This page separates the registered trial design and endpoint from statistical interpretation. The ClinicalTrials.gov record provides the registered study information and primary endpoint, while formal statistical analyses and outcome estimates are not posted in the record.
1. Trial at a Glance
HD10 is a clinical trial in early stage Hodgkin lymphoma patients with bulky lesions. The registry describes the study as evaluating the feasibility of interim dual-point PET acquisition in real-world clinical practice and describing the outcome of these patients.
| Feature | HD10 |
|---|---|
| Study acronym | HD10 |
| Condition | Hodgkin's Lymphoma |
| Population | Early stage Hodgkin lymphoma patients with bulky lesions |
| Intervention / study focus | Dual point PET scan acquisition |
| Number of arms | 1 |
| Enrollment | 150 |
| Primary endpoint | Event free survival (EFS) |
| Primary endpoint time frame | 1 year |
| Study status | UNKNOWN |
| Start date | 2012-01 |
| Primary completion date | 2015-10 |
| Lead sponsor | Ospedale Santa Croce-Carle Cuneo |
| Sponsor type | OTHER |
| ClinicalTrials.gov | NCT01399931 |
2. Clinical Question
The registry's central question is whether interim dual-point PET acquisition is feasible in the real-world clinical practice of early stage Hodgkin lymphoma patients with bulky lesions, while also describing their outcome.
Population
Early stage Hodgkin lymphoma patients with bulky lesions.
Intervention
Interim dual-point PET acquisition as described by the registry.
Comparator
The registry lists 1 study arm. A separate randomized comparator arm is not reported in the ClinicalTrials.gov record.
Primary question
Can interim dual-point PET acquisition be used feasibly in real-world clinical practice, while describing the 1-year event-free survival outcome?
3. Trial Design
The single-arm structure is important for statistical interpretation. In a randomized comparative trial, treatment effects can be expressed as contrasts between randomized groups. Here, the registry records one study arm, so the primary endpoint is naturally framed as an outcome measure within the enrolled population rather than as a randomized treatment effect.
4. Endpoints
| Endpoint | Time frame | Registry definition |
|---|---|---|
| Event free survival (EFS) | 1 year | To assess feasibility of using interim dual-point acquisition PET in real world of clinical practice as well as describing the outcome of early stage HL patients. |
The registered primary endpoint is event free survival (EFS) with a 1-year time frame. The endpoint description combines two study objectives: assessing the feasibility of interim dual-point PET acquisition in real-world clinical practice and describing the outcome of early stage Hodgkin lymphoma patients.
What the 1-year EFS endpoint represents
Event-free survival is a time-to-event endpoint. In a typical EFS analysis, each participant contributes follow-up from an appropriate time origin until an event occurs or the observation is censored. The event definition itself is central to interpreting an EFS estimate; the ClinicalTrials.gov endpoint description identifies EFS but does not provide a more detailed event-definition breakdown in the information reported here.
Here, T represents the time to the event defined for the endpoint. At a fixed time such as 1 year, a survival estimate describes the estimated probability of remaining event-free beyond that time under the specified endpoint definition.
5. Statistical Methodology
The ClinicalTrials.gov record identifies EFS as the primary endpoint but does not post statistical analyses for the endpoint. It also does not provide a reported treatment-effect estimate, confidence interval, or p-value.
For a single-arm time-to-event endpoint such as 1-year EFS, a standard descriptive analysis would generally begin with a Kaplan-Meier estimator. This approach allows participants with different amounts of follow-up to contribute information while accounting for right censoring.
Kaplan-Meier estimation
The Kaplan-Meier method estimates the event-free survival function over follow-up. At each observed event time, the estimated survival probability is updated according to the number of events and the number of participants still under observation immediately before that time.
where di is the number of events at time ti and ni is the number at risk immediately before that time.
One-year EFS estimation
The primary time frame is 1 year. If individual event and censoring times were available, the Kaplan-Meier curve could be evaluated at 1 year to obtain an estimated EFS probability. A confidence interval could then quantify uncertainty around that estimate.
Why a hazard ratio is not the natural primary statistic here
A hazard ratio is a comparative measure between groups or covariate-defined hazard functions. Because the registry records 1 study arm, there is no randomized treatment-versus-control contrast in the registered design from which a treatment hazard ratio would be obtained.
