This page provides an independent statistical analysis and educational interpretation of publicly reported results. ClinicalTrials.gov provides the official trial registry record. Numerical trial results on this page are restricted to the ClinicalTrials.gov record.
1. Trial at a Glance
RESORCE was a randomized, parallel-group, quadruple-masked phase 3 treatment trial evaluating regorafenib versus placebo in patients with hepatocellular carcinoma. The registry reports 573 enrolled participants, two study arms, one primary time-to-event endpoint, and posted statistical analyses using log-rank, stratified Cox, and Cochran-Mantel-Haenszel methods.
| Feature | RESORCE |
|---|---|
| Trial name | RESORCE |
| Brief title | Study of Regorafenib After Sorafenib in Patients With Hepatocellular Carcinoma |
| Phase | Phase 3 |
| Status | COMPLETED |
| Condition | Carcinoma, Hepatocellular |
| Allocation | RANDOMIZED |
| Design model | PARALLEL |
| Masking | QUADRUPLE |
| Primary purpose | TREATMENT |
| Enrollment | 573.0 |
| Interventions | Regorafenib (Stivarga, BAY73-4506); Placebo |
| Lead sponsor | Bayer |
| Sponsor type | INDUSTRY |
| Primary endpoint | Overall Survival (OS) |
| Primary endpoint type | Time-to-event |
| Hypothesis type | Superiority |
| Results posted | Yes |
| Statistical analyses posted | 15 |
2. Clinical Question
The central statistical question was whether randomized assignment to regorafenib could improve overall survival compared with placebo in patients with hepatocellular carcinoma, using a superiority framework.
Population
Patients enrolled in the RESORCE phase 3 study with the condition listed as carcinoma, hepatocellular.
Intervention
Regorafenib (Stivarga, BAY73-4506), including the 160 mg treatment specified in the posted statistical analyses.
Comparator
Placebo.
Primary question
Does regorafenib produce a different time-to-death distribution from placebo under the prespecified superiority comparison?
3. Trial Design
Regorafenib
- Regorafenib (Stivarga, BAY73-4506)
- Posted primary and secondary analyses specify Regorafenib 160 mg (BAY73-4506)
- Serious adverse events: 194 affected among 374 at risk
Placebo
- Placebo
- Compared directly with regorafenib in the posted analyses
- Serious adverse events: 92 affected among 193 at risk
The registry identifies the design as randomized and parallel with quadruple masking. It therefore establishes a randomized treatment comparison rather than an observational comparison between patients who chose different therapies.
4. Trial Timing and Registry Scope
Trial start
The registry lists 2013-05-14 as the study start date.
Primary completion
The registry lists 2016-02-29 as the primary completion date.
Current registry status
The ClinicalTrials.gov record identifies the study status as COMPLETED and reports results.
5. Endpoints
Primary endpoint
| Endpoint | Registry definition | Time frame |
|---|---|---|
| Overall Survival (OS) | Overall Survival (OS) was defined as the time from date of randomization (Day 1) to death due to any cause. Subjects still alive at the time of analysis were censored at their last date of last contact. | From randomization (Day 1) of the first subject until 419 days later |
Secondary endpoints with posted analyses
| Endpoint | Type | Registry time frame | Method |
|---|---|---|---|
| Time to Progression (TTP) | Time-to-event | From date of randomization until 30 days after last study treatment (assessed every 6 weeks until PD; and after 8 cycle assessed every 12 weeks) (approximately 33 months) | Log-rank test |
| Progression Free Survival (PFS) | Time-to-event | From date of randomization until 30 days after last study treatment (assessed every 6 weeks until PD; and after 8 cycle assessed every 12 weeks) (approximately 33 months) | Log-rank test |
| Objective Tumor Response Rate (ORR) | Binary | From date of randomization until 30 days after last study treatment (assessed every 6 weeks until PD; and after 8 cycle assessed every 12 weeks) (approximately 33 months) | Cochran-Mantel-Haenszel test |
| Disease Control Rate (DCR) | Binary | From date of randomization until 30 days after last study treatment (assessed every 6 weeks until PD; and after 8 cycle assessed every 12 weeks) (approximately 33 months) | Cochran-Mantel-Haenszel test |
6. Statistical Methodology
The posted analyses use two principal statistical families. Time-to-event outcomes were analyzed with log-rank testing and Cox regression, with several analyses explicitly identified as stratified or unstratified sensitivity analyses. Binary response outcomes were analyzed with the Cochran-Mantel-Haenszel test.
