Development and Validation of a Model to Identify Alzheimer’s Disease and Related Syndromes in Administrative Data

doi:10.2174/1567205018666210416094639

摘要

背景：行政数据用于阿尔茨海默病及相关综合征 (ADRS) 领域，但其识别 ADRS 的性能未知。目标：i) 开发和验证模型以识别法国行政数据 (SNDS) 中的 ADRS 流行病例，ii) 识别与假阴性相关的因素。方法：回顾性队列研究对象年龄≥65 岁，居住在法国西南部，在 2013 年 4 月至 12 月期间就诊于记忆诊所。ADRS 诊断的金标准是记忆诊所专科诊断。记忆诊所的数据与行政数据（药物报销、住院期间的诊断、昂贵的慢性病登记）相匹配。使用多变量逻辑回归模型为 1 年和 3 年期间的行政数据开发了预测模型。通过重新采样估计和校正整体模型性能、辨别力和校准的乐观度。 Youden 指数用于定义 ADRS 阳性并估计敏感性、特异性、阳性预测和阴性概率。使用多变量逻辑回归确定与假阴性相关的因素。结果：研究了 3360 名受试者，其中 52% 被记忆诊所诊断为 ADRS。基于年龄、全因住院、ADRS 登记为慢性病、抗痴呆药物数量、住院期间提及 ADRS 的预测模型具有良好的判别性能（c 统计量：0.814，敏感性：76.0%，特异性：74.2 % 为 2013 年数据）。 419 名假阴性 (24.0%) 较年轻，患有除阿尔茨海默病以外的 ADRS 类型、中等形式的 ADRS、近期诊断以及患有除真阳性以外的其他合并症。结论：管理数据显示了检测 ADRS 的可接受性能。应鼓励外部验证研究。

