Araştırma Çıktıları

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Author: search.filters.author.Asar, OzgurHas files: Yes

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    External Validation of the DynPG for Kidney Transplant Recipients
    (LIPPINCOTT WILLIAMS \& WILKINS, 2021-01-01) Lenain, Remi; Dantan, Etienne; Giral, Magali; Foucher, Yohann; Asar, Ozgur; Naesens, Maarten; Hazzan, Marc; Fournier, Marie-Cecile
    Background. In kidney transplantation, dynamic prediction of patient and kidney graft survival (DynPG) may help to promote therapeutic alliance by delivering personalized evidence-based information about long-term graft survival for kidney transplant recipients. The objective of the current study is to externally validate the DynPG. Methods. Based on 6 baseline variables, the DynPG can be updated with any new serum creatinine measure available during the follow-up. From an external validation sample of 1637 kidney recipients with a functioning graft at 1-year posttransplantation from 2 European transplantation centers, we assessed the prognostic performance of the DynPG. Results. As one can expect from an external validation sample, differences in several recipient, donor, and transplantation characteristics compared with the learning sample were observed. Patients were mainly transplanted from deceased donors (91.6\% versus 84.8\%
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    Longitudinal change in c-terminal fibroblast growth factor 23 and outcomes in patients with advanced chronic kidney disease
    (BMC, 2021-01-01) Alderson V, Helen; Chinnadurai, Rajkumar; Ibrahim, Sara T.; Asar, Ozgur; Ritchie, James P.; Middleton, Rachel; Larsson, Anders; Diggle, Peter J.; Larsson, Tobias E.; Kalra, Philip A.
    Background Fibroblast growth factor23 (FGF23) is elevated in CKD and has been associated with outcomes such as death, cardiovascular (CV) events and progression to Renal Replacement therapy (RRT). The majority of studies have been unable to account for change in FGF23 over time and those which have demonstrate conflicting results. We performed a survival analysis looking at change in c-terminal FGF23 (cFGF23) over time to assess the relative contribution of cFGF23 to these outcomes. Methods We measured cFGF23 on plasma samples from 388 patients with CKD 3-5 who had serial measurements of cFGF23, with a mean of 4.2 samples per individual. We used linear regression analysis to assess the annual rate of change in cFGF23 and assessed the relationship between time-varying cFGF23 and the outcomes in a cox-regression analysis. Results Across our population, median baseline eGFR was 32.3mls/min/1.73m(2), median baseline cFGF23 was 162 relative units/ml (RU/ml) (IQR 101-244 RU/mL). Over 70 months (IQR 53-97) median follow-up, 76 (19.6\%) patients progressed to RRT, 86 (22.2\%) died, and 52 (13.4\%) suffered a major non-fatal CV event. On multivariate analysis, longitudinal change in cFGF23 was significantly associated with risk for death and progression to RRT but not non-fatal cardiovascular events. Conclusion In our study, increasing cFGF23 was significantly associated with risk for death and RRT.
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    The influence of multiple episodes of acute kidney injury on survival and progression to end stage kidney disease in patients with chronic kidney disease
    (PUBLIC LIBRARY SCIENCE, 2019-01-01) Sykes, Lynne; Asar, Ozgur; Ritchie, James; Raman, Maharajan; Vassallo, Diana; Alderson, Helen V.; O'Donoghue, Donal J.; Green, Darren; Diggle, Peter J.; Kalra, Philip A.
    Background Acute kidney injury (AKI) and chronic kidney disease (CKD) are common syndromes associated with significant morbidity, mortality and cost. The extent to which repeated AKI episodes may cumulatively affect the rate of progression of all-cause CKD has not previously been investigated. In this study, we explored the hypothesis that repeated episodes of AKI increase the rate of renal functional deterioration loss in patients recruited to a large, all-cause CKD cohort. Methods Patients from the Salford Kidney Study (SKS) were considered. Application of KDIGO criteria to all available laboratory measurements of renal function identified episodes of AKI. A competing risks model was specified for four survival events: Stage 1 AKI
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    Robust joint modelling of longitudinal and survival data: Incorporating a time-varying degrees-of-freedom parameter
    (WILEY, 2021-01-01) McFetridge, Lisa M.; Asar, Ozgur; Wallin, Jonas
    Monitoring of individual biomarkers has the potential of explaining the hazard of survival outcomes. In practice, these measurements are intermittently observed and are known to be subject to substantial measurement error. Joint modelling of longitudinal and survival data enables us to associate intermittently measured error-prone biomarkers with risks of survival outcomes and thus plays an important role in the analysis of medical data. Most of the joint models available in the literature have been built on the Gaussian assumption. This makes them sensitive to outliers. In this work, we study a range of robust models to address this issue. Of particular interest is the common occurrence in medical data that outliers can occur with different frequencies over time, for example, in the period when patients adjust to treatment changes. Motivated by the analysis of data gathered from patients with primary biliary cirrhosis, a new model with a time-varying robustness is introduced. Through both the motivating example and a simulation study, this research not only stresses the need to account for longitudinal outliers in the analysis of medical data and in joint modelling research but also highlights the bias and inefficiency from not properly estimating the degrees-of-freedom parameter. This work presents a number of methods in addition to the time-varying robustness, and each method can be fitted using the R package robjm.