| Statistical component | How it appears in RESORCE | Purpose |
|---|---|---|
| Log-rank test | Used for OS, TTP, and PFS analyses | Compares time-to-event experience between randomized groups |
| Cox regression | Used to calculate hazard ratios and confidence intervals | Quantifies the relative event hazard between groups |
| Stratified analysis | Used for the primary OS analysis and several secondary analyses | Accounts for specified stratification factors in the survival comparison |
| Unstratified sensitivity analysis | Reported for OS, TTP, and PFS | Tests the robustness of the treatment estimate to the stratification specification |
| Cochran-Mantel-Haenszel test | Used for ORR and DCR | Compares binary outcomes using a stratified categorical-data framework |
Stratified Cox model for overall survival
For the primary OS analysis, the registry states that the hazard ratio and 95% confidence interval were calculated for stratified IVRS using a Cox model. The model was stratified by geographic region (Asia or Rest of the World), ECOG-PS (0 versus 1), AFP level, presence versus absence of extrahepatic disease, and presence versus absence of macrovascular invasion.
The registry reports a hazard ratio rather than a difference in median survival. The hazard ratio summarizes a relative event-rate comparison under the fitted Cox model and should not be interpreted as an absolute probability difference.
Kaplan-Meier estimation
The analysis notes state that Kaplan-Meier estimates for OS were used and that Kaplan-Meier survival curves were presented for each treatment. Kaplan-Meier estimation is appropriate for time-to-event data because it allows patients who remain event-free at the analysis point to contribute follow-up until censoring.
Here, di represents events at an event time and ni represents patients at risk immediately before that time. The ClinicalTrials.gov record does not provide the underlying event and censoring records needed to reconstruct the curve.
7. Primary Result: Overall Survival
Overall survival is the single registered primary endpoint. The ClinicalTrials.gov record contains three posted OS analyses. They represent the primary stratified analysis and two sensitivity analyses, rather than three separate primary endpoints.
| Analysis | Model specification | HR | 95% CI | P-value |
|---|---|---|---|---|
| Primary analysis | Stratified Cox model; stratified IVRS | 0.624 | 0.498–0.782 | = 0.000017 |
| Sensitivity analysis | Stratified RAVE | 0.660 | 0.527–0.828 | = 0.000149 |
| Sensitivity analysis | Unstratified | 0.674 | 0.546–0.831 | = 0.000107 |
Primary OS estimate
95% CI: 0.498–0.782 · P = 0.000017
Regorafenib 160 mg (BAY73-4506) versus placebo under the primary stratified analysis.
An HR of 0.624 means that, under the fitted stratified Cox model, the estimated instantaneous hazard of death in the regorafenib group was 0.624 times that in the placebo group. Equivalently, 1 − 0.624 = 0.376, so the model-based relative hazard is approximately 37.6% lower under the comparison represented by the reported hazard ratio.
This does not mean that 37.6% of patients avoided death, that each individual had a 37.6% lower probability of dying, or that overall survival was extended by 37.6%. A hazard ratio is a relative time-to-event measure, not an absolute survival probability or a treatment-effect percentage for every patient.
The 95% CI of 0.498–0.782 describes statistical uncertainty around the estimated hazard ratio under the model and analysis framework. It does not describe the range of effects experienced by individual patients.
The p-value of 0.000017 addresses evidence against the null hypothesis in the specified statistical test. It does not measure the size or clinical importance of the effect. Effect size and precision are better represented by the HR and its confidence interval.
The analysis is also dependent on the Cox-model framework, including the interpretation of a common hazard ratio over follow-up. The ClinicalTrials.gov record does not provide a formal assessment of the proportional-hazards assumption, so the HR should be understood as a model-based summary rather than a complete description of the survival experience.
Robustness across the posted OS analyses
The three posted estimates are 0.624, 0.660, and 0.674. Their confidence intervals all remain below 1.000, although they arise from different analysis specifications. The pattern is therefore useful statistically because the estimated treatment effect does not depend on one single reported Cox specification.
