ArticlePatient education and counseling2009
Assessing risk communication in breast cancer: are continuous measures of patient knowledge better than categorical?
Article in Patient education and counseling, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Does use of the adjuvant! model influence use of adjuvant therapy through better risk communication?Journal of the National Comprehensive Cancer Network : JNCCN · 2011Article
- Oncologist use of the Adjuvant! model for risk communication: a pilot study examining patient knowledge of 10-year prognosis.BMC cancer · 2009Article
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Authors and funding
3 authors.
Funding
Abstract
objectiveTo compare the performance of categorical and continuous measures of patient knowledge in the context of risk communication about breast cancer, in terms of statistical and clinical significance as well as efficiency.
methodsTwenty breast cancer patients provided estimates of 10-year mortality risk before and after their oncology visit. The oncologist reviewed risk estimates from Adjuvant!, a well-validated and commonly used prognostic model. Using the Adjuvant! estimates as a gold standard, we calculated how accurate the patient estimates were before and after the visit. We used three novel continuous measures of patient accuracy, the absolute bias, Brier, and Kullback-Leibler scores, and compared them to a categorical measure in terms of sensitivity to intervention effects. We also calculated the sample size required to replicate the primary study using the categorical and continuous measures, as a means of comparing efficiency.
resultsIn this sample, the Kullback-Leibler measure was most sensitive to the intervention effects (p=0.004), followed by Brier and absolute bias (both p=0.011), and finally the categorical measure (0.125). The sample size required to replicate the primary study was 18 for the Kullback-Leibler measure, 23 for absolute bias and Brier, and 37 for the categorical measure.
conclusionsThe continuous measures led to more efficient sample sizes and to rejection of the null hypothesis of no intervention effect. However, the difference in sensitivity of the continuous measures was not statistically significant, and the performance of the categorical measure depends on the researcher's categorical cutoff for accuracy. Continuous measures of patient accuracy may be more sensitive and efficient, while categorical measures may be more clinically relevant. PRACTICE IMPLICATIONS: Researchers and others interested in assessing the accuracy of patient knowledge should weigh the trade-offs between clinical relevance and statistical significance while designing or evaluating risk communication studies.
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