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Figure 1.  Willingness of Surveyed Patients With Cancer or Survivors of Cancer to Participate in Trials Requiring Additional Effort, by Respondent Income
Willingness of Surveyed Patients With Cancer or Survivors of Cancer to Participate in Trials Requiring Additional Effort, by Respondent Income

Additional effort is defined in terms of frequency of visits or travel to a more distant location to participate in a cancer clinical trial compared with the site where regular care is provided.

Figure 2.  Willingness of Surveyed Patients With Cancer or Survivors of Cancer to Adopt Remote Care Outside of a Clinical Trial
Willingness of Surveyed Patients With Cancer or Survivors of Cancer to Adopt Remote Care Outside of a Clinical Trial
Table.  Association of Decentralization Modifications With Self-reported Willingness to Enroll in a Trial, Cross-tabulated by Initial Reported Willingness to Participate in Trials
Association of Decentralization Modifications With Self-reported Willingness to Enroll in a Trial, Cross-tabulated by Initial Reported Willingness to Participate in Trials
Supplement.

eTable 1. Age at Time of Survey

eTable 2. Race

eTable 3. Last Treatment Time Frame

eTable 4. Primary Insurance Coverage

eTable 5. Ethnicity

eTable 6. Gender

eTable 7. Sexual Orientation

eTable 8. Type of Cancer

eTable 9. Highest Level of Education

eTable 10. Household Income

eTable 11. Distance to Facility of Provider Who Has or Had the Greatest Role in Planning Cancer Care

eTable 12. Reliable High-Speed Internet at Home

eTable 13. Rural, Urban, or Suburban (Home Residence)

eTable 14. Time to Facility of Provider Who Has or Had the Greatest Role in Planning Cancer Care

eTable 15. Access to Internet-Enabled Technologies at Home

eTable 16. Self-reported Willingness to Enroll in a Trial Using Wearable Technology to Collect Clinical Trial Data Remotely

eTable 17. Self-reported Willingness to Enroll in a Trial Using Health App(s) to Log Patient Health Information

eTable 18. Self-reported Willingness to Enroll in a Trial With Related Activities Taking Place at Home Under Video Supervision of Study Personnel

eTable 19. Self-reported Willingness to Enroll in a Trial With Related Check-In/Follow-Up Visits With Study Personnel via Live Video in the Home

eTable 20. Self-reported Willingness to Enroll in a Trial Performing Related Clinical Trial Activities (eg, Medications, Diagnostic Tests, Blood Draws) at a Local Facility by a Regular or Local Provider

eTable 21. Self-reported Willingness to Give Virtual Informed Consent Before Participating in a Clinical Trial

eTable 22. Self-reported Willingness to Enroll in a Clinical Trial With Oral Clinical Trial Medications Delivered to and Taken at Home

eTable 23. Self-reported Willingness to Enroll in a Clinical Trial With Intramuscular or Subcutaneous Clinical Trial Medications Delivered to and Injected at Home by Trial Personnel

eTable 24. Self-reported Willingness to Enroll in a Clinical Trial With Intravenous Clinical Trial Medications Delivered to and Infused at Home by Trial Personnel