关键词: 痴呆症、阿尔茨海默病、管理数据、索赔、验证研究、ADRS。

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[1] 
Hallas J, Hellfritzsch M, Rix M, Olesen M, Reilev M, Pottegård A. Odense pharmacoepidemiological database: A review of use and content. Basic Clin Pharmacol Toxicol  2017; 120(5): 419-25.
[http://dx.doi.org/10.1111/bcpt.12764] [PMID: 28164442] 
[2] 
Moulis G, Lapeyre-Mestre M, Palmaro A, Pugnet G, Montastruc J-L, Sailler L. French health insurance databases: What interest for medical research? Rev Med Interne  2015; 36(6): 411-7.
[http://dx.doi.org/10.1016/j.revmed.2014.11.009] [PMID: 25547954] 
[3] 
Nishtala P, Ndukwe H, Chyou T-Y, Salahudeen M, Narayan S. An overview of pharmacoepidemiology in New Zealand: Medical databases, registries and research achievements. N Z Med J  2017; 130(1449): 52-61.
[PMID: 28178730] 
[4] 
Palmaro A, Moulis G, Despas F, Dupouy J, Lapeyre-Mestre M. Overview of drug data within French health insurance databases and implications for pharmacoepidemiological studies. Fundam Clin Pharmacol  2016; 30(6): 616-24.
[http://dx.doi.org/10.1111/fcp.12214] [PMID: 27351637] 
[5] 
Pearson S-A, Pesa N, Langton JM, Drew A, Faedo M, Robertson J. Studies using Australia’s Pharmaceutical Benefits Scheme data for pharmacoepidemiological research: a systematic review of the published literature (1987-2013). Pharmacoepidemiol Drug Saf  2015; 24(5): 447-55.
[http://dx.doi.org/10.1002/pds.3756] [PMID: 25833702] 
[6] 
Wettermark B, Zoëga H, Furu K, et al. The Nordic prescription databases as a resource for pharmacoepidemiological research--a literature review. Pharmacoepidemiol Drug Saf  2013; 22(7): 691-9.
[http://dx.doi.org/10.1002/pds.3457] [PMID: 23703712] 
[7] 
Chen H, Kwong JC, Copes R, et al. Living near major roads and the incidence of dementia, Parkinson’s disease, and multiple sclerosis: a population-based cohort study. Lancet  2017; 389(10070): 718-26.
[http://dx.doi.org/10.1016/S0140-6736(16)32399-6] [PMID: 28063597] 
[8] 
Zissimopoulos JM, Barthold D, Brinton RD, Joyce G. Sex and race differences in the association between statin use and the incidence of Alzheimer disease. JAMA Neurol  2017; 74(2): 225-32.
[http://dx.doi.org/10.1001/jamaneurol.2016.3783] 
[9] 
Goodman RA, Lochner KA, Thambisetty M, Wingo TS, Posner SF, Ling SM. Prevalence of dementia subtypes in United States Medicare fee-for-service beneficiaries, 2011-2013. Alzheimers Dement  2017; 13(1): 28-37.
[http://dx.doi.org/10.1016/j.jalz.2016.04.002] [PMID: 27172148] 
[10] 
Wexler NS, Collett L, Wexler AR, et al. Incidence of adult Huntington’s disease in the UK: A UK-based primary care study and a systematic review. BMJ Open  2016; 6(2): e009070.
[http://dx.doi.org/10.1136/bmjopen-2015-009070] [PMID: 26908513] 
[11] 
Hunter CA, Kirson NY, Desai U, Cummings AKG, Faries DE, Birnbaum HG. Medical costs of Alzheimer’s disease misdiagnosis among US Medicare beneficiaries. Alzheimers Dement  2015; 11(8): 887-95.
[http://dx.doi.org/10.1016/j.jalz.2015.06.1889] [PMID: 26206626] 
[12] 
Brüggenjürgen B, Andersohn F, Ezzat N, Lacey L, Willich S. Medical management, costs, and consequences of Alzheimer’s disease in Germany: An analysis of health claims data. J Med Econ  2015; 18(6): 466-73.
[http://dx.doi.org/10.3111/13696998.2015.1014090] [PMID: 25692902] 
[13] 
Gilden DM, Kubisiak JM, Sarsour K, Hunter CA. Diagnostic pathways to Alzheimer Disease: Costs incurred in a medicare population. Alzheimer Dis Assoc Disord  2015; 29(4): 330-7.
[http://dx.doi.org/10.1097/WAD.0000000000000070] [PMID: 25635340] 
[14] 
Doblhammer G, Fink A, Fritze T. Short-term trends in dementia prevalence in Germany between the years 2007 and 2009. Alzheimers Dement  2015; 11(3): 291-9.