Stratified primary analysis
HR 0.624 with 95% CI 0.498–0.782 and P = 0.000017. The model incorporates the registry-specified stratification factors.
Stratified sensitivity analysis
HR 0.660 with 95% CI 0.527–0.828 and P = 0.000149. The registry identifies this as a stratified RAVE sensitivity analysis.
Unstratified sensitivity analysis
HR 0.674 with 95% CI 0.546–0.831 and P = 0.000107. This provides a comparison without the primary stratified specification.
Interpretive point
These are alternative analyses of the same primary endpoint, not three independent efficacy claims that should be counted as three separate primary hypotheses.
8. Secondary Results: Time to Progression
Time to Progression (TTP) is a time-to-event endpoint. The registry reports four statistical analyses: two based on stratified Cox regression and two based on unstratified Cox regression. The analysis notes state that one-sided p-values were calculated from the log-rank test and that 95% confidence intervals were computed using Kaplan-Meier estimates.
| Analysis | Specification | HR | 95% CI | P-value |
|---|---|---|---|---|
| TTP analysis | Stratified IVRS Cox regression | 0.439 | 0.355–0.542 | < 0.000001 |
| TTP analysis | Unstratified IVRS Cox regression | 0.471 | 0.388–0.572 | < 0.000001 |
| TTP analysis | Stratified IVRS Cox regression | 0.412 | 0.334–0.509 | < 0.000001 |
| TTP analysis | Unstratified IVRS Cox regression | 0.444 | 0.365–0.539 | < 0.000001 |
Reported TTP estimates
All four posted analyses report P < 0.000001 with two-sided 95% confidence intervals.
The consistency of the TTP estimates across stratified and unstratified specifications is notable from a methodological perspective. The smallest reported HR is 0.412 and the largest is 0.471. These values should not be combined into a single estimate; they are separate analyses using different specifications.
The hazard ratios are all below 1, indicating a lower estimated instantaneous progression hazard under the reported regorafenib comparison than under placebo. For example, an HR of 0.439 corresponds to a model-based estimated hazard approximately 43.9% as large as the comparator hazard, or approximately a 56.1% relative reduction in the estimated instantaneous hazard.
That interpretation does not imply that the probability of progression was reduced by exactly 56.1% for every patient. It also does not establish a particular median TTP because the ClinicalTrials.gov record contains no median estimates.
The p-values are extremely small under the reported testing framework, but they do not quantify the magnitude of the treatment effect. The HR and its confidence interval provide the effect-size and precision information.
Because the registry explicitly identifies one-sided testing for the p-value while reporting two-sided 95% confidence intervals, those quantities should not be treated as if they were generated under an identical one-sided/two-sided convention.
9. Secondary Results: Progression-Free Survival
Progression Free Survival (PFS) is also analyzed as a time-to-event endpoint. Four posted analyses are reported, again spanning stratified and unstratified Cox specifications.
| Analysis | Specification | HR | 95% CI | P-value |
|---|---|---|---|---|
| PFS analysis | Stratified IVRS Cox regression | 0.453 | 0.369–0.555 | < 0.000001 |
| PFS analysis | Unstratified Cox regression | 0.480 | 0.397–0.580 | < 0.000001 |
| PFS analysis | Stratified IVRS Cox regression | 0.425 | 0.347–0.522 | < 0.000001 |
| PFS analysis | Unstratified Cox regression | 0.454 | 0.376–0.548 | < 0.000001 |
Reported PFS estimates
All four posted analyses report P < 0.000001 with two-sided 95% confidence intervals.
The PFS hazard ratios range from 0.425 to 0.480. An HR of 0.453, for example, means that the fitted model estimates an instantaneous event hazard about 45.3% as large as the comparator hazard, corresponding to an approximately 54.7% lower estimated hazard.
The endpoint is still a time-to-event measure. A PFS hazard ratio does not provide a median PFS, a fixed-time PFS percentage, or an individual-level probability of remaining progression-free.
The confidence intervals provide the uncertainty around each estimate. The registry's analysis notes differ slightly across these records: some state that the 95% CI was computed using Cox regression, while another states Kaplan-Meier estimates. Those reported methodological distinctions should be preserved rather than silently harmonized.