eMethods. Survey Instrument

1.
Fogel  DB.  Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: a review.   Contemp Clin Trials Commun. 2018;11:156-164. doi:10.1016/j.conctc.2018.08.001 PubMedGoogle ScholarCrossref
2.
Unger  JM, Cook  E, Tai  E, Bleyer  A.  The role of clinical trial participation in cancer research: barriers, evidence, and strategies.   Am Soc Clin Oncol Educ Book. 2016;35(36):185-198. doi:10.1200/EDBK_156686 PubMedGoogle ScholarCrossref
3.
Loree  JM, Anand  S, Dasari  A,  et al.  Disparity of race reporting and representation in clinical trials leading to cancer drug approvals from 2008 to 2018.   JAMA Oncol. 2019;5(10):e191870. doi:10.1001/jamaoncol.2019.1870 PubMedGoogle ScholarCrossref
4.
Scher  KS, Hurria  A.  Under-representation of older adults in cancer registration trials: known problem, little progress.   J Clin Oncol. 2012;30(17):2036-2038. doi:10.1200/JCO.2012.41.6727 PubMedGoogle ScholarCrossref
5.
Waterhouse  DM, Harvey  RD, Hurley  P,  et al.  Early impact of COVID-19 on the conduct of oncology clinical trials and long-term opportunities for transformation: findings from an American Society of Clinical Oncology Survey.   JCO Oncol Pract. 2020;16(7):417-421. doi:10.1200/OP.20.00275 PubMedGoogle ScholarCrossref
6.
Upadhaya  S, Yu  JX, Hodge  J, Campbell  J.  COVID-19 impact on oncology clinical trials: a 1-year analysis.   Nat Rev Drug Discov. 2021;20(6):415-415. doi:10.1038/d41573-021-00086-8 PubMedGoogle ScholarCrossref
7.
US Food and Drug Administration.  FDA guidance on conduct of clinical trials of medical products during the COVID-19 public health emergency. August 30, 2021. Accessed January 20, 2022. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/fda-guidance-conduct-clinical-trials-medical-products-during-covid-19-public-health-emergency
8.
National Cancer Institute.  Interim guidance for clinical trial activities affected by the novel coronavirus. Accessed January 21, 2022. https://ctep.cancer.gov/investigatorResources/corona_virus_guidance.htm
9.
National Cancer Institute.  Additional guidance regarding alternative procedures for clinical trials supported by NCI CTEP and NCORP affected by the spread of the novel coronavirus. Accessed January 21, 2022. https://ctep.cancer.gov/investigatorResources/docs/Memorandum_on_Additional_Guidance_for_Clinical_Trial_Activities_Affected_by_the_Novel_Coronavirus_3-23-2020.pdf
10.
Unger  JM, Hershman  DL, Till  C,  et al.  “When offered to participate”: a systematic review and meta-analysis of patient agreement to participate in cancer clinical trials.   J Natl Cancer Inst. 2021;113(3):244-257. doi:10.1093/jnci/djaa155 PubMedGoogle ScholarCrossref
11.
Meropol  NJ, Buzaglo  JS, Millard  J,  et al.  Barriers to clinical trial participation as perceived by oncologists and patients.   J Natl Compr Canc Netw. 2007;5(8):655-664. doi:10.6004/jnccn.2007.0067 PubMedGoogle ScholarCrossref
12.
Javid  SH, Unger  JM, Gralow  JR,  et al.  A prospective analysis of the influence of older age on physician and patient decision-making when considering enrollment in breast cancer clinical trials (SWOG S0316).   Oncologist. 2012;17(9):1180-1190. doi:10.1634/theoncologist.2011-0384 PubMedGoogle ScholarCrossref
13.
Nipp  RD, Powell  E, Chabner  B, Moy  B.  Recognizing the financial burden of cancer patients in clinical trials.   Oncologist. 2015;20(6):572-575. doi:10.1634/theoncologist.2015-0068 PubMedGoogle ScholarCrossref
14.
Borno  HT, Zhang  L, Siegel  A, Chang  E, Ryan  CJ.  At what cost to clinical trial enrollment? a retrospective study of patient travel burden in cancer clinical trials.   Oncologist. 2018;23(10):1242-1249. doi:10.1634/theoncologist.2017-0628 PubMedGoogle ScholarCrossref
15.
Unger  JM, Hershman  DL, Albain  KS,  et al.  Patient income level and cancer clinical trial participation.   J Clin Oncol. 2013;31(5):536-542. doi:10.1200/JCO.2012.45.4553 PubMedGoogle ScholarCrossref
Original Investigation
Diversity, Equity, and Inclusion
July 5, 2022

Association of Remote Technology Use and Other Decentralization Tools With Patient Likelihood to Enroll in Cancer Clinical Trials

Author Affiliations
  • 1American Cancer Society Cancer Action Network, Washington, DC
JAMA Netw Open. 2022;5(7):e2220053. doi:10.1001/jamanetworkopen.2022.20053
Key Points

Question  What is the association of remote technology and other decentralization tools with patient likelihood to enroll in cancer clinical trials?

