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.

Lost in the plot: missing visual elements in Kaplan-Meier plots of phase III oncology trials.

Missing visual elements (MVE) in Kaplan-Meier (KM) curves can misrepresent data, preclude curve reconstruction, and hamper transparency. This study evaluated KM plots of phase III oncology trials. MVE were defined as an incomplete y-axis range or missing number at risk table in a KM curve. Surrogate endpoint KM curves were additionally evaluated for complete interpretability, defined by (1) reporting the number of censored patients and (2) correspondence of the disease assessment interval with the number at risk interval. Among 641 trials enrolling 518 235 patients, 116 trials (18%) had MVE in KM curves. Industry sponsorship, larger trials, and more recently published trials were correlated with lower odds of MVE. Only 3% of trials (15 of 574) published surrogate endpoint KM plots with complete interpretability. Improvements in the quality of KM curves of phase III oncology trials, particularly for surrogate endpoints, are needed for greater interpretability, reproducibility, and transparency in oncology research.

Effectiveness of the nutrition referral system in a multidisciplinary pancreatic cancer clinic.

PURPOSE: Proactive nutrition screening and intervention is associated with improved outcomes for patients with pancreatic adenocarcinoma (PDAC). To better optimize nutrition amongst our PDAC population, we implemented systematic malnutrition screening in the Johns Hopkins pancreas multidisciplinary clinic (PMDC) and assessed the effectiveness of our nutrition referral system. METHODS: This was a single institution prospective study of patients seen in the PMDC, screened for malnutrition using the Malnutrition Screening Tool (MST) (score range=0 to 5, score > 2 indicates risk of malnutrition), and offered referrals to the oncology dietitian. Patients that requested a referral but did not attend a nutrition appointment were contacted by phone to assess barriers to seeing the dietitian. Univariate (UVA) and multivariable (MVA) analyses were carried out to identify predictors of referral status and appointment completion status. RESULTS: A total of 97 patients were included in the study, of which 72 (74.2%) requested a referral and 25 (25.8%) declined. Of the 72 patients who requested a referral, 31 (43.1%) attended an appointment with the oncology dietitian. Data on information session attendance was available for 35 patients, of which 8 (22.9%) attended a pre-clinic information session in which the importance of optimal nutrition was highlighted. On MVA, information session attendance was significantly associated with requesting a referral (OR: 11.1, 95% CI 1.12-1.0E3, p=0.037) and successfully meeting with the oncology dietitian (OR: 5.88, 95% CI 1.00-33.3, p=0.049). CONCLUSION: PMDC teams should institute educational initiatives on the importance of optimal nutrition in order to increase patient engagement with nutrition services.

Food and Drug Administration approvals in phase 3 Cancer clinical trials.

BACKGROUND: Phase 3 oncologic randomized clinical trials (RCTs) can lead to Food and Drug Administration (FDA) approvals. In this study, we aim to identify trial-related factors associated with trials leading to subsequent FDA drug approvals. METHODS: We performed a database query through the ClinicalTrials.gov registry to search for oncologic phase 3 RCTs on February 2020. We screened all trials for therapeutic, cancer-specific, phase 3, randomized, multi-arm trials. We then identified whether a trial was used for subsequent FDA drug approval through screening of FDA approval announcements. RESULTS: In total, 790 trials were included in our study, with 225 trials (28.4%) generating data that were subsequently used for FDA approvals. Of the 225 FDA approvals identified, 65 (28.9%) were based on trials assessing overall survival (OS) as a primary endpoint (PEP), two (0.9%) were based on trials with a quality of life (QoL) PEP, and 158 approvals (70.2%) were based on trials with other PEP (P = 0.01). FDA approvals were more common among industry funded-trials (219, 97.3%; P < 0.001), and less common among trials sponsored by national cooperative groups (21, 9.3%; P < 0.001). Finally, increased pre-hoc power and meeting patients' accrual target were associated with FDA approvals (P < 0.001). CONCLUSIONS: The majority of FDA approvals are based on data generated from trials analyzing surrogate primary endpoints and trials receiving industry funding. Additional studies are required to understand the complexity of FDA approvals.

Exclusion of Men from Randomized Phase III Breast Cancer Clinical Trials.

