簡易檢索 / 詳目顯示

回結果列表
研究生： 賴嘉鎮
Lai, Chia-Cheng
論文名稱： 運用處方對稱分析法建立藥物不良反應偵測模式-以抗精神病藥物為例
Signal Detection of Adverse Drug Reactions by Prescription Sequence Symmetry Analysis (PSSA) - Using Antipsychotic Drugs as Example
指導教授： 高雅慧
Yang, Yea-Huei Kao
學位類別： 博士
Doctor
系所名稱： 醫學院 - 臨床藥學與藥物科技研究所
Institute of Clinical Pharmacy and Pharmaceutical sciences
論文出版年： 2015
畢業學年度： 103
語文別： 英文
論文頁數： 83
中文關鍵詞： 處方對稱分析法 、藥物不良反應 、風險偵測 、抗精神病藥物
外文關鍵詞： Prescription Sequence Symmetry Analysis, Signal Detection, Adverse Drug Reactions, Antipsychotics
相關次數： 點閱：134  下載：0 
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報

    • 研究背景
    由於臨床試驗的主要目的為證實藥品之有效性，所能提供的藥品安全資訊有限，仍有賴藥品上市後持續監測其風險，如不良反應自動通報系統、藥品上市後風險控管計畫等。而隨著健康與醫療電子資料庫發展，歐美各國得以更精確估算藥品不良事件的發生率，以做為風險控管之實證依據。我國目前也有許多應用健保資料的研究評估用藥安全，然而大多數仍是在既有假說之下進行相關性檢定，以印證臨床已知現象，至於風險訊號偵測與產生假說的研究仍相當有限。一般常用的相關性研究方法如：cohort study，執行時必須處理多量資料與變項，以致分析效率降低；即便對風險的評估準確性高且證據力強，但無法在短時間內或常規性地篩選出風險訊息，作為偵測工具並不合適。相對地，處方對稱分析法(PSSA)利用自身配對(self-control)與案例式(case-only based)之特性，具有高效率、高靈敏度、低研究偏差、與資料保護等優點，已被許多先進國家作視為藥品上市後監測之研究工具之一，應值得發展成我國藥品不良反應訊號偵測之模式。
    研究目的
    以抗精神病藥品為主題，運用PSSA方法建立我國藥品不良反應訊號偵測模式。
    研究方法
    以健保資料庫篩選出2003年至2011年精神分裂症世代族群，利用PSSA測量指標藥物(index drug) 與標記藥物(marker drug)之時序對稱性趨勢，建立抗精神病藥品藥物與不良反應之間的相關性。第一部分以抗精神病藥品與椎體外副作用為主題，建立PSSA之方法並進行確效，找出最適合運用之模式。第二部分為實際執行藥品不良反應訊號偵測，以sulpiride為目標藥品，採用PSSA建立sulpiride相關不良反應之本土數據；而第三部分將延續第二部分之成果，以尚未被證實的不良反應(unrecognized adverse event)為目標，運用其他相關性研究方法，如cohort study評估風險訊號。統計方法以計算序列比(sequence ratio，SR)作為PSSA評估藥物相關性的方式；而Cox-proportional hazard model進行分析。
    研究結果
    第一部分以抗精神病藥品與椎體外副作用為主題進行評估後發現PSSA可以再現meta-analysis之結果，有一定程度之精確性，原因可能來自於PSSA將案例自己本身視為控制組，可以有效的減低選擇偏差與干擾因子。第二部分實際執行PSSA即將抗精神病藥品sulpiride與所有其他處方(依照WHO之ATC 前5碼分類後)配對後進行風險訊號偵測。發現sulpiride可能與某些藥物有關，有潛在的一些如口腔潰瘍、皮膚搔癢、肌肉骨骼或關節疼痛、便秘和肺炎等副作用相關。第三部分利用retrospective cohort study design，發現比起haloperidol，olanzapine、quetiapine、risperidone、amisulpride 及sulpiride可能有較高的口腔潰瘍風險。
    結論
    建立風險偵測工具與藥物安全性資料與國人用藥品質提升的重要步驟，通過本研究三個階段並使用抗精神病藥物為例，除了得到重要的本土臨床資料，也證明了PSSA是信號檢測準確，再現性高的有效工具。利用PSSA這種效率較高及選擇偏差較少的工具，預期可快速且正確地偵測藥品風險訊號，使研究者或是國家政策裁決者可以對特定的訊號作進一步的評估，確立風險訊息正確性與相對風險程度，提升國人用藥安全。

    Background: The strengths of prescription sequence symmetry analysis (PSSA) characterized with case-only based and within individual comparisons include efficient computation, high sensitivity, less selection bias and confounding factors, and least requirement in data privacy. With these advantages, PSSA could be an excellent tool for signal detection in Taiwan post-market surveillance (PMS) system.