[http://dx.doi.org/10.1016/j.jalz.2014.02.006] [PMID: 25301681] 
[15] 
Princic N, Gregory C, Willson T, et al. Development and validation of an algorithm to identify patients with multiple myeloma using administrative claims data. Front Oncol  2016; 6: 224.
[http://dx.doi.org/10.3389/fonc.2016.00224] [PMID: 27833899] 
[16] 
Moulis G, Germain J, Adoue D, et al. Validation of immune thrombocytopenia diagnosis code in the French hospital electronic database. Eur J Intern Med  2016; 32: e21-2.
[http://dx.doi.org/10.1016/j.ejim.2016.02.021] [PMID: 27012473] 
[17] 
Bowker SL, Savu A, Lam NK, Johnson JA, Kaul P. Validation of administrative data case definitions for gestational diabetes mellitus. Diabet Med  2017; 34(1): 51-5.
[http://dx.doi.org/10.1111/dme.13030] [PMID: 26555571] 
[18] 
Funch D, Holick C, Velentgas P, et al. Algorithms for identification of Guillain-Barré Syndrome among adolescents in claims databases. Vaccine  2013; 31(16): 2075-9.
[http://dx.doi.org/10.1016/j.vaccine.2013.02.009] [PMID: 23474311] 
[19] 
Quantin C, Benzenine E, Hägi M, et al. Estimation of national colorectal-cancer incidence using claims databases. J Cancer Epidemiol  2012; 2012: 298369.
[http://dx.doi.org/10.1155/2012/298369] [PMID: 22792103] 
[20] 
Carnahan RM. Mini-Sentinel’s systematic reviews of validated methods for identifying health outcomes using administrative data: summary of findings and suggestions for future research. Pharmacoepidemiol Drug Saf  2012; 21(1): 90-9.
[http://dx.doi.org/10.1002/pds.2318] [PMID: 22262597] 
[21] 
Moisan F, Gourlet V, Mazurie J-L, et al. Prediction model of Parkinson’s disease based on antiparkinsonian drug claims. Am J Epidemiol  2011; 174(3): 354-63.
[http://dx.doi.org/10.1093/aje/kwr081] [PMID: 21606234] 
[22] 
Gershon AS, Wang C, Guan J, Vasilevska-Ristovska J, Cicutto L, To T. Identifying patients with physician-diagnosed asthma in health administrative databases. Can Respir J  2009; 16(6): 183-8.
[http://dx.doi.org/10.1155/2009/963098] [PMID: 20011725] 
[23] 
Hux JE, Ivis F, Flintoft V, Bica A. Diabetes in Ontario: Determination of prevalence and incidence using a validated administrative data algorithm. Diabetes Care  2002; 25(3): 512-6.
[http://dx.doi.org/10.2337/diacare.25.3.512] [PMID: 11874939] 
[24] 
Bezin J, Girodet P-O, Rambelomanana S, et al. Choice of ICD-10 codes for the identification of acute coronary syndrome in the French hospitalization database. Fundam Clin Pharmacol  2015; 29(6): 586-91.
[http://dx.doi.org/10.1111/fcp.12143] [PMID: 26301735] 
[25] 
Palmaro A, Gauthier M, Conte C, Grosclaude P, Despas F, Lapeyre-Mestre M. Identifying multiple myeloma patients using data from the French health insurance databases: Validation using a cancer registry. Medicine (Baltimore)  2017; 96(12): e6189.
[http://dx.doi.org/10.1097/MD.0000000000006189] [PMID: 28328805] 
[26] 
Sahli L, Lapeyre-Mestre M, Derumeaux H, Moulis G. Positive predictive values of selected hospital discharge diagnoses to identify infections responsible for hospitalization in the French national hospital database. Pharmacoepidemiol Drug Saf  2016; 25(7): 785-9.
[http://dx.doi.org/10.1002/pds.4006] [PMID: 27125251] 
[27] 
Zhu CW, Ornstein KA, Cosentino S, Gu Y, Andrews H, Stern Y. Misidentification of dementia in medicare claims and related costs. J Am Geriatr Soc  2019; 67(2): 269-76.
[http://dx.doi.org/10.1111/jgs.15638] [PMID: 30315744] 
[28] 
Tuppin P, de Roquefeuil L, Weill A, Ricordeau P, Merlière Y. French national health insurance information system and the permanent beneficiaries sample. Rev Epidemiol Sante Publique  2010; 58(4): 286-90.
