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.     

Current issues in non-inferiority trials

Non-inferiority (NI) trials enable a direct comparison of the relative benefit-to-risk profiles of an experimental intervention and a standard-of-care regimen. When the standard has clinical efficacy of substantial magnitude that is precisely estimated ideally using data from multiple adequate and well-controlled trials, with such estimates being relevant to the setting of the NI trial, then the NI trial can provide the scientific and regulatory evidence required to reliably assess the efficacy of the new intervention. In clinical practice, considerable uncertainty remains regarding when such trials should be conducted, how they should be designed, what standards for quality of trial conduct must be achieved, and how results should be interpreted. Recent examples will be considered to provide important insights and to highlight some of the challenges that remain to be adequately addressed regarding the use of the NI approach for the evaluation of new interventions. 'Imputed placebo' and 'margin'-based approaches to NI trial design will be considered, as well as the risk of 'bio-creep' with repeated NI trials, use of NI trials when determining whether excess safety risks can be ruled out, higher standards regarding quality of study conduct required with NI trials, and the myth that NI trials always require huge sample sizes.     

Doctor-patient interaction in a randomised controlled trial of decision-support tools

In this paper, we draw on the analytic perspectives of ethnomethodology to explore doctor-patient encounters in an experimental trial of a complex intervention: an efficacy randomised controlled trial (RCT) of decision-support tools in the UK. We show how the experimental context in which these encounters take place pervades the interactions within them. We argue that two interactional orders were at work in the encounters that we observed: (i) the ceremonial order of the consultation and (ii) the assemblage of the decision-support tool trial. We demonstrate how doctors in the trial oscillate between positions as authoritative clinician and neutralistic decision-support tool-implementer, and patients move between positions as passive recipients of clinical knowledge and as active subjects required to render their experience as calculable in terms of the demands of the decision-support tools and the broader trial they are embedded in. We demonstrate how the RCT coordinates the world of the clinical environment and the world of experimental evidence.     

Qualitative differences among cancer clinical trial explanations

This paper examines how medical oncologists present to breast cancer patients the option of participating in experimental treatment trials. The investigation takes a case study approach, comparing two contrasting presentations of the clinical trial option. One presentation constructs the experimental trial as a locally organized, joint physician-patient effort to determine "best" treatments, and minimizes uncertainty by oversimplification of the randomization process; the second presentation situates the clinical trial within the larger national research effort, underscores the uncertainty created by randomization, and casts non-enrollment as a reasonable option. These observations provide initial evidence that physician presentation of the clinical trial varies substantially and provides the first detailed look at actual discourse practices used in the United States to recruit patients to experimental protocols.     

POWER OF LOGRANK TEST AND COX REGRESSION MODEL IN CLINICAL TRIALS WITH HETEROGENEOUS SAMPLES

This paper evaluates the loss of power of the simple and stratified logrank tests due to heterogeneity of patients in clinical trials and proposes a flexible and efficient method of estimating treatment effects adjusting for prognostic factors. The results of the paper are based on the analyses of survival data from a large clinical trial which includes more than 6000 cancer patients. Major findings from the simulation study on power are: (i) for a heterogeneous sample, such as advanced cancer patients, a simple logrank test can yield misleading results and should not be used; (ii) the stratified logrank test may suffer some power loss when many prognostic factors need to be considered and the number of patients within stratum is small. To address the problems due to heterogeneity, the Cox regression method with a special hazard model is recommended. We illustrate the method using data from a gastric cancer clinical trial. © 1997 by John Wiley & Sons, Ltd.     

Communicating uncertainty can lead to less decision satisfaction: a necessary cost of involving patients in shared decision making?

