With Love: Using Promotoras for a Hispanic Community Palliative Care Promotora Palliative Care: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for With Love: Using Promotoras for a Hispanic Community Palliative Care Promotora Palliative Care (NCT03736031), a randomized na study. The primary outcome is Patient Health Questionnaire - 9 (PHQ-9).

2. Clinical Question

3. Trial Design

This was a completed, randomized, parallel-group pilot study sponsored by Texas Tech University Health Sciences Center, El Paso. The registry lists an enrollment of 102 and identifies the study intervention as behavioral. It lists the phase as NA. The study start date was 2018-05-08, and the primary completion date was 2019-10-04.

Participants were assigned to an Intervention (Promotora) group or a Self-Education (Control) group. The intervention description specifies three face-to-face meetings with a promotora. Both groups were to continue standard care for their oncologic diagnosis, as determined by the treating oncologist. The registry describes surveys covering demographics, quality of life, and pain management for the control group; the intervention description also indicates that participants completed surveys, though its text is truncated.

The trial is listed as single-masked, but which participants, clinicians, or assessors were masked is not reported in the registry record. The method used to generate the random allocation sequence, concealment of allocation, and the planned allocation ratio are also not reported in the registry record. It is therefore possible to describe the design as randomized and parallel, but not to assess the details of how randomization and masking were implemented.

The registry lists emergency department visits and intensive care unit admissions as secondary outcomes. It reports four outcome measures and four analyses, but the available record does not identify the analyses in enough detail to explain their methods or connect each one to a particular outcome. The study is described as a pilot; its sample-size justification and any prespecified decision criteria for progressing beyond a pilot 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: Participant enrollment and randomization occured at the same time. There were no enrolled participants excluded from the study before assignment to groups.

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 Patient Health Questionnaire - 9 (PHQ-9), measured over The PHQ-9 was administered at baseline and then again about six weeks later when study participation is completed...

The primary endpoint was the Patient Health Questionnaire-9 (PHQ-9), a continuous score. The registry gives its range as 0 to 27 and states that a lower score indicates a better outcome. The measure was administered at baseline and again about six weeks later, when study participation was completed.

In general, a questionnaire score can provide a standardized way to summarize participants’ reported symptoms or experiences. Repeated measurement can describe how scores change over time, while a comparison between randomized groups can help estimate whether the groups had different outcome patterns. Those are general reasons to use a measure such as the PHQ-9 in a clinical study; the registry does not state a specific rationale for selecting it as the primary endpoint.

The record identifies the score, its direction, and the approximate timing of measurement, but does not report a single primary-outcome comparison. It also does not specify whether the intended analysis was based on follow-up scores, change from baseline, or another summary. Without a reported estimate and its uncertainty, the outcome description alone cannot show how the groups’ PHQ-9 results differed.

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The registry identifies the study as randomized and parallel-group. In general, random assignment is intended to make the groups comparable, on average, with respect to factors that could affect outcomes. A parallel design follows distinct groups assigned to different study arms. These general design principles do not establish that allocation was concealed or that the groups were balanced in this particular study. The method of sequence generation, allocation concealment, and allocation ratio are not reported in the registry record.

What does the primary endpoint represent?

The endpoint is a continuous PHQ-9 score, reported as a mean with standard deviation. A mean describes the average score in a group, while a standard deviation describes the spread of individual scores around that group’s mean. They answer different questions: the mean summarizes the group’s location on the scale, and the standard deviation describes variation among participants. The registry gives the score range as 0 to 27 and says lower scores indicate a better outcome.

The measurement schedule includes baseline and a follow-up about six weeks later. A comparison could be framed using follow-up scores, change from baseline, or a model that accounts for repeated measurements. These approaches can target different estimands and can make different assumptions. The registry record does not specify which approach was planned or used, nor does it report a single comparison that can be interpreted as the primary result.

How should uncertainty be understood?

In general, a confidence interval presents a range of effect values compatible with the observed data under the assumptions of the statistical method. A narrow interval indicates greater precision than a wide interval, although precision alone does not establish clinical importance. A p-value addresses compatibility with a specified null hypothesis and model; it is not the probability that the null hypothesis is true, and it does not describe the size of an effect. No primary-outcome estimate, confidence interval, or p-value is reported in the registry information.

For a continuous outcome, interpretation depends on the scale and on the contrast being estimated. A difference in group means, for example, would express a contrast in PHQ-9 points. Whether a difference is meaningful would require relevant clinical context or a prespecified threshold, neither of which is reported in the registry record. The outcome’s direction is stated, but a meaningful-difference threshold is not.

