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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.
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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.
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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).
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Ensaios Clínicos Fase III como Assunto , Humanos , Neoplasias/terapia , Oncologia/estatística & dados numéricos , Ensaios Clínicos Controlados Aleatórios como Assunto/estatística & dados numéricos , Determinação de Ponto FinalRESUMO
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.
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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.
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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.
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Ensaios Clínicos Fase III como Assunto , Estimativa de Kaplan-Meier , Humanos , Ensaios Clínicos Fase III como Assunto/normas , Neoplasias/terapia , Oncologia/normas , Oncologia/métodosRESUMO
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 331â¯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.
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Oncologia , Neoplasias , Humanos , Estudos Transversais , Neoplasias/terapia , Razão de Chances , Ensaios Clínicos Controlados Aleatórios como Assunto , Ensaios Clínicos Fase III como AssuntoRESUMO
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.
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Neoplasias , Humanos , Neoplasias/mortalidade , Neoplasias/terapia , Ensaios Clínicos Fase III como Assunto , Projetos de Pesquisa/normas , Oncologia/normasRESUMO
BACKGROUND: The 'Table 1 Fallacy' refers to the unsound use of significance testing for comparing the distributions of baseline variables between randomised groups to draw erroneous conclusions about balance or imbalance. We performed a cross-sectional study of the Table 1 Fallacy in phase III oncology trials. METHODS: From ClinicalTrials.gov, 1877 randomised trials were screened. Multivariable logistic regressions evaluated predictors of the Table 1 Fallacy. RESULTS: A total of 765 randomised controlled trials involving 553,405 patients were analysed. The Table 1 Fallacy was observed in 25% of trials (188 of 765), with 3% of comparisons deemed significant (59 of 2353), approximating the typical 5% type I error assertion probability. Application of trial-level multiplicity corrections reduced the rate of significant findings to 0.3% (six of 2345 tests). Factors associated with lower odds of the Table 1 Fallacy included industry sponsorship (adjusted odds ratio [aOR] 0.29, 95% confidence interval [CI] 0.18-0.47; multiplicity-corrected P < 0.0001), larger trial size (≥795 versus <280 patients; aOR 0.32, 95% CI 0.19-0.53; multiplicity-corrected P = 0.0008), and publication in a European versus American journal (aOR 0.06, 95% CI 0.03-0.13; multiplicity-corrected P < 0.0001). CONCLUSIONS: This study highlights the persistence of the Table 1 Fallacy in contemporary oncology randomised controlled trials, with one of every four trials testing for baseline differences after randomisation. Significance testing is a suboptimal method for identifying unsound randomisation procedures and may encourage misleading inferences. Journal-level enforcement is a possible strategy to help mitigate this fallacy.
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Neoplasias , Humanos , Prevalência , Estudos Transversais , Neoplasias/epidemiologia , Neoplasias/terapia , Ensaios Clínicos Controlados Aleatórios como AssuntoRESUMO
Optimal management of cancer patients relies heavily on late-phase oncology randomized controlled trials. A comprehensive understanding of the key considerations in designing and interpreting late-phase trials is crucial for improving subsequent trial design, execution, and clinical decision-making. In this review, we explore important aspects of late-phase oncology trial design. We begin by examining the selection of primary endpoints, including the advantages and disadvantages of using surrogate endpoints. We address the challenges involved in assessing tumor progression and discuss strategies to mitigate bias. We define informative censoring bias and its impact on trial results, including illustrative examples of scenarios that may lead to informative censoring. We highlight the traditional roles of the log-rank test and hazard ratio in survival analyses, along with their limitations in the presence of nonproportional hazards as well as an introduction to alternative survival estimands, such as restricted mean survival time or MaxCombo. We emphasize the distinctions between the design and interpretation of superiority and noninferiority trials, and compare Bayesian and frequentist statistical approaches. Finally, we discuss appropriate utilization of phase II and phase III trial results in shaping clinical management recommendations and evaluate the inherent risks and benefits associated with relying on phase II data for treatment decisions.