The consistency of the estimates across stratified and unstratified models provides a useful sensitivity perspective, but these analyses should not be interpreted as independent opportunities to accumulate statistical significance.
10. Secondary Results: Objective Tumor Response Rate
Objective Tumor Response Rate (ORR) is a binary endpoint. The registry reports two Cochran-Mantel-Haenszel analyses with a reported difference as the effect measure.
| Analysis | Method | Reported difference | 95% CI | P-value |
|---|---|---|---|---|
| ORR analysis | Cochran-Mantel-Haenszel | -6.88 | -11.13 to -2.63 | = 0.003650 |
| ORR analysis | Cochran-Mantel-Haenszel | -4.15 | -7.55 to -0.75 | = 0.019991 |
The outcome unit is percentage of subjects. The registry comparison is ordered as “Placebo vs Regorafenib 160 mg (BAY73-4506),” and the effect measure is recorded as “Difference.” Because the ClinicalTrials.gov record does not explicitly state the subtraction convention used to construct that difference, the negative sign should not be independently translated into an arm-specific percentage-point advantage without assuming a formula that is not reported.
The Cochran-Mantel-Haenszel test is appropriate for comparing binary response outcomes while accounting for stratification. The reported confidence intervals quantify uncertainty around the reported difference.
The two estimates, -6.88 and -4.15, are not interchangeable and should not be averaged. They represent separate posted analyses.
The p-values of 0.003650 and 0.019991 address the corresponding statistical tests. They do not measure the magnitude of the response difference, and they should not be interpreted without considering the multiplicity and analysis context of the full trial.
11. Secondary Results: Disease Control Rate
Disease Control Rate (DCR) is also reported as a binary endpoint and analyzed with the Cochran-Mantel-Haenszel test.
| Analysis | Method | Reported difference | 95% CI | P-value |
|---|---|---|---|---|
| DCR analysis | Cochran-Mantel-Haenszel | -29.31 | -37.52 to -21.11 | < 0.000001 |
| DCR analysis | Cochran-Mantel-Haenszel | -31.39 | -39.57 to -23.22 | < 0.000001 |
As with ORR, the ClinicalTrials.gov record specifies the comparison order and identify the effect measure as a difference, but do not provide an explicit formula defining which arm is subtracted from which. The safest interpretation is therefore to report the estimates exactly as registered rather than imposing an unreported sign convention.
The two DCR estimates are -29.31 and -31.39, each accompanied by a 95% confidence interval that remains below zero and a p-value of < 0.000001.
These results indicate that the corresponding statistical comparisons were strongly separated under their reported analysis framework. They do not, by themselves, establish how long disease control lasted or how DCR translated into overall survival. Those are different clinical and statistical questions.
12. Secondary Results Summary
| Endpoint | Number of posted analyses | Effect measures reported | Statistical method |
|---|---|---|---|
| Overall Survival | 3 | HR 0.624; 0.660; 0.674 | Log-rank / Cox regression |
| Time to Progression | 4 | HR 0.439; 0.471; 0.412; 0.444 | Log-rank / Cox regression |
| Progression Free Survival | 4 | HR 0.453; 0.480; 0.425; 0.454 | Log-rank / Cox regression |
| Objective Tumor Response Rate | 2 | Difference -6.88; -4.15 | Cochran-Mantel-Haenszel |
| Disease Control Rate | 2 | Difference -29.31; -31.39 | Cochran-Mantel-Haenszel |
The registry therefore provides a coherent statistical pattern: time-to-event endpoints use survival-analysis methods and binary endpoints use a stratified categorical-data method. The different effect measures should not be collapsed into a single summary statistic because they answer different questions.
13. Serious Adverse Events
The ClinicalTrials.gov record reports serious adverse events by treatment arm as affected patients divided by patients at risk.
| Arm | Serious adverse events | At risk |
|---|---|---|
| Placebo | 92 | 193 |
| Regorafenib (Stivarga, BAY73-4506) | 194 | 374 |
The displayed bars are simple visualizations of the registry-reported affected and at-risk counts. They are not a formal comparative safety analysis. In particular, the ClinicalTrials.gov record does not provide a confidence interval, p-value, exposure-adjusted incidence rate, seriousness definition beyond the category itself, or a formal between-arm statistical test for serious adverse events.
