http://repub.eur.nl/res/aut/2545/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/16571/ 2009-04-01T00:00:00Z Objective: Although the results of aortic valve replacement with different valve prostheses are well documented in terms of survival, the risks of (valve-related) events are less well explored. Methods: We used a dataset of 3934 patients who underwent aortic valve replacement with either a bioprosthesis (73%) or a mechanical prosthesis (27%) between 1982 and 2003 to simulate the outcome of patients after aortic valve replacement with either valve type. With the use of microsimulation, we compared total age and gender-specific life expectancy, event-free life expectancy, reoperation-free life expectancy, lifetime risks of reoperation, and valve-related events for both valve types. Results: The total follow-up was 26,467 patient-years. The mean follow-up was 6.1 years in the biological arm and 8.5 years in the mechanical arm. The mean age at implantation was 70 and 58 years for biological and mechanical prostheses, respectively, and the percentage of concomitant coronary artery bypass grafting was 47% and 28%, respectively. For a 60-year-old man, simulated life expectancy in years for biological versus mechanical prostheses was 11.9 versus 12.2, event-free life expectancy was 9.8 versus 9.3, and reoperation-free life expectancy was 10.5 versus 11.9. Lifetime risk of reoperation was 25% versus 3%. Lifetime risk of bleeding was 12% versus 41%. Conclusion: Even for patients aged 60 years, event-free life expectancy is better with a bioprosthesis. Although the chance of reoperation is higher, the lifetime risk of bleeding is lower compared with a mechanical prosthesis. Comparing lifetime event risks between different types of valve prostheses provides more insight into patient outcome after aortic valve replacement and aids patient selection and counseling. http://repub.eur.nl/res/pub/28925/ 2008-04-01T00:00:00Z Completeness of follow-up is often used as a measure of the quality of follow-up, but the method used to compute it is often not declared. An ideal measure should be based on follow-up years instead of patients. Clark, Altman, and De Stavola proposed such a measure, called "C", which is the percentage of the maximum possible follow-up years, as of a given date, that has actually been accounted for or observed. However, such a measure will underestimate the true completeness, because the denominator (maximum possible follow-up years) does not account for unobserved patient deaths occurring before that date, and therefore, it is realistically unachievable. We propose a modification, C*, of Clark's C, which accounts for the effect of unobserved patient deaths in attenuating the maximum potential follow-up, and thus gives a higher percentage for achieved follow-up completeness. We validated this theoretical improvement by comparing the values of C and C* computed for our long-term coronary artery bypass graft patients to the true completeness, which was obtained by using the National Death Index to complete our missing follow-up data. Using Clark's C, the follow-up completeness was 80.4% and using our C* it is 84.5%, whereas the true follow-up completeness based on National Death Index information was 85.0%. http://repub.eur.nl/res/pub/29042/ 2008-02-01T00:00:00Z http://repub.eur.nl/res/pub/35244/ 2007-09-01T00:00:00Z Objective: Numerous reports have been published documenting the results of aortic valve replacement. It is often not easy to translate these outcomes involving the condition of the valve into the actual consequences for the patient. We previously developed an alternative method to study outcome after aortic valve replacement that allows direct estimation of patient outcome after aortic valve replacement: microsimulation modeling. The goal of this article is to provide insight into microsimulation methodology and to give an overview of the advantages and disadvantages of simulation methods (in particular microsimulation) in comparison with standard methods of outcome analysis. Methods: By using a primary dataset containing 1847 patients and 14,429 patient-years, advantages and disadvantages of standard methods of outcome analysis are discussed, and the potential role of microsimulation is illustrated by means of a step-by-step explanation of building, testing, and using such a model. Results: Total life expectancy, event-free life expectancy, and reoperation-free life expectancy for a 65-year-old male patient were 10.6 years, 9.2 years, and 9.8 years, respectively. Lifetime risk of reoperation due to structural valve deterioration was 13.3%. Conclusions: Microsimulation is capable of providing accurate estimates of age-related life expectancy and lifetime risk of reoperation for patients who underwent aortic valve replacement with the Carpentier-Edwards supra-annular valve. It provides a useful tool to facilitate and optimize the choice for a specific heart valve prosthesis in a particular patient. http://repub.eur.nl/res/pub/35463/ 2007-05-01T00:00:00Z The probability of a type of failure that is not inevitable, but can be precluded by other events such as death, is given by the cumulative incidence function. In cardiac research articles, it has become known as the actual probability, in contrast to the actuarial methods of estimation, usually implemented by the Kaplan-Meier (KM) estimate. Unlike cumulative incidence, KM attempts to predict what the latent failure probability would be if death were eliminated. To do this, the KM method assumes that the risk of dying and the risk of failure are independent. But this assumption is not true for many cardiac applications in which the risks of failure and death are negatively correlated (ie, patients with a higher risk of dying have a lower risk of failure, and patients with a lower risk of death have a higher risk of failure, which is a condition called informative censoring). Recent editorials in two cardiac journals have promoted the use of the KM method (actuarial estimate) for competing risk events (specifically for heart valve performance) and criticized the use of the cumulative incidence (actual) estimates. This report has two aims: to explain the difference between these two estimates and to show why the KM is generally not appropriate. In the process we will rely on alternative representations of the KM estimator (using redistribution to the right and inverse probability weighting) to explain the difference between the two estimates and to show how it may be possible to adjust KM to overcome the informative censoring. http://repub.eur.nl/res/pub/8309/ 2004-01-01T00:00:00Z BACKGROUND: Mechanical valves and bioprostheses are widely used for aortic valve replacement. Though previous randomised studies indicate that there is no important difference in outcome after implantation with either type of valve, knowledge of outcomes after aortic valve replacement is incomplete. OBJECTIVE: To predict age and sex specific outcomes of patients after aortic valve replacement with bileaflet mechanical valves and stented porcine bioprostheses, and to provide evidence based support for the choice of prosthesis. METHODS: Meta-analysis of published results of primary aortic valve replacement with bileaflet mechanical prostheses (nine reports, 4274 patients, and 25,726 patient-years) and stented porcine bioprostheses (13 reports, 9007 patients, and 54,151 patient-years) was used to estimate the annual risks of postoperative valve related events and their outcomes. These estimates were entered into a microsimulation model, which was employed to calculate age and sex specific outcomes after aortic valve replacement. RESULTS: Life expectancy (LE) and event-free life expectancy (EFLE) for a 65 year old man after implantation with a mechanical valve or a bioprosthesis were 10.4 and 10.7 years and 7.7 and 8.4 years, respectively. The lifetime risk of at least one valve related event for a mechanical valve was 48%, and for a bioprosthesis, 44%. For LE and EFLE, the age crossover point between the two valve types was 59 and 60 years, respectively. CONCLUSIONS: Meta-analysis based microsimulation provides insight into the long term outcome after aortic valve replacement and suggests that the currently recommended age threshold for implanting a bioprosthesis could be lowered further.