    Objective: This study aimed to use antipsychotic drugs as example to establish signal detection of adverse drug reactions by PSSA. The study was divided into three parts: establishments and validation of PSSA by testing the association between antipsychotics and extrapyramidal symptom (EPS); the application of PSSA on detecting safety signal of sulpiride; and we evaluated the safety signal (antipsychotics and oral ulcerations) obtained from the second part by using retrospectively cohort study design and to test the robustness of the results.
    Results: We tested extrapyramidal syndrome and the results were consistent with a meta-analysis of 150 clinical studies, which confirmed the validity of using PSSA to evaluate therapeutic risk of antipsychotics. When applying PSSA to detect the safety signal, we found sulpiride to be associated with an increased risk the use of additional drugs for managing adverse effects, including stomatological, dermatological, and musculoskeletal or joint side effects, constipation, and pneumonia. And one of the aforementioned safety signal, stomatological adverse events, were further confirmed by using retrospective cohort design that we found olanzapine, quetiapine, risperidone, amisulpride and sulpiride posed a higher risk of oral ulcerations compared with haloperidol who newly initiated antipsychotic therapy.
    Conclusion: By using antipsychotics as an example, we demonstrated that PSSA is an efficient tool for signal detection with accurate and reproducible results. The PSSA could be routinely executed in Taiwan PMS system.

    摘要 I ABSTRACT III FUNDING SOURCE IV CHAPTER ONE - OVERVIEW 1 CHAPTER TWO - BACKGROUND 3 Section 1 - Introduction of Prescription Sequence Symmetry Analysis 3 Section 2 - Theoretical and Conceptual Framework of PSSA 5 Section 3 - Purpose of PSSA and Types of Indicators 6 Section 4 - Adverse Events of and Successful Treatment of Antipsychotics 7 Section 5 - Effectiveness and Safety of Sulpiride 8 Section 6 - Antipsychotics and Oral Ulcerations 9 CHAPTER THREE - METHOD 11 Section 1 - Data Source 11 Section 2 - Ethics Statement 12 Section 3 - Objectives and Study Design 13 Part 1 - Prescription Sequence Symmetry Analysis Establishment and Validation (PSSA Validation) 13 Part 2 - Prescription Sequence Symmetry Analysis Applications (PSSA Application) 18 Part 3 - Evaluation of the Signal Detected by Prescription Sequence Symmetry Analysis (Signal Evaluation) 21 Section 4 - Statistical Analysis of Prescription Sequence Symmetry Analysis 24 CHAPTER FOUR - RESULTS 27 Part 1 - PSSA Validation 27 Part 2 - PSSA Application 29 Part 3 - Signal Evaluation 31 CHAPTER FIVE - DISCUSSION & CONCLUSION 33 Part 1 - PSSA Validation 33 Part 2 - PSSA Application 35 Part 3 - Signal Evaluation 40 CHAPTER SIX - SUMMARY OF PRESCRIPTION SEQUENCE SYMMETRY ANALYSIS 45 CHAPTER SEVEN - OVERALL CONCLUSION 55 REFERENCES 57 TABLES AND FIGURES 65 Table 1. Study using sequence symmetry analysis from current publication before May 2015 65 Table 2. Exploratory analyses on possible adverse events of sulpiride by ATC groups 67 Table 3. Baseline Characteristics of All Selected Patient in the Taiwan National Health Insurance Research Database 69 Table 4. Evaluation of risk of oral ulceration by cox regression hazard model 72 Figure 1. Flowchart of study cohort selection 73 Figure 2. Hypothesized association charts between index and marker drugs 74 Figure 3. The distribution of age of patients by antipsychotic drugs 75 Figure 4. Confirmatory analyses on adverse events of sulpiride and other antipsychotics 76 Figure 5. Evaluation of risk of secondary outcome by cox regression hazard model 77 Appendix Table 1. Hypothyroidism Association After Antiepileptic Drug Exposure 78 Appendix Table 2. Sensitivity analysis 79 Appendix Figure 1. Theoretical and conceptual framework of PSSA 80 Appendix Figure 2. Null-effect sequence ratio by average versus individual probability of the drugs sequence 81 Appendix Figure 3. Distribution of the frequency of AED initiation before and after thyroxine initiation 82

    Hall GC, Sauer B, Bourke A, Brown JS, Reynolds MW, LoCasale R. Guidelines for good database selection and use in pharmacoepidemiology research. Pharmacoepidemiol Drug Saf 2012;21:1-10.