Male breast cancer treatment regimens are often extrapolated from female-based studies because of a paucity of literature analyzing male breast cancer. Using ClinicalTrials.gov, we analyzed breast cancer randomized clinical trials (RCTs) to determine which factors were associated with male-gender inclusion. Of 131 breast cancer RCTs identified, male patients represented 0.087% of the total study population, which is significantly less than the proportion of male patients with breast cancer in the U.S. (0.95%; p < .001). Twenty-seven trials included male patients (20.6%). Lower rates of male inclusion were seen in trials that randomized or mandated hormone therapy as part of the trial protocol compared with trials that did not randomize or mandate endocrine therapy (2.5% vs. 28.6% male inclusion; p < .001). It is imperative for breast cancer clinical trials to include men when allowable in order to improve generalizability and treatment decisions in male patients with breast cancer.

Professional Medical Writer Assistance in Oncology Clinical Trials.

BACKGROUND: The use of professional medical writers (PMWs) has been historically low, but contemporary data regarding PMW usage are scarce. In this study, we sought to quantify PMW use in oncologic phase III randomized controlled trials (RCTs). METHODS: We performed a database query through ClinicalTrials.gov to identify cancer-specific phase III RCTs; we then identified whether a PMW was involved in writing the associated trial manuscript reporting primary endpoint results. RESULTS: Two-hundred sixty trials of 600 (43.3%) used a PMW. Industry-funded trials used PMWs more often than nonindustry trials (54.9% vs. 3.0%, p < .001). Increased PMW usage was further noted among trials meeting their primary endpoint (53.4% vs. 32.9%, p < .001) and trials that led to subsequent Food and Drug Administration approval (63.1% vs. 36.3%, p < .001). By treatment interventions, PMW use was highest among systemic therapy trials (50.2%). Lastly, the use of PMWs increased significantly over time (odds ratio: 1.11/year, p = .001). CONCLUSION: PMW use rates are high among industry-funded trials. We urge continued and increased transparency in reporting the funding and use of PMWs.

Tobacco exposure as a major modifier of oncologic outcomes in human papillomavirus (HPV) associated oropharyngeal squamous cell carcinoma.

BACKGROUND: The incidence of oropharyngeal squamous cell carcinoma (OPSCC) in the US is rapidly increasing, driven largely by the epidemic of human papillomavirus (HPV)-mediated OPSCC. Although survival for patients with HPV mediated OPSCC (HPV+ OPSCC) is generally better than that of patients with non-virally mediated OPSCC, this effect is not uniform. We hypothesized that tobacco exposure remains a critical modifier of survival for HPV+ OPSCC patients. METHODS: We conducted a retrospective analysis of 611 OPSCC patients with concordant p16 and HPV testing treated at a single institute (2002-2013). Survival analysis was performed using Kaplan-Meier analysis and Cox regression. Recursive partitioning analysis (RPA) was used to define tobacco exposure associated with survival (p < 0.05). RESULTS: Tobacco exposure impacted overall survival (OS) for HPV+ patients on univariate and multivariate analysis (p = 0.002, p = 0.003 respectively). RPA identified 30 pack-years (PY) as a threshold at which survival became significantly worse in HPV+ patients. OS and disease-free survival (DFS) for HPV+ > 30 PY patients didn't differ significantly from HPV- patients (p = 0.72, p = 0.27, respectively). HPV+ > 30 PY patients had substantially lower 5-year OS when compared to their ≤30 PYs counterparts: 78.4% vs 91.6%; p = 0.03, 76% vs 88.3%; p = 0.07, and 52.3% vs 74%; p = 0.05, for stages I, II, and III (AJCC 8th Edition Manual), respectively. CONCLUSIONS: Tobacco exposure can eliminate the survival benefit associated with HPV+ status in OPSCC patients. Until this effect can be clearly quantified using prospective datasets, de-escalation of treatment for HPV + OPSCC smokers should be avoided.

Performance Status Restriction in Phase III Cancer Clinical Trials.