Findings  In this cross-sectional survey study of 1183 patients with cancer and survivors of cancer, self-reported patient disposition toward enrollment in cancer clinical trials increased for modifications using remote technology and other decentralization tools. The majority of respondents (60%-85%) reported being more likely to enroll if the participation-related time and travel burden decreased as a result of these practices.

Meaning  These findings suggest that greater adoption of practices that reduce patient time and travel burden associated with clinical trial participation could improve enrollment in cancer trials.

Abstract

Importance  Logistical challenges such as travel time and distance to a clinical trial site can be a barrier to patient participation. The association of remote technology use and other decentralization tools that can reduce these barriers with likelihood to enroll in cancer trials is not well understood.

Objective  To assess the association of remote technology and other decentralization tools used to reduce participation-related time and travel with the likelihood to enroll in cancer clinical trials.

Design, Setting, and Participants  Between July 6 and September 8, 2021, a 41-question, cross-sectional, internet-based survey was administered to patients with cancer and survivors of cancer in the US who had been diagnosed with or treated for cancer in the past 7 years.

Main Outcomes and Measures  Increase in self-reported likelihood to enroll in cancer clinical trials that use remote technology and other decentralization tools to decrease the need for travel to the trial site.

Results  There were 1183 survey respondents, with a mean (SD) age of 58.2 (12.5) years. Respondents self-reported their gender, race and ethnicity, cancer type, and treatment status. Of the 1183 respondents, 848 (72%) were female, 296 (25%) were male, 8 (1%) were other/nonbinary, and 31 (3%) declined to answer. With regard to race, 28 respondents (3%) were American Indian or Alaska Native, 25 (2%) were Asian, 234 (20%) were Black or African American, 20 (2%) were Native Hawaiian or Other Pacific Islander, 825 (70%) were White, and 51 (4%) declined to answer. With regard to ethnicity, 115 respondents (10%) were Hispanic, Latino/Latina, or of Spanish origin, whereas 1017 (86%) were not and 51 (4%) declined to answer. Regarding cancer type and treatment status, 483 respondents (41%) either had or had survived breast cancer and 325 (28%) were being treated for cancer during the survey period. Individuals older than 55 years were more likely to say that they would only participate in trials no farther from their home than their regular care health care practitioner compared with younger respondents (26% vs 16%, respectively; P = .02). Higher-income earners (ie, those in households earning >$125 000/y) were significantly more likely than lower-income earners (ie, those in households earning <$70 000/y) to say they would participate in trials requiring additional effort (62% vs 41%, respectively; P = .03). If given the opportunity to enroll in a cancer clinical trial that required travel farther than their regular care, a majority of respondents (range, 60%-85%) indicated that they would be more likely to participate if the trial used remote technology and other tools to decrease the need for travel to a trial site.

Conclusions and Relevance  In this cross-sectional study, the survey findings suggest that cancer clinical trials leveraging remote technology and decentralization tools to reduce patient time and travel burden associated with participation may increase the patient consent rate.