Descriptive question
What proportion of participants remains event-free at 1 year, accounting for censoring?
Comparative question
Does one randomized treatment produce a different EFS distribution from another treatment? That question requires a comparative design, which is not recorded here.
No formal statistical analyses were posted to ClinicalTrials.gov.
6. Statistical Methods Explained
Why is Kaplan-Meier estimation appropriate for EFS?
EFS is a time-to-event outcome. Participants may have different lengths of observable follow-up, and some may reach the end of observation without an event. Kaplan-Meier estimation handles this right-censoring structure while using the available follow-up from each participant.
What does a 1-year EFS estimate mean?
A 1-year EFS estimate represents the estimated probability of remaining event-free through 1 year under the endpoint definition. It is different from the proportion of patients simply observed to have no event in a complete 1-year dataset because censoring and unequal follow-up can affect the estimate.
Why is censoring important?
If a participant is event-free at the last time they can be observed, the participant's outcome after that point is unknown. Rather than treating that person as having experienced an event, a time-to-event analysis generally censors the observation at the last informative follow-up, provided the censoring assumptions are appropriate.
Why is a single-arm study different from a randomized trial?
A randomized trial estimates differences between treatment assignments because randomization establishes the comparison groups. A single-arm study instead describes outcomes within the enrolled cohort. Without a separate randomized comparator, an observed EFS estimate cannot by itself establish that an intervention caused a particular outcome relative to another treatment.
What would a confidence interval add?
A confidence interval around a 1-year EFS estimate would quantify statistical uncertainty associated with the estimated survival probability. A narrow interval would indicate greater statistical precision than a wide interval, all else equal. The interval would not describe the range of individual patient outcomes.
Why does feasibility matter statistically?
The endpoint description explicitly includes feasibility of using interim dual-point PET in real-world clinical practice. Feasibility is a different statistical concept from efficacy. A feasibility objective may concern whether the imaging approach can be implemented as intended, whereas EFS describes a time-to-event outcome. The two objectives therefore answer different questions even though they appear in the same primary endpoint description.
7. Planned Analysis
The registry identifies event free survival (EFS) at 1 year as the primary endpoint and describes the objective as assessing the feasibility of interim dual-point PET acquisition in real-world clinical practice while describing the outcome of early stage Hodgkin lymphoma patients.
For an endpoint of this type, the usual statistical framework would be a time-to-event analysis using Kaplan-Meier estimation. The resulting survival function can be evaluated at 1 year to estimate the probability of remaining event-free through that time point, with appropriate handling of censored observations.
If the analysis were intended to summarize uncertainty, a confidence interval around the 1-year EFS estimate would ordinarily accompany the point estimate. If the study had a prespecified benchmark or historical comparison, that benchmark could provide a separate hypothesis-testing framework; the registry information reported here does not specify such a comparator or benchmark.
8. Interpreting a Single-Arm EFS Study
A reported 1-year EFS estimate would describe the estimated event-free status of the enrolled cohort at the prespecified time point. Its interpretation would depend on the exact event definition, censoring rules, follow-up completeness, and analysis population.
An EFS estimate from a single-arm study would not by itself establish that dual-point PET caused a particular outcome. Causal treatment comparisons require an appropriate comparator or another design that supports the relevant causal contrast.
EFS is not a universal event definition. Different studies can define an event using different combinations of progression, relapse, death, treatment failure, or other outcomes. The registry identifies EFS as the endpoint but does not provide a more detailed event-component definition in the reported record.
A 1-year endpoint requires adequate observation through the relevant time horizon. Participants with incomplete follow-up contribute information according to the time-to-event analysis, but extensive or informative loss to follow-up can affect the reliability of the resulting estimate.
