An Evaluation of Clinical Trial Multimedia to Support Hispanic Cancer Patients’ Informational and Decision-Making Needs

2019 ◽  
Author(s):  
Soroya Julian McFarlane ◽  
Susan E. Morgan ◽  
Aurora Occa ◽  
Wei Peng
Keyword(s):  
Clinical Trial ◽  
Decision Making ◽  
Cancer Patients

Why Cancer Patients Enter Randomized Clinical Trials: Exploring the Factors That Influence Their Decision

2004 ◽  
Vol 22 (21) ◽  
pp. 4312-4318 ◽  
Author(s):  
James R. Wright ◽  
Timothy J. Whelan ◽  
Susan Schiff ◽  
Sacha Dubois ◽  
Dauna Crooks ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Decision Making ◽  
Clinical Trials ◽  
Logistic Regression ◽  
Cancer Patients ◽  
Randomized Clinical Trials ◽  
Univariate Analysis ◽  
Multivariate Logistic Regression Model ◽  
Decision Making Process ◽  
Trial Entry

Purpose Few interventions have been designed and tested to improve recruitment to clinical trials in oncology. The multiple factors influencing patients' decisions have made the prioritization of specific interventions challenging. The present study was undertaken to identify the independent predictors of a cancer patient's decision to enter a randomized clinical trial. Methods A list of factors from the medical literature was augmented with a series of focus groups involving cancer patients, physicians, and clinical research associates (CRAs). A series of questionnaires was developed with items based on these factors and were administered concurrently to 189 cancer patients, their physicians, and CRAs following the patient's decision regarding trial entry. Forward logistic regression modeling was performed using the items significantly correlated (by univariate analysis) with the decision to enter a clinical trial. Results A number of items were significantly correlated with the patient's decision. In the multivariate logistic regression model, the patient's perception of personal benefit was the most important, with an odds ratio (OR) of 3.08 (P < .05). CRA-related items involving supportive aspects of the decision-making process were also important. These included whether the CRA helped with the decision (OR = 1.71; P < .05), and whether the decision was hard for the patient to make (OR = 0.52; P < .05). Conclusion Strategies that better address the potential benefits of trial entry may result in improved accrual. Interventions or aids that focus on the supportive aspects of the decision-making process while respecting the need for information and patient autonomy may also lead to meaningful improvements in accrual.

Decision Making in Cancer Prevention and Control

2018 ◽  
Author(s):  
Erin M. Ellis ◽  
Rebecca A. Ferrer
Keyword(s):  
Clinical Trial ◽  
Decision Making ◽  
Palliative Care ◽  
Cancer Patients ◽  
Trial Participation ◽  
Clinical Trial Participation ◽  
High Stakes ◽  
Life And Death ◽  
Fundamental Knowledge ◽  
And Control

Being diagnosed with cancer introduces the need to make many high-stakes decisions about treatments, clinical trial participation, palliative care, advanced care planning, and (sometimes) end-of-life preferences. These decisions can be intensely emotional themselves, and occur within the affectively laden context of cancer-related issues, such as symptom management, interpersonal concerns, and existential questions about life and death. This chapter outlines how affect/emotion influences several decisions faced by cancer patients, and how emotions are relevant to the interpersonal context in which these decisions occur. Emotion has pervasive and predictable—sometimes deleterious and sometimes advantageous—influences on decision making. Fundamental knowledge regarding how affect influences cancer-related decision making could be leveraged to develop interventions to optimize decisions about treatment, clinical trial participation, and palliative care among cancer patients and survivors, thereby improving cancer-related outcomes.

scholarly journals A Model of Cancer Clinical Trial Decision-making Informed by African-American Cancer Patients

2014 ◽  
Vol 2 (2) ◽  
pp. 192-199 ◽  
Author(s):  
Jennifer A. Wenzel ◽  
Olive Mbah ◽  
Jiayun Xu ◽  
Gyasi Moscou-Jackson ◽  
Haneefa Saleem ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Decision Making ◽  
African American ◽  
Cancer Patients ◽  
Cancer Clinical Trial

scholarly journals “When Offered to Participate”: A Systematic Review and Meta-Analysis of Patient Agreement to Participate in Cancer Clinical Trials

2020 ◽  
Author(s):  
Joseph M Unger ◽  
Dawn L Hershman ◽  
Cathee Till ◽  
Lori M Minasian ◽  
Raymond U Osarogiagbon ◽  
...  
Keyword(s):  
Systematic Review ◽  
Clinical Trial ◽  
Decision Making ◽  
Clinical Trials ◽  
Cancer Patients ◽  
Meta Analysis ◽  
Cancer Control ◽  
Trial Participation ◽  
Clinical Trial Participation ◽  
Black Patients

