Time and Expected Value of Sample Information Wait for No Patient

Objective:  The expected value of sample information (EVSI) from prospective trials has previously been modeled as the product of EVSI per patient, and the number of patients across the relevant time horizon less those "used up" in trials. However, this implicitly assumes the eligible patient population to which information from a trial can be applied across a time horizon are independent of time for trial accrual, follow-up and analysis.
Methods:  This article demonstrates that in calculating the EVSI of a trial, the number of patients who benefit from trial information should be reduced by those treated outside as well as within the trial over the time until trial evidence is updated, including time for accrual, follow-up and analysis.
Results:  Accounting for time is shown to reduce the eligible patient population: 1) independent of the size of trial in allowing for time of follow-up and analysis, and 2) dependent on the size of trial for time of accrual, where the patient accrual rate is less than incidence. Consequently, the EVSI and expected net gain (ENG) at any given trial size are shown to be lower when accounting for time, with lower ENG reinforced in the case of trials undertaken while delaying decisions by additional opportunity costs of time.
Conclusions:  Appropriately accounting for time reduces the EVSI of trial design and increase opportunity costs of trials undertaken with delay, leading to lower likelihood of trialing being optimal and smaller trial designs where optimal.     

Increasing Primary Care Physician Support for and Promotion of Cancer Clinical Trials

Only 2.5%–3% of adult cancer patients participate in cancer clinical trials, yet about 20% of cancer patients are medically eligible to participate. Research suggests that the primary care provider (PCP) can influence a patient''s awareness of, and potentially, his or her decision to consider a clinical trial. To address low cancer clinical trial accrual rates, ‘Imi Hale Native Hawaiian Cancer Network partnered with The Queen''s Cancer Center to provide and evaluate education on clinical trials to Hawai‘i PCPs. The educational materials were developed from a national curriculum and tailored to local audiences. Objectives of the curriculum were to educate PCPs about common myths (attitudinal barriers) around clinical trials and suggest ways that PCPs can introduce the concept of clinical trials to their patients with cancer or suspicion of cancer. The curriculum was tested on 128 PCPs in 2012. Knowledge of the PCP''s role and their willingness to mention clinical trials were measured through a post-test immediately following the presentation, which 74 (58%) PCPs completed. The post-test results suggested an increase in awareness among PCPs of their potential role in cancer clinical trial accrual, and an increase in PCP willingness to mention clinical trials to their patients with suspicion of cancer or diagnosed with cancer. Although findings suggest that this intervention is useful in increasing PCP receptivity to promoting cancer clinical trials, more research is needed to test if increased willingness results in increased accrual of cancer patients into clinical trials in Hawai‘i.     

Patient and clinician collaboration in the design of a national randomized breast cancer trial

Objective To show breast cancer patient involvement in the design of a national randomized trial of hormone replacement therapy (HRT) in symptomatic patients will increase accrual. Setting and participants Three stakeholder groups [(1) researchers from the Lynda Jackson Macmillan Centre, (2) the Consumers’ Advisory Group for Clinical Trials (CAG‐CT), (3) clinicians responsible for a pilot randomized HRT study in breast cancer patients] developed this collaborative study. Methods (1) Nine focus group discussions were conducted to identify issues relevant to breast cancer patients about HRT and a national trial: six involved women from breast cancer support groups nationwide and three patients who had previously participated in the pilot randomized HRT study. (2) Recommendations from the focus groups (analysed by Grounded Theory) were debated by the research stakeholders and focus group representatives at a 1‐day meeting and consensus reached (using a voting system) on mutual priorities for incorporation into the design of a national HRT trial. (3) Representatives from the CAG‐CT and focus groups participated in subsequent national HRT steering committee meetings to ensure that these priorities were accounted for and the resulting trial design summary was circulated to the CAG‐CT and all focus group representatives for comment. Results Focus groups demonstrated that the complexity of factors relating to trial participation was not just restricted to the research topic in question. Patient–clinician interaction provided a platform for negotiating potential conflicts over trial design and outcomes. Patient feedback suggested that mutually agreed priorities were accounted for in the trial design. Interpretation Clinical research planning should involve all research stakeholders at the outset. Quantifying the impact of patient involvement in terms of trial accrual may be too simple given the complexity of their motivations for participating in trials.     

