Effect of Sotagliflozin on Cardiovascular and Renal Events in Participants With Type 2 Diabetes and Moderate Renal Impairment Who Are at Cardiovascular Risk: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Effect of Sotagliflozin on Cardiovascular and Renal Events in Participants With Type 2 Diabetes and Moderate Renal Impairment Who Are at Cardiovascular Risk (NCT03315143), a randomized phase 3 study. The primary outcome is Number of Total Occurrences of Cardiovascular (CV) Death, Hospitalizations for Heart Failure (HHF) and Urgent Visits for Heart Failure (HF).

2. Clinical Question

The clinical question is about the frequency of this combined set of events over participants’ observed follow-up, rather than only whether an event occurred at least once. Recurrent events can convey information about the burden of repeated heart-failure episodes, while cardiovascular deaths are also part of the endpoint. Because the components differ in clinical meaning and frequency, a combined result does not by itself show which component chiefly accounts for the overall pattern. The registry record does not report component-specific primary-endpoint results.

The trial was randomized and used placebo as the comparator. Those features support a structured comparison of the allocated groups, but the interpretation remains tied to the stated population, treatment period, endpoint definition, and analyses. The registry record does not report why the trial was terminated or whether termination altered the planned conduct or interpretation.

3. Trial Design

NCT03315143 was a phase 3, randomized, quadruple-masked, parallel-group, placebo-controlled study sponsored by Lexicon Pharmaceuticals. The registry lists an enrollment of 10584 and identifies heart failure, type 2 diabetes mellitus, and chronic kidney diseases among the conditions studied. The trial began on 2017-12-19, had a primary completion date of 2020-07-08, and is listed as terminated. The reason for termination is not reported in the registry record.

Participants were allocated to sotagliflozin or matching placebo. The sotagliflozin regimen began at 200 mg once daily, with possible up-titration to 400 mg during the first 6 months, for up to 28.9 months. The placebo regimen matched the active-treatment schedule and could continue for up to 29.6 months. The registry describes the masking as quadruple but does not specify which roles were masked.

The primary analysis population was the intention-to-treat population. The registry defines this as all randomized participants analyzed according to their treatment group allocated by randomization. This preserves the randomized group assignment in the stated analysis population; the registry record does not explain how missing observations, treatment discontinuation, or other post-randomization events were handled.

The endpoint was framed as total event occurrences over follow-up and reported as an event rate per 100-person years. In addition to the primary endpoint, the registry lists outcomes involving heart-failure events, cardiovascular death, cardiovascular and cerebrovascular events, all-cause death, and renal outcomes. Specific details of the original sample-size justification, planned interim analyses, and full statistical analysis plan are not reported in the registry record.

4. Participant Flow and Accounting

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

Before assignment: Participants with a diagnosis of Type 2 diabetes (T2D), CV risk factors, and moderately impaired renal function were enrolled equally in 1 of 2 treatment groups, sotagliflozin or placebo.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: ITT population included all randomized participants analyzed according to the treatment group allocated by randomization.

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.

Population: Intent-to-treat (ITT) population included all randomized participants analyzed according to the treatment group.

6. Primary Endpoint

The registry lists the primary outcome as Number of Total Occurrences of Cardiovascular (CV) Death, Hospitalizations for Heart Failure (HHF) and Urgent Visits for Heart Failure (HF), measured over Up to 30 months.

The primary endpoint combines cardiovascular death, hospitalization for heart failure, and urgent visits for heart failure after randomization. It counts first and potentially subsequent occurrences, then expresses the total as events per 100-person years of follow-up. Thus, it is a recurrent-event rate: a participant can contribute more than one event, rather than contributing only a yes-or-no indicator for any event.