14. Statistical Methods Explained
Why was a log-rank test used for overall survival?
Overall survival records the time from randomization to death and therefore contains both event timing and censoring information. A log-rank test is designed to compare survival distributions between groups across follow-up rather than reducing every patient to a simple binary outcome.
What does the primary hazard ratio of 0.624 mean?
It is a relative time-to-event estimate from the Cox model. Under the fitted model, the estimated instantaneous hazard of death in the regorafenib group is 0.624 times the comparator hazard. The corresponding relative reduction in estimated hazard is 37.6%. This is not an absolute survival difference and does not imply that every patient experiences the same proportional reduction.
Why was the OS analysis stratified?
The registry states that the primary OS Cox model was stratified by geographic region, ECOG-PS, AFP level, presence or absence of extrahepatic disease, and presence or absence of macrovascular invasion. Stratification allows the survival comparison to account for these prespecified factors without requiring the model to assign a single regression coefficient to each factor in the hazard-ratio estimate.
Why are there three OS hazard ratios?
The registry posts three analyses of the same primary endpoint: a stratified IVRS analysis, a stratified RAVE sensitivity analysis, and an unstratified sensitivity analysis. These are useful for assessing how the estimated treatment effect behaves under alternative analysis specifications. They should not be interpreted as three independent primary endpoints.
Why do the TTP and PFS analyses mention one-sided testing but report two-sided confidence intervals?
The registry explicitly states that one-sided p-values were calculated from the log-rank test while 95% confidence intervals were calculated separately. A p-value and a confidence interval are related but are not interchangeable summaries, and their sidedness should be reported exactly as specified rather than silently converting one to the other.
What does a confidence interval tell us?
A 95% confidence interval quantifies statistical uncertainty around an estimated effect under the relevant model and sampling framework. For the primary OS estimate, the interval is 0.498–0.782. It does not describe the probability that the true hazard ratio lies inside that particular interval, nor does it describe individual-patient treatment effects.
Why should the ORR and DCR differences not be interpreted like hazard ratios?
ORR and DCR are binary outcomes, so their reported effect measure is a difference rather than a hazard ratio. The numerical scale is therefore different. A difference should not be described as a relative reduction in hazard, and a hazard ratio should not be described as a percentage-point difference.
15. One-Sided Testing and Two-Sided Confidence Intervals
The registry provides an important methodological detail for TTP and PFS: the p-value was calculated using a one-sided log-rank test, while the reported confidence intervals are 95% and two-sided.
One-sided p-value
A one-sided test evaluates evidence in a prespecified direction. Its interpretation depends on the direction defined in the statistical hypothesis.
Two-sided 95% CI
A two-sided confidence interval communicates uncertainty on both sides of the estimated effect and is not simply a graphical restatement of a one-sided p-value.
This distinction matters when reading a registry table because it is possible to mistakenly assume that every reported inferential quantity uses the same sidedness. The ClinicalTrials.gov record explicitly say otherwise for the TTP and PFS analyses.
16. Stratified Analysis
Stratification is one of the recurring statistical themes in RESORCE. The primary OS analysis used a Cox model stratified by geographic region, ECOG-PS, AFP level, extrahepatic disease status, and macrovascular invasion status. Several TTP and PFS analyses are likewise identified as stratified or unstratified.
| Stratification factor | Registry categories |
|---|---|
| Geographic region | Asia or Rest of the World (ROW) |
| ECOG-PS | 0 versus 1 |
| AFP level | Registry identifies AFP level as a stratification factor; the ClinicalTrials.gov record does not specify its categories |
| Extrahepatic disease | Presence versus absence |
| Macrovascular invasion | Presence versus absence |
A stratified analysis does not change the randomized treatment assignment. Instead, it changes how the statistical comparison uses the information associated with the specified strata. The availability of both stratified and unstratified analyses in the registry also creates a useful sensitivity-analysis framework.
17. Cochran-Mantel-Haenszel Analysis
The Cochran-Mantel-Haenszel test was used for ORR and DCR. This is a categorical-data method that can compare treatment groups while accounting for stratification. It is conceptually different from the survival-analysis machinery used for OS, TTP, and PFS.
