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Identification of Cancer Care and Protocol Characteristics Associated With Recruitment in Breast Cancer Clinical Trials

Julie Lemieux, Pamela J. Goodwin, Kathleen I. Pritchard, Karen A. Gelmon, Louise J. Bordeleau, Thierry Duchesne, Stéphanie Camden, Caroline H. Speers

From the Unité de Recherche en Santé des Populations, Centre des Maladies du Sein Deschênes-Fabia, Hôpital St-Sacrement, and Centre d’Hématologie, Centre Hospitalier Affilié Universitaire de Québec; Département de Médecine and Mathématiques et de Statistique, Université Laval, Québec, Québec; Samuel Lunenfeld Research Institute of the Mount Sinai Hospital; Department of Medicine, University of Toronto; Sunnybrook Health Sciences Centre, Toronto, Ontario; British Columbia Cancer Agency; and Breast Cancer Outcomes Unit, Vancouver, British Columbia, Canada

Corresponding author: Julie Lemieux, MD, MSc, FRCPC, Unité de Recherché en Santé des Populations, Hôpital St-Sacrement du Centre Hospitalier Affilié Universitaire de Québec, 1050 Chemin Sainte-Foy, Québec, QC, Canada G1S 4L8; e-mail: julie.lemieux{at}uresp.ulaval.ca

	ABSTRACT

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Purpose It is estimated that only 5% of patients with cancer participate in a clinical trial. Barriers to participation may relate to available protocols, physicians, and patients, but few data exist on barriers related to cancer care environments and protocol characteristics.

Methods The primary objective was to identify characteristics of cancer care environments and clinical trial protocols associated with a low recruitment into breast cancer clinical trials. Secondary objectives were to determine yearly recruitment fraction onto clinical trials from 1997 to 2002 in Ontario, Canada, and to compare recruitment fraction among years. Questionnaires were sent to hospitals requesting characteristics of cancer care environments and to cooperative groups/pharmaceutical companies for information on protocols and the number of patients recruited per hospital/year. Poisson regression was used to estimate the recruitment fraction.

Results Questionnaire completion rate varied between 69% and 100%. Recruitment fraction varied between 5.4% and 8.5% according to year. More than 30% of patients were diagnosed in hospitals with no available trials. In multivariate analysis, the following characteristics were associated with recruitment: use of placebo versus not (relative risk [RR] = 0.80; P = .05), nonmetastatic versus metastatic trial (RR = 2.80; P < .01), and for nonmetastatic trials, protocol allowing an interval of 12 weeks or longer versus less than 12 weeks (from diagnosis, surgery, or end of therapy) before enrollment (RR = 1.36; P < .01).

Conclusion Allowable interval of 12 weeks or longer to randomly assign patients in clinical trials could help recruitment. In our study, absence of an available clinical trial represented the largest barrier to recruitment.

	INTRODUCTION

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It has been estimated that fewer than 3% to 5% of patients with cancer participate in a clinical trial.¹ Low recruitment may lead to several adverse consequences. First, trials may close prematurely because of poor enrollment, with consequent smaller sample size and decrease in study power. Second, the time period required to enroll the target sample size may be longer, leading to increased costs and delay in obtaining results. Third, generalizability may be poor if a particular subgroup of patients was not enrolled with the same frequency as other subgroups. Finally, from an ethical point of view, the contribution of patients who enroll in a study that closes prematurely because of poor accrual is devalued because no answer to the research question is obtained.

Barriers to recruitment have been reviewed^2-4 and belong to three main categories: administrative/protocol, physicians, and patients. Regarding administrative/protocol barriers, the most obvious one is the absence of a protocol open for a patient's type and stage of cancer.⁴ For example, in a center where physicians were surveyed about enrollment in clinical trials of their patients with breast cancer, 27% did not have a trial available for a given cancer stage.⁵ Another study reported that 59.2% of patients with cancer did not enroll in clinical trials because there were none available, although this number was less than 50% for patients with breast cancer.⁶ In the same study, ineligibility accounted for 8.5% of reasons of nonparticipation in a trial.⁶ In the United States, the majority of patients with cancer are treated in private practice, where clinical trials are less frequently available.⁷ Increase in administrative requirements and more stringent legislation can also impact on protocol availability.^1,8-10 Concerning physician-related barriers, the main factors cited by physicians relate to: time constraints, impact on physician-patient relationship, recognition, staff support, and consent procedure.² Lastly, Mills et al³ conducted a systematic review to assess barriers at the patient level. The three most common reasons found were "quality of life might be reduced," "dislike possibility of placebo," and "potential side effects."

