This page provides an independent statistical analysis and educational interpretation of publicly reported results. ClinicalTrials.gov provides the official trial registry record. Numerical results on this page are restricted to the trial data reported in the ClinicalTrials.gov record.
1. Trial at a Glance
TROPiCS-04 was a randomized, parallel-group, open-label phase 3 trial evaluating sacituzumab govitecan-hziy (SG) versus treatment of physician's choice in participants with locally advanced or metastatic unresectable urothelial cancer. The registered primary endpoint was overall survival (OS), a time-to-event endpoint analyzed using the Kaplan-Meier method and a stratified time-to-event comparison.
| Feature | TROPiCS-04 |
|---|---|
| Phase | Phase 3 |
| Condition | Locally Advanced or Metastatic Unresectable Urothelial Cancer |
| Design | Randomized, parallel-group, open-label |
| Allocation | Randomized |
| Primary purpose | Treatment |
| Primary endpoint | Overall Survival (OS) |
| Primary endpoint type | Time-to-event |
| Enrollment | 711 |
| Arms | 2 |
| Status | Completed |
| Lead sponsor | Gilead Sciences |
| Sponsor type | Industry |
| ClinicalTrials.gov | NCT04527991 |
2. Clinical Question
The central statistical question was whether sacituzumab govitecan-hziy should be compared with treatment of physician's choice with respect to overall survival in participants with locally advanced or metastatic unresectable urothelial cancer.
Population
Participants with locally advanced or metastatic unresectable urothelial cancer.
Intervention
Sacituzumab Govitecan-hziy (SG).
Comparator
Treatment of Physician's Choice. The registered interventions include paclitaxel, docetaxel, and vinflunine.
Primary question
Does SG produce a different overall-survival profile from treatment of physician's choice under the prespecified superiority framework?
3. Trial Design
Sacituzumab Govitecan-hziy
- Sacituzumab Govitecan-hziy (SG)
- Primary comparison against treatment of physician's choice
- Serious adverse events reported for 185 of 349 participants at risk
Treatment of Physician's Choice
- Physician's choice of treatment
- Registered drug interventions include paclitaxel, docetaxel, and vinflunine
- Serious adverse events reported for 110 of 337 participants at risk
4. Trial Timing and Registry Status
Trial start
The registered trial start date was January 13, 2021.
Primary completion
The registered primary completion date was July 4, 2025.
Completed
The trial is recorded as completed, with results posted in ClinicalTrials.gov.
5. Endpoints
| Endpoint | Role / time frame | Registry definition or analysis |
|---|---|---|
| Overall Survival (OS) | Primary Up to 42 months |
OS was defined as time from the date of randomization to the date of death, regardless of cause. Kaplan-Meier estimates were used for analysis. |
| Progression-Free Survival (PFS) by Investigator Assessment | Secondary Up to 42 months |
Time-to-event endpoint analyzed with a stratified log-rank test and stratified hazard ratio. |
| Progression-Free Survival (PFS) by BICR | Secondary Up to 42 months |
Time-to-event endpoint analyzed with blinded independent central review and a stratified log-rank framework. |
| Objective Response Rate (ORR) by Investigator Assessment | Secondary Up to 42 months |
Binary endpoint analyzed using a Cochran-Mantel-Haenszel approach. |
| Objective Response Rate (ORR) by BICR | Secondary Up to 42 months |
Binary endpoint analyzed using a Cochran-Mantel-Haenszel approach. |
| Clinical Benefit Rate (CBR) by Investigator Assessment | Secondary Up to 42 months |
Binary endpoint analyzed using a Cochran-Mantel-Haenszel approach. |
| Clinical Benefit Rate (CBR) by BICR | Secondary Up to 42 months |
Binary endpoint analyzed using a Cochran-Mantel-Haenszel approach. |
| Change From Baseline in EORTC-QLQ-C30 Domain Score | Secondary Cycle 5 Day 1; Cycle length = 21 days |
Continuous outcome analyzed using a mixed-effects model for repeated measures (MMRM). |
The registry reports 13 outcome measures and 11 statistical analyses. The ClinicalTrials.gov record includes the primary OS analysis, six additional efficacy analyses, and four health-related quality-of-life analyses.