What can be said about the analysis plan?

The record lists four analyses and four outcome measures, but does not report enough analysis details to identify the statistical model, adjustment variables, hypothesis-testing approach, or handling of repeated measurements. It does not report whether analyses were conducted according to randomized assignment or restricted to participants with observed follow-up data. Those details matter because analytic choices affect both the estimated comparison and its uncertainty.

In general, adjustment for baseline measurements can sometimes improve precision, while a model for repeated observations can use information from more than one measurement occasion. These methods require assumptions and a clearly defined target comparison. Their use in this trial cannot be inferred from the outcome schedule alone. The statistical plan, including any interim analyses, is not reported in the registry record.

What does over-dispersion mean in general?

For count outcomes, over-dispersion means that observed variability exceeds what a chosen count model expects. If it is ignored, standard errors can be too small and confidence intervals too narrow. This is a general issue for analyses of counts; the registry does not report a count model or state whether over-dispersion was assessed for emergency department visits or intensive care unit admissions.

The sample-size assumptions describe a planning illustration based on the observed effect, with a two-sided significance level of 0.05, equal allocation, and a normal approximation. The assumptions state that the effect to detect is a stated fraction of the observed effect and distinguish participants per arm for most outcomes from total events for time-to-event outcomes. The numerical planning illustrations and a trial-specific sample-size justification are not reported in the registry record. Such illustrations are planning tools, not observed power and not evidence about the outcome results.

10. Multiplicity, Missing Data and Analysis Populations

The registry lists four outcome measures and four analyses, but the available information does not identify all outcomes, their hierarchy, or how the analyses map to particular outcomes. It does not report whether one endpoint was designated as the sole confirmatory test, whether secondary comparisons were adjusted for multiplicity, or how multiple time points or subgroup analyses were handled. A multiplicity strategy is therefore not reported in the registry record.

In general, testing many outcomes or contrasts can increase the chance of at least one apparently unusual result under a setting where none of the effects is real. Adjustment methods, prespecified hierarchies, or clear separation of confirmatory and exploratory analyses can help readers understand that risk. This general concern cannot be resolved for the trial without its analysis plan and results.

The registry describes baseline and follow-up PHQ-9 measurement, but does not report the number of participants with observed scores at each time point or how missing measurements were handled. It does not state whether missing data were imputed, excluded, or addressed with a model, or what assumptions were made about why data might be missing. The 102 enrolled participants should not automatically be treated as the number with complete primary-outcome data.

The analysis population is also not described in the available record. It is not reported whether the primary analysis included all randomized participants, only participants who completed follow-up, or another defined group. Without this information, readers cannot determine how missing observations or post-randomization exclusions may have affected the analysis.

11. 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: hospital admission (3.6%).

The registry lists serious adverse events for each group using counts and numbers at risk: 2 serious adverse events among 56 participants at risk in the Intervention (Promotora) group, and 1 among 46 participants at risk in the Self-Education (Control) group. Hospital admission is listed as the leading serious-event term, with 3.6%. The record does not give enough detail to determine the event-level circumstances or the denominator used for that percentage.

The registry also lists 27 other adverse events among 56 participants at risk in the intervention group and 21 among 46 at risk in the control group. It reports 2 deaths in the intervention group and 4 in the control group. These are descriptive counts, not adjusted comparisons. The record does not state whether deaths were considered related to the intervention or study procedures, and it does not provide the timing or causes of death.

In general, adverse-event counts need context, including definitions, observation time, seriousness criteria, and assessment of relatedness. Those details are not reported in the registry record. The counts should therefore be read as reported event information, not as proof that the intervention caused or prevented an event.

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

The study addresses an access and education challenge described in the registry: palliative care is not widely integrated in oncology, and access and uptake are described as lower in rural and Hispanic communities. Its approach was to use community health workers, also known as promotoras, to provide a palliative care intervention for Hispanic oncology patients. The randomized, parallel-group pilot design provides a framework for comparing that approach with a Self-Education control while participants continued standard oncologic care.

The registry information establishes the intervention’s stated format, the primary measure, and the measurement schedule. It does not provide a single primary-outcome comparison. Consequently, it cannot establish the size or precision of a PHQ-9 difference between groups. The listed emergency department visit and intensive care unit admission outcomes also lack comparative results in the information available. No conclusion about those outcomes can be drawn from their names alone.