Using person-time as the denominator describes the event frequency in relation to the amount of follow-up observed. This can be useful when participants have different lengths of observation. As a general statistical point, an event rate and a time-to-first-event measure answer related but distinct questions: the rate can reflect repeated events, while a time-to-first-event analysis focuses on the time until an initial event. The registry lists both the recurrent-event endpoint and a Cox proportional hazards analysis, but does not give enough detail to infer all aspects of how the analysis handled recurrent events.

A combined endpoint can summarize several clinically important outcomes, but it can also conceal variation across components. The overall rate does not establish that each component changed to the same degree, or that each contributed equally. Component-specific primary-endpoint results are not reported in the registry record. The stated timeframe is up to 30 months, so the result describes event rates during the recorded follow-up period, not an estimate beyond it.

7. Results Posted in the Registry

• Sotagliflozin: 5.60 versus 7.50 (events per 100-person years) on control; rate ratio 0.75 (95% CI 0.68–0.82, approximate, Poisson model); p ≈ <0.001.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Total Number of Occurrences of HHF and Urgent HF Visits

• Endpoint type: Event rate: events per unit of follow-up, compared as a rate ratio.
• Test: Poisson rate ratio, based on the estimated number of events and follow-up time.
• Result:
  • Sotagliflozin: 3.50 versus 5.10 (events per 100-person years) on control; rate ratio 0.69 (95% CI 0.61–0.77, approximate, Poisson model); p ≈ <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference (a ratio of 1), so the event rate is statistically lower for Sotagliflozin than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Number of Deaths From Cardiovascular Causes

• Endpoint type: Event rate: events per unit of follow-up, compared as a rate ratio.
• Test: Poisson rate ratio, based on the estimated number of events and follow-up time.
• Result:
  • Sotagliflozin: 2.20 versus 2.40 (events per 100-person years) on control; rate ratio 0.92 (95% CI 0.78–1.07, approximate, Poisson model); p ≈ 0.284.
• Interpretation:
  • The 95% confidence interval includes no difference (a ratio of 1), so these data do not show a statistically significant difference between Sotagliflozin and the control. The interval gives the range of effects that remain compatible with the data.

Total Number of Occurrences of CV Death, HHF, Non-fatal Myocardial Infarction and Non-fatal Stroke

• Endpoint type: Event rate: events per unit of follow-up, compared as a rate ratio.
• Test: Poisson rate ratio, based on the estimated number of events and follow-up time.
• Result:
  • Sotagliflozin: 7.60 versus 10.40 (events per 100-person years) on control; rate ratio 0.73 (95% CI 0.67–0.79, approximate, Poisson model); p ≈ <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference (a ratio of 1), so the event rate is statistically lower for Sotagliflozin than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcomes extend the primary question to related heart-failure events, cardiovascular death, broader cardiovascular composites, all-cause death, and renal outcomes. Across the posted secondary results, the pattern is not uniform: some event-rate comparisons favor sotagliflozin and have unadjusted p values below 0.001, while the cardiovascular-death comparison does not show clear statistical evidence of a difference. These outcomes provide context around the primary result rather than replacing it.

Secondary outcomes overlap conceptually with the primary endpoint. Heart-failure events appear in the primary and secondary definitions, and several composites include cardiovascular death or other cardiovascular events. Results across overlapping endpoints are therefore not independent confirmations. They can help describe which outcome domains were examined, but a favorable result for a related composite does not establish an effect on every component or a separate outcome.

The registry lists seven secondary outcomes, while the posted results include analyses for some of them; the record does not report a multiplicity-adjustment procedure. When many outcomes are tested, the chance of obtaining at least one apparently significant result can increase. As a general statistical principle, unadjusted secondary p values should therefore carry less weight than a prespecified primary analysis, particularly when the outcomes overlap and the testing strategy is not documented.

The registry does not report whether secondary analyses were prespecified in the statistical analysis plan, how missing data were handled for each outcome, or whether any outcome hierarchy controlled interpretation. Consequently, the secondary findings are best viewed as supportive or exploratory evidence whose strength depends on endpoint definitions and analysis plans that are not fully described in the registry record. They should not be used to claim consistent effects across all outcomes.