6. Statistical Methodology
Overall survival and time-to-event analysis
Overall survival is a time-to-event endpoint because both the timing of death and whether death has occurred matter. The registry defines OS from randomization to death from any cause and specifies Kaplan-Meier estimation. The primary formal comparison used a log-rank test, with a stratified hazard ratio estimated from a Cox model adjusted for the randomization stratification factors reported in the electronic case report form (eCRF).
Here, S(t) represents the probability of remaining event-free beyond time t. Kaplan-Meier estimation permits patients who have not experienced the event by their last available observation to contribute information through their censoring time.
Stratified log-rank test
The registry identifies the log-rank test as the primary OS comparison and the stratified log-rank test for the reported PFS analyses. Stratification allows the comparison to account for prespecified or recorded randomization factors rather than treating all participants as belonging to a single homogeneous risk set.
Cox proportional-hazards model
The primary OS hazard ratio and its confidence interval were calculated using a Cox model adjusted for randomization stratification factors as reported in the eCRF. The hazard ratio is therefore a model-based relative measure of the event hazard rather than a direct comparison of probabilities at one fixed time point.
This derived interpretation follows directly from 1 − 0.86 = 0.14. It does not mean that 14% of participants avoided death, nor does it imply that every participant experienced the same relative reduction.
Intention-to-treat analysis
The primary OS analysis used the Intent-to-treat (ITT) Analysis Set. The registry defines this population as all participants who had been randomized to the trial. An ITT analysis preserves treatment assignment as the basis for the comparison and therefore maintains the connection between the outcome analysis and the randomized design.
Cochran-Mantel-Haenszel analysis
The investigator-assessed and BICR response and clinical-benefit endpoints were analyzed using Cochran-Mantel-Haenszel statistics adjusted for randomization stratification factors. The effect measure reported was a stratified odds ratio.
MMRM for health-related quality of life
The quality-of-life analyses used an MMRM model. The registry text states that the model included all visits up to and including Cycle 5 Day 1. The analysis population was the HRQoL Evaluable Analysis Set with available data, defined in the registry as participants in the ITT Analysis Set who had an evaluable assessment.
7. Primary Result: Overall Survival
The registered primary endpoint was overall survival through up to 42 months. Participants in the ITT Analysis Set were analyzed. The comparison was sacituzumab govitecan-hziy versus treatment of physician's choice.
Stratified hazard ratio for death
95% CI: 0.73–1.02 · P = 0.0870
Two-sided confidence interval · Superiority hypothesis
| Primary endpoint | SG | Physician's choice | Effect estimate |
|---|---|---|---|
| Overall Survival | ITT Analysis Set | Stratified HR 0.86 95% CI 0.73–1.02 P = 0.0870 |
|
What the estimate means: The stratified hazard ratio of 0.86 corresponds to an estimated hazard of death that is 14% lower in the SG group relative to the physician's-choice group under the fitted Cox model, after adjustment for the randomization stratification factors reported in the eCRF.
What it does not mean: A hazard ratio of 0.86 does not mean that 14% of patients benefited, that mortality was reduced by exactly 14% for every patient, or that the absolute probability of death was 14 percentage points lower.
What the confidence interval says: The two-sided 95% confidence interval extends from 0.73 to 1.02. It quantifies uncertainty around the estimated hazard ratio under the statistical model and sampling framework. Because the interval includes 1, the data are compatible with a range of relative effects that includes no hazard-ratio difference.
Why the P-value is not an effect size: The P-value of 0.0870 measures the strength of evidence against the null hypothesis under the specified testing framework; it does not describe the magnitude or clinical importance of the observed hazard ratio. The magnitude is described by the hazard ratio itself, while the confidence interval describes its precision.
Important caution: The Cox-model interpretation depends on the model's assumptions, including the proportional-hazards framework. Censoring, treatment discontinuation, subsequent treatment, and the exact composition of the analysis population can also affect the interpretation of a time-to-event estimate. The ClinicalTrials.gov record does not provide a separate proportional-hazards diagnostic or a time-varying treatment-effect analysis.