In general, a pilot study can help establish whether a larger evaluation is feasible and can inform later study planning. A pilot’s role and decision criteria depend on its prespecified objectives; those objectives beyond the intervention description are not reported in the registry record. The record does not provide enough information to judge recruitment, retention, acceptability, or implementation fidelity.

The reported adverse-event and death counts are useful descriptive information, but they do not establish causation. The registry does not report event attribution or sufficient context to determine whether differences in the counts reflect the intervention, participants’ underlying conditions, chance, or other factors.

Overall, the record supports a description of a completed randomized pilot and its intended comparison. It does not support a conclusion that the promotora approach improved, worsened, or had no effect on the primary outcome or the named secondary outcomes. Such conclusions require comparative outcome estimates, their uncertainty, and sufficient information about the analysis and completeness of follow-up.

13. Why This Trial Matters Statistically

Several statistical features make this study a useful example for reading a pilot-trial record carefully. Randomization and a parallel-group design describe how the comparison was structured, but they do not substitute for reporting the result. For the primary PHQ-9 endpoint, readers need a defined contrast and an estimate with uncertainty to understand the direction, magnitude, and precision of the group comparison. The registry information does not report a single such comparison.

The outcome was measured at baseline and about six weeks later, which raises an important interpretive question: does the analysis compare follow-up scores, changes from baseline, or repeated measurements in a model? These approaches are not interchangeable by default. The registry record does not identify the intended or reported approach. This illustrates why outcome timing alone is not enough to reconstruct a statistical analysis.

The record also lists multiple outcome measures and analyses without detailing their relationship or any multiplicity strategy. In general, when a study evaluates multiple outcomes, readers need to know which comparisons were central and how additional tests were interpreted. Likewise, sample-size planning illustrations are not a substitute for a sample-size justification tied to a prespecified target effect, and they are not evidence of observed power. The trial-specific justification is not reported.

Finally, the safety counts illustrate the limits of descriptive event data. Counts by group are worth noting, but without definitions, timing, relatedness assessments, and a clear analysis plan, they cannot establish why events occurred. The statistical lesson is to distinguish what the record documents—the design, endpoint definition, and event counts—from what requires comparative estimates and additional methods information.

14. 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 primary limitation for interpreting efficacy is that the registry record does not report a single PHQ-9 comparison. It gives the score range, direction, and approximate follow-up timing, but not group-level outcome estimates, change estimates, confidence intervals, or p-values. The magnitude and precision of any primary-outcome difference therefore cannot be assessed from the recorded information.

The trial’s planned analysis is not described in sufficient detail. The record does not state how the baseline and follow-up measurements were modeled, which analysis population was used, how missing data were handled, or whether analyses adjusted for other variables. It also does not describe any multiplicity approach across the listed outcome measures and analyses.

Important design details are absent: the randomization sequence method, allocation concealment, allocation ratio, and the identity of those masked are not reported in the registry record. The eligibility criteria and detailed participant characteristics are not included in the available information. The intervention description for one group is truncated, and the control activities are not described beyond standard care and surveys.

Although the registry lists emergency department visits and intensive care unit admissions as secondary outcomes, their results are not reported in the available information. Safety information lacks event-level context, timing, and attribution. The trial-specific sample-size justification and the rationale for the selected endpoint are also not reported. These gaps limit assessment of both the strength of the evidence and how broadly the findings might apply.

15. Related Tutorials

16. Related Statistical Calculators

17. Sources

• ClinicalTrials.gov: With Love: Using Promotoras for a Hispanic Community Palliative Care Promotora Palliative Care — NCT03736031.
• Registry record last updated 2020-10-26; status last verified 2020-10.
• Results first posted 2020-10-26.
• 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.

18. Record Summary

NCT03736031 is a completed randomized, single-masked, parallel-group pilot study sponsored by Texas Tech University Health Sciences Center, El Paso. The registry lists an enrollment of 102. The intervention involved three face-to-face meetings with a promotora; the comparator was Self-Education (Control), with standard oncologic care continuing in both groups.

The primary outcome was PHQ-9 score, measured at baseline and about six weeks later. The registry states that the score ranges from 0 to 27 and that lower scores indicate a better outcome. It also lists emergency department visits and intensive care unit admissions as secondary outcomes. A single primary-outcome comparison and comparative results for the named secondary outcomes are not reported in the registry record.

The record lists serious adverse events, other adverse events, and deaths by group, but does not provide enough contextual detail to establish causation. The statistical analysis plan, missing-data handling, analysis populations, and trial-specific sample-size justification are not reported.