    2. Matsushita Y, Kuroda Y, Niwa S, Sonehara S, Hamada C, Yoshimura I. Criteria revision and performance comparison of three methods of signal detection applied to the spontaneous reporting database of a pharmaceutical manufacturer. Drug Saf 2007;30:715-26.
    3. Wahab IA, Pratt NL, Wiese MD, Kalisch LM, Roughead EE. The validity of sequence symmetry analysis (SSA) for adverse drug reaction signal detection. Pharmacoepidemiol Drug Saf 2013;22:496-502.
    4. Wahab IA, Pratt NL, Kalisch LM, Roughead EE. Comparing time to adverse drug reaction signals in a spontaneous reporting database and a claims database: a case study of rofecoxib-induced myocardial infarction and rosiglitazone-induced heart failure signals in Australia. Drug Saf 2014;37:53-64.
    5. Hallas J. Evidence of depression provoked by cardiovascular medication: a prescription sequence symmetry analysis. Epidemiology 1996;7:478-84.
    6. I AW, Pratt NL, Kalisch LM, Roughead EE. Comparing time to adverse drug reaction signals in a spontaneous reporting database and a claims database: a case study of rofecoxib-induced myocardial infarction and rosiglitazone-induced heart failure signals in Australia. Drug Saf 2014;37:53-64.
    7. Maclure M, Mittleman MA. Should we use a case-crossover design? Annu Rev Public Health 2000;21:193-221.
    8. Maclure M. The case-crossover design: a method for studying transient effects on the risk of acute events. Am J Epidemiol 1991;133:144-53.
    9. Maclure M, Mittleman MA. Case-crossover designs compared with dynamic follow-up designs. Epidemiology 2008;19:176-8.
    10. Caughey GE, Roughead EE, Pratt N, Shakib S, Vitry AI, Gilbert AL. Increased risk of hip fracture in the elderly associated with prochlorperazine: is a prescribing cascade contributing? Pharmacoepidemiol Drug Saf 2010;19:977-82.
    11. Garrison SR, Dormuth CR, Morrow RL, Carney GA, Khan KM. Nocturnal leg cramps and prescription use that precedes them: a sequence symmetry analysis. Arch Intern Med 2012;172:120-6.
    12. Pratt NL, Ilomaki J, Raymond C, Roughead EE. The performance of sequence symmetry analysis as a tool for post-market surveillance of newly marketed medicines: a simulation study. BMC Med Res Methodol 2014;14:66.
    13. Pratt N, Chan EW, Choi NK, et al. Prescription sequence symmetry analysis: assessing risk, temporality, and consistency for adverse drug reactions across datasets in five countries. Pharmacoepidemiol Drug Saf 2015.
    14. Lai EC, Yang YH, Lin SJ, Hsieh CY. Use of antiepileptic drugs and risk of hypothyroidism. Pharmacoepidemiol Drug Saf 2013;22:1071-9.
    15. Cher DJ. Myocardial infarction and acute cholecystitis: an application of sequence symmetry analysis. Epidemiology 2000;11:446-9.
    16. Cole JA, Farraye FA, Cabral HJ, Zhang Y, Rothman KJ. Irritable bowel syndrome and hysterectomy: a sequence symmetry analysis. Epidemiology 2007;18:837-8.
    17. Lai EC, Hsieh CY, Kao Yang YH, Lin SJ. Detecting potential adverse reactions of sulpiride in schizophrenic patients by prescription sequence symmetry analysis. Plos One 2014;9:e89795.
    18. Roughead EE, Kalisch LM, Pratt NL, Killer G, Barnard A, Gilbert AL. Managing glaucoma in those with co-morbidity: not as easy as it seems. Ophthalmic Epidemiol 2012;19:74-82.
    19. Tsiropoulos I, Andersen M, Hallas J. Adverse events with use of antiepileptic drugs: a prescription and event symmetry analysis. Pharmacoepidemiol Drug Saf 2009;18:483-91.