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

• Total Number of Occurrences of HHF and Urgent HF Visits
• Number of Deaths From Cardiovascular Causes
• Total Number of Occurrences of CV Death, HHF, Non-fatal Myocardial Infarction and Non-fatal Stroke
• Total Number of Occurrences of HHF, Urgent HF Visit, CV Death, and HF While Hospitalized
• Number of Occurrences After Randomization of the Composite of Sustained ≥50% Decrease in Estimated Glomerular Filtration Rate (eGFR) From Baseline (for ≥30 Days), Chronic Dialysis, Renal Transplant, or Sustained eGFR <15 mL/Min/1.73 m^2 (for ≥30 Days)
• Number of Deaths From Any Cause
• Total Number of Occurrences of CV Death, Non-fatal Myocardial Infarction and Non-fatal Stroke

9. Statistical Interpretation

10. Statistical Methods Explained

The primary endpoint is a recurrent-event rate. It counts cardiovascular death, hospitalization for heart failure, and urgent heart-failure visits, including first and potentially subsequent events, and expresses the total relative to person-time. A rate differs from a participant-level risk: the rate is event occurrences per exposure time, while a risk is the proportion of participants with an event over a specified period. General statistical interpretation should therefore keep the unit and denominator in view.

What does the recalculated rate ratio describe?

The recalculated comparison is an unadjusted rate ratio based on the posted group rates. A ratio below 1 indicates a lower estimated event rate in the sotagliflozin group than in the placebo group. For the primary endpoint, the reported group rates are 5.6 and 7.5 events per 100-person years, respectively. The recalculated comparison has p <0.001. It is a simple summary-statistic re-calculation, not a substitute for the trial’s reported analysis or a model adjusted for other variables.

Event counts are often modeled with Poisson methods when events accrue over exposure time. A basic Poisson model assumes that the event-count variability is consistent with its mean after accounting for exposure. As a general statistical matter, over-dispersion means the counts vary more than that assumption allows; ignoring it can make uncertainty estimates too small. The registry’s posted calculations are marked as Poisson, but it does not report a dispersion estimate or describe a correction for over-dispersion. Since repeated events from the same participant may be related, the details of how dependence was handled also matter and are not reported in the registry record.

How does the reported Cox result differ?

The registry reports a Cox proportional hazards model and a hazard ratio of 0.74 for the primary endpoint analysis, with a 95% confidence interval from 0.63 to 0.88 and p <0.001. In general, a hazard ratio compares the instantaneous event rates between groups among those still at risk at a given time, under the model’s assumptions. It is not the same quantity as a ratio of total recurrent-event rates. The registry does not report enough detail to determine precisely how the Cox model was applied to the endpoint that counts first and potentially subsequent occurrences.

The proportional-hazards assumption means, in general, that the relative hazard is treated as stable over time. The registry record does not report a test of this assumption or diagnostics for the model. Nor does it describe covariate adjustment for the reported analysis. Those details should not be inferred from the model name alone.

What does the p value tell readers?

A p value describes how incompatible the observed data are with a specified null model, under the statistical assumptions used. It is not the probability that the null hypothesis is true, nor does it measure the size or clinical importance of an effect. The primary Cox analysis reports p <0.001. The recalculated rate comparison also reports an unadjusted p value of <0.001. Their shared direction is informative, but the estimates come from different measures and should be interpreted according to their respective definitions.

For a count-rate analysis, event totals and time at risk contribute to estimation; for a time-to-event analysis, the timing of events and censoring are relevant. Censoring occurs when follow-up ends without an observed event, and general survival methods rely on assumptions about that process. The registry record does not describe censoring rules, missing-data methods, or sensitivity analyses. It also does not report whether the proportional-hazards model was the prespecified primary inferential method.

Why distinguish reported from recalculated analyses?

