Heesen, C., Gaissmaier, W., Nguyen, F., Stellmann, J.-P., Kasper, J., Köpke, S., Lederer, C., Neuhaus, A., & Daumer, M. (2013).  Prognostic risk estimates of patients with Multiple Sclerosis and their physicians: Comparison to an online analytical risk counseling tool. PLoS ONE8(5):e59042

Abstract:  Prognostic counseling in multiple sclerosis (MS) is difficult because of the high variability of disease progression. Simultaneously, patients and physicians are increasingly confronted with making treatment decisions at an early stage, which requires taking individual prognoses into account to strike a good balance between benefits and harms of treatments. It is therefore important to understand how patients and physicians estimate prognostic risk, and whether and how these estimates can be improved. An online analytical processing (OLAP) tool based on pooled data from placebo cohorts of clinical trials offers short-term prognostic estimates that can be used for individual risk counseling.
Objective. The aim of this study was to clarify if personalized prognostic information as presented by the OLAP tool is considered useful and meaningful by patients. Furthermore, we used the OLAP tool to evaluate patients' and physicians' risk estimates. Within this evaluation process we assessed short-time prognostic risk estimates of patients with MS (final n = 110) and their physicians (n = 6) and compared them with the estimates of OLAP.
Results. Patients rated the OLAP tool as understandable and acceptable, but to be only of moderate interest. It turned out that patients, physicians, and the OLAP tool ranked patients similarly regarding their risk of disease progression. Both patients' and physicians' estimates correlated most strongly with those disease covariates that the OLAP tool's estimates also correlated with most strongly. Exposure to the OLAP tool did not change patients' risk estimates.
Conclusion. While the OLAP tool was rated understandable and acceptable, it was only of modest interest and did not change patients' prognostic estimates. The results suggest, however, that patients had some idea regarding their prognosis and which factors were most important in this regard. Future work with OLAP should assess long-term prognostic estimates and clarify its usefulness for patients and physicians facing treatment decisions.

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