Practical modifications to the time-to-event continual reassessment method for phase I cancer trials with fast patient accrual and late-onset toxicities

The goal of phase I cancer trials is to determine the highest dose of a treatment regimen with an acceptable toxicity rate. Traditional designs for phase I trials, such as the Continual Reassessment Method (CRM) and the 3 + 3 design, require each patient or a cohort of patients to be fully evaluated for the dose-limiting toxicity (DLT) before new patients can be enrolled. As such, the trial duration may be prohibitively long. The Time-to-Event Continual Reassessment Method (TITE-CRM, Cheung and Chappell, 2000) circumvents this limitation by allowing staggered patient accrual without the need for complete DLT follow-up of previously treated patients. However, in the setting of fast patient accrual and late-onset toxicities, the TITE-CRM results in overly aggressive dose escalation and exposes a considerable number of patients to toxic doses. We examine a modification to the TITE-CRM proposed by the original TITE-CRM creator and propose an alternative approach useful in this setting by incorporating an accrual suspension rule. A simulation study designed based on a neuro-oncology trial indicates that the modified methods provide a much improved degree of safety than the TITE-CRM while maintaining desirable design accuracy. The practical aspects of the proposed designs are discussed. The modifications presented are useful when planning phase I trials involving chemoradiation therapy.     

A strategic view of randomized trial design in low-incidence paediatric cancer.

We use a statistical model to examine the relationship between alpha level, sample size, trial duration, patient accrual rate and therapeutic innovation rate on the increase in treatment efficacy achieved after a series of two-treatment randomized phase III trials. In a setting where the trials include most of the patients in the target population for inference, as in some paediatric cancers, we show that the traditional criteria by which one determines trial size are difficult to justify and apply. In particular, using as a measure of evidence type I error levels larger than the typical 5 per cent for judging treatment differences, and performing smaller trials than one would usually consider feasible, yields on average, over a 25-year research course, larger gains in cure rate. Judicious choice of type I error rate and trial size keeps the chance of worsening treatment efficacy at a low level, even while increasing the chance of making large improvements in cure rate. We propose that a more appropriate view of trial design in low-incidence cancer settings is in the overall context of the research setting and long-term goals rather than in the narrow context of the current single trial. From this viewpoint, insistence on large trials and stringent evidence for accepting new treatments can be counter-productive, in that likely gains in efficacy of treatment will be smaller over the long term.     

Modeling and validating Bayesian accrual models on clinical data and simulations using adaptive priors

Slow recruitment in clinical trials leads to increased costs and resource utilization, which includes both the clinic staff and patient volunteers. Careful planning and monitoring of the accrual process can prevent the unnecessary loss of these resources. We propose two hierarchical extensions to the existing Bayesian constant accrual model: the accelerated prior and the hedging prior. The new proposed priors are able to adaptively utilize the researcher's previous experience and current accrual data to produce the estimation of trial completion time. The performance of these models, including prediction precision, coverage probability, and correct decision‐making ability, is evaluated using actual studies from our cancer center and simulation. The results showed that a constant accrual model with strongly informative priors is very accurate when accrual is on target or slightly off, producing smaller mean squared error, high percentage of coverage, and a high number of correct decisions as to whether or not continue the trial, but it is strongly biased when off target. Flat or weakly informative priors provide protection against an off target prior but are less efficient when the accrual is on target. The accelerated prior performs similar to a strong prior. The hedging prior performs much like the weak priors when the accrual is extremely off target but closer to the strong priors when the accrual is on target or only slightly off target. We suggest improvements in these models and propose new models for future research. Copyright © 2014 John Wiley & Sons, Ltd.     

Late-starter sites in randomized controlled trials

In a cohort of 14 randomized controlled trials conducted by the Adult AIDS Clinical Trials Group between 1986 and 1999 with a target sample size of >400 (total enrollment 15,531 patients), we evaluated whether "late-starter" sites can make a meaningful contribution to eventual trial accrual. The sites that started recruiting within 5 months from the time the first patient entered the trial were eventually responsible for over 90% of the total enrollment in 11 of the 14 trials. Across the 14 trials, some sites were consistently among the first to start enrollment, whereas others were routinely among the last. The late-starter sites are unlikely to make important contributions to eventual trial enrollment in large clinical trials conducted by groups with a fixed number of sites. Protracting administrative efforts to add more sites many months after a multicenter trial has started may not be useful to trial accrual.     

Predicting the performance of a strategic alliance: an analysis of the Community Clinical Oncology Program.