Introduction

Adequate enrollment of participants in cancer clinical trials is essential for trial success and for advancing new standards of cancer care. Inadequate enrollment can lead to trial failure1 or affect the interpretation of study results.2 Even when recruitment is successful, cancer trials often do not reflect the diversity of the US population diagnosed with cancer,3,4 which can limit the generalizability of results and lead to an unequal benefit in treatment advancements. The COVID-19 pandemic has disrupted all aspects of cancer clinical research, including enrollment in trials,5 as many ongoing trials were suspended and the start of planned studies was delayed.6 In an effort to reduce the risks of SARS-CoV-2 transmission to patients and research staff and to move research forward, the US Food and Drug Administration7 and the National Cancer Institute8,9 issued guidance for trial investigators on clinical trial conduct for the duration of the federal Coronavirus Disease 2019 Public Health Emergency (PHE). This guidance provided flexibility for the adoption of methods to facilitate trial decentralization through the remote collection of trial data8,9 outside of a standard, in-person, centralized clinical trial assessment site. These methods included use of virtual clinic visits, delivery of investigational products to the home, and use of alternative laboratories or imaging centers.

Although most patients accept when offered to participate in cancer clinical trials,10 logistical challenges such as travel time and distance to a trial site are often a barrier to patient enrollment.11-13 Decentralization of clinical trials beyond the PHE could provide an opportunity to increase access to and enrollment in available trials by reducing the participant time and travel burden. The effects of remote technology and other decentralization tools on the likelihood to increase patient disposition toward participation in cancer clinical trials are not yet well understood. This study aimed to assess the association of remote technology and other decentralization tools used to reduce time and travel related to clinical trial participation with patient likelihood to enroll in cancer trials.

Methods

The cross-sectional survey study was deemed exempt by the Morehouse School of Medicine Institutional Review Board. Participant informed consent was obtained electronically. Participation was voluntary and could be withdrawn at any time. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cross-sectional studies where applicable.

Participants were included from the American Cancer Society Cancer Action Network’s Survivor Views panel and augmented with commercially available web survey panels. Panelists were aged 18 years or older, had been diagnosed with and/or treated for cancer within the past 7 years, and were US residents. A series of questions were designed regarding telehealth, remote care technologies, and willingness to participate in cancer clinical trials (eMethods in the Supplement). These questions were incorporated into the existing survey program and sent to 1269 Survivor Views participants between July 6 and September 8, 2021, and to an undefinable number of commercial web survey panelists who were contacted through a Dynata panel. A total of 591 Survivor Views responses were received for an estimated response rate of 46.5% from the panel. The response rate for the remaining 592 responses obtained via other sources was undefinable because it is unclear how many received the invitation to participate, owing to uncertainty of email delivery status. Socioeconomic data, including race and ethnicity defined by the investigator, were identified by self-report and were accessed to ascertain differential associations of trial decentralization by socioeconomic factors. We classified race into 6 categories: American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Pacific Islander, White, or declined to answer. We classified ethnicity into 3 categories: Hispanic, Latino/Latina, or Spanish origin (yes or no) or declined to answer.

Statistical Analysis

For comparisons of statistical significance, we used independent t tests for means and independent z tests for percentages. Statistical significance was set at α = .05. All statistical analyses were performed with IBM SPSS, version 27.

Results

The 1183 survey respondents had a mean (SD) age of 58.2 (12.5) years. Respondents self-reported their gender, race and ethnicity, cancer type, and treatment status. Of the 1183 respondents, 848 (72%) were female, 296 (25%) were male, 8 (1%) were other/nonbinary, and 31 (3%) declined to answer. With regard to race, 28 respondents (3%) were American Indian or Alaska Native, 25 (2%) were Asian, 234 (20%) were Black or African American, 20 (2%) were Native Hawaiian or Pacific Islander, 825 (70%) were White, and 51 (4%) declined to answer. With regard to ethnicity, 115 respondents (10%) were Hispanic, Latino/Latina, or of Spanish origin, whereas 1017 (86%) were not and 51 (4%) declined to answer. There were 483 patients (41%) who had breast cancer or were survivors of breast cancer and 325 (28%) were being treated for cancer at the time of the survey (eTables 1-15 in the Supplement provide additional demographic data).

