James Rooney1, Alice Vajda2, Mark Heverin2, Marwa Elamin2, Arlene Crampsie2, Russell McLaughlin2, Anthony Staines2, Orla Hardiman2. 1. From the Academic Unit of Neurology (J.R., A.V., M.H., M.E., R.M., O.H.), Trinity Biomedical Sciences Institute, Trinity College, Dublin; School of Geography, Planning & Environmental Policy (A.C.), University College Dublin Belfield, Dublin; School of Nursing and Human Sciences (A.S.), Dublin City University; and Department of Neurology (O.H.), Beaumont Hospital, Ireland. jrooney@rcsi.ie. 2. From the Academic Unit of Neurology (J.R., A.V., M.H., M.E., R.M., O.H.), Trinity Biomedical Sciences Institute, Trinity College, Dublin; School of Geography, Planning & Environmental Policy (A.C.), University College Dublin Belfield, Dublin; School of Nursing and Human Sciences (A.S.), Dublin City University; and Department of Neurology (O.H.), Beaumont Hospital, Ireland.
Abstract
OBJECTIVE: Few spatial cluster analyses of amyotrophic lateral sclerosis (ALS) incidence have been conducted on prospective incident population-based cohorts; we report results of a formal cluster analysis of the Irish ALS cohort from January 1, 1995, to December 31, 2013. METHODS: We identified 1,684 incident cases from the Irish ALS register. Population data from 4 census years were used to calculate age- and sex-standardized expected ALS cases for 3,355 areas. Spatial cluster analysis was performed to identify high-risk clusters using both SaTScan and FleXScan software. Poisson-based, time period-stratified statistics and time-stratified Bayesian smoothed risk mapping were used to audit completeness of case ascertainment of the register. RESULTS: No significant high-risk clusters of incident ALS were identified. However, SaTScan revealed 2 significant areas of lower-than-average ALS risk-one centered on County Kilkenny (relative risk 0.53, p = 0.012) and a smaller area in County Clare (relative risk 0.0, p = 0.029). Audit of case ascertainment did not indicate any failure to detect cases in these areas. CONCLUSIONS: The absence of high-risk ALS clusters in Ireland contrasts with previous studies. Our study has several advantages, notably the use of a long-running prospective ALS register with nationwide case ascertainment. The presence of 2 low-risk areas was unexpected. No obvious ascertainment, demographic, or common environmental factors explain this finding. However, we postulate that historical factors may have led to altered genetic admixture in these regions, possibly contributing to lower rates.
OBJECTIVE: Few spatial cluster analyses of amyotrophic lateral sclerosis (ALS) incidence have been conducted on prospective incident population-based cohorts; we report results of a formal cluster analysis of the Irish ALS cohort from January 1, 1995, to December 31, 2013. METHODS: We identified 1,684 incident cases from the Irish ALS register. Population data from 4 census years were used to calculate age- and sex-standardized expected ALS cases for 3,355 areas. Spatial cluster analysis was performed to identify high-risk clusters using both SaTScan and FleXScan software. Poisson-based, time period-stratified statistics and time-stratified Bayesian smoothed risk mapping were used to audit completeness of case ascertainment of the register. RESULTS: No significant high-risk clusters of incident ALS were identified. However, SaTScan revealed 2 significant areas of lower-than-average ALS risk-one centered on County Kilkenny (relative risk 0.53, p = 0.012) and a smaller area in County Clare (relative risk 0.0, p = 0.029). Audit of case ascertainment did not indicate any failure to detect cases in these areas. CONCLUSIONS: The absence of high-risk ALS clusters in Ireland contrasts with previous studies. Our study has several advantages, notably the use of a long-running prospective ALS register with nationwide case ascertainment. The presence of 2 low-risk areas was unexpected. No obvious ascertainment, demographic, or common environmental factors explain this finding. However, we postulate that historical factors may have led to altered genetic admixture in these regions, possibly contributing to lower rates.
Authors: Angeline S Andrew; Erik P Pioro; Meifang Li; Xun Shi; Jiang Gui; Elijah W Stommel; Tanya H Butt; Daniel Peipert; Patricia Henegan; Maeve Tischbein; Pamela Cazzolli; John Novak; Adam Quick; K Doug Pugar; Komal Sawlani; Bashar Katirji; Todd A Hayes; D Kevin Horton; Paul Mehta; Walter G Bradley Journal: Neuroepidemiology Date: 2021-04-26 Impact factor: 3.282
Authors: Katy Tobin; Mark S Gilthorpe; James Rooney; Mark Heverin; Alice Vajda; Anthony Staines; Orla Hardiman Journal: J Neurol Date: 2016-07-02 Impact factor: 4.849