Background Given the large number of interventions of uncertain effectiveness, research on communicating uncertainty is needed to examine its impact on patients’ health decisions. Objective To examine physicians’ communication of uncertainty and its impact on patients’ decisions and decision satisfaction. Design, setting, and participants Participants included female patients seen in a breast health centre whose physicians were discussing a decision with them, with no clear ‘best’ choice based on outcome evidence. Main variables Decision communication was measured using the OPTION scale, a measure of the degree to which physicians involve patients in a decision‐making process. One‐to‐two weeks after the discussion, patients reported their satisfaction with the decision‐making process and their decision. Decisions were verified in medical charts with patient consent. Results Seventy‐five women agreed to participate (94% response rate). The mean translated score of the OPTION scale was 68.0 (SD 18.3), but only 33.2 (SD 19.1) for the uncertainty items. Among cancer patients, communicating uncertainty was negatively related to decision satisfaction (P < 0.002), and there was an interaction between patient involvement in decisions and communicating uncertainty in relation to patients’ decision satisfaction (P < 0.03). Discussion Communicating scientific uncertainty might lead to less decision satisfaction among women facing cancer treatment decisions; this could be a natural outcome of the decision making process. Involving patients in decisions might help them tolerate uncertainty. Conclusion Future studies should consider assessing other outcomes (e.g. knowledge, physician support) of the decision making process. There may be trade‐offs between acknowledging uncertainty and immediate decision satisfaction.     

Sense and sensitivity when correcting for observed exposures in randomized clinical trials

Standard intent-to-treat analyses of randomized clinical trials can yield biased estimates of treatment efficacy and toxicity when not all patients comply with their assigned treatment. Flexible methods have been proposed which correct for this by modelling expected contrasts between an individual's observed outcome and his/her potential outcome in the absence of exposure. Because such comparisons often require untestable assumptions, a sensitivity analysis is warranted. We show how this can be performed in a meaningful and practically useful way. Following the approach of Molenberghs, Kenward and Goetghebeur in a missing data context, we evaluate the separate contributions of structural uninformativeness and sampling variation to uncertainty about the population parameters. This leads us to consider Honestly Estimated Ignorance Regions (HEIRs) and Estimated Uncertainty RegiOns (EUROs), respectively. We use the results to estimate the causal effect of observed exposure on successful blood pressure reduction in a randomized controlled clinical trial with partial non-compliance.     

A comparison of Bayesian adaptive randomization and multi‐stage designs for multi‐arm clinical trials

When several experimental treatments are available for testing, multi‐arm trials provide gains in efficiency over separate trials. Including interim analyses allows the investigator to effectively use the data gathered during the trial. Bayesian adaptive randomization (AR) and multi‐arm multi‐stage (MAMS) designs are two distinct methods that use patient outcomes to improve the efficiency and ethics of the trial. AR allocates a greater proportion of future patients to treatments that have performed well; MAMS designs use pre‐specified stopping boundaries to determine whether experimental treatments should be dropped. There is little consensus on which method is more suitable for clinical trials, and so in this paper, we compare the two under several simulation scenarios and in the context of a real multi‐arm phase II breast cancer trial. We compare the methods in terms of their efficiency and ethical properties. We also consider the practical problem of a delay between recruitment of patients and assessment of their treatment response. Both methods are more efficient and ethical than a multi‐arm trial without interim analyses. Delay between recruitment and response assessment attenuates this efficiency gain. We also consider futility stopping rules for response adaptive trials that add efficiency when all treatments are ineffective. Our comparisons show that AR is more efficient than MAMS designs when there is an effective experimental treatment, whereas if none of the experimental treatments is effective, then MAMS designs slightly outperform AR. © 2014 The Authors Statistics in Medicine Published by John Wiley & Sons, Ltd.     

Invited commentary: Postmenopausal unopposed estrogen and breast cancer risk in the Women's Health Initiative--before and beyond

Three large clinical trials provoked major debate when hormone replacement therapy (HRT) did not reduce coronary heart disease in postmenopausal women as expected from observational epidemiologic studies. Less discussion has ensued about breast cancer or other adverse events. In this issue of the Journal, investigators from the Women's Health Initiative (WHI) compare breast cancer findings from the randomized trial of unopposed estrogen with those from the large WHI observational study. This commentary briefly summarizes historical highlights of menopausal hormone use; risk-versus-benefit evaluations; scientific, clinical, and policy influences immediately before and during the WHI trial; breast cancer incidence trends; and the post-trial response in US clinical practice. Factors complicating interpretation of the results include differences in breast cancer risk profiles between women in the trial and those in the observational study cohort as well as heterogeneity in the definitions of menopause and prior use of HRT as applied by the WHI investigators to the two populations. Because millions of women use HRT, it is important to consider how the WHI and other research investigations might contribute to reducing gaps in understanding the relation between HRT and breast cancer risk.     