The endpoint determines what information the statistical model must preserve. Binary response records whether an event occurred; time-to-event analysis additionally uses when the event occurred and handles censoring.
This distinction explains why the RESORCE statistical record contains both “Other difference” effect measures and hazard ratios. They are not alternative ways of reporting exactly the same estimand.
18. Multiplicity and the Interpretation of Multiple Analyses
The ClinicalTrials.gov record contains 15 statistical analyses: 3 for the primary OS endpoint, 4 for TTP, 4 for PFS, 2 for ORR, and 2 for DCR. The registry identifies OS as the single primary endpoint and the remaining outcomes as secondary endpoints.
| Endpoint family | Analyses posted | Role |
|---|---|---|
| Overall Survival | 3 | Primary endpoint and sensitivity analyses |
| Time to Progression | 4 | Secondary endpoint |
| Progression Free Survival | 4 | Secondary endpoint |
| Objective Tumor Response Rate | 2 | Secondary endpoint |
| Disease Control Rate | 2 | Secondary endpoint |
Multiple reported analyses do not automatically imply multiple independent confirmatory hypotheses. Sensitivity analyses are generally intended to evaluate robustness, while secondary endpoints address additional questions. Without a complete multiplicity strategy from the statistical analysis plan, the ClinicalTrials.gov record does not justify reconstructing a familywise-error hierarchy beyond what is explicitly reported.
19. Censoring and Time-to-Event Interpretation
The primary OS definition states that subjects who were alive at the time of analysis were censored at their last date of last contact. This is a central feature of survival analysis: a censored patient is not treated as having experienced the event at the censoring time.
Event
For OS, the event is death due to any cause.
Censoring
A subject still alive at analysis is censored at the last date of last contact.
Why this matters
Survival methods preserve follow-up information without pretending that an unobserved future event occurred at the last observed time.
Model dependence
The Cox hazard ratio adds a model-based summary on top of the underlying time-to-event data.
The ClinicalTrials.gov record does not provide the individual event and censoring records, so no independent Kaplan-Meier curve, median survival estimate, or reconstructed event count is generated on this page.
20. What the Primary Hazard Ratio Does — and Does Not — Mean
The primary OS HR of 0.624 represents a relative hazard estimate. Numerically, it is 37.6% below 1.000, so it can be described as an approximately 37.6% lower estimated instantaneous hazard under the model.
The HR does not say that the absolute probability of death was reduced by 37.6 percentage points. No absolute survival probabilities are reported in the ClinicalTrials.gov record, so an absolute risk difference should not be invented.
A population-level hazard ratio does not imply that every individual experienced the same proportional change in risk. It summarizes the randomized groups statistically.
The 95% CI of 0.498–0.782 shows the precision of the estimated HR under the specified analysis framework. It is not an interval containing individual treatment effects.
The p-value of 0.000017 describes the evidence against the null hypothesis under the specified test. It is not a probability that the null hypothesis is true and is not a measure of clinical magnitude.
21. Primary Analysis vs Sensitivity Analyses
The structure of the OS results is particularly useful for teaching sensitivity analysis. The registry reports a primary stratified analysis and two additional analyses using alternative specifications.
| Feature | Primary OS analysis | Sensitivity analyses |
|---|---|---|
| Analysis label | Primary | Stratified RAVE; unstratified |
| Model | Cox model | Cox model |
| Stratification | Specified clinical and geographic factors | Stratified or unstratified depending on analysis |
| HR | 0.624 | 0.660; 0.674 |
| 95% CI | 0.498–0.782 | 0.527–0.828; 0.546–0.831 |
| P-value | = 0.000017 | = 0.000149; = 0.000107 |
The estimates are not identical, which is expected when the statistical specification changes. What matters for a sensitivity analysis is whether the substantive conclusion is highly dependent on one particular modeling choice. Within the ClinicalTrials.gov record, all three estimates are below 1 and all three reported confidence intervals remain below 1.
22. Limitations
- Registry-only numerical scope: this page is restricted to the ClinicalTrials.gov record and therefore does not add median survival, event counts, subgroup estimates, baseline characteristics, or other results that are not provided.