9. What the Registry Does and Does Not Establish
| Question | What the ClinicalTrials.gov record establishes |
|---|---|
| Who was studied? | Early stage Hodgkin lymphoma patients with bulky lesions. |
| What was studied? | Interim dual-point PET acquisition in real-world clinical practice. |
| How many participants were enrolled? | 150. |
| How many study arms were registered? | 1. |
| What was the primary endpoint? | Event free survival (EFS). |
| What was the primary time frame? | 1 year. |
| What was the registered study objective? | To assess feasibility of using interim dual-point acquisition PET in real world of clinical practice as well as describing the outcome of early stage HL patients. |
| Were formal statistical analyses posted? | No. |
| Was an EFS estimate posted? | No. |
| Was a confidence interval posted? | No. |
| Was a p-value posted? | No. |
10. Design Topics Relevant to This Trial
Non-inferiority margin
A non-inferiority margin is not reported in the ClinicalTrials.gov record. Because the registry records 1 study arm, the available design information does not describe a randomized non-inferiority comparison.
Crossover
A crossover design is not reported in the ClinicalTrials.gov record. No treatment crossover structure is described in the registered information.
Factorial design
A factorial design is not reported. The registry records 1 study arm rather than a factorial allocation structure.
Multiplicity
The record identifies 1 registered primary endpoint, EFS at 1 year. It does not report an alpha-allocation strategy, multiplicity adjustment, or hierarchical testing procedure.
Interim analysis
The intervention concerns interim dual-point PET acquisition, but that phrase describes the timing or structure of the imaging acquisition rather than establishing that a formal interim statistical analysis was performed. The registry does not report an interim efficacy analysis, alpha-spending procedure, or stopping boundary.
Missing data and imputation
The registry information does not report a missing-data strategy or imputation method. For a time-to-event endpoint, incomplete follow-up is ordinarily handled through censoring rather than automatically replacing an unobserved event time with an imputed value.
Stratification
No randomization stratification factors are reported. The registered study has 1 arm, so the usual randomized stratified-treatment comparison framework does not apply to the design as recorded.
Bayesian methods
No Bayesian statistical method is reported in the ClinicalTrials.gov record.
11. Limitations
- Single-arm design: the registry records 1 study arm, so the design does not provide a randomized treatment-versus-control comparison.
- Endpoint detail: EFS is registered with a 1-year time frame, but the record does not provide a more detailed breakdown of the events composing the endpoint.
- No posted statistical analysis: formal statistical analyses, effect estimates, confidence intervals, and p-values are not posted in the ClinicalTrials.gov record.
- No reported comparator: the registry does not identify a separate randomized comparator arm.
- No reported analysis population: the available record does not specify separate intention-to-treat, per-protocol, or safety analysis populations.
- No reported censoring rules: the available registry information does not specify detailed censoring conventions for the EFS analysis.
- No reported missing-data strategy: the registry does not describe how incomplete follow-up or other missing information was handled statistically.
- Status uncertainty: the ClinicalTrials.gov record lists the study status as UNKNOWN.
- Generalizability: interpretation of the outcome is tied to the population described by the registry: early stage Hodgkin lymphoma patients with bulky lesions.
12. Why This Trial Matters Statistically
HD10 is a useful teaching example because it illustrates the difference between a clinical endpoint and a comparative treatment effect. The registered primary endpoint is event-free survival at 1 year, while the study has 1 registered arm. That structure changes which statistical questions can be answered directly.
| Concept | How it appears in HD10 |
|---|---|
| Time-to-event analysis | The primary endpoint is event free survival. |
| Fixed time horizon | EFS is assessed at 1 year. |
| Kaplan-Meier estimation | A standard approach for estimating EFS over time while accounting for censoring. |
| Censoring | Relevant to interpreting any time-to-event estimate when complete event information is unavailable for every participant. |
| Single-arm design | The registry records 1 study arm, so interpretation centers on cohort outcome rather than a randomized treatment contrast. |
| Confidence intervals | Would quantify uncertainty around an estimated EFS probability if an estimate were reported. |
| Endpoint definition | The exact meaning of EFS depends on the events included in its definition. |
| Feasibility versus efficacy | The registered objective combines feasibility of dual-point PET acquisition with description of patient outcome. |
| Missing-data interpretation | Incomplete follow-up is an important consideration for any 1-year time-to-event analysis. |
13. A Statistical Reading of the Primary Endpoint
The phrase event free survival (EFS), 1 year contains several statistical ideas in a compact form. First, it identifies a time-to-event outcome rather than a simple binary endpoint. Second, it specifies a fixed evaluation horizon. Third, it implies that follow-up duration and censoring must be incorporated into the analysis rather than simply counting participants who happen to have an event by the end of observation.
