Abstract：
To evaluate the impact of 1) updating the existing algorithm to improve case-finding sensitivity and 2) reclassifying the Registry\'s diagnostic status nomenclature into four new categories (\"confirmed ALS,\" \"likely ALS,\" \"undetermined ALS,\" or \"not ALS\") versus the current three (\"definite ALS,\" \"possible ALS,\" or \"not ALS\") to be more inclusive and descriptive of cases and individuals.
A retrospective analysis of Registry data from 2011-2017 was conducted to follow \"possible ALS\" individuals over time to determine what qualifier caused them to convert, if at all and when, to Registry-eligible cases (i.e. \"confirmed ALS\" or \"likely ALS\").
In 2011, 720 individuals were classified by the Registry algorithm as having \"possible ALS\". By 2017, 42% of these had converted to Registry-eligible ALS cases. Approximately 14% of those who were identified solely based on an ALS prescription drug never converted to Registry-eligible cases. This analysis indicates that \"possible ALS\" individuals with a single prescription for an ALS drug should be converted to Registry-eligible cases which would add between 300-500 cases per year on average.
The Registry\'s existing algorithm likely results in the under-ascertainment of ALS cases. However, updating the algorithm with the inclusion of patients having been prescribed ALS-specific drugs, even with a single prescription, leads to improved epidemiologic estimates of ALS in the US. This and future algorithmic updates will help the Registry more accurately depict the true disease burden of ALS in the US.
A retrospective analysis of Registry data from 2011-2017 was conducted to follow \"possible ALS\" individuals over time to determine what qualifier caused them to convert, if at all and when, to Registry-eligible cases (i.e. \"confirmed ALS\" or \"likely ALS\").
In 2011, 720 individuals were classified by the Registry algorithm as having \"possible ALS\". By 2017, 42% of these had converted to Registry-eligible ALS cases. Approximately 14% of those who were identified solely based on an ALS prescription drug never converted to Registry-eligible cases. This analysis indicates that \"possible ALS\" individuals with a single prescription for an ALS drug should be converted to Registry-eligible cases which would add between 300-500 cases per year on average.
The Registry\'s existing algorithm likely results in the under-ascertainment of ALS cases. However, updating the algorithm with the inclusion of patients having been prescribed ALS-specific drugs, even with a single prescription, leads to improved epidemiologic estimates of ALS in the US. This and future algorithmic updates will help the Registry more accurately depict the true disease burden of ALS in the US.
摘要：
目标：评估以下因素的影响：1）更新现有算法以提高病例发现的敏感性，以及2）将注册中心的诊断状态命名法重新分类为四个新类别（“确认的ALS，\"\"可能是ALS,\"\"未确定的ALS,\"或\"非ALS\")与当前三个(\"确定ALS，\"\"可能的ALS,\"或\"非ALS\")对病例和个人更具包容性和描述性。方法：对2011-2017年的注册数据进行回顾性分析，以追踪“可能的ALS”个体，以确定是什么限定符导致他们转换，如果有的话，什么时候，符合登记处资格的病例(即\“确认ALS\”或\“可能ALS\”)。结果：2011年，通过注册表算法将720名个体分类为“可能的ALS”。到2017年，其中42％已转化为符合注册条件的ALS病例。仅根据ALS处方药确定的患者中，约有14％从未转化为符合注册条件的病例。该分析表明，使用单一ALS药物处方的“可能的ALS”个人应转换为符合注册条件的病例，平均每年增加300-500例。结论：注册表的现有算法可能导致ALS病例的确定不足。然而,更新算法，包括已处方ALS特异性药物的患者，即使只有一个处方，改善了美国ALS的流行病学估计。这个和未来的算法更新将有助于注册表更准确地描述美国ALS的真实疾病负担。
