Journal of Clinical Oncology · 2004 · 138 citations · 24 references
MedicineOncologyCancer ControlClinical Decision SupportOutcomes ResearchClinical Trial DesignClinical TrialsClinical Trials In OncologyPatient SelectionStudy DesignEntryLogistic RegressionMajor Decision-making ProcessOdds Ratio ModelingRandomized Clinical TrialsTreatment Decision-making SupportUnivariate Analysis
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.
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Choice Reviews Online · 1990 · 35.7K citations
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Best Subsets Logistic Regression
David W. Hosmer, Borko Jovanovic, Stanley Lemeshow · Biometrics · 1989 · 1.2K citations
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Steven Joffe, E. Francis Cook, Paul D. Cleary et al. · The Lancet · 2001 · 659 citations
Medicine, Oncology, Medical Ethics +11