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Neoplasias , Humanos , Teorema de Bayes , Tomada de Decisão Clínica , Oncologia , Neoplasias/radioterapia , Ensaios Clínicos Controlados Aleatórios como AssuntoRESUMO
Importance: Primary end point (PEP) changes to an active clinical trial raise questions regarding trial quality and the risk of outcome reporting bias. It is unknown how the frequency and transparency of the reported changes depend on reporting method and whether the PEP changes are associated with trial positivity (ie, the trial met the prespecified statistical threshold for PEP positivity). Objectives: To assess the frequency of reported PEP changes in oncology randomized clinical trials (RCTs) and whether these changes are associated with trial positivity. Design, Setting, and Participants: This cross-sectional study used publicly available data for complete oncology phase 3 RCTs registered in ClinicalTrials.gov from inception through February 2020. Main Outcomes and Measures: The main outcome was change between the initial PEP and the final reported PEP, assessed using 3 methods: (1) history of tracked changes on ClinicalTrials.gov, (2) self-reported changes noted in the article, and (3) changes reported within the protocol, including all available protocol documents. Logistic regression analyses were performed to evaluate whether PEP changes were associated with US Food and Drug Administration approval or trial positivity. Results: Of 755 included trials, 145 (19.2%) had PEP changes found by at least 1 of the 3 detection methods. Of the 145 trials with PEP changes, 102 (70.3%) did not have PEP changes disclosed within the manuscript. There was significant variability in rates of PEP detection by each method (χ2 = 72.1; P < .001). Across all methods, PEP changes were detected at higher rates when multiple versions of the protocol (47 of 148 [31.8%]) were available compared with 1 version (22 of 134 [16.4%]) or no protocol (76 of 473 [16.1%]) (χ2 = 18.7; P < .001). Multivariable analysis demonstrated that PEP changes were associated with trial positivity (odds ratio, 1.86; 95% CI, 1.25-2.82; P = .003). Conclusions and Relevance: This cross-sectional study revealed substantial rates of PEP changes among active RCTs; PEP changes were markedly underreported in published articles and mostly occurred after reported study completion dates. Significant discrepancies in the rate of detected PEP changes call into question the role of increased protocol transparency and completeness in identifying key changes occurring in active trials.
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Oncologia , Neoplasias , Humanos , Incidência , Ensaios Clínicos Controlados Aleatórios como Assunto , Viés , Neoplasias/epidemiologiaRESUMO
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.
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Adenocarcinoma , Desnutrição , Neoplasias Pancreáticas , Humanos , Avaliação Nutricional , Estudos Prospectivos , Neoplasias Pancreáticas/terapia , Estado Nutricional , Desnutrição/diagnóstico , Desnutrição/etiologia , Desnutrição/terapia , Encaminhamento e Consulta , Neoplasias PancreáticasAssuntos
Carcinoma Hepatocelular , Neoplasias Hepáticas , Neoplasias Pulmonares , Humanos , Carcinoma Hepatocelular/tratamento farmacológico , Carcinoma Hepatocelular/patologia , Neoplasias Hepáticas/tratamento farmacológico , Neoplasias Hepáticas/patologia , Anticorpos Monoclonais Humanizados/uso terapêutico , Neoplasias Pulmonares/tratamento farmacológicoRESUMO
This cohort study assesses the relative stability of median and mean survival time estimates reported in cancer clinical trials.
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Neoplasias , Humanos , Taxa de Sobrevida , Neoplasias/tratamento farmacológico , Análise de SobrevidaAssuntos
Quimiorradioterapia , Carcinoma Nasofaríngeo , Neoplasias Nasofaríngeas , Radioterapia de Intensidade Modulada , Humanos , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Quimiorradioterapia/métodos , Intervalo Livre de Doença , Carcinoma Nasofaríngeo/tratamento farmacológico , Carcinoma Nasofaríngeo/patologia , Carcinoma Nasofaríngeo/radioterapia , Neoplasias Nasofaríngeas/tratamento farmacológico , Neoplasias Nasofaríngeas/patologia , Neoplasias Nasofaríngeas/radioterapia , Estadiamento de Neoplasias , Radioterapia de Intensidade Modulada/métodos , Estudos RetrospectivosRESUMO