Previous studies have some limitations. First, they have rarely used data from all types of clinical trials (cooperative groups and pharmaceutical industry) at a population-based level, leading to uncertainty about the true recruitment rate. In fact, the most comprehensive data regarding recruitment come from cooperative groups or National Cancer Institute–sponsored trials.^1,11 Pharmaceutical industry trials are often conducted in parallel with cooperative groups; according to the National Institutes of Health clinical trials registry, 41% of breast cancer clinical trials in 2008 were sponsored by the industry.¹² Second, the availability and characteristics of trials in centers have not often been the focus of previous research. Third, studies looking at enrollment rates in multiple hospitals have not analyzed their data by hospital. This is important because cancer care setting characteristics such as number of research nurses and work load could potentially be associated with recruitment rate. Here we present the results of a study addressing barriers to clinical trials enrollment that relate to cancer care environments and to characteristics of clinical trial protocols.

	METHODS

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The primary objective was to identify characteristics of cancer care settings and clinical trial protocols associated with a low recruitment fraction in breast cancer clinical trials. Secondary objectives were to determine the yearly recruitment fraction of patients with breast cancer onto clinical trials from 1997 to 2002 in Ontario, Canada, and to compare the recruitment fraction across years.

The selected population was the province of Ontario (12 million inhabitants). Ontario has a public health care system. Cancer care is delivered through cancer centers, although other academic or community hospitals can provide cancer care. At the time of our study, there were 11 cancer centers and 68 hospitals with 10 or more cases of breast cancer diagnosed yearly according to the Ontario Cancer Registry (OCR). Small community hospitals with fewer than 10 new cases of breast cancer per year (approximately 19 hospitals) were not used (< 5% of women were diagnosed in these hospitals).

Questionnaire Sent to Hospitals and Cancer Centers
The first questionnaire was designed to reflect characteristics found in the literature that could possibly represent a barrier or were thought to be a potential barrier based on the experience of the investigators. The first questionnaire was designed to capture cancer care characteristics and was sent to hospitals and cancer centers. Questions were asked about the numbers of medical oncologists, medical oncologists treating breast cancer, surgeons, investigators, clinical research staff, and breast cancer trials opened.

Questionnaire Sent to Cooperative Group/Pharmaceutical Industry and Cancer Centers for In-House Trials
The second questionnaire was developed to capture information on protocol characteristics and to obtain the number of patients entered onto each trial. Cooperative groups and pharmaceutical companies were identified by experts in the breast cancer field. For intergroup trials, we asked that the coordinating group complete the questionnaire. For confidentiality reasons, we did not ask for specific trials but we asked for information for all clinical trials that were opened at any time between 1997 and 2002 in Ontario. Items asked are found in Table 1. Organizations were asked to provide the opening and closing date of the protocol in each hospital and the number of patients enrolled per year.

Denominators were adjusted for the number of days a protocol was open.

Nonmetastatic Population
Incident numbers of patients with invasive breast cancer were obtained from the OCR, using the ninth edition of the International Classification of Diseases, code 174. For cancer centers only, the OCR also provided the number of cases of breast cancer per year of diagnosis who visited a cancer center (patients could be diagnosed in other hospitals but referred to the cancer center for treatment). Among these patients, 62.7% received systemic treatment. Thus, because most trials in our study were for systemic treatment, we multiplied the number of cases in each cancer center by 62.7% to obtain the number of incident cancers per year for each cancer center. This method could slightly overestimate the recruitment fraction for nonmetastatic trials in cancer centers (eg, radiation trials); sensitivity analyses were conducted without this adjustment (Table 2).

Proportion of Patients Potentially Eligible for Each Protocol
From these nonmetastatic and metastatic populations, we derived the numbers of patients who would have met the main eligibility criteria for each protocol. Criteria used were: staging, hormone receptor status, HER2 status, age (if appropriate), and previous treatment (eg, anthracycline exposure), if available. Because staging information was not available centrally in Ontario, we used data obtained from the BC BCOU. Her2 status was not available for that time period in the BC BCOU; therefore, an estimate of 20% of patients positive for HER2 was used.^14,15 The BC BCOU provided the annual proportion of their cases meeting the main eligibility criteria (for nonmetastatic and metastatic protocols), which was then applied to our population in Ontario.

Statistical Analysis
Descriptive statistics were generated for each cancer care setting and for specific characteristics. Univariate and stepwise multivariate analyses of characteristics associated with recruitment fraction were performed using Poisson regression (the log of the denominator used as the offset). A P value of .05 or less was considered significant. No adjustment was done for multiple comparisons.