    20. Buchanan RW, Kreyenbuhl J, Kelly DL, et al. The 2009 schizophrenia PORT psychopharmacological treatment recommendations and summary statements. Schizophr Bull 2010;36:71-93.
    21. Kreyenbuhl J, Buchanan RW, Dickerson FB, Dixon LB. The Schizophrenia Patient Outcomes Research Team (PORT): updated treatment recommendations 2009. Schizophr Bull 2010;36:94-103.
    22. Farley JF, Hansen RA, Yu-Isenberg KS, Maciejewski ML. Antipsychotic adherence and its correlation to health outcomes for chronic comorbid conditions. Prim Care Companion CNS Disord 2012;14.
    23. DeBattista C, DeBattista K. Safety considerations of the use of second generation antipsychotics in the treatment of major depression: extrapyramidal and metabolic side effects. Curr Drug Saf 2010;5:263-6.
    24. Rummel-Kluge C, Komossa K, Schwarz S, et al. Second-generation antipsychotic drugs and extrapyramidal side effects: a systematic review and meta-analysis of head-to-head comparisons. Schizophr Bull 2012;38:167-77.
    25. Leucht S, Corves C, Arbter D, Engel RR, Li C, Davis JM. Second-generation versus first-generation antipsychotic drugs for schizophrenia: a meta-analysis. Lancet 2009;373:31-41.
    26. Yang SY, Kao Yang YH, Chong MY, Yang YH, Chang WH, Lai CS. Risk of extrapyramidal syndrome in schizophrenic patients treated with antipsychotics: a population-based study. Clin Pharmacol Ther 2007;81:586-94.
    27. Lai EC, Chang CH, Kao Yang YH, Lin SJ, Lin CY. Effectiveness of sulpiride in adult patients with schizophrenia. Schizophr Bull 2013;39:673-83.
    28. Al-Zakwani IS, Barron JJ, Bullano MF, Arcona S, Drury CJ, Cockerham TR. Analysis of healthcare utilization patterns and adherence in patients receiving typical and atypical antipsychotic medications. Curr Med Res Opin 2003;19:619-26.
    29. Bratfos O, Haug JO. Comparison of sulpiride and chlorpromazine in psychoses. A double-blind multicentre study. Acta Psychiatr Scand 1979;60:1-9.
    30. Schwartz M, Moguillansky L, Lanyi G, Sharf B. Sulpiride in tardive dyskinesia. J Neurol Neurosurg Psychiatry 1990;53:800-2.
    31. Soares BG, Fenton M, Chue P. Sulpiride for schizophrenia. Cochrane Database Syst Rev 2000:CD001162.
    32. Gerlach J, Behnke K, Heltberg J, Munk-Anderson E, Nielsen H. Sulpiride and haloperidol in schizophrenia: a double-blind cross-over study of therapeutic effect, side effects and plasma concentrations. Br J Psychiatry 1985;147:283-8.
    33. Omori IM, Wang J. Sulpiride versus placebo for schizophrenia. Cochrane Database Syst Rev 2009:CD007811.
    34. Taylor HL, Jacobs DR, Jr., Schucker B, Knudsen J, Leon AS, Debacker G. A questionnaire for the assessment of leisure time physical activities. Journal of chronic diseases 1978;31:741-55.
    35. McPhillips JB, Pellettera KM, Barrett-Connor E, Wingard DL, Criqui MH. Exercise patterns in a population of older adults. American journal of preventive medicine 1989;5:65-72.
    36. Sheiham A, Steele JG, Marcenes W, Finch S, Walls AW. The impact of oral health on stated ability to eat certain foods; findings from the National Diet and Nutrition Survey of Older People in Great Britain. Gerodontology 1999;16:11-20.
    37. Makhija SK, Gilbert GH, Litaker MS, et al. Association between aspects of oral health-related quality of life and body mass index in community-dwelling older adults. J Am Geriatr Soc 2007;55:1808-16.
    38. Walls AW, Steele JG, Sheiham A, Marcenes W, Moynihan PJ. Oral health and nutrition in older people. Journal of public health dentistry 2000;60:304-7.
    39. Kumar M, Chandu GN, Shafiulla MD. Oral health status and treatment needs in institutionalized psychiatric patients: one year descriptive cross sectional study. Indian journal of dental research : official publication of Indian Society for Dental Research 2006;17:171-7.