Of the survey respondents, 217 (18%) had participated in a cancer clinical trial, and 73 (6%) looked for a trial on their own but did not find one. Only 88 respondents (7%) declined to participate in a trial they were told they qualified for, whereas 543 (46%) had never discussed trial participation with their health care practitioner. There were 909 respondents (77%) who said they would join a cancer clinical trial if it were at least as easy as their regular care in terms of distance and frequency of visits, and 557 (47%) said they would participate even if it required additional effort in terms of travel distance or frequency of visits. There were 353 respondents (30%) who said they would be willing to travel up to 90 minutes or more from their regular care to join a trial. Respondents older than 55 years were significantly more likely to say they would only participate in trials no farther from their home than their regular care compared with younger respondents (158 [26%] vs 39 [16%], respectively; P = .02). Individuals in higher-income households (>$125 000/y) were significantly more likely than those in lower-income households (<70 000/y) to say they would participate in trials requiring additional effort (147 [62%] vs 354 [41%], respectively; P = .03) (Figure 1).

Many respondents had already begun engaging in remote care outside of a clinical trial. For example, 520 (44%) had previously participated in a video visit with a health care practitioner for an issue related to their cancer for which they would have otherwise had to go into the office. These experiences were overwhelmingly positive, with 496 respondents (95%) reporting that their issues and questions were well addressed during the video visit.

Respondents were asked about their general willingness to adopt technologies and tools related to remote care not specifically within the clinical trial context. They were subsequently asked whether the adoption of these technologies and tools by a trial that would otherwise require more distant travel would make them more likely to enroll. More than 80% of respondents (range, 999-1033) expressed willingness to adopt the majority (6 of 8) of remote interventions (Figure 2); similarly, the use of these interventions was associated with an increase in self-reported likelihood to enroll in a trial among a majority of respondents (range, 60%-85%) (Table). The proposed modifications were associated with an increase in willingness to enroll by the greatest amount among respondents who expressed the highest interest in enrolling in a trial absent such modifications (range, 429-509 [77%-91%]), but increases in willingness were reported by all groups, even among those who initially reported that they would not join a clinical trial under any circumstances (range, 7-13 [26%-48%]) or unless there were extremely compelling reasons (range, 55-114 [34%-70%]) (Table). For each modification, a minority of respondents reported that the modification would decrease their willingness to participate. For example, “intravenous (IV) clinical trial medications delivered to and infused in the home by trial personnel” was the most notable, with 239 respondents (20%) indicating that the modification would make them less likely to participate (eTables 16-24 in the Supplement). Finally, 1015 respondents (86%) said it was important to have the option for in-person visits when desired if enrolled in a trial in which all trial-related activities could be done in their home.

Discussion

The results of this cross-sectional survey study suggest that most patients with cancer and survivors of cancer are willing to participate in cancer clinical trials if recommended by their health care practitioner, even if participation requires additional effort in terms of frequency of visits or travel to a more distant location compared with their regular health care practitioner. However, willingness to participate in trials requiring additional effort varies by income and age, with lower-income earners and older respondents less likely to travel farther or attend more frequent visits. Previous research has established a higher travel burden experienced by patients living in low-income areas and enrolled in trials14 and a positive correlation between patient income and their likelihood to participate in a trial.15

The COVID-19 pandemic and subsequent regulatory guidance on the conduct of clinical trials increased the adoption of decentralized clinical trials; however, many of the regulatory flexibilities permitted during the pandemic are set to expire at the conclusion of the PHE. Decentralization of trials through remote technology and other tools can alleviate travel burden associated with trial participation by delinking where a patient is evaluated and/or treated in respect to a trial and where a trial is hosted, potentially allowing for a larger and more diverse cohort of trial participants. Our data show that patients with cancer and survivors of cancer are receptive to these technologies and tools and use in the context of trials is associated with an increase in self-reported likelihood to consent if the technology or tool decreases the need to travel to a trial site. However, the degree to which respondents would be more likely to join a trial varied by approach, and the ability to have the option for in-person visits at a trial site when desired remained important.