BACKGROUND: Patients with good performance status (PS) tend to be favored in randomized clinical trials (RCTs), possibly limiting the generalizability of trial findings. We aimed to characterize trial-related factors associated with the use of PS eligibility criteria and analyze patient accrual breakdown by PS. METHODS: Adult, therapeutic, multiarm phase III cancer-specific RCTs were identified through ClinicalTrials.gov. PS data were extracted from articles. Trials with a PS restriction ECOG score ≤1 were identified. Factors associated with PS restriction were determined, and the use of PS restrictions was analyzed over time. RESULTS: In total, 600 trials were included and 238,213 patients had PS data. Of those trials, 527 studies (87.8%) specified a PS restriction cutoff, with 237 (39.5%) having a strict inclusion criterion (ECOG PS ≤1). Enrollment criteria restrictions based on PS (ECOG PS ≤1) were more common among industry-supported trials (P<.001) and lung cancer trials (P<.001). Nearly half of trials that led to FDA approval included strict PS restrictions. Most patients enrolled across all trials had an ECOG PS of 0 to 1 (96.3%). Even among trials that allowed patients with ECOG PS ≥2, only 8.1% of those enrolled had a poor PS. Trials of lung, breast, gastrointestinal, and genitourinary cancers all included <5% of patients with poor PS. Finally, only 4.7% of patients enrolled in trials that led to subsequent FDA approval had poor PS. CONCLUSIONS: Use of PS restrictions in oncologic RCTs is pervasive, and exceedingly few patients with poor PS are enrolled. The selective accrual of healthier patients has the potential to severely limit and bias trial results. Future trials should consider a wider cancer population with close toxicity monitoring to ensure the generalizability of results while maintaining patient safety.

Relationship between treatment center case volume and survival for localized Ewing sarcoma: The role of radiotherapy timing.

In the treatment of localized Ewing sarcoma (EWS), delays in local therapy are known to adversely impact overall survival (OS). However, the role of treatment center volume in EWS outcomes, and the interaction between center volume and local therapy timing with definitive radiotherapy, remains unknown. Using the National Cancer Database, we demonstrate that treatment at the lowest EWS volume centers is associated with reduced OS, explained partly by higher rates of delayed local therapy. Treatment at the highest volume centers results in improved OS, but appears independent of radiotherapy timing. Future efforts to improve care for EWS patients across treatment centers are imperative.

Non-English language validation of patient-reported outcome measures in cancer clinical trials.

Patient-reported outcome measures (PROMs) are increasingly incorporated as endpoints in oncology clinical trials but are often only validated in English. ClinicalTrials.gov was queried for cancer-specific randomized control trials (RCTs) addressing a therapeutic intervention and enrolling primarily in the USA. Peer-reviewed validation of Spanish and Chinese versions of each PROM was assessed. Of 103 eligible trials, a PROM was used as a primary endpoint in 25 RCTs (24.3%) and as a secondary endpoint in 78 RCTs (75.7%). A total of 61 of the 103 eligible trials (59.2%) and 17 of the 25 trials with a PROM primary endpoint (68.0%) used a PROM with either no Spanish or Chinese validation. The absence of validated PROM translations may diminish the voices of non-English language speaking trial participants. With an increasingly diverse US population, validation of non-English PROM translations may decrease disparities in trial participation and improve generalizability of study results.

Radiographic retropharyngeal lymph node involvement in HPV-associated oropharyngeal carcinoma: Patterns of involvement and impact on patient outcomes.

BACKGROUND: The objective of the current study was to characterize the incidence, pattern, and impact on oncologic outcomes of retropharyngeal lymph node (RPLN) involvement in HPV-associated oropharyngeal cancer (OPC). METHODS: Data regarding patients with HPV-associated OPC who were treated at The University of Texas MD Anderson Cancer Center with intensity-modulated radiotherapy from 2004 through 2013 were analyzed retrospectively. RPLN status was determined by reviewing pretreatment imaging and/or reports. Outcomes analysis was restricted to patients with lymph node-positive (+) disease. Kaplan-Meier survival estimates were generated and survival curves were compared using the log-rank test. Bayesian information criterion assessed model performance changes with the addition of RPLN status to current American Joint Committee on Cancer staging. Competing risk analysis compared modes of disease recurrence. RESULTS: The incidence of radiographic RPLN involvement was 9% (73 of 796 patients) and was found to vary by primary tumor site. The 5-year rates of freedom from distant metastases (FDM) and overall survival were lower in patients with RPLN(+) status compared with those with RPLN-negative (-) status (84% vs 93% [P = .0327] and 74% vs 87% [P = .0078], respectively). RPLN(+) status was not found to be associated with outcomes on multivariate analysis. Bayesian information criterion analysis demonstrated that current American Joint Committee on Cancer staging was not improved with the inclusion of RPLN. Locoregional and distant disease recurrence probabilities for those patients with RPLN(+) status were 8% and 13%, respectively, compared with 10% and 6%, respectively, for those with RPLN(-) status. RPLN(+) status portended worse 5-year FDM in the low-risk subgroup (smoking history of <10 pack-years) and among patients who received concurrent chemotherapy but not induction chemotherapy. CONCLUSIONS: RPLN(+) status was associated with worse overall survival and FDM on univariate but not multivariate analysis. In subgroup analyses, RPLN(+) status was associated with poorer FDM in both patients with a smoking history of <10 pack-years and those who received concurrent chemotherapy, suggesting that RPLN(+) status could be considered an exclusion criteria in treatment deintensification efforts seeking to omit chemotherapy.