[http://dx.doi.org/10.1016/j.respe.2010.04.005] [PMID: 20598822] 
[29] 
Croisile B, Tedesco A, Gavant S, Minssieux-Catrix G, Mollion H. The specialist-referred patients represent 42% of the activity of an academic memory clinic. Presse Medicale Paris Fr  1983; 41(7-8): e391-396.
[30] 
Anthony S, Pradier C, Chevrier R, Festraëts J, Tifratene K, Robert P. The French National Alzheimer database: A fast growing database for researchers and clinicians. Dement Geriatr Cogn Disord  2014; 38(5-6): 271-80.
[http://dx.doi.org/10.1159/000360281] [PMID: 24994018] 
[31] 
Pradier C, Sakarovitch C, Le Duff F, et al. The mini mental state examination at the time of Alzheimer’s disease and related disorders diagnosis, according to age, education, gender and place of residence: A cross-sectional study among the French National Alzheimer database. PLoS One  2014; 9(8): e103630.
[http://dx.doi.org/10.1371/journal.pone.0103630] [PMID: 25093735] 
[32] 
Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res  1975; 12(3): 189-98.
[http://dx.doi.org/10.1016/0022-3956(75)90026-6] [PMID: 1202204] 
[33] 
Grober E, Buschke H, Crystal H, Bang S, Dresner R. Screening for dementia by memory testing. Neurology  1988; 38(6): 900-3.
[http://dx.doi.org/10.1212/WNL.38.6.900] [PMID: 3368071] 
[34] 
Kasai M, Meguro K, Hashimoto R, Ishizaki J, Yamadori A, Mori E. Non-verbal learning is impaired in very mild Alzheimer’s disease (CDR 0.5): Normative data from the learning version of the Rey-Osterrieth Complex Figure Test. Psychiatry Clin Neurosci  2006; 60(2): 139-46.
[http://dx.doi.org/10.1111/j.1440-1819.2006.01478.x] [PMID: 16594936] 
[35] 
Deloche G, Hannequin D. Test de dénomination orale d’images (DO80) Paris: ECPA .  1997.
[36] 
Cardebat D, Doyon B, Puel M, Goulet P, Joanette Y. Formal and semantic lexical evocation in normal subjects. Performance and dynamics of production as a function of sex, age and educational level. Acta Neurol Belg  1990; 90(4): 207-17.
[PMID: 2124031] 
[37] 
Cahn DA, Salmon DP, Monsch AU, et al. Screening for dementia of the alzheimer type in the community: The utility of the Clock Drawing Test. Arch Clin Neuropsychol  1996; 11(6): 529-39.
[http://dx.doi.org/10.1093/arclin/11.6.529] [PMID: 14588458] 
[38] 
Reitan R. Validity of the trail making test as an indicator of organic brain damage. Percept Mot Skills  1958; (8): 271-6.
[http://dx.doi.org/10.2466/pms.1958.8.3.271] 
[39] 
Lawton MP, Brody EM. Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontologist  1969; 9(3): 179-86.
[http://dx.doi.org/10.1093/geront/9.3_Part_1.179] [PMID: 5349366] 
[40] 
Le Duff F, Develay AE, Quetel J, et al. The 2008-2012 French Alzheimer plan: Description of the national Alzheimer information system. J Alzheimers Dis  2012; 29(4): 891-902.
[http://dx.doi.org/10.3233/JAD-2012-111943] [PMID: 22366771] 
[41] 
Rey G, Jougla E, Fouillet A, Hémon D. Ecological association between a deprivation index and mortality in France over the period 1997 - 2001: Variations with spatial scale, degree of urbanicity, age, gender and cause of death. BMC Public Health  2009; 9: 33.
[http://dx.doi.org/10.1186/1471-2458-9-33] [PMID: 19161613] 
[42] 
Harrell FE Jr, Lee KL, Mark DB. Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med  1996; 15(4): 361-87.
[http://dx.doi.org/10.1002/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4] [PMID: 8668867] 
[43] 
Newcomer R, Clay T, Luxenberg JS, Miller RH. Misclassification and selection bias when identifying Alzheimer’s disease solely from Medicare claims records. J Am Geriatr Soc  1999; 47(2): 215-9.
[http://dx.doi.org/10.1111/j.1532-5415.1999.tb04580.x] [PMID: 9988293] 
[44] 