    40. Jainkittivong A, Aneksuk V, Langlais RP. Oral mucosal conditions in elderly dental patients. Oral diseases 2002;8:218-23.
    41. Scully C. Drug effects on salivary glands: dry mouth. Oral diseases 2003;9:165-76.
    42. Gerlach J. New antipsychotics: classification, efficacy, and adverse effects. Schizophr Bull 1991;17:289-309.
    43. Lertxundi U, Hernandez R, Medrano J, Domingo-Echaburu S, Garcia M, Aguirre C. Antipsychotics and seizures: higher risk with atypicals? Seizure : the journal of the British Epilepsy Association 2013;22:141-3.
    44. Scully C, Bagan JV. Adverse drug reactions in the orofacial region. Critical reviews in oral biology and medicine : an official publication of the American Association of Oral Biologists 2004;15:221-39.
    45. Dangore-Khasbage S, Khairkar PH, Degwekar SS, et al. Prevalence of oral mucosal disorders in institutionalized and non-institutionalized psychiatric patients: a study from AVBR Hospital in central India. Journal of oral science 2012;54:85-91.
    46. Kivelä SL LE. Sulpiride and placebo in depressed elderly outpatients: A double-blind study. International Journal of Geriatric Psychiatry 1987:255–60.
    47. Pajukoski H, Meurman JH, Halonen P, Sulkava R. Prevalence of subjective dry mouth and burning mouth in hospitalized elderly patients and outpatients in relation to saliva, medication, and systemic diseases. Oral surgery, oral medicine, oral pathology, oral radiology, and endodontics 2001;92:641-9.
    48. National Health Insurance Research Database, Taiwan. http://w3.nhri.org.tw/nhird//en/Data_Subsets.html#S3. Accessed September 23, 2012.
    49. Mollmann H, Egbers HJ. [Comparative study on the influence of psychotropic agents on stress induced lesions of the gastric mucosa]. Arzneimittel-Forschung 1972;22:743-51.
    50. Leucht S, Samara M, Heres S, Patel MX, Woods SW, Davis JM. Dose equivalents for second-generation antipsychotics: the minimum effective dose method. Schizophr Bull 2014;40:314-26.
    51. Schneeweiss S, Rassen JA, Glynn RJ, Avorn J, Mogun H, Brookhart MA. High-dimensional propensity score adjustment in studies of treatment effects using health care claims data. Epidemiology 2009;20:512-22.
    52. Curtis LH, Hammill BG, Eisenstein EL, Kramer JM, Anstrom KJ. Using inverse probability-weighted estimators in comparative effectiveness analyses with observational databases. Medical care 2007;45:S103-7.
    53. Cookson J, Hodgson R, Wildgust HJ. Prolactin, hyperprolactinaemia and antipsychotic treatment: a review and lessons for treatment of early psychosis. J Psychopharmacol 2012;26:42-51.
    54. Inder WJ, Castle D. Antipsychotic-induced hyperprolactinaemia. Aust N Z J Psychiatry 2011;45:830-7.
    55. Kim EY, Kim SH, Lee NY, Jung DC, Kim YS, Ahn YM. Relationship between prolactin levels and subjective endocrine-related adverse effects in patients with schizophrenia receiving long-term treatment with amisulpride. Pharmacopsychiatry 2012;45:57-63.
    56. Kivelä SL, Lehtomäki E. Sulpiride and placebo in depressed elderly outpatients: A double‐blind study. Int J Geriatr Psychiatry 1987;2:255-60.
    57. Ozbilen M, Adams CE, Marley J. Anticholinergic effects of oral antipsychotic drugs of typicals versus atypicals over medium- and long-term: Systematic review and meta-analysis. Curr Med Chem 2012.
    58. Sjogren R, Nordstrom G. Oral health status of psychiatric patients. J Clin Nurs 2000;9:632-8.
    59. Pugh CR, Steinert J, Priest RG. Propranolol in schizophrenia: a double blind, placebo controlled trial of propranolol as an adjunct to neuroleptic medication. Br J Psychiatry 1983;143:151-5.
    60. Lacro JP, Dunn LB, Dolder CR, Leckband SG, Jeste DV. Prevalence of and risk factors for medication nonadherence in patients with schizophrenia: a comprehensive review of recent literature. J Clin Psychiatry 2002;63:892-909.
    61. Kuo CJ, Yang SY, Liao YT, et al. Second-Generation Antipsychotic Medications and Risk of Pneumonia in Schizophrenia. Schizophr Bull 2012.