Limitations

This study has some limitations. The survey questions assess hypothetical participation in cancer clinical trials and do not measure the extent to which stated participation intent corresponds to actual participation. The survey questions assessing willingness to participate in cancer clinical trials were not evaluated by clinical trial phase or by type of trial intervention. Each clinical trial phase has different goals, and cancer clinical trials range in terms of the intensity of the intervention that may be required (eg, an experimental drug vs an experimental drug plus a surgical intervention), which may affect an individual’s willingness to participate in a cancer clinical trial. A potential source of bias inherent to the methodology is that respondents taking part in survey research may be more predisposed to research in general.

Conclusions

In this cross-sectional study of patients with and survivors of cancer, most respondents expressed a strong willingness to participate in cancer clinical trials. However, willingness to participate in trials requiring additional effort in terms of the frequency of visits and travel distance, compared with regular care, varied by income and age. The use of remote technology and other decentralization tools that can decrease the need for travel to a trial site was associated with an increase in self-reported patient likelihood toward participation in cancer trials. Greater adoption of remote technology and other decentralization tools may alleviate patient barriers such as travel time and distance to a trial site, which in turn may increase patient consent rates.

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Article Information

Accepted for Publication: May 17, 2022.

Published: July 5, 2022. doi:10.1001/jamanetworkopen.2022.20053

Open Access: This is an open access article distributed under the terms of the CC-BY-NC-ND License. © 2022 Adams DV et al. JAMA Network Open.

Corresponding Author: Devon V. Adams, MPH, RN, American Cancer Society Cancer Action Network, 655 15th St NW, Ste 503, Washington, DC 20005 (devon.adams@cancer.org).

Author Contributions: Ms Long had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Mr Adams and Dr Fleury contributed equally to this work.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: Adams, Long.

Drafting of the manuscript: Adams, Long.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Long.

Administrative, technical, or material support: All authors.

Supervision: All authors.

Conflict of Interest Disclosures: Mr Adams reporting managing projects unrelated to this publication funded through grants to his employer from Amgen, Bayer, Bristol Myers Squibb, EMD Serono, Foundation Medicine Inc, Merck, NeoGenomics, Pfizer, and Sanofi outside the submitted work. Mr Adams also reported that his salary is funded through institutional grants to his employer from Amgen, Bayer, Blueprint Medicine, Genentech, Janssen, and Pfizer. Ms Long reported that her salary is funded through institutional grants to her employer from Bristol Myers Squibb, Amgen, Merck, Pfizer, and Sanofi. Dr Fleury reported managing projects supported by grants to his employer from Amgen, Bayer, Bristol Myers Squibb, EMD Serono, Foundation Medicine Inc, Genentech, Merck, NeoGenomics, Parexel, Pfizer, Sanofi, and Seagen outside the submitted work.

Funding/Support: Funding for building the survey cohort and survey administration was provided by Amgen, Bristol Myers Squibb, Merck, Pfizer, and Sanofi.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: We recognize the following individuals for assistance with content development for the data collection instrument: Leigh M. Boehmer, PharmD, Association of Community Cancer Centers; Archana Sah, MSc (Pharm), Medable Inc; Joseph Unger, PhD, MS, Fred Hutchinson Cancer Research Center, University of Washington; and Peter Fredette, BS, IQVIA. No compensation was provided for this assistance. We thank all of the patients with cancer and survivors of cancer who volunteered their time to answer the survey.