OBJECTIVE. This study is designed to examine the effects of environment and structure of the Community Clinical Oncology Program (CCOP) on performance as measured by patient accrual to National Cancer Institute (NCI)-approved treatment protocols. DATA SOURCES/STUDY SETTING. Data and analysis are part of a larger evaluation of the NCI Community Clinical Oncology Program during its second funding cycle, June 1987-May 1990. Data, taken from primary and secondary sources, included a survey of selected informants in CCOPs and research bases, CCOP grant applications, CCOP annual progress reports, and site visits to a subsample of CCOPs (N = 20) and research bases (N = 5). Accrual data were obtained from NCI records. STUDY DESIGN. Analysis involved three complementary sets of factors: the local health care resources environment available to the CCOP, the larger policy environment as reflected by the relationship of the CCOP to selected research bases and the NCI, and the operational structure of the CCOP itself. A hierarchical model examined the separate and cumulative effects of local and policy environment and structure on performance. PRINCIPAL FINDINGS. Other things equal, the primary predictors of treatment accrual were: (1) the larger policy environment, as measured by the attendance of nurses at research base meetings; and (2) operational structure, as measured by the number and character of components within participating CCOPs and the number of hours per week worked by data managers. These factors explained 73 percent of the total variance in accrual performance. CONCLUSIONS. Findings suggest criteria for selecting the types of organizations to participate in the alliance, as well as for establishing guidelines for managing such alliances. A future challenge is to determine the extent to which factors predicting accrual to cancer treatment clinical trials are equally important as predictors of accrual to cancer prevention and control trials.     

Predicting accrual in clinical trials with Bayesian posterior predictive distributions

Investigators need good statistical tools for the initial planning and for the ongoing monitoring of clinical trials. In particular, they need to carefully consider the accrual rate-how rapidly patients are being recruited into the clinical trial. A slow accrual decreases the likelihood that the research will provide results at the end of the trial with sufficient precision (or power) to make meaningful scientific inferences. In this paper, we present a method for predicting accrual. Using a Bayesian framework we combine prior information with the information known up to a monitoring point to obtain a prediction. We provide posterior predictive distributions of the accrual. The approach is attractive since it accounts for both parameter and sampling distribution uncertainties. We illustrate the approach using actual accrual data and discuss practical points surrounding the accrual problem.     

Accrual strategies for phase I trials with delayed patient outcome.

Phase I dose-finding trials typically are conducted using adaptive rules that select dose levels for successive patient cohorts based on the outcomes of patients treated previously in the trial. When patient outcome cannot be observed immediately after treatment, the problem arises of how to deal with new patients while waiting to observe the current patient cohort's outcomes. We consider two alternative approaches to this problem in the context of a phase I trial conducted using the continual reassessment method. With the first approach, a patient requiring treatment before the next cohort opens is treated off protocol with standard therapy, and otherwise waits until the next cohort opens. The second approach treats each patient immediately upon arrival at the dose recommended based on currently available data. We compare these two approaches by simulation under varying dose--toxicity curves, accrual rates, cohort sizes and early stopping rules. We evaluate patient waiting time, trial duration, number of patients treated off protocol and the probabilities of toxicity and of selecting the correct dose. We also study three strategies for assigning patients to trials when two or more phase I trials may be ongoing simultaneously. Based on our results, we provide practical guidelines for deciding among these approaches and strategies in a given clinical setting.     

A two-stage Bayesian design for co-development of new drugs and companion diagnostics

Most new drug development in oncology is based on targeting specific molecules. Genomic profiles and deregulated drug targets vary from patient to patient making new treatments likely to benefit only a subset of patients traditionally grouped in the same clinical trials. Predictive biomarkers are being developed to identify patients who are most likely to benefit from a particular treatment; however, their biological basis is not always conclusive. The inclusion of marker-negative patients in a trial is therefore sometimes necessary for a more informative evaluation of the therapy. In this paper, we present a two-stage Bayesian design that includes both marker-positive and marker-negative patients in a clinical trial. We formulate a family of prior distributions that represent the degree of a priori confidence in the predictive biomarker. To avoid exposing patients to a treatment to which they may not be expected to benefit, we perform an interim analysis that may stop accrual of marker-negative patients or accrual of all patients. We demonstrate with simulations that the design and priors used control type I errors, give adequate power, and enable the early futility analysis of test-negative patients to be based on prior specification on the strength of evidence in the biomarker.     

