Biomarker testing and tissue journey among patients with metastatic non-small cell lung cancer receiving first-line therapy in The US Oncology Network.

OBJECTIVES: The MYLUNG (Molecularly Informed Lung Cancer Treatment in a Community Cancer Network) consortium pragmatic study assessed real-world biomarker testing rates and turnaround times within a large community-based oncology network. MATERIALS AND METHODS: This retrospective observational chart review study investigated patients with mNSCLC initiating first-line (1L) systemic therapy between 01-April-2018 and 31-March-2020. Biomarker testing rates and timing relative to 1L therapy for EGFR, ALK, ROS1, BRAF, and PD-L1 were assessed, including use of next-generation sequencing (NGS). RESULTS: Among 3474 adults: 74% had adenocarcinoma and 76% had a documented ECOG performance status of 0 or 1. Ninety percent had testing for at least one biomarker, and 46% received all 5 biomarker tests. Changes in testing rates from 2018 to 2020 were 71% to 71% for EGFR, 71% to 70% for ALK, 69% to 67% for ROS1, 51% to 59% for BRAF, 82% to 84% for PD-L1, and 42% to 49% for all 5 biomarkers. NGS testing increased from 33% to 45% (p < 0.0001). Median time from mNSCLC diagnosis to 1L therapy was 35 days. Median turnaround times from biomarker testing orders to results ranged from 10 to 15 days for the individual biomarkers and 18 days for NGS. CONCLUSION: In this real-world study, while most patients received at least one biomarker test prior to 1L, <50% received all 5 tests. NGS testing also occurred in < 50% of patients but appeared to increase over time. The next phase of MYLUNG will evaluate contemporary ordering practices and turnaround times prospectively.

Characteristics of oncology clinical trials: insights from a systematic analysis of ClinicalTrials.gov.

IMPORTANCE: Clinical trials are essential to cancer care, and data about the current state of research in oncology are needed to develop benchmarks and set the stage for improvement. OBJECTIVE: To perform a comprehensive analysis of the national oncology clinical research portfolio. DESIGN: All interventional clinical studies registered on ClinicalTrials.gov between October 2007 and September 2010 were identified using Medical Subject Heading terms and submitted conditions. They were reviewed to validate classification, subcategorized by cancer type, and stratified by design characteristics to facilitate comparison across cancer types and with other specialties. RESULTS: Of 40 970 interventional studies registered between October 2007 and September 2010, a total of 8942 (21.8%) focused on oncology. Compared with other specialties, oncology trials were more likely to be single arm (62.3% vs 23.8%; P < .001), open label (87.8% vs 47.3%; P < .001), and nonrandomized (63.9% vs 22.7%; P < .001). There was moderate but significant correlation between number of trials conducted by cancer type and associated incidence and mortality (Spearman rank correlation coefficient, 0.56 [P = .04] and 0.77 [P = .001], respectively). More than one-third of all oncology trials were conducted solely outside North America. CONCLUSIONS AND RELEVANCE: There are significant variations between clinical trials in oncology and other diseases, as well as among trials within oncology. The differences must be better understood to improve both the impact of cancer research on clinical practice and the use of constrained resources.

The importance of doing trials right while doing the right trials.

Effort is being expended in investigating efficiency measures (i.e., doing trials right) through achievement of accrual and endpoint goals for clinical trials. It is time to assess the impact of such trials on meeting the critical needs of cancer patients by establishing effectiveness measures (i.e., doing the right trials).

The prevalence and economic impact of low-enrolling clinical studies at an academic medical center.

PURPOSE: The authors assessed the prevalence and associated economic impact of low-enrolling clinical studies at a single academic medical center. METHOD: The authors examined all clinical studies receiving institutional review board (IRB) review between FY2006 and FY2009 at Oregon Health & Science University (OHSU) for recruitment performance and analyzed them by type of IRB review (full-board, exempt, expedited), funding mechanism, and academic unit. A low-enrolling study included those with zero or one participant at the time of study termination. The authors calculated the costs associated with IRB review, financial setup, contract negotiation, and department study start-up activities and the total economic impact on OHSU of low-enrolling studies for FY2009. RESULTS: A total of 837 clinical studies were terminated during the study period, 260 (31.1%) of which were low-enrolling. A greater proportion of low-enrolling studies were government funded than industry funded (P=.006). The authors found significant differences among the various academic units with respect to percentages of low-enrolling studies (from 10% to 67%). The uncompensated economic impact of low-enrolling studies was conservatively estimated to be nearly $1 million for FY2009. CONCLUSIONS: A substantial proportion of clinical studies incurred high institutional and departmental expense but resulted in little scientific benefit. Although a certain percentage of low-enrolling studies can be expected in any research organization, the overall number of such studies must be managed to reduce the aggregate costs of conducting research and to maximize research opportunities. Effective, proactive interventions are needed to address the prevalence and impact of low enrollment.