8. Secondary Time-to-Event Results
Progression-Free Survival by Investigator Assessment
Stratified hazard ratio
95% CI: 0.68–0.95 · P = 0.0117
Up to 42 months · ITT Analysis Set
The hazard ratio of 0.81 corresponds to an estimated 19% lower hazard of progression or death in the SG group under the reported stratified Cox-model framework. The 95% CI of 0.68–0.95 is entirely below 1, while the two-sided P-value is 0.0117.
The estimate describes a relative event rate over follow-up, not a difference in median PFS or a fixed percentage of participants who experienced benefit. The ClinicalTrials.gov record does not report median PFS or time-specific PFS probabilities, so those quantities are not substituted for the reported hazard ratio.
Progression-Free Survival by Blinded Independent Central Review
Stratified hazard ratio
95% CI: 0.72–1.03 · P = 0.1095
Up to 42 months · ITT Analysis Set
The BICR-assessed PFS hazard ratio of 0.86 corresponds to an estimated 14% lower hazard of progression or death in the SG group under the reported model. The 95% CI of 0.72–1.03 crosses 1, indicating appreciable uncertainty around the relative treatment effect. The P-value of 0.1095 is a measure of evidence under the specified testing framework, not a measure of effect size.
The difference between the investigator-assessed and BICR-assessed estimates illustrates why assessment method matters. These are two analyses of a related time-to-event outcome using different assessment frameworks; they should not be silently combined into a single estimate.
9. Secondary Response and Clinical-Benefit Results
| Endpoint | Method | Effect measure | Estimate | 95% CI | P-value |
|---|---|---|---|---|---|
| ORR by Investigator Assessment | Cochran-Mantel-Haenszel | Stratified odds ratio | 1.32 | 0.90–1.95 | 0.1594 |
| ORR by BICR | Cochran-Mantel-Haenszel | Stratified odds ratio | 1.84 | 1.24–2.73 | 0.0022 |
| CBR by Investigator Assessment | Cochran-Mantel-Haenszel | Stratified odds ratio | 1.67 | 1.19–2.34 | 0.0032 |
| CBR by BICR | Cochran-Mantel-Haenszel | Stratified odds ratio | 1.68 | 1.19–2.37 | 0.0034 |
How to interpret the odds ratios
The ORR and CBR analyses use odds ratios rather than hazard ratios because these endpoints are binary outcomes. An odds ratio of 1.84, for example, means that the estimated odds of the response outcome were 1.84 times as high in the SG group as in the physician's-choice group after adjustment for the reported randomization stratification factors.
An odds ratio is not the same as a risk ratio or a percentage-point difference. Without the underlying response counts or arm-specific response probabilities in the ClinicalTrials.gov record, it would not be appropriate to convert these odds ratios into absolute response rates.
The investigator-assessed ORR analysis produced a stratified odds ratio of 1.32 with a 95% CI of 0.90–1.95 and P = 0.1594. The BICR analysis produced a stratified odds ratio of 1.84 with a 95% CI of 1.24–2.73 and P = 0.0022.
The two response analyses therefore give different estimates and levels of statistical evidence. That difference should be reported rather than averaged or treated as an inconsistency that can be resolved without knowing more about the assessment data. The BICR result has a confidence interval entirely above 1, while the investigator-assessed result has a confidence interval that includes 1.
Clinical Benefit Rate
The investigator-assessed CBR analysis reported a stratified odds ratio of 1.67 (95% CI 1.19–2.34; P = 0.0032). The BICR analysis reported a stratified odds ratio of 1.68 (95% CI 1.19–2.37; P = 0.0034).
The close numerical similarity of the two CBR estimates is descriptive of these two reported analyses. It does not by itself establish that the two assessment approaches are interchangeable, because the underlying classifications and assessment processes are different.
10. Health-Related Quality of Life Results
The registry reports four secondary analyses of change from baseline in EORTC-QLQ-C30 domain scores at Cycle 5 Day 1, with a cycle length of 21 days. These analyses used MMRM and compared SG with treatment of physician's choice using least-square mean differences.
| Domain / analysis | Method | LS mean difference | 95% CI | P-value |
|---|---|---|---|---|
| Physical Functioning | MMRM | 1.1 | -2.5–4.7 | 0.5638 |
| Global Health Status / QoL | MMRM | 0.0 | -3.9–3.9 | 0.9944 |
| Pain | MMRM | -2.7 | -7.8–2.4 | 0.3007 |
| Fatigue | MMRM | -2.0 | -6.6–2.6 | 0.3871 |
The MMRM estimates are between-group differences in least-square mean change from baseline at Cycle 5 Day 1, not hazard ratios or odds ratios. For example, the physical-functioning estimate of 1.1 indicates a modeled SG-versus-physician's-choice difference of 1.1 score units in change from baseline at the specified time point.