The recalculated rate comparison is an unadjusted re-calculation from posted summaries. The registry’s reported Cox model is the trial’s posted analysis and uses a hazard ratio. Differences between these measures can arise because they target different summaries and make different assumptions; they are not automatically evidence of inconsistency. In this trial the discrepancy flag is false. The registry record does not report a full analysis plan that would permit independent verification of every modeling choice.

Randomization supports comparison of allocated groups in expectation, while the intention-to-treat definition keeps participants classified by randomized group for the stated analysis. Neither feature removes uncertainty or supplies information about unreported modeling assumptions. Statistical interpretation therefore combines the endpoint definition, effect measure, confidence interval, p value, analysis population, and the registry’s limits on methodological detail.

11. Confidence Intervals and Precision

The registry’s reported primary Cox estimate is a hazard ratio of 0.74, with a 95% confidence interval from 0.63 to 0.88. The interval lies below 1, the value representing equal hazards in this measure. In general, a confidence interval describes a range of values compatible with the data and model at the stated confidence level; it is not a range containing a guaranteed proportion of individual outcomes.

The recalculated event-rate comparison is reported as a rate ratio with an interval of 0.679 to 0.821 in the underlying calculation, but those values exceed the permitted display precision for this explanation and are not repeated. The posted rates are 5.6 events per 100-person years for sotagliflozin and 7.5 for placebo. The interval for the reported Cox result and the interval for the recalculated rate ratio refer to different effect measures, so their widths should not be compared as though they quantify precisely the same uncertainty.

The confidence interval conveys estimation uncertainty under the corresponding analysis assumptions. It does not account for every limitation, such as unreported missing-data handling, potential model misspecification, or uncertainty about multiplicity across secondary outcomes. The registry does not report diagnostics or sensitivity analyses that would show how robust the interval is to alternative assumptions.

Precision also depends on the amount and distribution of outcome information, not enrollment alone. For a recurrent-event rate, event frequency and person-time matter; for a time-to-event analysis, event timing and censoring contribute. The registry record does not report all of those analysis details. The confidence interval should therefore be read as precision for the stated model and endpoint, not as a complete measure of certainty about broader clinical interpretation.

12. Planning a Similar Trial: Sample Size

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

The planning illustrations use the observed effect as a reference and show participant counts per arm for the rate endpoint. The rows consider planning for 100% of the observed effect, 75% of the observed effect, and 50% of the observed effect. For each assumed effect, the columns give participants per arm for 80% power and participants per arm for 90% power. These are alternative planning scenarios, not additional trial results.

The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is the stated fraction of the observed effect. The trial’s original design assumptions and sample-size justification are not reported in the registry record; these illustrations are based on the observed effect and are not a reconstruction of the trial’s original design.

Power is the probability, under a specified assumed effect and analysis model, of detecting an effect at the chosen significance level. The 80% column describes the planning count associated with an 80% chance of detecting the assumed effect under those assumptions; the 90% column describes the count associated with a 90% chance. The displayed values are participants per arm, not the total number of participants across both arms and not total events. The sample-size illustrations are not observed power.

Smaller assumed effects require more participants to achieve the same target power, all else equal. This pattern is visible across the rows: planning for 50% of the observed effect requires larger per-arm counts than planning for 75% or 100%. These figures are illustrative because actual requirements depend on the design, analysis, outcome frequency, follow-up, and assumptions used. The registry does not report the original trial’s full planning assumptions, so the illustrations should not be used to infer what the investigators anticipated before observing results.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, λ₀ and λ₁ are event rates per patient-year, and T is follow-up per participant in years. This assumes Poisson counts and equal follow-up.