- Incomplete endpoint wording: the registry-reported secondary-endpoint time frame ends with “after 8 cycle ”. It is reproduced without attempting to infer the missing text.
- Hazard-ratio assumptions: Cox hazard ratios are model-based summaries. The ClinicalTrials.gov record does not provide a formal assessment of the proportional-hazards assumption.
- No median survival values: the ClinicalTrials.gov record reports hazard ratios and confidence intervals but do not provide median OS, TTP, or PFS estimates.
- No individual-level data: the underlying event and censoring records are not available in the ClinicalTrials.gov recordset, preventing independent reconstruction of Kaplan-Meier curves.
- Secondary-endpoint multiplicity: the ClinicalTrials.gov record identifies one primary endpoint and multiple secondary analyses but do not provide a complete multiplicity-adjustment strategy.
- Difference sign convention: ORR and DCR are reported as “Difference,” but the ClinicalTrials.gov record does not define the exact subtraction convention. The negative estimates are therefore reported without imposing an unprovided formula.
- Safety comparison: serious adverse event counts and denominators are provided, but no formal between-arm safety analysis is reported.
- Analysis populations: the ClinicalTrials.gov record does not provide enough information to reconstruct the full analysis-population definitions for every posted endpoint.
23. Why This Trial Matters Statistically
RESORCE is a useful teaching case because the registry results show how a modern randomized oncology trial can combine several statistical frameworks within one study. The primary endpoint is a time-to-event outcome, while response outcomes are binary. The analysis also provides both stratified and unstratified sensitivity specifications.
| Concept | How it appears in RESORCE |
|---|---|
| Randomization | The registry identifies the allocation as RANDOMIZED. |
| Parallel design | The design model is PARALLEL. |
| Blinding | The masking designation is QUADRUPLE. |
| Time-to-event endpoint | Overall Survival is the registered primary endpoint. |
| Kaplan-Meier estimation | Used for OS estimates and survival curves in the analysis notes. |
| Log-rank test | Used for OS, TTP, and PFS. |
| Hazard ratio | Used for OS, TTP, and PFS. |
| Stratified analysis | Used in the primary OS model and several secondary analyses. |
| Sensitivity analysis | Alternative stratified and unstratified Cox specifications are posted. |
| Cochran-Mantel-Haenszel test | Used for ORR and DCR. |
| One-sided testing | Explicitly reported for the TTP and PFS p-values. |
| Two-sided confidence intervals | Reported for the hazard-ratio and binary difference estimates. |
| Superiority | The registry identifies the hypothesis type as SUPERIORITY. |
The important lesson is that statistical interpretation should follow the endpoint. A hazard ratio is appropriate for describing the reported time-to-event comparison; a difference is the effect measure posted on ClinicalTrials.gov for ORR and DCR. Neither should be converted into the other merely for convenience.
24. Statistical Concepts in This Trial
Learn more about the methods used in this trial:
25. Related Statistical Calculators
26. Sources
- ClinicalTrials.gov: NCT01774344.
- PubMed: PubMed record 29704513.
- PubMed: PubMed record 27932229.
- PubMed: PubMed record 40388796.
- PubMed: PubMed record 30738047.
Continue through the Clinical Biostats statistical pathway
Explore tutorials and statistical calculators related to survival analysis, hazard ratios, confidence intervals, stratified testing, and clinical-trial methods.
27. Record Summary
RESORCE provides a compact teaching example of how randomized clinical-trial evidence can be analyzed through multiple statistical lenses. The primary endpoint, overall survival, was analyzed with log-rank testing and a stratified Cox model, producing a primary hazard ratio of 0.624 with a 95% confidence interval of 0.498–0.782 and a p-value of 0.000017. Sensitivity analyses produced HRs of 0.660 and 0.674. Secondary time-to-event analyses for TTP and PFS also used log-rank and Cox methods, while ORR and DCR used Cochran-Mantel-Haenszel testing with reported differences.
The statistical story is therefore not simply the collection of p-values. It involves the choice of endpoint, the distinction between time-to-event and binary outcomes, stratification, censoring, model-based hazard ratios, confidence intervals, one-sided testing, and sensitivity analyses. The serious-adverse-event counts add a separate safety dimension, but the ClinicalTrials.gov record does not provide a formal comparative safety analysis.