    62. Trifiro G. Antipsychotic drug use and community-acquired pneumonia. Curr Infect Dis Rep 2011;13:262-8.
    63. Trifiro G, Gambassi G, Sen EF, et al. Association of community-acquired pneumonia with antipsychotic drug use in elderly patients: a nested case-control study. Ann Intern Med 2010;152:418-25, W139-40.
    64. Pratt N, Roughead EE, Ramsay E, Salter A, Ryan P. Risk of hospitalization for hip fracture and pneumonia associated with antipsychotic prescribing in the elderly: a self-controlled case-series analysis in an Australian health care claims database. Drug Saf 2011;34:567-75.
    65. Kimura T, Matsushita Y, Yang YH, Choi NK, Park BJ. Pharmacovigilance systems and databases in Korea, Japan, and Taiwan. Pharmacoepidemiol Drug Saf 2011;20:1237-45.
    66. Fleischhacker WW. Second-generation antipsychotic long-acting injections: systematic review. Br J Psychiatry Suppl 2009;52:S29-36.
    67. Srisurapanont M, Disayavanish C, Taimkaew K. Quetiapine for schizophrenia. Cochrane Database Syst Rev 2000:Cd000967.
    68. Bhana N, Foster RH, Olney R, Plosker GL. Olanzapine: an updated review of its use in the management of schizophrenia. Drugs 2001;61:111-61.
    69. Ozbilen M, Adams CE. Systematic overview of Cochrane reviews for anticholinergic effects of antipsychotic drugs. J Clin Psychopharmacol 2009;29:141-6.
    70. Godoy T, Riva A, Ekstrom J. Atypical antipsychotics--effects of amisulpride on salivary secretion and on clozapine-induced sialorrhea. Oral diseases 2012;18:680-91.
    71. Loy F, Isola M, Isola R, et al. The antipsychotic amisulpride: ultrastructural evidence of its secretory activity in salivary glands. Oral diseases 2013.
    72. Desoutter A, Soudain-Pineau M, Munsch F, Mauprivez C, Dufour T, Coeuriot JL. Xerostomia and medication: a cross-sectional study in long-term geriatric wards. The journal of nutrition, health & aging 2012;16:575-9.
    73. Khanna P, Suo T, Komossa K, et al. Aripiprazole versus other atypical antipsychotics for schizophrenia. Cochrane Database Syst Rev 2014;1:Cd006569.
    74. Mortazavi H, Baharvand M, Movahhedian A, Mohammadi M, Khodadoustan A. Xerostomia due to systemic disease: a review of 20 conditions and mechanisms. Annals of medical and health sciences research 2014;4:503-10.
    75. Kerr GD, Sellars C, Bowie L, et al. Xerostomia after acute stroke. Cerebrovasc Dis 2009;28:624-6.
    76. Maclure M. 'Why me?' versus 'why now?'--differences between operational hypotheses in case-control versus case-crossover studies. Pharmacoepidemiol Drug Saf 2007;16:850-3.
    77. Glesby MJ, Hoover DR. Survivor treatment selection bias in observational studies: examples from the AIDS literature. Ann Intern Med 1996;124:999-1005.
    78. Hernan MA, Alonso A, Logan R, et al. Observational studies analyzed like randomized experiments: an application to postmenopausal hormone therapy and coronary heart disease. Epidemiology 2008;19:766-79.
    79. Hallas J, Gaist D, Bjerrum L. The waiting time distribution as a graphical approach to epidemiologic measures of drug utilization. Epidemiology 1997;8:666-70.
    80. Correa-Lima AR, Miranda-Filho DD, Valenca MM, Andrade-Valenca L. Risk Factors for Acute Symptomatic Seizure in Bacterial Meningitis in Children. J Child Neurol 2014.
    81. Barrons RW, Murray KM, Richey RM. Populations at risk for penicillin-induced seizures. Ann Pharmacother 1992;26:26-9.
    82. Beghi E, Shorvon S. Antiepileptic drugs and the immune system. Epilepsia 2011;52 Suppl 3:40-4.
    83. Gothe F, Enache D, Wahlund LO, et al. Cerebrovascular diseases and depression: epidemiology, mechanisms and treatment. Panminerva Med 2012;54:161-70.
    84. Flock A, Zobel A, Bauriedel G, et al. Antiplatelet effects of antidepressant treatment: a randomized comparison between escitalopram and nortriptyline. Thromb Res 2010;126:e83-7.