Worked calculation for this trial

1. Control rate λ₀ = 0.0750; treatment rate λ₁ = 0.0560 events per patient-year; follow-up T = 2.50 years.
2. n = (1.96 + 0.842)² × (1/0.0750 + 1/0.0560) / (2.50 × [ln(0.747)]²) = 1,147.4, rounded up to 1,148 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
lambda0 <- 0.075                      # control rate, events per patient-year
lambda1 <- 0.056                      # treatment rate
tt      <- 2.5                       # follow-up per participant, years
n_per_arm <- function(power, frac = 1) {
  l1 <- lambda0 * (lambda1 / lambda0)^frac   # smaller effect = fraction of the observed log rate ratio
  ceiling(round((z_a + qnorm(power))^2 * (1 / lambda0 + 1 / l1) / (tt * log(l1 / lambda0)^2), 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Simulation 1: Poisson counts. Simulation 2: over-dispersed counts (variance = 1.5 x mean), analysed with the matching variance.
set.seed(3315143)
n    <- n_per_arm(0.80)
reps <- 20000
m0 <- lambda0 * n * tt; m1 <- lambda1 * n * tt
x0 <- rpois(reps, m0); x1 <- rpois(reps, m1)
z  <- log(x1 / x0) / sqrt(1 / x0 + 1 / x1)
cat(sprintf("Simulated power, Poisson counts, n = %s per arm: %.3f\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE)))
phi <- 1.5
y0 <- rnbinom(reps, mu = m0, size = m0 / (phi - 1)); y1 <- rnbinom(reps, mu = m1, size = m1 / (phi - 1))
z2 <- log(y1 / y0) / sqrt(phi * (1 / y0 + 1 / y1))
cat(sprintf("Simulated power, over-dispersed counts (phi = 1.5), same n: %.3f\n", mean(abs(z2) > z_a, na.rm = TRUE)))

Output from running the code

100% of observed effect: n per arm = 1,148 (80% power), 1,537 (90% power)
 75% of observed effect: n per arm = 1,958 (80% power), 2,621 (90% power)
 50% of observed effect: n per arm = 4,233 (80% power), 5,667 (90% power)
Simulated power, Poisson counts, n = 1,148 per arm: 0.807
Simulated power, over-dispersed counts (phi = 1.5), same n: 0.634

The first simulation draws Poisson counts and should land close to the target power. The second allows extra variability (variance 1.5 times the mean, a purely illustrative value), which lowers the power at the same sample size, so rate trials usually need more participants than the Poisson formula suggests.

14. Analyses Reported by the Sponsor

The registry’s reported primary analysis is a Cox proportional hazards model, with a hazard ratio of 0.74, a 95% confidence interval from 0.63 to 0.88, and p <0.001. The recalculated summary comparison is an unadjusted rate ratio based on the posted recurrent-event rates, with p <0.001. Both indicate a lower observed value for sotagliflozin than placebo, but one is a hazard ratio and the other a rate ratio. They answer related, not identical, statistical questions.

The recalculated result is not an alternative sponsor analysis or an adjustment to the reported model. It is a simple unadjusted calculation from the posted summary statistics. The registry record does not provide sufficient detail to reproduce all aspects of the Cox model or determine how its analysis handled recurrent events. It also does not describe any covariate adjustment for that reported result.

The discrepancy flag is false, so the posted summaries do not identify a flagged discrepancy between the re-calculation and reported analysis. The figures should still be read according to their measure and analysis method rather than treated as numerically interchangeable. The registry identifies Lexicon Pharmaceuticals as sponsor; it does not provide additional information about review or verification of the reported analysis.

15. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when investigators test several outcomes or comparisons. As a general statistical matter, repeated testing can increase the chance that at least one result appears statistically significant even if the underlying effects are absent. This concern is relevant because the registry lists multiple secondary outcomes, including overlapping cardiovascular and heart-failure composites.

The registry reports unadjusted p values for the posted secondary comparisons but does not report a multiplicity correction, a testing hierarchy, or a family-wise error strategy. Whether such methods were specified elsewhere is not reported in the registry record. The secondary p values should therefore be interpreted with caution and should not be treated as if each were an isolated confirmatory test.

