Towards Treatment Effect Interpretability: A Bayesian Re-analysis of 194,129 Patient Outcomes Across 230 Oncology Trials.

Most oncology trials define superiority of an experimental therapy compared to a control therapy according to frequentist significance thresholds, which are widely misinterpreted. Posterior probability distributions computed by Bayesian inference may be more intuitive measures of uncertainty, particularly for measures of clinical benefit such as the minimum clinically important difference (MCID). Here, we manually reconstructed 194,129 individual patient-level outcomes across 230 phase III, superiority-design, oncology trials. Posteriors were calculated by Markov Chain Monte Carlo sampling using standard priors. All trials interpreted as positive had probabilities > 90% for marginal benefits (HR < 1). However, 38% of positive trials had ≤ 90% probabilities of achieving the MCID (HR < 0.8), even under an enthusiastic prior. A subgroup analysis of 82 trials that led to regulatory approval showed 30% had ≤ 90% probability for meeting the MCID under an enthusiastic prior. Conversely, 24% of negative trials had > 90% probability of achieving marginal benefits, even under a skeptical prior, including 12 trials with a primary endpoint of overall survival. Lastly, a phase III oncology-specific prior from a previous work, which uses published summary statistics rather than reconstructed data to compute posteriors, validated the individual patient-level data findings. Taken together, these results suggest that Bayesian models add considerable unique interpretative value to phase III oncology trials and provide a robust solution for overcoming the discrepancies between refuting the null hypothesis and obtaining a MCID.

Secondary Endpoint Utilization and Publication Rate among Phase III Oncology Trials.

Secondary endpoints (SEP) provide crucial information in the interpretation of clinical trials, but their features are not yet well understood. Thus, we sought to empirically characterize the scope and publication rate of SEPs among late-phase oncology trials. We assessed SEPs for each randomized, published phase III oncology trial across all publications and ClinicalTrials.gov, performing logistic regressions to evaluate associations between trial characteristics and SEP publication rates. After screening, a total of 280 trials enrolling 244,576 patients and containing 2,562 SEPs met the inclusion criteria. Only 22% of trials (62/280) listed all SEPs consistently between ClinicalTrials.gov and the trial protocol. The absolute number of SEPs per trial increased over time, and trials sponsored by industry had a greater number of SEPs (median 9 vs. 5 SEPs per trial; P < 0.0001). In total, 69% of SEPs (1,770/2,562) were published. The publication rate significantly varied by SEP category [X2 (5, N = 2,562) = 245.86; P < 0.001]. SEPs that place the most burden on patients, such as patient-reported outcomes and translational correlatives, were published at 63% (246/393) and 44% (39/88), respectively. Trials with more SEPs were associated with lower overall SEP publication rates. Overall, our findings are that SEP publication rates in late-phase oncology trials are highly variable based on the type of SEP. To avoid undue burden on patients and promote transparency of findings, trialists should weigh the biological and clinical relevance of each SEP together with its feasibility at the time of trial design. SIGNIFICANCE: In this investigation, we characterized the utilization and publication rates of SEPs among late-phase oncology trials. Our results draw attention to the proliferation of SEPs in recent years. Although overall publication rates were high, underpublication was detected among endpoints that may increase patient burden (such as translational correlatives and patient-reported outcomes).

Increasing Power in Phase III Oncology Trials With Multivariable Regression: An Empirical Assessment of 535 Primary End Point Analyses.

PURPOSE: A previous study demonstrated that power against the (unobserved) true effect for the primary end point (PEP) of most phase III oncology trials is low, suggesting an increased risk of false-negative findings in the field of late-phase oncology. Fitting models with prognostic covariates is a potential solution to improve power; however, the extent to which trials leverage this approach, and its impact on trial interpretation at scale, is unknown. To that end, we hypothesized that phase III trials using multivariable PEP analyses are more likely to demonstrate superiority versus trials with univariable analyses. METHODS: PEP analyses were reviewed from trials registered on ClinicalTrials.gov. Adjusted odds ratios (aORs) were calculated by logistic regressions. RESULTS: Of the 535 trials enrolling 454,824 patients, 69% (n = 368) used a multivariable PEP analysis. Trials with multivariable PEP analyses were more likely to demonstrate PEP superiority (57% [209 of 368] v 42% [70 of 167]; aOR, 1.78 [95% CI, 1.18 to 2.72]; P = .007). Among trials with a multivariable PEP model, 16 conditioned on covariates and 352 stratified by covariates. However, 108 (35%) of 312 trials with stratified analyses lost power by categorizing a continuous variable, which was especially common among immunotherapy trials (aOR, 2.45 [95% CI, 1.23 to 4.92]; P = .01). CONCLUSION: Trials increasing power by fitting multivariable models were more likely to demonstrate PEP superiority than trials with unadjusted analysis. Underutilization of conditioning models and empirical power loss associated with covariate categorization required by stratification were identified as barriers to power gains. These findings underscore the opportunity to increase power in phase III trials with conventional methodology and improve patient access to effective novel therapies.

Improving the clinical meaning of surrogate endpoints: An empirical assessment of clinical progression in phase III oncology trials.

Disease progression in clinical trials is commonly defined by radiologic measures. However, clinical progression may be more meaningful to patients, may occur even when radiologic criteria for progression are not met, and often requires a change in therapy in clinical practice. The objective of this study was to determine the utilization of clinical progression criteria within progression-based trial endpoints among phase III trials testing systemic therapies for metastatic solid tumors. The primary manuscripts and protocols of phase III trials were reviewed for whether clinical events, such as refractory pain, tumor bleeding, or neurologic compromise, could constitute a progression event. Univariable logistic regression computed odds ratios (OR) and 95% CI for associations between trial-level covariates and clinical progression. A total of 216 trials enrolling 148,190 patients were included, with publication dates from 2006 through 2020. A major change in clinical status was included in the progression criteria of 13% of trials (n = 27), most commonly as a secondary endpoint (n = 22). Only 59% of trials (n = 16) reported distinct clinical progression outcomes that constituted the composite surrogate endpoint. Compared with other disease sites, genitourinary trials were more likely to include clinical progression definitions (16/33 [48%] vs. 11/183 [6%]; OR, 14.72; 95% CI, 5.99 to 37.84; p < .0001). While major tumor-related clinical events were seldom considered as disease progression events, increased attention to clinical progression may improve the meaningfulness and clinical applicability of surrogate endpoints for patients with metastatic solid tumors.