Differential Treatment Effects of Subgroup Analyses in Phase 3 Oncology Trials From 2004 to 2020.

Importance: Subgroup analyses are often performed in oncology to investigate differential treatment effects and may even constitute the basis for regulatory approvals. Current understanding of the features, results, and quality of subgroup analyses is limited. Objective: To evaluate forest plot interpretability and credibility of differential treatment effect claims among oncology trials. Design, Setting, and Participants: This cross-sectional study included randomized phase 3 clinical oncology trials published prior to 2021. Trials were screened from ClinicalTrials.gov. Main Outcomes and Measures: Missing visual elements in forest plots were defined as a missing point estimate or use of a linear x-axis scale for hazard and odds ratios. Multiplicity of testing control was recorded. Differential treatment effect claims were rated using the Instrument for Assessing the Credibility of Effect Modification Analyses. Linear and logistic regressions evaluated associations with outcomes. Results: Among 785 trials, 379 studies (48%) enrolling 331 653 patients reported a subgroup analysis. The forest plots of 43% of trials (156 of 363) were missing visual elements impeding interpretability. While 4148 subgroup effects were evaluated, only 1 trial (0.3%) controlled for multiple testing. On average, trials that did not meet the primary end point conducted 2 more subgroup effect tests compared with trials meeting the primary end point (95% CI, 0.59-3.43 tests; P = .006). A total of 101 differential treatment effects were claimed across 15% of trials (55 of 379). Interaction testing was missing in 53% of trials (29 of 55) claiming differential treatment effects. Trials not meeting the primary end point were associated with greater odds of no interaction testing (odds ratio, 4.47; 95% CI, 1.42-15.55, P = .01). The credibility of differential treatment effect claims was rated as low or very low in 93% of cases (94 of 101). Conclusions and Relevance: In this cross-sectional study of phase 3 oncology trials, nearly half of trials presented a subgroup analysis in their primary publication. However, forest plots of these subgroup analyses largely lacked essential features for interpretation, and most differential treatment effect claims were not supported. Oncology subgroup analyses should be interpreted with caution, and improvements to the quality of subgroup analyses are needed.

Bayesian Interim Analysis and Efficiency of Phase III Randomized Trials.

IMPORTANCE: Improving the efficiency of interim assessments in phase III trials should reduce trial costs, hasten the approval of efficacious therapies, and mitigate patient exposure to disadvantageous randomizations. OBJECTIVE: We hypothesized that in silico Bayesian early stopping rules improve the efficiency of phase III trials compared with the original frequentist analysis without compromising overall interpretation. DESIGN: Cross-sectional analysis. SETTING: 230 randomized phase III oncology trials enrolling 184,752 participants. PARTICIPANTS: Individual patient-level data were manually reconstructed from primary endpoint Kaplan-Meier curves. INTERVENTIONS: Trial accruals were simulated 100 times per trial and leveraged published patient outcomes such that only the accrual dynamics, and not the patient outcomes, were randomly varied. MAIN OUTCOMES AND MEASURES: Early stopping was triggered per simulation if interim analysis demonstrated ≥ 85% probability of minimum clinically important difference/3 for efficacy or futility. Trial-level early closure was defined by stopping frequencies ≥ 0.75. RESULTS: A total of 12,451 simulations (54%) met early stopping criteria. Trial-level early stopping frequency was highly predictive of the published outcome (OR, 7.24; posterior probability of association, >99.99%; AUC, 0.91; P < 0.0001). Trial-level early closure was recommended for 82 trials (36%), including 62 trials (76%) which had performed frequentist interim analysis. Bayesian early stopping rules were 96% sensitive (95% CI, 91% to 98%) for detecting trials with a primary endpoint difference, and there was a high level of agreement in overall trial interpretation (Bayesian Cohen's κ, 0.95; 95% CrI, 0.92 to 0.99). However, Bayesian interim analysis was associated with >99.99% posterior probability of reducing patient enrollment requirements ( P < 0.0001), with an estimated cumulative enrollment reduction of 20,543 patients (11%; 89 patients averaged equally over all studied trials) and an estimated cumulative cost savings of 851 million USD (3.7 million USD averaged equally over all studied trials). CONCLUSIONS AND RELEVANCE: Bayesian interim analyses may improve randomized trial efficiency by reducing enrollment requirements without compromising trial interpretation. Increased utilization of Bayesian interim analysis has the potential to reduce costs of late-phase trials, reduce patient exposures to ineffective therapies, and accelerate approvals of effective therapies. KEY POINTS: Question: What are the effects of Bayesian early stopping rules on the efficiency of phase III randomized oncology trials?Findings: Individual-patient level outcomes were reconstructed for 184,752 patients from 230 trials. Compared with the original interim analysis strategy, in silico Bayesian interim analysis reduced patient enrollment requirements and preserved the original trial interpretation. Meaning: Bayesian interim analysis may improve the efficiency of conducting randomized trials, leading to reduced costs, reduced exposure of patients to disadvantageous treatments, and accelerated approval of efficacious therapies.