The stated primary population is intention-to-treat: all randomized participants analyzed according to the group allocated by randomization. This defines the population and treatment-group assignment for the primary analysis. It does not describe the treatment of missing outcome information, participants lost to follow-up, treatment discontinuation, or protocol deviations. Those details are not reported in the registry record.

For time-to-event analyses, censoring rules and assumptions affect interpretation; for event-rate analyses, the handling of incomplete exposure and repeated events matters. The registry record does not describe these procedures, report sensitivity analyses, or explain whether the same analysis population was used for every secondary outcome. It also does not report an interim-analysis plan or stopping boundaries. Since the trial is listed as terminated, the absence of the termination reason and analysis-plan details limits assessment of whether the final analysis followed the original plan. These are uncertainties about reporting and interpretation, not evidence that a particular method was or was not used.

16. 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: cardiac failure (2.8%), acute kidney injury (1.2%), acute myocardial infarction (1.1%), pneumonia (1.1%), myocardial infarction (1.0%).

The registry reports serious adverse events affecting 1236 participants at risk in the sotagliflozin group and 1331 participants at risk in the placebo group. The corresponding numbers at risk for these serious-event summaries are 5291 and 5286. These counts describe participants with a serious adverse event, not the total number of serious-event episodes, and they do not by themselves establish whether an event was caused by treatment.

For other adverse events, the registry reports 705 affected participants among 5291 at risk in the sotagliflozin group and 609 among 5286 at risk in the placebo group. Deaths are reported as 246 in each group. The registry does not give confidence intervals or comparative statistical tests for these safety summaries, so they should be read descriptively rather than as formal evidence of a difference.

The most frequently listed serious adverse-event terms include cardiac failure at 2.8%, acute kidney injury at 1.2%, acute myocardial infarction at 1.1%, pneumonia at 1.1%, myocardial infarction at 1.0%, and angina unstable at 1.0%. The registry does not specify in this listing whether those term percentages are presented separately by treatment group, so they should not be assigned to a group. Serious-event counts and listed terms do not capture event severity, timing, duration, or causal attribution in full.

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

The posted data show lower primary event rates in the sotagliflozin group than in the placebo group over follow-up of up to 30 months. The registry’s reported Cox analysis also estimates a hazard ratio below 1, with a 95% confidence interval that lies below 1 and p <0.001. These are statistical descriptions of the randomized comparison for the defined population, regimen, endpoint, and follow-up.

The result does not show that every participant benefited, or that every event component changed in the same way. The primary endpoint combines cardiovascular death, hospitalization for heart failure, and urgent heart-failure visits, including subsequent occurrences. Component-specific results for the primary endpoint are not reported in the registry record. The estimate also does not describe effects after the recorded follow-up or in populations not represented by the trial.

A statistically significant result is not itself a measure of clinical importance. The registry record does not report a threshold for a clinically meaningful difference, nor does it supply enough detail to evaluate every assumption of the analyses. The confidence interval describes uncertainty under the model used; it does not eliminate uncertainty from missing methodological details, multiplicity among secondary analyses, or limits of generalizability.

The secondary results add context but involve multiple outcomes, some of which overlap with the primary endpoint. The registry does not report multiplicity adjustment, so unadjusted secondary findings should receive less weight than the primary result. Safety counts are descriptive and do not establish causality or a comparative safety conclusion on their own.

Accordingly, the results support a statistical difference in the primary comparison as reported, while leaving questions about component contributions, unreported analysis details, clinical importance, and application beyond the trial population unresolved. The trial status is terminated, but the reason is not reported in the registry record; that status alone does not explain the result or its interpretation.

18. Why This Trial Matters Statistically

This trial is statistically informative because its primary endpoint counts recurrent occurrences rather than only recording whether a participant had an event. That distinction matters for cardiovascular and heart-failure outcomes, where repeated hospitalizations or urgent visits can contribute to the observed burden. Reporting an event rate per 100-person years relates event occurrence to follow-up exposure, while the registry’s Cox analysis supplies a time-to-event measure.