Training Community Health Workers About Cancer Clinical Trials

Innovative projects to reduce disparities in cancer treatment and research include partnerships between academic and community cancer centers, patient navigation programs and strategies to promote community awareness, education and engagement. A 4 h training program about cancer clinical trials was developed through a needs assessment and in collaboration with community health workers who served as consultants and a larger advisory board comprised of community health workers, educators and clinical trialists. This program was delivered first as a collaboration between a phsycian who is experienced in the conduct of clinical research and two community health workers, and subsequently by the community health workers alone. We report on four workshops attended by a total of 61 community health workers recruited from Boston-area hospitals, community health centers and outreach programs. Support for and knowledge of clinical trials was measured in a pretest and post-test, which also included a satisfaction rating. Participants had a range of prior experience with clinical trials in the context of their personal and professional experience. Mean accuracy of knowledge about clinical trials increased from 72 to 84%, support for clinical trials improved considerably, and satisfaction with the training experience was high. Knowledge gaps and low levels of support for cancer clinical trials among community health workers can be improved with a short training program delivered by other community health workers. Further research is needed to identify the impact of this training on accrual to cancer clinical trials.     

Monitoring distributional assumptions and early stopping for a prospective clinical trial using Monte Carlo simulation

We have applied the technique of Monte Carlo simulation to the determination of sample size for a partially completed clinical trial of chemotherapy for breast cancer. Simulations based on results observed after the entry of 243 patients in 2 years indicated a power greater than that predicted by the calculations made before the protocol was activated, and allowed a recommendation for an eventual trial closure earlier than would have been permitted by traditional methods. Both estimative and predictive approaches to the simulation of expected survival times for censored patients are presented. The use of simulation is recommended as an aid in reassessing the exact nature of the underlying survival distributions (as these affect the sample size calculations) and in optimizing stopping rules relating to patient accrual to a clinical trial in progress.     

Clinical Trial and Research Study Recruiters’ Verbal Communication Behaviors

The lack of accrual to research studies and clinical trials is a persistent problem with serious consequences: Advances in medical science depend on the participation of large numbers of people, including members of minority and underserved populations. The current study examines a critical determinant of accrual: the approach of patients by professional recruiters who request participation in research studies and clinical trials. Findings indicate that recruiters use a number of verbal strategies in the communication process, including translating study information (such as simplifying, using examples, and substituting specific difficult or problematic words), using linguistic reframing or metaphors, balancing discussions of research participation risks with benefits, and encouraging potential participants to ask questions. The identification of these verbal strategies can form the basis of new communication protocols that will help medical and nonmedical professionals communicate more clearly and effectively with patients and other potential participants about research studies and clinical trials, which should lead to increased accrual in the future.     

Novel designs for multi-arm clinical trials with survival outcomes with an application in ovarian cancer

With the increasing pace of drug development, it is not unusual for several promising treatment regimens to be ready simultaneously for testing in a randomized phase III setting. Various limiting factors, including the time needed to transfer research results to clinical practice and a narrow 'window of opportunity', may make it unfeasible to perform trials to test such regimens sequentially against a control treatment in a traditional two-arm parallel group design. We present an approach to trial design based on eliminating inferior contenders at an early stage, allowing through to a second stage only treatments that show a predefined degree of advantage against a control treatment. The first stage of testing utilizes a marker known to be a valid intermediate outcome measure or surrogate for the definitive outcome. The experimental arms are compared pairwise with control according to this intermediate outcome measure. Arms that survive the comparison enter a second stage of patient accrual culminating in comparisons against control on the outcome measure of primary interest. We show how the design may be realized in practice by considering hypothetically distinct trials at stages 1 and 2, each with their own operating characteristics. The overall operating characteristics are computed from the stage 1 and 2 size and power and the correlation between the treatment effects on the intermediate and primary outcome measures according to a bivariate Normal approximation. The correlation is estimated by bootstrapping individual patient data from previous trials. We illustrate the general approach in a design of a real trial of four new chemotherapy regimens for advanced ovarian cancer. The intermediate outcome measure is progression-free survival. An international randomized controlled trial using the new design is already under way.     

Advocacy for clinical trials: do the Royal Colleges and State cancer councils play an appropriate role?

BACKGROUND: Endorsement of clinical trials by prominent local or national organisations may help to promote public awareness of and enhance patient and doctor participation in randomised trials. METHOD: A survey was undertaken of the specialist medical colleges of Australia, State and Territory cancer councils and national cancer organisations, inquiring about their formal position on patient participation in randomised clinical trials and any activities they undertake to promote clinical trial participation. RESULTS: Responses were received from 18 of 20 organisations surveyed. The majority (13/18) support the idea that patients should be invited to participate in well-designed clinical trials. Only 9/18 organisations have any formal policy encouraging clinical trial participation and only five undertake any activity to promote clinical trials. These activities relate more to facilitating clinician participation through affiliation with cooperative oncology groups/clinical trial organisations and provision of funds for data management. Only two organisations are proactive in promoting trials to clinicians and patients. CONCLUSION: Promoting/endorsing clinical trial participation is a priority area identified in the national cancer control plan and implementation strategy. Prominent organisations such as specialist medical colleges and State cancer councils should explore ways in which they can act as advocates to promote clinical trial participation.     