Proportional Hazards Violations in Phase 3 Cancer Clinical Trials: A Potential Source of Trial Misinterpretation.

BACKGROUND: Survival analyses of novel agents with long-term responders often exhibit differential hazard rates over time. Such proportional hazards violations (PHVs) may reduce the power of the log-rank test and lead to misinterpretation of trial results. We aimed to characterize the incidence and study attributes associated with PHVs in phase 3 oncology trials and assess the utility of restricted mean survival time (RMST) and MaxCombo as additional analyses. METHODS: Clinicaltrials.gov and PubMed were searched to identify 2-arm, randomized, phase 3 superiority-design cancer trials with time-to-event primary endpoints and published results through 2020. Patient-level data were reconstructed from published Kaplan-Meier curves. PHVs were assessed using Schoenfeld residuals. RESULTS: Three hundred fifty-seven Kaplan-Meier comparisons across 341 trials were analyzed, encompassing 292,831 enrolled patients. PHVs were identified in 85/357 (23.8%; 95%CI 19.7%, 28.5%) comparisons. In multivariable analysis, non-OS endpoints (odds ratio [OR] 2.16 [95%CI 1.21, 3.87]; P=.009) were associated with higher odds of PHVs, and immunotherapy comparisons (OR 1.94 [95%CI 0.98, 3.86]; P=.058) were weakly suggestive of higher odds of PHVs. Few trials with PHVs (25/85, 29.4%) pre-specified a statistical plan to account for PHVs. Fourteen trials with PHVs exhibited discordant statistical signals with RMST or MaxCombo, of which ten (71%) reported negative results. CONCLUSION: PHVs are common across therapy types, and attempts to account for PHVs in statistical design are lacking despite the potential for results exhibiting non-proportional hazards to be misinterpreted.

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).

Association of differential censoring with survival and suboptimal control arms among oncology clinical trials.

Differential censoring, which refers to censoring imbalance between treatment arms, may bias the interpretation of survival outcomes in clinical trials. In 146 phase III oncology trials with statistically significant time-to-event surrogate primary endpoints, we evaluated the association between differential censoring in the surrogate primary endpoints, control arm adequacy, and the subsequent statistical significance of overall survival results. Twenty-four (16%) trials exhibited differential censoring that favored the control arm, whereas 15 (10%) exhibited differential censoring that favored the experimental arm. Positive overall survival was more common in control arm differential censoring trials (63%) than in trials without differential censoring (37%) or with experimental arm differential censoring (47%; odds ratio = 2.64, 95% confidence interval = 1.10 to 7.20; P = .04). Control arm differential censoring trials more frequently used suboptimal control arms at 46% compared with 20% without differential censoring and 13% with experimental arm differential censoring (odds ratio = 3.60, 95% confidence interval = 1.29 to 10.0; P = .007). The presence of control arm differential censoring in trials with surrogate primary endpoints, especially in those with overall survival conversion, may indicate an inadequate control arm and should be examined and explained.