Background: Amongst patients with recurrent hepatocellular carcinoma (HCC) post-liver transplantation, systemic therapy options may be limited by immunosuppression or poor performance status. Thus, we aimed to assess the impact of metastasis-directed therapy to all sites of disease (MDT-All) in HCC patients with limited disease recurrence [i.e., oligorecurrence (oligoM1)] post-transplantation and characterize pre-transplant characteristics associated with oligoM1. Methods: In this retrospective cohort study, patients at a single institution with recurrent HCC post-liver transplantation were identified. OligoM1 disease was defined as ≤3 lesions at recurrence, while polyrecurrent (polyM1) disease was defined as >3 lesions. Outcomes were compared in patients with oligoM1 disease by receipt of MDT-All. Regression analyses were used to identify predictors of polyM1 disease and characteristics associated with post-recurrence outcomes. Results: Forty-three patients with recurrent HCC post-liver transplantation from 2005-2022 were identified. Twenty-seven (63%) patients had oligoM1. Microvascular invasion was independently associated with polyM1 [odds ratio (OR): 14.64; 95% confidence interval (CI): 1.48-144.77; P=0.022]. Elevated alpha-fetoprotein (AFP) ≥400 ng/mL [hazard ratio (HR): 2.44; 95% CI: 1.08, 5.52; P=0.033] at recurrence was independently associated with inferior overall survival (OS), while oligoM1 (HR: 0.42; 95% CI: 0.21, 0.87; P=0.018) was independently associated with favorable OS. Amongst patients with oligoM1 who received MDT-All (n=15) median OS was 38.4 vs. 16.1 months for those who did not receive MDT-All (log-rank P=0.021). There was a non-significant improvement in polyprogression-free survival (polyPFS) (median 14.0 vs. 10.7 months, P=0.1) amongst oligoM1 patients who received MDT-All compared to those who did not. Conclusions: Receipt of MDT-All was associated with improved OS amongst patients with limited HCC disease recurrence following liver transplantation.
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Prior malignancy exclusion criteria (PMEC) are often utilized in cancer clinical trials; however, the incidence of PMEC and the association of PMEC with trial participant age disparities remain poorly understood. This study aimed to identify age disparities in oncologic randomized clinical trials as a result of PMEC. Using a comprehensive collection of modern phase III cancer clinical trials obtained via ClinicalTrials.gov, we assessed the incidence and covariates associated with trials excluding patients with prior cancers within 5+ years from registration (PMEC-5). Using the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) database, we further sought to determine the correlation between PMEC-5 and age disparities. PMEC-5 were used in 41% of all trials, with higher PMEC-5 utilization among industry-supported trials as well as trials evaluating a targeted therapy. Comparing trial patient median ages with population-matched median ages by disease site and time-period, we assessed the association between PMEC-5 and age disparities among trial participants. PMEC-5 were independently associated with heightened age disparities, which further worsened with longer exclusionary timeframes. Together, PMEC likely contribute to age disparities, suggesting that eligibility criteria modernization through narrower PMEC timeframes may work toward reducing such disparities in cancer clinical trial enrollment.
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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.
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Neoplasias/epidemiologia , Ensaios Clínicos como Assunto , Humanos , Estados Unidos , United States Food and Drug AdministrationRESUMO
Unpublished randomized controlled trial (RCT) frequency, correlates, and financial impact are not well understood. We sought to characterize the nonpublication of peer-reviewed manuscripts among interventional, therapeutic, multi-arm, phase 3 oncology RCTs. Trials were identified by searching ClinicalTrials.gov, while publications and abstracts were identified through PubMed and Google Scholar. Trial data were extracted from ClinicalTrials.gov and individual publications. Publication was defined as a peer-reviewed manuscript addressing the primary endpoint. Patient accrual cost was extrapolated from experimental data; investigators/sponsors were contacted to determine nonpublication reasons. Six hundred eighty-four completed RCTs met inclusion criteria, which accrued 434,610 patients from 1994 to 2015; 638 were published (93.3%) and 46 were unpublished (6.7%). Among the unpublished trials, the time difference from primary endpoint maturity to data abstraction was a median of 6 years (interquartile range, 4 to 8 years). On multiple binary logistic regression analysis, factors associated with unpublished trials included lack of cooperative group sponsorship (odds ratio, 5.91, 95% CI, 1.35 to 25.97; P=.019) and supportive care investigation (odds ratio, 2.90; 95% CI, 1.13 to 7.41; P=.027). The estimated inflation-adjusted average cost of patient accrual for all unpublished trials was $113,937,849 (range, $41,136,883 to $320,201,063). Direct contact with sponsors/investigators led to a 50.0% response rate (n=23 of 46); manuscript in preparation and/or in submission (n=10 of 23) was the most commonly cited reason for nonpublication. In conclusion, approximately 1 in 15 clinical oncology RCTs are unpublished and this has a profound impact on the research enterprise. The cooperative group infrastructure may serve as a blueprint to reduce nonpublication.