Predicting accrual achievement: monitoring accrual milestones of NCI-CTEP-sponsored clinical trials.

PURPOSE: The need to increase the number oncology clinical trials with sufficient enrollments is a well-known issue, particularly for trials targeting therapeutic applications. It is critical to identify early predictors of eventual study accrual achievement. EXPERIMENTAL DESIGN: All nonpediatric phase I, I/II, II, and III therapeutic studies supported by the National Cancer Institute Cancer Therapy Evaluation Program (NCI-CTEP) between 2000 and 2007 (n = 764) were analyzed for accrual performance. Accrual achievement is defined as those enrolling 100% or more of the stated minimum accrual goal at the time of trial closure. Two accrual milestones were analyzed per trial: time to first patient enrollment and expected time to accrual goal. Multivariate logistic regression analysis was used to calculate the OR with respect to the likelihood of clinical trial accrual achievement. RESULTS: A total of 81.5% (n = 623) of the trials did not achieve the projected accrual goals within the anticipated accruing period. Furthermore, 37.2% (n = 284) of trials failed to achieve the minimum projected accrual at study closure regardless of time the trial was open. Trials that accrue the first enrollment beyond 2 months (n = 379, 49.6%) are significantly less likely to achieve the accrual performance than those trials that enroll patients under 2 months (OR: 0.637, 95% CI: 0.464-0.875, P = 0.005). Of the studies that are open beyond the anticipated enrollment period (n = 603), those do not achieve at least 60.0% of the projected minimum accrual (n = 391, 64.8%) have a significantly less likelihood of achieving final accruals by study closure (OR: 0.190, 95% CI: 0.055-0.652, P = 0.008). CONCLUSIONS: The time to first patient enrollment and expected time to accrual goal are shown to be valid measures to evaluate the likelihood of achieving the minimum projected accrual.

Phase III clinical trial development: a process of chutes and ladders.

PURPOSE: The Institute of Medicine report on cooperative groups and the National Cancer Institute (NCI) report from the Operational Efficiency Working Group both recommend changes to the processes for opening a clinical trial. This article provides evidence for the need for such changes by completing the first comprehensive review of all the time and steps required to open a phase III oncology clinical trial and discusses the effect of time to protocol activation on subject accrual. METHODS: The Dilts and Sandler method was used at four cancer centers, two cooperative groups, and the NCI Cancer Therapy Evaluation Program. Accrual data were also collected. RESULTS: Opening a phase III cooperative group therapeutic trial requires 769 steps, 36 approvals, and a median of approximately 2.5 years from formal concept review to study opening. Time to activation at one group ranged from 435 to 1,604 days, and time to open at one cancer center ranged from 21 to 836 days. At centers, group trials are significantly more likely to have zero accruals (38.8%) than nongroup trials (20.6%; P < 0.0001). Of the closed NCI Cancer Therapy Evaluation Program-approved phase III clinical trials from 2000 to 2007, 39.1% resulted in <21 accruals. CONCLUSIONS: The length, variability, and low accrual results demonstrate the need for the NCI clinical trials system to be reengineered. Improvements will be of only limited effectiveness if done in isolation; there is a need to return to the collaborative spirit with all parties creating an efficient and effective system. Recommendations put forth by the Institute of Medicine and Operational Efficiency Working Group reports, if implemented, will aid this renewal.

A sense of urgency: Evaluating the link between clinical trial development time and the accrual performance of cancer therapy evaluation program (NCI-CTEP) sponsored studies.