The 95% confidence intervals for all four reported analyses include 0. The corresponding P-values range from 0.3007 to 0.9944. These P-values should not be interpreted as measures of the magnitude of the quality-of-life differences; the estimates and confidence intervals provide the direct information about the size and precision of the modeled differences.
11. Safety
The ClinicalTrials.gov record reports serious adverse events by randomized treatment arm using affected participants over participants at risk. These are the safety figures available for this page.
| Safety measure | Sacituzumab Govitecan-hziy | Treatment of Physician's Choice |
|---|---|---|
| Serious adverse events | 185/349 | 110/337 |
The denominators in these safety results are the reported numbers at risk for the respective arms. They should not be replaced by the overall enrollment of 711, and the ClinicalTrials.gov record does not provide sufficient detail to construct a broader adverse-event table.
12. Analysis Populations and Why They Matter
| Analysis population | Definition / role in the ClinicalTrials.gov record |
|---|---|
| Intent-to-treat (ITT) Analysis Set | Included all participants who had been randomized to the trial; used for the primary OS analysis and the reported efficacy analyses. |
| HRQoL Evaluable Analysis Set | Participants in the ITT Analysis Set who had an evaluable assessment; used for the registry-reported EORTC-QLQ-C30 MMRM analyses. |
| Safety populations | Serious adverse events are reported using arm-specific numbers at risk: 349 for SG and 337 for physician's choice. |
The distinction between populations is statistically important. The ITT population preserves the randomized comparison, whereas an evaluable quality-of-life population requires observed assessment data. These populations answer related but not identical questions.
13. Statistical Methods Explained
Why was a log-rank test used for overall survival?
Overall survival records both whether death occurs and when it occurs. A log-rank test is designed for comparing time-to-event distributions while accounting for differing follow-up and right censoring. In this trial, the primary OS method was reported as a log-rank test, with a stratified hazard ratio obtained from a Cox model.
What does the OS hazard ratio of 0.86 mean?
A hazard ratio of 0.86 means that the estimated instantaneous hazard of death was 0.86 times that in the comparator group under the fitted model. Equivalently, 1 − 0.86 = 0.14, or a 14% lower estimated hazard. It is not a 14-percentage-point reduction in mortality and does not mean that 14% of participants benefited.
Why is the confidence interval important?
The 95% CI of 0.73–1.02 shows the uncertainty around the estimated OS hazard ratio. A point estimate alone can give a false impression of precision. The confidence interval shows that the observed estimate is compatible with a range of underlying relative effects, including values slightly above 1.
Why use the Cochran-Mantel-Haenszel test for ORR and CBR?
ORR and CBR are binary outcomes, so a time-to-event method is not required for the basic comparison. The Cochran-Mantel-Haenszel approach allows the analysis to incorporate randomization stratification factors while estimating a stratified odds ratio and its associated confidence interval and P-value.
Why is an odds ratio not the same as a response-rate difference?
Odds are defined as probability divided by one minus probability. An odds ratio therefore compares odds, not probabilities directly. An odds ratio of 1.84 means the odds are 1.84 times as large; it does not by itself tell us the absolute difference in response percentages.
Why was MMRM used for the quality-of-life analyses?
Quality-of-life scores are repeatedly measured over visits. MMRM is designed for longitudinal continuous outcomes and can model the relationship between repeated observations rather than reducing each participant to a single measurement. In this registry analysis, the model included visits through Cycle 5 Day 1.
Why does investigator assessment versus BICR matter?
Investigator assessment and blinded independent central review are different measurement processes. In an open-label trial, investigator assessment can potentially be influenced by knowledge of treatment assignment. BICR introduces an independent review process that can provide a distinct assessment of progression or response. The two sets of estimates should therefore be reported separately.
14. Understanding the Primary P-value
The three quantities answer different questions. The hazard ratio describes the estimated relative treatment effect, the confidence interval describes statistical precision, and the P-value describes evidence against the null hypothesis under the specified testing framework.