Taylor DH Jr, Fillenbaum GG, Ezell ME. The accuracy of medicare claims data in identifying Alzheimer’s disease. J Clin Epidemiol  2002; 55(9): 929-37.
[http://dx.doi.org/10.1016/S0895-4356(02)00452-3] [PMID: 12393082] 
[45] 
Williams SE, Carnahan R, McPheeters ML. A systematic review of validated methods for identifying uveitis using administrative or claims data. Vaccine  2013; 31(10): K88-97.
[http://dx.doi.org/10.1016/j.vaccine.2013.03.077] [PMID: 24331079] 
[46] 
Chung CP, Rohan P, Krishnaswami S, McPheeters ML. A systematic review of validated methods for identifying patients with rheumatoid arthritis using administrative or claims data. Vaccine  2013; 31(Suppl. 10): K41-61.
[http://dx.doi.org/10.1016/j.vaccine.2013.03.075] [PMID: 24331074] 
[47] 
Sharifi M, Krishanswami S, McPheeters ML. A systematic review of validated methods to capture acute bronchospasm using administrative or claims data. Vaccine  2013; 31(10): K12-20.
[http://dx.doi.org/10.1016/j.vaccine.2013.06.091] [PMID: 24331069] 
[48] 
Hudson M, Avina-Zubieta A, Lacaille D, Bernatsky S, Lix L, Jean S. The validity of administrative data to identify hip fractures is high--a systematic review. J Clin Epidemiol  2013; 66(3): 278-85.
[http://dx.doi.org/10.1016/j.jclinepi.2012.10.004] [PMID: 23347851] 
[49] 
Townsend L, Walkup JT, Crystal S, Olfson M. A systematic review of validated methods for identifying depression using administrative data. Pharmacoepidemiol Drug Saf  2012; 21(1): 163-73.
[http://dx.doi.org/10.1002/pds.2310] [PMID: 22262603] 
[50] 
Andrade SE, Harrold LR, Tjia J, et al. A systematic review of validated methods for identifying cerebrovascular accident or transient ischemic attack using administrative data. Pharmacoepidemiol Drug Saf  2012; 21(1): 100-28.
[http://dx.doi.org/10.1002/pds.2312] [PMID: 22262598] 
[51] 
Lin P-J, Kaufer DI, Maciejewski ML, Ganguly R, Paul JE, Biddle AK. An examination of Alzheimer’s disease case definitions using Medicare claims and survey data. Alzheimers Dement  2010; 6(4): 334-41.
[http://dx.doi.org/10.1016/j.jalz.2009.09.001] [PMID: 20434960] 
[52] 
Pressley JC, Trott C, Tang M, Durkin M, Stern Y. Dementia in community-dwelling elderly patients: A comparison of survey data, medicare claims, cognitive screening, reported symptoms, and activity limitations. J Clin Epidemiol  2003; 56(9): 896-905.
[http://dx.doi.org/10.1016/S0895-4356(03)00133-1] [PMID: 14505776] 
[53] 
Phung TKT, Andersen BB, Høgh P, Kessing LV, Mortensen PB, Waldemar G. Validity of dementia diagnoses in the Danish hospital registers. Dement Geriatr Cogn Disord  2007; 24(3): 220-8.
[http://dx.doi.org/10.1159/000107084] [PMID: 17690555] 
[54] 
Solomon A, Ngandu T, Soininen H, Hallikainen MM, Kivipelto M, Laatikainen T. Validity of dementia and Alzheimer’s disease diagnoses in Finnish national registers. Alzheimers Dement  2014; 10(3): 303-9.
[http://dx.doi.org/10.1016/j.jalz.2013.03.004] [PMID: 23849592] 
[55] 
Rizzuto D, Feldman AL, Karlsson IK, Dahl Aslan AK, Gatz M, Pedersen NL. Detection of dementia cases in two swedish health registers: A validation study. J Alzheimers Dis  2018; 61(4): 1301-10.
[http://dx.doi.org/10.3233/JAD-170572] [PMID: 29376854] 
[56] 
Taylor DH Jr, Østbye T, Langa KM, Weir D, Plassman BL. The accuracy of Medicare claims as an epidemiological tool: The case of dementia revisited. J Alzheimers Dis  2009; 17(4): 807-15.
[http://dx.doi.org/10.3233/JAD-2009-1099] [PMID: 19542620] 
[57] 
Bharmal MF, Weiner M, Sands LP, Xu H, Craig BA, Thomas J III. Impact of patient selection criteria on prevalence estimates and prevalence of diagnosed dementia in a Medicaid population. Alzheimer Dis Assoc Disord  2007; 21(2): 92-100.