The distinction is important. Suppose a participant remains event-free for part of the observation period but is no longer observed before 1 year. That participant has contributed information about the event-free experience up to the last known follow-up, but the participant's status at exactly 1 year is not directly observed. Kaplan-Meier methodology is designed to use this partial follow-up without automatically classifying the participant as either an event or a 1-year survivor.
The resulting EFS curve would therefore provide more information than a single crude proportion when follow-up times differ. A 1-year estimate extracted from that curve would summarize the estimated event-free probability at the prespecified time point.
Why a crude proportion can differ from Kaplan-Meier EFS
A simple proportion might divide the number of participants known to be event-free at 1 year by the number enrolled. That calculation requires adequate 1-year status for the relevant participants and does not naturally accommodate different censoring times. Kaplan-Meier estimation instead uses the risk set at each event time and accounts for censoring during follow-up.
Why the one-arm structure changes interpretation
In a randomized trial, an EFS curve can be compared between treatment groups, often using a stratified log-rank test and a Cox model. In a single-arm study, the EFS curve is instead a description of the observed cohort. A comparison to an external historical benchmark would require that benchmark to be specified and justified separately, including consideration of differences in patient selection, endpoint definitions, follow-up, and calendar period.
14. Feasibility and Outcome Are Distinct Statistical Questions
Feasibility
The registry describes an objective of assessing whether interim dual-point PET acquisition can be used in real-world clinical practice.
Outcome
The registered primary endpoint is event free survival at 1 year, providing a time-to-event framework for describing patient outcome.
These objectives should not be conflated. A procedure or measurement strategy can be feasible to implement without demonstrating an improvement in a clinical outcome. Conversely, an outcome analysis can describe the course of a patient cohort without establishing that the imaging approach caused that course.
The registry wording therefore places methodological feasibility and patient outcome alongside one another. Statistically, each objective requires its own operational definition and appropriate analysis framework.
15. Study Timeline
Study start
The ClinicalTrials.gov record lists January 2012 as the study start date.
Primary completion
The record lists October 2015 as the primary completion date.
UNKNOWN
The ClinicalTrials.gov record currently identifies the study status as UNKNOWN.
16. What Would Be Needed to Interpret a Reported 1-Year EFS Estimate?
A numerical EFS estimate is most useful when accompanied by the statistical context needed to understand how it was obtained. For this trial, that context would include the precise event definition, the time origin, censoring rules, the number of participants contributing follow-up, the number and timing of events, and the method used to calculate uncertainty.
| Information | Why it matters |
|---|---|
| Event definition | Determines what counts as an EFS event and therefore what the endpoint represents. |
| Time origin | Defines when follow-up begins for each participant. |
| Event times | Determine the changes in the estimated event-free survival curve. |
| Censoring times | Determine how much follow-up each participant contributes without an observed event. |
| Number at risk | Provides context for the amount of information supporting the estimate at different times. |
| Confidence interval method | Determines how statistical uncertainty around the survival estimate is quantified. |
| Analysis population | Defines which participants are included in the reported estimate. |
Without these elements, the phrase "1-year EFS" identifies the endpoint and time horizon but does not by itself provide a complete statistical result.
17. Sources
- ClinicalTrials.gov: HD10 (NCT01399931).
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18. Record Summary
HD10 is registered as a 150-participant, 1-arm clinical trial evaluating dual-point PET acquisition in early stage Hodgkin lymphoma patients with bulky lesions. Its primary endpoint is event free survival at 1 year, with the stated objective of assessing the feasibility of interim dual-point PET acquisition in real-world clinical practice while describing patient outcome.
Statistically, the key feature is the combination of a time-to-event primary endpoint and a single-arm design. A Kaplan-Meier framework is a natural method for estimating EFS over time and obtaining a 1-year estimate while accounting for censoring. Interpretation of such an estimate requires attention to the endpoint definition, follow-up, censoring, and analysis population. Because the registry does not post formal statistical analyses or outcome estimates, the ClinicalTrials.gov record establishes the study design and registered endpoint rather than a numerical EFS result.