Patterns of patient enrollment in randomized controlled trials

We aimed to describe enrollment patterns in a large cohort of randomized controlled trials (RCTs) and evaluate whether early recruitment predicts the ability of RCTs to reach their target enrollment. We considered all 77 efficacy RCTs initiated by the AIDS Clinical Trials Group between 1986 and 1996 (28,992 patients enrolled until November 1999). Thirteen RCTs (17%) failed to reach half their target recruitment. Enrollment trajectories showed that the initial rate of accrual determined the subsequent rates of enrollment. The target sample size was attained by 7/8, 11/14, 15/35 and 4/20 of trials with very rapid, rapid, moderate and slow enrollment during the first 3 months, respectively (P < 0.001). Enrollment during the first month or two strongly correlated with subsequent accrual (P < 0.001). The patient pool, the eligibility criteria, the attractiveness of a trial and adequacy of the network of clinical sites may influence RCT enrollment. Early enrollment offers strong evidence on the feasibility of a trial and is indicative of its future pace of recruitment.     

Building efficient comparative effectiveness trials through adaptive designs,utility functions,and accrual rate optimization: finding the sweet spot

The time is right for the use of Bayesian Adaptive Designs (BAD) in comparative effectiveness trials. For example, Patient Centered Outcomes Research Institute has joined the Food and Drug Administration and National Intitutes of Health in adopting policies/guidelines encouraging their use. There are multiple aspects to BAD that need to be considered when designing a comparative effectiveness design. First, the adaptation rules can determine the expected size of the trial. Second, a utility function can be used to combine extremely important co‐endpoints (e.g., efficacy and tolerability) and is a valuable tool for incorporating clinical expertise and potentially patient preference. Third, accrual rate is also very, very important. Specifically, there is a juxtaposition related to accrual and BAD. If accrual rate is too fast we never gain efficient information for adapting. If accrual rate is too slow we never finish the clinical trial. We propose methodology for finding the ‘sweet spot’ for BAD that addresses these as design parameters. We demonstrate the methodology on a comparative effectiveness BAD of pharmaceutical agents in cryptogenic sensory polyneuropathy. The study has five arms with two endpoints that are combined with a utility function. The accrual rate is assumed to stem from multiple sites. We perform simulations from which the composite accrual rates across sites result in various piecewise Poisson distributions as parameter inputs. We balance both average number of patients needed and average length of time to finish the study. Copyright © 2015 John Wiley & Sons, Ltd.     

Conducting clinical trials in a constantly changing health care environment

Continuous change and cost containment characterize the current health care system, making conduct of clinical trials and other clinical research difficult. Identification, accrual, and follow-up of patients who move between health care environments such as hospitals, nursing homes, schools and the home is particularly challenging. This article describes a circuit rider approach to patient identification and follow-up that was established by the Communication Sciences and Disorders Clinical Trials Research Group. It also gives suggestions for design of clinical trials in a constantly changing environment.     

Statistical modeling and prediction of clinical trial recruitment

Real-time prediction of clinical trial accrual can support logistical planning, ensuring that studies meet but do not exceed sample size targets. We describe a novel, simulation-based prediction method that is founded on a realistic model for the underlying processes of recruitment. The model reflects key features of enrollment such as the staggered initiation of new centers, heterogeneity in enrollment capacity, and declining accrual within centers. The model's first stage assumes that centers join the trial (ie, initiate accrual) according to an inhomogeneous Poisson process in discrete time. The second part assumes that each center's enrollment pattern reflects an early plateau followed by a slow decline, with a burst at the end of the trial following the announcement of an imminent closing date. By summing up achieved and projected enrollment, one can predict accrual as a function of time and, thereby, the time when the trial will achieve a planned enrollment target. We applied our method retrospectively to two real-world trials: NSABP B-38 and REMATCH (Randomized Evaluation of Mechanical Assistance for the Treatment of Congestive Heart Failure). In both studies, the proposed method produced prediction intervals for time to completion that were more accurate than those from conventional predictions that assume a constant rate of enrollment, estimated either from the entire trial to date or over a recent time window. The advantage is substantial in the early stages of NSABP B-38. We conclude that a method based on a realistic accrual model offers improved accuracy in the prediction of enrollment landmarks, especially at the early stages of large trials that involve many centers.