[http://dx.doi.org/10.1097/WAD.0b013e31805c0835] [PMID: 17545733] 
[58] 
Pippenger M, Holloway RG, Vickrey BG. Neurologists’ use of ICD-9CM codes for dementia. Neurology  2001; 56(9): 1206-9.
[http://dx.doi.org/10.1212/WNL.56.9.1206] [PMID: 11342688] 
[59] 
van de Vorst IE, Vaartjes I, Sinnecker LF, Beks LJM, Bots ML, Koek HL. The validity of national hospital discharge register data on dementia: A comparative analysis using clinical data from a university medical centre. Neth J Med  2015; 73(2): 69-75.
[PMID: 25753071] 
[60] 
Quan H, Li B, Saunders LD, et al. Assessing validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions in a unique dually coded database. Health Serv Res  2008; 43(4): 1424-41.
[http://dx.doi.org/10.1111/j.1475-6773.2007.00822.x] [PMID: 18756617] 
[61] 
Brown A, Kirichek O, Balkwill A, et al. Comparison of dementia recorded in routinely collected hospital admission data in England with dementia recorded in primary care. Emerg Themes Epidemiol  2016; 13: 11.
[http://dx.doi.org/10.1186/s12982-016-0053-z] [PMID: 27800007] 
[62] 
Jaakkimainen RL, Bronskill SE, Tierney MC, Herrmann N, Green D, Young J, et al. Identification of physician-diagnosed Alzheimer’s disease and related dementias in population-based administrative data: A validation study using family physicians’ electronic medical records. J Alzheimers Dis JAD  2016; 54(1): 337-49.
[63] 
Wilkinson T, Schnier C, Bush K, et al. Identifying dementia outcomes in UK Biobank: a validation study of primary care, hospital admissions and mortality data. Eur J Epidemiol  2019; 34(6): 557-65.
[http://dx.doi.org/10.1007/s10654-019-00499-1] [PMID: 30806901] 
[64] 
Chen Y, Tysinger B, Crimmins E, Zissimopoulos JM. Analysis of dementia in the US population using Medicare claims: Insights from linked survey and administrative claims data. Alzheimers Dement (N Y)  2019; 5: 197-207.
[http://dx.doi.org/10.1016/j.trci.2019.04.003] [PMID: 31198838] 
[65] 
Sommerlad A, Perera G, Singh-Manoux A, Lewis G, Stewart R, Livingston G. Accuracy of general hospital dementia diagnoses in England: Sensitivity, specificity, and predictors of diagnostic accuracy 2008-2016. Alzheimers Dement  2018; 14(7): 933-43.
[http://dx.doi.org/10.1016/j.jalz.2018.02.012] [PMID: 29703698] 
[66] 
St Germaine-Smith C, Metcalfe A, Pringsheim T, et al. Recommendations for optimal ICD codes to study neurologic conditions: A systematic review. Neurology  2012; 79(10): 1049-55.
[http://dx.doi.org/10.1212/WNL.0b013e3182684707] [PMID: 22914826] 
[67] 
Wilkinson T, Ly A, Schnier C, et al. Identifying dementia cases with routinely collected health data: A systematic review. Alzheimers Dement  2018; 14(8): 1038-51.
[http://dx.doi.org/10.1016/j.jalz.2018.02.016] [PMID: 29621480] 
[68] 
Ponjoan A, Garre-Olmo J, Blanch J, et al. How well can electronic health records from primary care identify Alzheimer’s disease cases? Clin Epidemiol  2019; 11: 509-18.
[http://dx.doi.org/10.2147/CLEP.S206770] [PMID: 31456649] 
[69] 
Fowler NR, Chen Y-F, Thurton CA, Men A, Rodriguez EG, Donohue JM. The impact of Medicare prescription drug coverage on the use of antidementia drugs. BMC Geriatr  2013; 13: 37.
[http://dx.doi.org/10.1186/1471-2318-13-37] [PMID: 23621892] 

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DOI https://dx.doi.org/10.2174/1567205018666210416094639	Print ISSN 1567-2050
Publisher Name Bentham Science Publisher	Online ISSN 1875-5828

当代阿耳茨海默病研究

开发和验证管理数据中识别阿尔茨海默病和相关综合征的模型

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当代阿耳茨海默病研究

开发和验证管理数据中识别阿尔茨海默病和相关综合征的模型

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