Mark Sherlock1, Raoul C Reulen, Aurora Aragon-Alonso, John Ayuk, Richard N Clayton, Michael C Sheppard, Michael M Hawkins, Andrew S Bates, Paul M Stewart. 1. Endocrinology, Diabetes, and Metabolism (M.S., A.A.-A., J.A., M.C.S., P.M.S.), Division of Medical Sciences, University of Birmingham, Birmingham B15 2TH, United Kingdom; Centre for Childhood Cancer Survivor Studies (R.C.R., M.M.H.), School of Health and Population Sciences, Public Health Building, University of Birmingham, Birmingham B15 2TT, United Kingdom; Department of Endocrinology (J.A.), Queen Elizabeth Hospital Birmingham, Birmingham B152TH, United Kingdom; Department of Postgraduate Medicine (R.N.C.), University of Keele, Hartshill, Stoke-on-Trent ST4 7QB, United Kingdom; Birmingham Heartlands and Solihull National Health Service Trust (A.S.B.), Birmingham B9 5SS, United Kingdom; and Department of Endocrinology and Diabetes (M.S.), Adelaide and Meath Hospitals, Incorporating the National Children's Hospital and Trinity College, Dublin, Ireland.
Abstract
CONTEXT: Acromegaly is associated with reduced life expectancy, which has been reported to be normalized if treatment is successful in controlling GH/IGF-I levels. OBJECTIVE: Most previous studies have invariably used the last available GH/IGF-I, which may be biased as it only assesses exposure at a single point in time. We compared the last available GH/IGF-I analysis to a "time-dependent" and cumulative method, during follow-up to assess risk of mortality in the West Midlands Acromegaly study (n = 501). RESULTS: Using the last available GH, there was a statistically significant increase in mortality comparing groups as low as GH ≤ 1 μg/L vs >1 μg/L (relative risks [RR] 1.8, P = .03). This was not the case when using the "time-dependent method," where only comparisons of GH values of GH ≤5 μg/L vs >5 μg/L were suggestive of being associated with an increased risk of mortality (RR = 1.5, P = .08). When the time-dependent GH method of analysis was used, the RR of mortality at each level was lower and the associated P value was less significant. Irrespective of using the last available or time-dependent method, when IGF-I was divided into levels according to quartile or arbitrary cutoffs, there was no significant increase in mortality with higher levels. CONCLUSIONS: This study emphasizes the potential bias of using the latest available GH/IGF-I levels to predict mortality. Our study again highlights the limitations of IGF-I in predicting mortality.
CONTEXT: Acromegaly is associated with reduced life expectancy, which has been reported to be normalized if treatment is successful in controlling GH/IGF-I levels. OBJECTIVE: Most previous studies have invariably used the last available GH/IGF-I, which may be biased as it only assesses exposure at a single point in time. We compared the last available GH/IGF-I analysis to a "time-dependent" and cumulative method, during follow-up to assess risk of mortality in the West Midlands Acromegaly study (n = 501). RESULTS: Using the last available GH, there was a statistically significant increase in mortality comparing groups as low as GH ≤ 1 μg/L vs >1 μg/L (relative risks [RR] 1.8, P = .03). This was not the case when using the "time-dependent method," where only comparisons of GH values of GH ≤5 μg/L vs >5 μg/L were suggestive of being associated with an increased risk of mortality (RR = 1.5, P = .08). When the time-dependent GH method of analysis was used, the RR of mortality at each level was lower and the associated P value was less significant. Irrespective of using the last available or time-dependent method, when IGF-I was divided into levels according to quartile or arbitrary cutoffs, there was no significant increase in mortality with higher levels. CONCLUSIONS: This study emphasizes the potential bias of using the latest available GH/IGF-I levels to predict mortality. Our study again highlights the limitations of IGF-I in predicting mortality.
Authors: Roberto Salvatori; Murray B Gordon; Whitney W Woodmansee; Adriana G Ioachimescu; Don W Carver; Beloo Mirakhur; David Cox; Mark E Molitch Journal: Pituitary Date: 2017-12 Impact factor: 4.107
Authors: Robert D'Arcy; C Hamish Courtney; Una Graham; Steven Hunter; David R McCance; Karen Mullan Journal: Endocrinol Diabetes Metab Date: 2017-12-27
Authors: Whitney W Woodmansee; Murray B Gordon; Mark E Molitch; Adriana G Ioachimescu; Don W Carver; Beloo Mirakhur; David Cox; Roberto Salvatori Journal: Endocrine Date: 2018-05-16 Impact factor: 3.633