References
1.
Fogel  DB.  Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: a review.   Contemp Clin Trials Commun. 2018;11:156-164. doi:10.1016/j.conctc.2018.08.001 PubMedGoogle ScholarCrossref
2.
Unger  JM, Cook  E, Tai  E, Bleyer  A.  The role of clinical trial participation in cancer research: barriers, evidence, and strategies.   Am Soc Clin Oncol Educ Book. 2016;35(36):185-198. doi:10.1200/EDBK_156686 PubMedGoogle ScholarCrossref
3.
Loree  JM, Anand  S, Dasari  A,  et al.  Disparity of race reporting and representation in clinical trials leading to cancer drug approvals from 2008 to 2018.   JAMA Oncol. 2019;5(10):e191870. doi:10.1001/jamaoncol.2019.1870 PubMedGoogle ScholarCrossref
4.
Scher  KS, Hurria  A.  Under-representation of older adults in cancer registration trials: known problem, little progress.   J Clin Oncol. 2012;30(17):2036-2038. doi:10.1200/JCO.2012.41.6727 PubMedGoogle ScholarCrossref
5.
Waterhouse  DM, Harvey  RD, Hurley  P,  et al.  Early impact of COVID-19 on the conduct of oncology clinical trials and long-term opportunities for transformation: findings from an American Society of Clinical Oncology Survey.   JCO Oncol Pract. 2020;16(7):417-421. doi:10.1200/OP.20.00275 PubMedGoogle ScholarCrossref
6.
Upadhaya  S, Yu  JX, Hodge  J, Campbell  J.  COVID-19 impact on oncology clinical trials: a 1-year analysis.   Nat Rev Drug Discov. 2021;20(6):415-415. doi:10.1038/d41573-021-00086-8 PubMedGoogle ScholarCrossref
7.
US Food and Drug Administration.  FDA guidance on conduct of clinical trials of medical products during the COVID-19 public health emergency. August 30, 2021. Accessed January 20, 2022. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/fda-guidance-conduct-clinical-trials-medical-products-during-covid-19-public-health-emergency
8.
National Cancer Institute.  Interim guidance for clinical trial activities affected by the novel coronavirus. Accessed January 21, 2022. https://ctep.cancer.gov/investigatorResources/corona_virus_guidance.htm
9.
National Cancer Institute.  Additional guidance regarding alternative procedures for clinical trials supported by NCI CTEP and NCORP affected by the spread of the novel coronavirus. Accessed January 21, 2022. https://ctep.cancer.gov/investigatorResources/docs/Memorandum_on_Additional_Guidance_for_Clinical_Trial_Activities_Affected_by_the_Novel_Coronavirus_3-23-2020.pdf
10.
Unger  JM, Hershman  DL, Till  C,  et al.  “When offered to participate”: a systematic review and meta-analysis of patient agreement to participate in cancer clinical trials.   J Natl Cancer Inst. 2021;113(3):244-257. doi:10.1093/jnci/djaa155 PubMedGoogle ScholarCrossref
11.
Meropol  NJ, Buzaglo  JS, Millard  J,  et al.  Barriers to clinical trial participation as perceived by oncologists and patients.   J Natl Compr Canc Netw. 2007;5(8):655-664. doi:10.6004/jnccn.2007.0067 PubMedGoogle ScholarCrossref
12.
Javid  SH, Unger  JM, Gralow  JR,  et al.  A prospective analysis of the influence of older age on physician and patient decision-making when considering enrollment in breast cancer clinical trials (SWOG S0316).   Oncologist. 2012;17(9):1180-1190. doi:10.1634/theoncologist.2011-0384 PubMedGoogle ScholarCrossref
13.
Nipp  RD, Powell  E, Chabner  B, Moy  B.  Recognizing the financial burden of cancer patients in clinical trials.   Oncologist. 2015;20(6):572-575. doi:10.1634/theoncologist.2015-0068 PubMedGoogle ScholarCrossref
14.
Borno  HT, Zhang  L, Siegel  A, Chang  E, Ryan  CJ.  At what cost to clinical trial enrollment? a retrospective study of patient travel burden in cancer clinical trials.   Oncologist. 2018;23(10):1242-1249. doi:10.1634/theoncologist.2017-0628 PubMedGoogle ScholarCrossref
15.
Unger  JM, Hershman  DL, Albain  KS,  et al.  Patient income level and cancer clinical trial participation.   J Clin Oncol. 2013;31(5):536-542. doi:10.1200/JCO.2012.45.4553 PubMedGoogle ScholarCrossref
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