive management with no care or no symptom support. The secondary results offer separate information about pain, depression, and anxiety, but their unadjusted status and intervals that include zero limit confirmatory interpretation. The composite result and secondary findings should be considered together without treating the secondary measures as a replacement primary endpoint.

Finally, the registry record gives only selected details about the analysis. It reports the MMRM label and identifies participants with no follow-up who were excluded, but does not provide the full model specification or detailed missing-data analyses. These limitations affect how completely the estimate can be independently evaluated. The most direct reading is that the registry reports a modest point estimate with appreciable uncertainty, rather than a definitive demonstration of benefit, harm, or equivalence.

17. Why This Trial Matters Statistically

Statistically, CAMMPS illustrates the challenge of evaluating an intervention aimed at several related symptoms at once. The primary composite combines standardized measures of pain, anxiety, and depression, matching the trial’s stated focus on their co-occurrence. That approach produces a single outcome for the principal comparison, but the composite must be interpreted as a combined measure rather than as a result for any one symptom domain.

The active-comparator design is also important. Both groups received automated symptom monitoring and self-management modules, while the comprehensive arm added nurse-physician care management. The relevant contrast is therefore the incremental difference between these management strategies as defined in the registry. This makes the estimate distinct from a comparison of care against no support.

The record also demonstrates why a point estimate should be read with its interval. The primary estimate has a direction, but its reported interval crosses zero. A single p-value cannot convey that range of plausible contrasts or answer whether a difference is practically important. Because the registry does not state a meaningful-difference threshold, clinical importance cannot be inferred from statistical summaries alone.

Finally, the study’s reported analysis population and the stated absence of follow-up for some participants matter to interpretation, as do unadjusted secondary comparisons. The record offers useful evidence about the estimated group contrast, while leaving aspects of the analysis plan and missing-data handling unreported. Keeping those limits visible is central to reading a completed randomized trial carefully.

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.

Several trial-specific details needed for a full appraisal are not reported in the registry record. These include the original sample-size justification, randomization implementation, identity of those masked, full MMRM specification, covariates, and the detailed assumptions used to handle missing measurements. The registry reports the primary analysis exclusion for participants with no follow-up after baseline, but does not provide a full account of missing data by assessment or sensitivity analyses.

The primary composite combines three standardized symptom measures. This aligns with a multidomain question, but the posted primary comparison does not separate the contribution of pain, anxiety, or depression. Secondary results provide some domain-specific context, but they are unadjusted and their interpretation is limited by multiplicity. A separate secondary BPI comparison is not reported in the registry record, although BPI is named as a component of the primary composite.

The record provides one 12-month primary comparison and does not report enough detail to assess the full trajectory of symptoms or the stability of the estimate over time. It also does not report a threshold for a clinically meaningful difference on the composite. The adverse-event figures are descriptive counts without a reported comparative analysis or event-relatedness assessment in the available record. These limitations constrain interpretation of precision, clinical importance, safety comparisons, and the extent to which the posted results can be independently reproduced.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Comprehensive vs. Assisted Management of Mood and Pain Symptoms — NCT01757301.
• Registry record last updated 2019-03-13; status last verified 2019-03.
• Results first posted 2019-03-13.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

22. Record Summary

CAMMPS was a completed randomized, parallel-group trial comparing Assisted Symptom Management with Comprehensive Symptom Management among Veterans with pain and comorbid anxiety and/or depression. CSM added nurse-physician care management to the monitoring and self-management components used in ASM. The primary endpoint was a 12-month composite z-score derived from pain, anxiety, and depression measures.

The primary mean difference for CSM compared with ASM was -0.13, with a reported interval from -0.363 to 0.103 and an unadjusted p-value of 0.275. The interval includes zero, and the registry does not report a threshold for a clinically meaningful difference. Secondary symptom estimates are unadjusted. The record notes that seven participants in each group had no post-baseline follow-up and were excluded from the primary MMRM analysis. Further details about the original design assumptions, full analysis plan, and missing-data sensitivity analyses are not reported in the registry record.