PURPOSE: Postactivation barriers to oncology clinical trial accruals are well documented; however, potential barriers prior to trial opening are not. We investigate one such barrier: trial development time. EXPERIMENTAL DESIGN: National Cancer Institute Cancer Therapy Evaluation Program (CTEP)-sponsored trials for all therapeutic, nonpediatric phase I, I/II, II, and III studies activated between 2000 and 2004 were investigated for an 8-year period (n = 419). Successful trials were those achieving 100% of minimum accrual goal. Time to open a study was the calendar time from initial CTEP submission to trial activation. Multivariate logistic regression analysis was used to calculate unadjusted and adjusted odds ratios (OR), controlling for study phase and size of expected accruals. RESULTS: Among the CTEP-approved oncology trials, 37.9% (n = 221) failed to attain the minimum accrual goals, with 70.8% (n = 14) of phase III trials resulting in poor accrual. A total of 16,474 patients (42.5% of accruals) accrued to those studies were unable to achieve the projected minimum accrual goal. Trials requiring less than 12 months of development were significantly more likely to achieve accrual goals (OR, 2.15; 95% confidence interval, 1.29-3.57, P = 0.003) than trials with the median development times of 12 to 18 months. Trials requiring a development time of greater than 24 months were significantly less likely to achieve accrual goals (OR, 0.40; 95% confidence interval, 0.20-0.78; P = 0.011) than trials with the median development time. CONCLUSIONS: A large percentage of oncology clinical trials do not achieve minimum projected accruals. Trial development time appears to be one important predictor of the likelihood of successfully achieving the minimum accrual goals.

Steps and time to process clinical trials at the Cancer Therapy Evaluation Program.

PURPOSE: To examine the processes and document the calendar time required for the National Cancer Institute's Cancer Therapy Evaluation Program (CTEP) and Central Institutional Review Board (CIRB) to evaluate and approve phase III clinical trials. METHODS: Process steps were documented by (1) interviewing CTEP and CIRB staff regarding the steps required to activate a trial from initial concept submission to trial activation by a cooperative group, (2) reviewing standard operating procedures, and (3) inspecting trial records and documents for selected trials to identify any additional steps. Calendar time was collected from initial concept submission to activation using retrospective data from the CTEP Protocol and Information Office. RESULTS: At least 296 distinct processes are required for phase III trial activation: at least 239 working steps, 52 major decision points, 20 processing loops, and 11 stopping points. Of the 195 trials activated during the January 1, 2000, to December 31, 2007, study period, a sample of 167 (85.6%) was used for gathering timing data. Median calendar days from initial formal concept submission to CTEP to trial activation by a cooperative group was 602 days (interquartile range, 454 to 861 days). This time has not significantly changed over the past 8 years. There is a high variation in the time required to activate a clinical trial. CONCLUSION: Because of their complexity, the overall development time for phase III clinical trials is lengthy, process laden, and highly variable. To streamline the process, a solution must be sought that includes all parties involved in developing trials.

Processes to activate phase III clinical trials in a Cooperative Oncology Group: the Case of Cancer and Leukemia Group B.

PURPOSE: National Cancer Institute-sponsored cooperative oncology groups are major sponsors of phase III clinical trials, yet the time and steps required to design and activate such studies has not been well studied. We examine the processes and document the calendar time required to activate such studies opened by the Cancer and Leukemia Group B (CALGB). METHODS: Setup steps were documented by (1) interviewing CALGB headquarters and statistical center staff and committee chairs to discover the steps required to transit from concept development to final study activation, (2) reviewing procedure manuals, and (3) inspecting all study records, documents, and e-mails to identify any additional steps. Calendar time was collected for each major process. RESULTS: Thirteen phase III studies were activated by CALGB during the study period of May 2002 to May 2005. More than 370 distinct processes were required for study activation: 317 work steps, 42 decision points, and 29 processing loops. Sixty-three percent of the decision points were outside CALGB. The complete process map measures 243.5" x 41" in 8-point font. Median calendar days to activate a phase III study at CALGB was 580 days (range, 295 to 1,248 days) from concept approval and 784 days (range, 537 to 1,130 days) from initial conception of the study. CONCLUSION: Setup of a phase III study at a major cooperative oncology group is a complex and lengthy process, with the majority of decision points external to the cooperative group. To improve the activation process, research should to be directed toward both internal and external groups and processes.