    85. Thacker EL, Schneeweiss S. Initiation of acetylcholinesterase inhibitors and complications of chronic airways disorders in elderly patients. Drug Saf 2006;29:1077-85.
    86. Benedetti MS, Whomsley R, Baltes E, Tonner F. Alteration of thyroid hormone homeostasis by antiepileptic drugs in humans: involvement of glucuronosyltransferase induction. Eur J Clin Pharmacol 2005;61:863-72.
    87. Takada M, Fujimoto M, Hosomi K. Difference in risk of gastrointestinal complications between users of enteric-coated and buffered low-dose aspirin. Int J Clin Pharmacol Ther 2014;52:181-91.
    88. Maclure M, Fireman B, Nelson JC, et al. When should case-only designs be used for safety monitoring of medical products? Pharmacoepidemiol Drug Saf 2012;21 Suppl 1:50-61.
    89. Takada M, Fujimoto M, Yamazaki K, Takamoto M, Hosomi K. Association of statin use with sleep disturbances: data mining of a spontaneous reporting database and a prescription database. Drug Saf 2014;37:421-31.
    90. Wahab IA, Pratt NL, Kalisch LM, Roughead EE. Sequence Symmetry Analysis and Disproportionality Analyses: What
    Percentage of Adverse Drug Reaction do they Signal? Adv Pharmacoepidemiol Drug Saf 2013;2:140.
    91. Pratt N, Andersen M, Bergman U, et al. Multi-country rapid adverse drug event assessment: the Asian Pharmacoepidemiology Network (AsPEN) antipsychotic and acute hyperglycaemia study. Pharmacoepidemiol Drug Saf 2013;22:915-24.
    92. Andersen M, Bergman U, Choi NK, et al. The Asian Pharmacoepidemiology Network (AsPEN): promoting multi-national collaboration for pharmacoepidemiologic research in Asia. Pharmacoepidemiol Drug Saf 2013;22:700-4.
    93. Asian Pharmacoepidemiology Network: http://aspennet.asia/ [April 4. 2015].
    94. Lindberg G, Hallas J. Cholesterol-lowering drugs and antidepressants--a study of prescription symmetry. Pharmacoepidemiol Drug Saf 1998;7:399-402.
    95. Bytzer P, Hallas J. Drug-induced symptoms of functional dyspepsia and nausea. A symmetry analysis of one million prescriptions. Aliment Pharmacol Ther 2000;14:1479-84.
    96. Corrao G, Botteri E, Bagnardi V, et al. Generating signals of drug-adverse effects from prescription databases and application to the risk of arrhythmia associated with antibacterials. Pharmacoepidemiol Drug Saf 2005;14:31-40.
    97. Vegter S, de Jong-van den Berg LT. Misdiagnosis and mistreatment of a common side-effect--angiotensin-converting enzyme inhibitor-induced cough. Br J Clin Pharmacol 2010;69:200-3.
    98. Caughey GE, Roughead EE, Pratt N, Killer G, Gilbert AL. Stroke risk and NSAIDs: an Australian population-based study. Med J Aust 2011;195:525-9.
    99. Pouwels KB, Visser ST, Bos HJ, Hak E. Angiotensin-converting enzyme inhibitor treatment and the development of urinary tract infections: a prescription sequence symmetry analysis. Drug Saf 2013;36:1079-86.
    100. van Boven JF, de Jong-van den Berg LT, Vegter S. Inhaled corticosteroids and the occurrence of oral candidiasis: a prescription sequence symmetry analysis. Drug Saf 2013;36:231-6.
    101. Fujimoto M, Higuchi T, Hosomi K, Takada M. Association of statin use with storage lower urinary tract symptoms (LUTS): data mining of prescription database. Int J Clin Pharmacol Ther 2014;52:762-9.
    102. Kalisch Ellett LM, Pratt NL, Barratt JD, Rowett D, Roughead EE. Risk of medication-associated initiation of oxybutynin in elderly men and women. J Am Geriatr Soc 2014;62:690-5.
    103. Fujimoto M, Higuchi T, Hosomi K, Takada M. Association between statin use and cancer: data mining of a spontaneous reporting database and a claims database. Int J Med Sci 2015;12:223-33.

    無法下載圖示 校內：2025-12-31公開
    校外：不公開
    電子論文尚未授權公開，紙本請查館藏目錄
    QR CODE