BMJ’s recent paper and editorial on cardiovascular (CVD) risk prediction models are relevant to patients, clinicians and policy makers. We agree that there is a need to validate the risk models, but we would also suggest to broaden the scope for the risk prediction models, in particular with respect to mortality. Typically, these risk prediction models only consider cause-specific, CVD mortality. While this may make sense from a medical point of view, where medications are considered only to be effective with respect to a specific kind of disease, we are less certain that this carries over to the perspective of patients and policy makers. Rather, we find it likely that their interest would lie in when a patient will die, irrespective of cause. Whether a patient will choose to change life style or take a medication, will likely not only depend on their CVD risk, but also their total mortality risk. It would appear natural to supplement CVD risk information with the corresponding expected lowering in all-cause mortality risk, should they choose to start an intervention. But, as far as we know, such information is not available from current models, for example the European Heart-SCORE model1. It is however possible to amend the model based on a competing risk approach to include non-cardiovascular mortality, and further compute the expected gain based on the current evidence of statin effectiveness, as we have documented recently2. Further, such a coherent model allows computing the expected residual lifetime for the patient, both with and without medication, which in turn allows estimation of the expected prolongation of life due to starting medication. There is evidence that lay people are better able to understand intervention benefits when they are presented in terms of prolongation of life than risk reductions. It is still unclear which kind of information is most requested and best understood by patients, but regardless we think that risk prediction models should not only be valid, but preferably also be flexible and consistent. Only then will they be able to provide useful information in a format that is accessible to patients.
References
1. Conroy RM, Pyörälä K, Fitzgerald AP, Sans S, Menotti A, De Backer G, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J. 2003 Jun;24(11):987–1003.
2. Støvring H, Harmsen CG, Wisløff T, Jarbøl DE, Nexøe J, Nielsen JB, et al. A competing risk approach for the European Heart SCORE model based on cause-specific and all-cause mortality. Eur J Prev Cardiolog [Internet]. 2012 Apr 12 [cited 2012 Apr 16]; Available from: http://www.ncbi.nlm.nih.gov/pubmed/22498473
Rapid Response:
Re: Comparing risk prediction models
BMJ’s recent paper and editorial on cardiovascular (CVD) risk prediction models are relevant to patients, clinicians and policy makers. We agree that there is a need to validate the risk models, but we would also suggest to broaden the scope for the risk prediction models, in particular with respect to mortality. Typically, these risk prediction models only consider cause-specific, CVD mortality. While this may make sense from a medical point of view, where medications are considered only to be effective with respect to a specific kind of disease, we are less certain that this carries over to the perspective of patients and policy makers. Rather, we find it likely that their interest would lie in when a patient will die, irrespective of cause. Whether a patient will choose to change life style or take a medication, will likely not only depend on their CVD risk, but also their total mortality risk. It would appear natural to supplement CVD risk information with the corresponding expected lowering in all-cause mortality risk, should they choose to start an intervention. But, as far as we know, such information is not available from current models, for example the European Heart-SCORE model1. It is however possible to amend the model based on a competing risk approach to include non-cardiovascular mortality, and further compute the expected gain based on the current evidence of statin effectiveness, as we have documented recently2. Further, such a coherent model allows computing the expected residual lifetime for the patient, both with and without medication, which in turn allows estimation of the expected prolongation of life due to starting medication. There is evidence that lay people are better able to understand intervention benefits when they are presented in terms of prolongation of life than risk reductions.
It is still unclear which kind of information is most requested and best understood by patients, but regardless we think that risk prediction models should not only be valid, but preferably also be flexible and consistent. Only then will they be able to provide useful information in a format that is accessible to patients.
References
For further enquiries, please contact Henrik Støvring (stovring@biostat.au.dk).
Competing interests: No competing interests