For missing data on cancer care setting characteristics, missing data in the questionnaires, and missing questionnaires (Table 3), we used the College of Physicians and Surgeons of Ontario and the Ontario Institute of Cancer Research Network Web sites. For each cooperative group and pharmaceutical company that did not participate, we verified on ClinicalTrials.gov or their Web site whether trials could have been included in our study. When possible, publications arising from these trials were used to find centers that participated in the study and to enter protocol characteristics from available publications. The median recruitment fraction was imputed for missing data for these studies.

Ethics
The project received approval from the research ethics board of the coordinating hospital (Mount Sinai Hospital) and from the Ontario Cancer research ethics board. This project was funded by the Canadian Breast Cancer Foundation–Ontario Chapter. Financial compensation was provided to participants/organizations for the time taken to complete the questionnaire(s).

	RESULTS

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Questionnaire Completion Rates
The participation rate is presented in Table 3. Response rates varied between 69.2% and 100%.

Availability of a Clinical Trial
To assess the completeness of trials from which we obtained information, we asked hospitals to provide the number of breast cancer clinical trials that were ongoing in their hospital during the period of interest. In parallel, from data obtained from cooperative groups and pharmaceutical companies, we calculated the number of trials in each hospital in each year. Table 4 presents the median difference between the number obtained from hospitals and the number calculated from the latter sources. This difference is small, and the median varies between 0 and +2. For the raw number of trials reported by hospitals, there were two outliers that reported up to 52 trials open in a single year. We think this was unlikely and may have been due to inclusion of clinical trials from other tumor sites or of clinical trials that were closed to enrollment but were still observing patients.

Hospital and Cancer Care Characteristics
None of the cancer care setting characteristics was significantly associated with recruitment fraction in univariate analysis. Among protocol characteristics, the following were associated with a higher recruitment fraction: population (nonmetastatic, 7.9%; metastatic, 4.2%; both, 14.8%; P < .01), number of eligibility criteria ( 21, 5.9% v > 21, 9.3%; P < .01), and the presence of a maximal age limit (yes, 9.2% v no, 6.9%; P = .05). Univariate sensitivity analyses imputing missing data and using different combinations of denominators did not have a substantial impact on these results (Table 5).

In multivariate analysis (Table 6), we found that trials involving a placebo were less likely to recruit than trials in which no placebo was used (relative risk [RR] = 0.80; P = .05). Nonmetastatic trials were more likely to recruit than metastatic trials (RR = 2.80; P < .01). Nonmetastatic trials that allowed an interval of 12 weeks or longer between diagnosis/surgery/end of therapy and enrollment were more likely to recruit than those that allowed a shorter interval (RR = 1.36; P < .01). Multivariate analyses were repeated using the same variables found in the original model (Table 6) with missing data imputed and different denominators (Table 2). All variables remained significant except for the use of placebo in the model NM² + M² (P = .09) and with imputed data (P = .22) and the interval for models NM³ + M¹ (P = .23), NM³ + M² (P = .23), and imputed data (P = .09).

	DISCUSSION

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Other factors probably explain the observed differences in recruitment fraction. The following hypotheses might explain the differences. First, even though the number of physicians and clinical research associates did not impact recruitment fraction, the quality of approach may vary between centers and within a hospital in ways that may not be easily captured. Albrecht et al²¹ showed that communication skills may impact on the likelihood of a patient deciding to enroll onto a clinical trial. Second, patient populations between hospitals may differ in their education level, English fluency, and attitudes toward participation in research. Finally, mechanisms to identify patients potentially eligible for a trial may vary; for example, are all new patients presented systematically at tumor board or flagged by a study nurse for potential study participation?

Metastatic clinical trials seem to be a challenge in terms of recruitment. Patients in the metastatic setting may be sicker and more likely to be ineligible or patients may be less likely to accept a trial once they have metastatic disease.

One factor that has a large impact on recruitment is whether a trial is available or not. In our study, approximately 66% of women diagnosed with breast cancer were in a hospital with at least one clinical trial open in the nonmetastatic setting. It is likely that a proportion of them did not have a trial for their specific stage of disease. Addressing administrative barriers could increase the availability of trials by shortening the time for activation of trials. Dilts and Sandler²² showed that approximately 50% of steps to activate a trial are non–value added. Also, registries of clinical trials, which are emerging, could help patients and doctors find active clinical trials for a specific disease.

Our study has limitations. First, our denominators were estimated from stage distribution in the BC BCOU, and we assumed that this would be similar across hospitals and provinces. However, it is possible that some stages (eg, locally advanced breast cancer) could have been preferentially referred to larger hospitals. Second, we did not have the information on whether women diagnosed in one hospital were treated in that or another hospital. For large cities with many centers providing cancer care, our estimate for the denominator may have been incorrect. Third, it is possible that we did not capture every clinical trial open during that time period. We identified seven trials conducted between 1997 and 2002 for which we did not receive information. Additional trials could have been missed if a trial closed prematurely or if data have not been published. However, there was no major change in our conclusions when we imputed for missing data. Fourth, our findings may not apply to private health care systems where insurance may not cover costs associated with participation in clinical trials, and this may limit patient enrollment.^1,9 Finally, it is possible that the sample size and variability may have been too small to detect clinically significant differences.