A P-value should not be converted into a probability that the treatment has no effect. Likewise, a P-value of 0.0870 does not mean that the treatment effect has an 8.70% probability of being due to chance. Those interpretations confuse the frequentist definition of a P-value with a posterior probability.
For a time-to-event result, read the hazard ratio first to understand the estimated direction and relative magnitude; inspect the 95% confidence interval to understand precision and whether it includes the null value of 1; then consider the P-value within the prespecified hypothesis-testing framework. Finally, examine the analysis population, censoring, stratification, assessment method, and proportional-hazards assumptions before drawing broader conclusions.
15. Stratification and Covariate Adjustment
The analyses posted on ClinicalTrials.gov repeatedly state that effect estimates were adjusted for randomization stratification factors. For the OS analysis, the Cox model used the randomization stratification factors as reported in the eCRF. The PFS analyses used the same type of adjustment, while the ORR and CBR analyses used Cochran-Mantel-Haenszel statistics adjusted for randomization stratification factors.
Why stratify?
Stratification can account for important factors used in the randomized design when comparing outcomes between treatment groups.
Why adjust the analysis?
The adjusted estimate is aligned with the trial's stratified design rather than treating the randomized population as completely unstructured.
The ClinicalTrials.gov record does not identify the individual randomization stratification factors. They should therefore not be reconstructed from external publications or assumed from common urothelial-cancer trial designs.
16. Multiplicity and Multiple Secondary Endpoints
The registry contains one registered primary endpoint and multiple secondary endpoints, including two PFS analyses, two ORR analyses, two CBR analyses, and four quality-of-life analyses in the ClinicalTrials.gov record.
| Endpoint family | Reported analyses | Statistical method |
|---|---|---|
| Overall survival | 1 primary analysis | Log-rank test; stratified Cox hazard ratio |
| Progression-free survival | 2 secondary analyses | Stratified log-rank test; stratified Cox hazard ratio |
| Objective response rate | 2 secondary analyses | Cochran-Mantel-Haenszel; stratified odds ratio |
| Clinical benefit rate | 2 secondary analyses | Cochran-Mantel-Haenszel; stratified odds ratio |
| Quality of life | 4 secondary analyses | MMRM; LS mean difference |
17. Censoring and Proportional-Hazards Considerations
Because OS and PFS are time-to-event outcomes, some participants may contribute follow-up without experiencing the event during the observation period. Kaplan-Meier methods account for right censoring under their usual assumptions, while Cox-model hazard ratios summarize relative event hazards under a proportional-hazards framework.
The primary OS result should therefore not be read as though it were a simple comparison of two proportions. A hazard ratio is a model-based summary of event rates over time. If the relative hazard changes materially during follow-up, a single hazard ratio may not fully describe the treatment-effect pattern.
18. Results Summary
| Endpoint | Role | Estimate | 95% CI | P-value |
|---|---|---|---|---|
| Overall Survival | Primary | HR 0.86 | 0.73–1.02 | 0.0870 |
| PFS, Investigator Assessment | Secondary | HR 0.81 | 0.68–0.95 | 0.0117 |
| PFS, BICR | Secondary | HR 0.86 | 0.72–1.03 | 0.1095 |
| ORR, Investigator Assessment | Secondary | OR 1.32 | 0.90–1.95 | 0.1594 |
| ORR, BICR | Secondary | OR 1.84 | 1.24–2.73 | 0.0022 |
| CBR, Investigator Assessment | Secondary | OR 1.67 | 1.19–2.34 | 0.0032 |
| CBR, BICR | Secondary | OR 1.68 | 1.19–2.37 | 0.0034 |
| Physical Functioning | Secondary | LS mean difference 1.1 | -2.5–4.7 | 0.5638 |
| Global Health Status / QoL | Secondary | LS mean difference 0.0 | -3.9–3.9 | 0.9944 |
| Pain | Secondary | LS mean difference -2.7 | -7.8–2.4 | 0.3007 |
| Fatigue | Secondary | LS mean difference -2.0 | -6.6–2.6 | 0.3871 |
This table intentionally keeps effect measures in their native statistical forms. Hazard ratios, odds ratios, and mean differences cannot be interpreted as interchangeable quantities.