Vaccine approaches to malaria control and elimination: Insights from mathematical models

A licensed malaria vaccine would provide a valuable new tool for malaria control and elimination efforts. Several candidate vaccines targeting different stages of the malaria parasite's lifecycle are currently under development, with one candidate, RTS,S/AS01 for the prevention of Plasmodium falciparum infection, having recently completed Phase III trials. Predicting the public health impact of a candidate malaria vaccine requires using clinical trial data to estimate the vaccine's efficacy profile—the initial efficacy following vaccination and the pattern of waning of efficacy over time. With an estimated vaccine efficacy profile, the effects of vaccination on malaria transmission can be simulated with the aid of mathematical models.Here, we provide an overview of methods for estimating the vaccine efficacy profiles of pre-erythrocytic vaccines and transmission-blocking vaccines from clinical trial data. In the case of RTS,S/AS01, model estimates from Phase II clinical trial data indicate a bi-phasic exponential profile of efficacy against infection, with efficacy waning rapidly in the first 6 months after vaccination followed by a slower rate of waning over the next 4 years. Transmission-blocking vaccines have yet to be tested in large-scale Phase II or Phase III clinical trials so we review ongoing work investigating how a clinical trial might be designed to ensure that vaccine efficacy can be estimated with sufficient statistical power. Finally, we demonstrate how parameters estimated from clinical trials can be used to predict the impact of vaccination campaigns on malaria using a mathematical model of malaria transmission.     

Attitudes to randomized clinical trials amongst out-patients attending a medical oncology clinic

Objective  To assess the understanding of and attitudes towards randomized clinical trials amongst patients attending oncology out-patient clinics.
Design  Cross-sectional survey.
Subjects  Patients attending medical oncology out-patient clinics at a Sydney teaching hospital.
Main outcome  Patients' willingness to participate in a randomized clinical trial.
Results  Sixty consecutive patients were surveyed. The mean age was 55.2 (SD 14) years. Eighty-eight per cent of respondents thought that patients should be asked to participate in trials testing new treatments, however, only a third would consider participating in a randomized trial themselves. If a trial was endorsed by an independent cancer information service such as the NSW Cancer Council, 72% of respondents would be more likely to participate. Knowledge about randomized trials was not high. Respondents scored a median of 3 out of 7 (interquartile range, 2–4) correct answers to a series of questions about randomized trials. Patients willing to participate in a randomized trial were more likely to perceive the doctor favourably ( P  = 0.05), less likely to perceive trials as experimental ( P  = 0.05) and less likely to perceive trials as representing an inconvenience or loss of control ( P  = 0.09).
Conclusions  Understanding amongst patients of the need for and mechanisms of randomized clinical trials is not good. This may contribute to the difficulties investigators face in seeking consent for clinical trials. Evaluation of new strategies to educate the public and patients about randomized trials is needed. Involvement of consumers in the design and conduct of clinical trials and evaluation of strategies to improve doctors' communication of clinical trial information is also required.     

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.     

The assessment of the economic return from controlled clinical trials

Clinical trials can be considered health interventions as their primary aim is to impact on the health of a population. Given that resources are scarce for both health care and health related research, trials could be designed such that they can be demonstrated to be cost-effective, i.e., the costs of conducting the trial are justified given the forecasted long-term benefits.We demonstrate how a model can be used to predict the cost-effectiveness of undertaking a clinical trial comparing alternative regimens of colorectal cancer follow-up.The model forecasts costs and survival under two scenarios,with and without conducting a clinical trial, with the outcome assessed in terms of years to payback for the clinical trial.The methodology shown can be used both to provide information on appropriate trial design and/or in prioritizing between potential trials. Douglas Coyle Clinical Epidemiology Unit, Ottawa Health Research Institute, 1053 Carling Avenue,Ottawa Hospital,Ottawa, Ontario K1Y 4E9,Canada, e-mail: dcoyle@ohri.ca     