Abstract Background Patient participation in clinical trials is vital for knowledge advancement and outcomes improvement. Few adult cancer patients participate in trials. Although patient   decision-making about trial participation has been frequently examined, the participation rate for patients actually offered a trial is unknown. Methods A systematic review and meta-analysis using 3 major search engines was undertaken. We identified studies from January 1, 2000, to January 1, 2020, that examined clinical trial participation in the United States. Studies must have specified the numbers of patients offered a trial and the number enrolled. A random effects model of proportions was used. All statistical tests were 2-sided. Results We identified 35 studies (30 about treatment trials and 5 about cancer control trials) among which 9759 patients were offered trial participation. Overall, 55.0% (95% confidence interval [CI] = 49.4% to 60.5%) of patients agreed to enroll. Participation rates did not differ between treatment (55.0%, 95% CI = 48.9% to 60.9%) and cancer control trials (55.3%, 95% CI = 38.9% to 71.1%; P = .98). Black patients participated at similar rates (58.4%, 95% CI = 46.8% to 69.7%) compared with White patients (55.1%, 95% CI = 44.3% to 65.6%; P = .88). The main reasons for nonparticipation were treatment choice or lack of interest. Conclusions More than half of all cancer patients offered a clinical trial do participate. These findings upend several conventional beliefs about cancer clinical trial participation, including that Black patients are less likely to agree to participate and that patient decision-making is the primary barrier to participation. Policies and interventions to improve clinical trial participation should focus more on modifiable systemic structural and clinical barriers, such as improving access to available trials and broadening eligibility criteria.

scholarly journals What matters in clinical trial decision‐making: a systematic review of interviews exploring cancer patients’ experiences

2019 ◽  
Vol 33 (2) ◽  
pp. 266-278 ◽  
Author(s):  
Trine A. Gregersen ◽  
Regner Birkelund ◽  
Maiken Wolderslund ◽  
Mette Løwe Netsey‐Afedo ◽  
Karina Dahl Steffensen ◽  
...  
Keyword(s):  
Systematic Review ◽  
Clinical Trial ◽  
Decision Making ◽  
Cancer Patients ◽  
What Matters

Analysis of PSA-Specific T-Cell Responses of Prostate Cancer Patients Given a PSA-Based Vaccine on a Clinical Trial

2003 ◽  
Author(s):  
James Gulley ◽  
William Dahut ◽  
Philip M. Arlen ◽  
Kwong Tsang ◽  
Jeffrey Schlom
Keyword(s):  
Prostate Cancer ◽  
Clinical Trial ◽  
T Cell ◽  
Cancer Patients ◽  
T Cell Responses ◽  
Cell Responses

Is the Deductive Falsification Approach a Better Basis for Clinical Trial Appraisal?

2019 ◽  
Vol 14 (3) ◽  
pp. 224-228
Author(s):  
Steffen Mickenautsch
Keyword(s):  
Clinical Trial ◽  
Decision Making ◽  
Empirical Evidence ◽  
Clinical Decision Making ◽  
Inductive Reasoning ◽  
Clinical Decision ◽  
Future Trial ◽  
Grading Systems ◽  
Component Scores ◽  
Current Clinical Trial

Background: Inductive reasoning relies on an infinite regress without sufficient factual basis and verification is at any time vulnerable to single contrary observation. Thus, appraisal based on inductive verification, as applied in current clinical trial appraisal scales, checklists or grading systems, cannot prove or justify trial validity. Discussion: Trial appraisal based on deductive falsification can identify invalid trials and give evidence for the recommendation to exclude these from clinical decision-making. Such appraisal remains agnostic towards corroborated trials that pass all appraisal criteria. The results of corroborated trials cannot be considered more robust than falsified trials since nothing within a particular set of complied trial criteria can give certainty for trial compliance with any other appraisal criterion in future. A corroborated trial may or may not reflect therapeutic truth and may thus be the basis for clinical guidance, pending results of any future trial re-appraisal. Conclusion: Trial grading following appraisal based on deductive falsification should be binary (0 = Invalid or 1 = Unclear) and single component scores should be multiplied. Appraisal criteria for the judgment of trial characteristics require a clear rationale, quantification of such rationale and empirical evidence concerning the effect of trial characteristics on trial results.

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