The strengths of our study were that it is population-based and participation was high. Previous research has examined barriers related to poor accrual onto clinical trials. This research has shown that barriers to enrollment are multifactorial. Previous intervention studies aimed at improving the knowledge and attitude of the patient toward clinical trials, the readability of informed consent, and the communication of the information to the patient by physicians have not shown these interventions to result in an increase in enrollment rates.^23-28 Given the multiplicity of barriers and the relatively small contribution of each of them, it is likely that an intervention targeting multiple barriers from protocol development to informed consent is more likely to provide benefit than an intervention targeting only one aspect of the trial enrollment process.

In summary, our study confirmed that recruitment fraction of patients with breast cancer onto clinical trials remains low, at between 5% and 10% of potentially eligible patients. More than 30% of patients are treated in hospitals where there is no clinical trial, and expansion of clinical trials into these centers would likely increase the enrollment fraction. Apart from this, we have not been able to identify a unique strong modifiable factor associated with poor enrollment, and further studies on factors affecting patient recruitment need to be conducted. Extending the maximum interval between diagnosis/surgery/end of therapy and randomization to recruit patients into clinical trials could help recruitment without affecting the outcome of patients. Barriers to recruitment are multiple. Interventions designed to facilitate awareness, implementation, and access to clinical trials are needed to ultimately improve recruitment to trials.

	AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

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Although all authors completed the disclosure declaration, the following author(s) indicated a financial or other interest that is relevant to the subject matter under consideration in this article. Certain relationships marked with a "U" are those for which no compensation was received; those relationships marked with a "C" were compensated. For a detailed description of the disclosure categories, or for more information about ASCO's conflict of interest policy, please refer to the Author Disclosure Declaration and the Disclosures of Potential Conflicts of Interest section in Information for Contributors.

Employment or Leadership Position: None Consultant or Advisory Role: Julie Lemieux, Abraxis (C), Bristol-Myers Squibb (C), Eli Lilly (C), Pfizer (C), Roche (C); Kathleen I. Pritchard, Aventis (C), Roche (C), Pharmacia (C), Ortho Biotech (C), Pfizer (C), YM BioSciences (C), Biomira (C) Stock Ownership: None Honoraria: Kathleen I. Pritchard, Aventis, AstraZeneca, Pharmacia, Pfizer Research Funding: None Expert Testimony: Kathleen I. Pritchard, Aventis (C), AstraZeneca (C) Other Remuneration: None

	AUTHOR CONTRIBUTIONS

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Conception and design: Julie Lemieux, Pamela J. Goodwin, Karen A. Gelmon, Louise J. Bordeleau

Provision of study materials or patients: Kathleen I. Pritchard, Karen A. Gelmon

Collection and assembly of data: Julie Lemieux, Kathleen I. Pritchard, Karen A. Gelmon, Caroline H. Speers

Data analysis and interpretation: Julie Lemieux, Pamela J. Goodwin, Kathleen I. Pritchard, Karen A. Gelmon, Louise J. Bordeleau, Thierry Duchesne, Stéphanie Camden

Manuscript writing: Julie Lemieux, Pamela J. Goodwin, Kathleen I. Pritchard, Karen A. Gelmon, Louise J. Bordeleau, Thierry Duchesne, Stéphanie Camden, Caroline H. Speers

Final approval of manuscript: Julie Lemieux, Pamela J. Goodwin, Kathleen I. Pritchard, Karen A. Gelmon, Louise J. Bordeleau, Thierry Duchesne, Stéphanie Camden, Caroline H. Speers

	ACKNOWLEDGMENTS

 
We thank the Ontario Institute for Cancer Research Clinical Trials Network for its collaboration.

	NOTES

 
Supported by the Canadian Breast Cancer Foundation–Ontario Chapter.

Presented in part at the 43rd Annual Meeting of the American Society of Clinical Oncology, June 1-5, 2007, Chicago, IL.

Authors’ disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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Submitted November 27, 2007; accepted May 20, 2008.

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This Article Abstract Full Text (PDF) Purchase Article View Shopping Cart Alert me when this article is cited Alert me if a correction is posted Services Email this article to a colleague Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Save to my personal folders Download to citation manager Rights & Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Lemieux, J. Articles by Speers, C. H. Search for Related Content PubMed PubMed Citation Articles by Lemieux, J. Articles by Speers, C. H. Social Bookmarking                            What's this?