The Comparison of Trial Data–Based and Registry Data–Based Cost-Effectiveness of Infliximab Treatment for Rheumatoid Arthritis in Sweden Using a Modeling Approach

ObjectiveTo evaluate the precision of the predictive cost-effectiveness assessment based on a phase 3 clinical trial with infliximab for the treatment of rheumatoid arthritis in Swedish clinical practice.MethodsThree patient cohorts were identified: the patients included in the infliximab trial (ATTRACT), patients initially treated with infliximab from a Swedish registry (STURE), a subset of these registry patients meeting inclusion criteria for the ATTRACT trial was the third patient cohort; two sets of assumptions in relation to the efficacy data were evaluated: “ATTRACT” (efficacy data over the duration of the trial) and “STURE” (effectiveness data over 10 years). In addition, the impact of including the placebo effect for the comparator was evaluated as a basis for the calculation of cost-effectiveness by using a modeling approach. A health economic model was utilized to estimate the cost per quality-adjusted life-year (QALY) gained.ResultsThe results for the three patient cohorts ranged from cost saving to a cost per QALY gained of €2,400 and €24,900 to €26,000 when the ATTRACT and STURE assumptions were used, respectively. Sensitivity analyses indicated that the inclusion of placebo effect had the largest effect on the results, increasing the cost per QALY gained to approximately €50,000 for all patient cohorts.ConclusionsThe treatment effect of infliximab measured in clinical trials and clinical practice results in comparable cost-effectiveness ratios, as calculated by using a modeling approach, whereas the assumptions made in relation to the effectiveness data and the chosen comparator have a large impact on the results. This reinforces the value of early modeling studies based on randomized clinical trial data, but assumptions made need to be carefully assessed.     

The impact of heterogeneity on the comparison of survival times

We consider several sources of heterogeneity in a clinical trial with patients' survival time as the main response criterion: differences in prognosis which can be attributed to a latent or ignored prognostic factor; differences in treatment efficacy in subgroups of patients, and differences in treatment combinations received by the patients. The impact of these types of heterogeneity on the treatment comparison is studied assuming a proportional hazards model. It is measured by the size and power of the logrank and proportional hazards score tests and by the bias of the estimated treatment effect. We show that heterogeneity can seriously affect the treatment comparison and has to be considered during the planning stage as well as at the analysis of a clinical trial.     

Last Resort or Roll of the Die? Exploring the Role of Metaphors in Cancer Clinical Trials Education Among Medically Underserved Populations

Improving communication about cancer clinical trials may help increase patients' understanding of medical research and their interest in participating. It is unfortunate that there is little empirical research to provide guidance on how to adapt clinical trial messages to maximize cultural sensitivity. This study examines (a) how medically underserved women conceptualize clinical trials by examining the language they use to describe them and (b) how this audience interprets metaphorical language used to explain randomization in the context of Phase III cancer clinical trials. The author conducted in-depth interviews and focus groups with 41 rural, low-income older women who either had been diagnosed with cancer or were caregivers for a person with cancer. The most commonly used lay metaphors for clinical trials had strong negative connotations and included treatment by trial and error, patients are guinea pigs, and treatment of last resort. Participants also expressed strong, unfavorable responses to conventional metaphors that equate randomization with the roll of a die or use other gambling language. Low-literacy definition approaches were unexpectedly problematic, suggesting the potential effectiveness of culturally grounded metaphors for communicating about clinical trials. Ethical implications of these findings for cancer communication are discussed.     

TUTORIAL IN BIOSTATISTICS: BAYESIAN DATA MONITORING IN CLINICAL TRIALS

Many clinical trials organizations use regular interim canalyses to monitor the accruing results in large clinical trials. In disease areas such as cancer, where survival is usually a major outcome variable, ethical considerations may lead to a stipulated requirement for data monitoring of mortality. This monitoring has frequently taken the form of limiting interim analyses to be few in number, and specifying an extreme p-value of, for example, p<0⋅001 or p<0⋅01 as grounds for early termination of the trial. Group-sequential methods are also used. However, none of these approaches formally assesses the impact that the results of a clinical trial may have upon clinical practice. Thus a trial might be terminated early because of apparent treatment benefits, but might fail to influence sceptical clinicians to modify their future treatment policy. We discuss the application of Bayesian methods, including the use of uninformative, sceptical and enthusiastic priors, and demonstrate that the necessary calculations are both straightforward to perform and easy to interpret statistically and clinically. Methods are illustrated with interim analyses of a clinical trial in oesophageal cancer. © 1997 by John Wiley & Sons, Ltd.     