19. Limitations
- Open-label design: masking was recorded as none. This is particularly relevant to outcomes involving investigator assessment.
- Assessment framework: investigator-assessed and BICR endpoints produced different estimates for PFS and ORR, illustrating the importance of how an outcome is measured.
- Primary OS precision: the 95% CI for the primary OS hazard ratio was 0.73–1.02, so the interval includes the null hazard ratio of 1.
- Secondary-endpoint multiplicity: the ClinicalTrials.gov record reports numerous secondary analyses but do not provide an alpha-allocation or multiplicity-adjustment scheme for those analyses.
- Hazard-ratio assumptions: the Cox model provides a compact summary of relative event hazards, but a single hazard ratio may be incomplete if proportional hazards do not hold over time.
- Incomplete absolute-effect information: the ClinicalTrials.gov record does not provide median OS, median PFS, or time-specific survival probabilities.
- Quality-of-life population: the MMRM analyses use the HRQoL Evaluable Analysis Set with available data rather than the entire ITT population.
- Safety detail: only serious adverse events by arm are reported here; event-specific safety profiles are not reconstructed.
- Stratification details: the analysis records state that randomization stratification factors were used, but the ClinicalTrials.gov record does not identify the individual factors.
- Registry scope: this page is restricted to the ClinicalTrials.gov record and does not import additional numerical results from publications.
20. Why This Trial Matters Statistically
TROPiCS-04 provides a useful teaching example because the registry combines several common clinical-trial analysis frameworks within a single randomized phase 3 study. The primary endpoint is time-to-event, while secondary outcomes span survival, binary response, clinical benefit, and repeated quality-of-life measurements.
| Concept | How it appears in TROPiCS-04 |
|---|---|
| Randomization | Participants were randomized in a two-arm parallel design. |
| Intention-to-treat analysis | The primary OS analysis used all randomized participants in the ITT Analysis Set. |
| Kaplan-Meier estimation | The registered OS endpoint specifies Kaplan-Meier estimates. |
| Log-rank test | The primary OS comparison used a log-rank test. |
| Stratified log-rank test | The registry-reported PFS analyses used stratified log-rank tests. |
| Hazard ratio | OS and PFS were summarized with stratified hazard ratios. |
| Cox model | The OS hazard ratio and confidence interval were calculated using a Cox model adjusted for randomization stratification factors. |
| Cochran-Mantel-Haenszel test | ORR and CBR analyses used Cochran-Mantel-Haenszel statistics. |
| Odds ratio | Binary efficacy outcomes were summarized using stratified odds ratios. |
| MMRM | EORTC-QLQ-C30 change-from-baseline analyses used mixed-effects models for repeated measures. |
| Open-label assessment | The trial had no masking, while some endpoints were separately evaluated by BICR. |
21. Related Tutorials
Learn more about the methods used in this trial:
22. Related Statistical Calculators
23. Sources
- ClinicalTrials.gov: TROPiCS-04, NCT04527991. Trial registry record and the source of the numerical trial data used on this page.
- PubMed: PubMed record for PMID 41277126.
- PubMed: PubMed record for PMID 39472646.
Continue through Clinical Biostats
Explore statistical tutorials and calculators related to survival analysis, categorical outcomes, confidence intervals, and repeated-measures methods.
24. Record Summary
TROPiCS-04 is a randomized phase 3 trial with 711 participants and a single registered primary time-to-event endpoint: overall survival through up to 42 months. The primary analysis used the ITT population, a log-rank test, and a stratified Cox-model hazard ratio. The reported OS estimate was 0.86, with a two-sided 95% CI of 0.73–1.02 and P = 0.0870.
The secondary analyses illustrate several additional statistical frameworks. Investigator-assessed PFS had a stratified HR of 0.81, while BICR-assessed PFS had a stratified HR of 0.86. Binary ORR and CBR outcomes were analyzed with Cochran-Mantel-Haenszel methods and stratified odds ratios. Quality-of-life outcomes were analyzed using MMRM and reported as least-square mean differences at Cycle 5 Day 1.
The most useful statistical reading of this trial therefore combines the effect measure, confidence interval, P-value, analysis population, assessment method, and model assumptions. These elements provide more information than any single number in isolation.