Considering both measures makes clear why endpoint definitions and estimands matter. A rate ratio and a hazard ratio are not interchangeable, even when both point in the same direction. The posted group rates and reported Cox estimate each describe the comparison from a different statistical perspective. Readers should interpret each in its stated framework instead of treating one as a direct validation of the other.

The trial also illustrates the importance of uncertainty and analysis transparency. The primary confidence interval lies below 1, while details such as censoring rules, missing-data methods, model diagnostics, and the original analysis plan are not reported in the registry record. Those omissions do not negate the posted result, but they constrain independent assessment of robustness.

Finally, the presence of multiple overlapping secondary outcomes shows why multiplicity matters. Secondary analyses can add useful context, yet unadjusted findings carry less confirmatory weight when the registry does not describe a testing hierarchy or adjustment. Taken together, the trial provides a useful case for separating the primary result, recurrent-event rates, time-to-event estimates, safety descriptions, and broader inferential limits.

19. 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.
• Rate comparisons use a Poisson approximation unless the sponsor posted confidence limits; real event counts are often over-dispersed.

The registry record leaves important design and analysis details unspecified. It does not report the original sample-size justification, the full statistical analysis plan, or planned interim analyses. The trial is listed as terminated, but the reason for termination is not reported. These gaps prevent a complete assessment of whether the posted analyses followed the original design and whether termination affected planned follow-up or inference.

The primary endpoint combines cardiovascular death, hospitalization for heart failure, and urgent heart-failure visits, including potentially repeated events. Component-specific results are not reported in the registry record, so the overall estimate cannot show how much each component contributed. The record also does not provide full detail on the method used to account for dependence among repeated events or the assumptions and diagnostics for the reported Cox model.

Handling of missing outcomes, censoring, treatment discontinuation, and protocol deviations is not reported. The intention-to-treat definition identifies randomized participants and their allocated treatment groups, but does not alone explain how incomplete follow-up was addressed. The registry also does not report model diagnostics, sensitivity analyses, or a multiplicity procedure for the several secondary outcomes.

Safety results are presented as counts and selected serious-event terms without comparative uncertainty estimates or causal attribution. The registry listing does not specify whether the serious-term percentages are group-specific. As a result, those figures are descriptive and cannot resolve comparative safety questions by themselves. Generalization is also bounded by the trial’s population, regimens, and follow-up of up to 30 months; the record does not establish what would occur beyond those conditions.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Effect of Sotagliflozin on Cardiovascular and Renal Events in Participants With Type 2 Diabetes and Moderate Renal Impairment Who Are at Cardiovascular Risk — NCT03315143.
• Registry record last updated 2022-10-28; status last verified 2022-09.
• Results first posted 2022-10-28.
• 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.

23. Record Summary

NCT03315143 was a phase 3, randomized, quadruple-masked, parallel-group trial of sotagliflozin versus matching placebo in participants with type 2 diabetes, cardiovascular risk factors, and impaired renal function. The registry lists enrollment of 10584 and identifies Lexicon Pharmaceuticals as sponsor. The trial is listed as terminated; the reason is not reported in the registry record.

The primary endpoint counted total occurrences of cardiovascular death, hospitalization for heart failure, and urgent heart-failure visits, expressed as events per 100-person years over follow-up of up to 30 months. Posted rates were 5.6 for sotagliflozin and 7.5 for placebo. The registry’s reported Cox analysis gave a hazard ratio of 0.74, with a 95% confidence interval from 0.63 to 0.88 and p <0.001.

The rate comparison and Cox result use different measures. Missing-data procedures, the original sample-size justification, interim analyses, and multiplicity methods are not reported in the registry record. Secondary findings and safety counts therefore require interpretation within those limits.