The impact of health insurance mandates on drug innovation: evidence from the United States

An important health policy issue is the low rate of patient enrollment into clinical trials, which may slow down the process of clinical trials and discourage their supply, leading to delays in innovative life-saving drug treatments reaching the general population. In the US, patients’ cost of participating in a clinical trial is considered to be a major barrier to patient enrollment. In order to reduce this barrier, some states in the US have implemented policies requiring health insurers to cover routine care costs for patients enrolled in clinical trials. This paper evaluates empirically how effective these policies were in increasing the supply of clinical trials and speeding up their completion, using data on cancer clinical trials initiated in the US between 2001 and 2007. Our analysis indicates that the policies did not lead to an increased supply in the number of clinical trials conducted in mandate states compared to non-mandate states. However, we find some evidence that once clinical trials are initiated, they are more likely to finish their patient recruitment in a timely manner in mandate states than in non-mandate states. As a result, the overall length to completion was significantly shorter in mandate states than in non-mandate states for cancer clinical trials in certain phases. The findings hint at the possibility that these policies might encourage drug innovation in the long run.     

Feasibility and acceptability of a decision aid designed for people facing advanced or terminal illness: a pilot randomized trial

Background Patients nearing the end of their lives face an array of difficult decisions. Objective This study was designed to assess the feasibility and acceptability of a decision aid (DA) designed for patients facing advanced or terminal illness. Design We conducted a pilot randomized clinical trial of Health Dialog’s Looking Ahead: choices for medical care when you’re seriously ill DA (booklet and DVD) applied to patients on a hospital‐based palliative care (PC) service. Setting University of Colorado Hospital – December 2009 and May 2010. Participants All adult, English‐speaking patients or their decision makers were potentially eligible. Patients were not approached if they were in isolation, did not speak English or if any provider felt that they were not appropriate because of issues such as family conflict or actively dying. Intervention All participants received a standard PC consultation. Participants in the intervention arm also received a copy of the DA. Measurements Primary outcomes included decision conflict and knowledge. Participants in the intervention arm also completed an acceptability questionnaire and qualitative exit interviews. Results Of the 239 patients or decision makers, 51(21%) enrolled in the trial. The DA had no significant effect on decision conflict or knowledge. Exit interviews indicated it was acceptable and empowering, although they wished they had access to the DA earlier. Conclusions While the DA was acceptable, feasibility was limited by late‐life illness challenges. Future trials of this DA should be performed on patients earlier in their illness trajectory and should include additional outcome measures such as self‐efficacy and confidence.     

A semiparametric joint model for terminal trend of quality of life and survival in palliative care research

Palliative medicine is an interdisciplinary specialty focusing on improving quality of life (QOL) for patients with serious illness and their families. Palliative care programs are available or under development at over 80% of large US hospitals (300+ beds). Palliative care clinical trials present unique analytic challenges relative to evaluating the palliative care treatment efficacy which is to improve patients’ diminishing QOL as disease progresses towards end of life (EOL). A unique feature of palliative care clinical trials is that patients will experience decreasing QOL during the trial despite potentially beneficial treatment. Often longitudinal QOL and survival data are highly correlated which, in the face of censoring, makes it challenging to properly analyze and interpret terminal QOL trend. To address these issues, we propose a novel semiparametric statistical approach to jointly model the terminal trend of QOL and survival data. There are two sub‐models in our approach: a semiparametric mixed effects model for longitudinal QOL and a Cox model for survival. We use regression splines method to estimate the nonparametric curves and AIC to select knots. We assess the model performance through simulation to establish a novel modeling approach that could be used in future palliative care research trials. Application of our approach in a recently completed palliative care clinical trial is also presented.