Minimizing signal detection time in postmarket sequential analysis: Balancing positive predictive value and sensitivity

Pharmacoepidemiology and Drug Safety

Volumn 23, Issue 8, 2014, Pages 839-848

  Maro, Judith C ^a   Brown, Jeffrey S ^a   Dal Pan, Gerald J ^b   Kulldorff, Martin ^a  

^a HARVARD MEDICAL SCHOOL   (United States)

^b CENTER FOR DRUG EVALUATION AND RESEARCH   (United States)

Author keywords

Adverse drug event; Bias (epidemiology); Outcome measurement error; Pharmacoepidemiology; Pharmacovigilance; Postmarketing product surveillance

Indexed keywords

LIVE VACCINE; VACCINE;

ALGORITHM; ARTICLE; CHILD; CHILDHOOD DISEASE; CONTROLLED STUDY; DRUG SURVEILLANCE PROGRAM; HUMAN; IDIOPATHIC THROMBOCYTOPENIC PURPURA; INCIDENCE; MAJOR CLINICAL STUDY; MEASUREMENT ERROR; OUTCOME ASSESSMENT; PREDICTIVE VALUE; PRIORITY JOURNAL; SENSITIVITY ANALYSIS; SIGNAL DETECTION; SINGLE DRUG DOSE; VACCINATION; VALIDATION STUDY; COMPUTER SIMULATION; EPIDEMIOLOGY; FACTUAL DATABASE; FOOD AND DRUG ADMINISTRATION; POSTMARKETING SURVEILLANCE; PROCEDURES; RISK; SENSITIVITY AND SPECIFICITY; SENTINEL SURVEILLANCE; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; TIME; UNITED STATES;

ADVERSE DRUG REACTION REPORTING SYSTEMS; ALGORITHMS; COMPUTER SIMULATION; DATABASES, FACTUAL; EPIDEMIOLOGIC RESEARCH DESIGN; HUMANS; MODELS, STATISTICAL; OUTCOME ASSESSMENT (HEALTH CARE); PHARMACOVIGILANCE; PREDICTIVE VALUE OF TESTS; PRODUCT SURVEILLANCE, POSTMARKETING; RISK; SENSITIVITY AND SPECIFICITY; SENTINEL SURVEILLANCE; TIME FACTORS; UNITED STATES; UNITED STATES FOOD AND DRUG ADMINISTRATION; VACCINES;

EID: 84904979278     PISSN: 10538569     EISSN: 10991557     Source Type: Journal    
DOI: 10.1002/pds.3618     Document Type: Article

References (45)

1. 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(Suppl 1): 90-99. doi:10.1002/pds.2318.
2. Cutrona SL, Toh S, Iyer A, et al. Validation of acute myocardial infarction in the Food and Drug Administration's Mini-Sentinel program. Pharmacoepidemiol Drug Saf 2013; 22: 40-54. doi:10.1002/pds.3310.
3. Walsh KE, Cutrona SL, Foy S, et al. Validation of anaphylaxis in the Food and Drug Administration's Mini-Sentinel. Pharmacoepidemiol Drug Saf 2013. doi:10.1002/pds.3505.
4. Lo Re V, 3rd, Haynes K, Goldberg D, et al. Validity of diagnostic codes to identify cases of severe acute liver injury in the US Food and Drug Administration's Mini-Sentinel Distributed Database. Pharmacoepidemiol Drug Saf 2013; 22: 861-872. doi:10.1002/pds.3470.
5. Jurek AM, Greenland S, Maldonado G. How far from non-differential does exposure or disease misclassification have to be to bias measures of association away from the null? Int J Epidemiol 2008; 37: 382-385. doi:10.1093/ije/dym291.
6. Greenland S, Gustafson P. Accounting for independent nondifferential misclassification does not increase certainty that an observed association is in the correct direction. Am J Epidemiol 2006; 164: 63-68. doi:10.1093/aje/kwj155.
7. Jurek AM, Greenland S, Maldonado G, Church TR. Proper interpretation of non-differential misclassification effects: expectations vs observations. Int J Epidemiol 2005; 34: 680-687. doi:10.1093/ije/dyi060.
8. Fox MP, Lash TL, Greenland S. A method to automate probabilistic sensitivity analyses of misclassified binary variables. Int J Epidemiol 2005; 34: 1370-1376. doi:10.1093/ije/dyi184.
9. Greenland S. Basic methods for sensitivity analysis of biases. Int J Epidemiol 1996; 25: 1107-1116.
10. Mullooly JP. Misclassification model for person-time analysis of automated medical care databases. Am J Epidemiol 1996; 144: 782-792.
11. Brenner H, Gefeller O. Use of the positive predictive value to correct for disease misclassification in epidemiologic studies. Am J Epidemiol 1993; 138: 1007-1015.
12. Poole C. Exception to the rule about nondifferential misclassification. (Abstract). Am J Epidemiol 1985; 122: 508.
13. Green MS. Use of predictive value to adjust relative risk estimates biased by misclassification of outcome status. Am J Epidemiol 1983; 117: 98-105.
14. Copeland KT, Checkoway H, McMichael AJ, Holbrook RH. Bias due to misclassification in the estimation of relative risk. Am J Epidemiol 1977; 105: 488-495.
15. Greenland S. Multiple-bias modelling for analysis of observational data. J R Stat Soc A Stat Soc 2005; 168: 267-306. doi:10.1111/j.1467-985X.2004.00349.x.
16. Jennison C, Turnbull BW. Group Sequential Methods With Applications to Clinical Trials. Boca Raton: Chapman & Hall/CRC, 2000.
17. Whitehead J. The Design and Analysis of Sequential Clinical Trials. Chichester, UK: Wiley, 1997.
18. Xu S, Newcomer S, Nelson J, et al. Signal detection of adverse events with imperfect confirmation rates in vaccine safety studies using self-controlled case series design. Biom J 2014: n/a-n/a. doi: 10.1002/bimj.201300012
19. McClure DL, Glanz JM, Xu S, Hambidge SJ, Mullooly JP, Baggs J. Comparison of epidemiologic methods for active surveillance of vaccine safety. Vaccine 2008; 26: 3341-3345. doi:10.1016/j.vaccine.2008.03.074.
20. Maro JC, Brown JS, Kulldorff M. Medical product safety surveillance: how many databases to use? Epidemiology 2013; 24: 692-699. doi:10.1097/EDE.0b013e31829dde59.
21. Maro JC, Brown JS. Impact of exposure accrual on sequential postmarket evaluations: a simulation study. Pharmacoepidemiol Drug Saf 2011; 20: 1184-1191. doi:10.1002/pds.2223.
22. Platt R, Carnahan RM, Brown JS, et al. The U.S. Food and Drug Administration's Mini-Sentinel program: status and direction. Pharmacoepidemiol Drug Saf 2012; 21(Suppl 1): 1-8. doi:10.1002/pds.2343.
23. Nelson JC, Cook AJ, Yu O, et al. Challenges in the design and analysis of sequentially monitored postmarket safety surveillance evaluations using electronic observational health care data. Pharmacoepidemiol Drug Saf 2012; 21(Suppl 1): 62-71. doi:10.1002/pds.2324.
24. Chubak J, Pocobelli G, Weiss NS. Tradeoffs between accuracy measures for electronic health care data algorithms. J Clin Epidemiol 2012; 65: 343-349.e2. doi: 10.1016/j.jclinepi.2011.09.002
25. Yih WK, Lee GM, Lieu TA, et al. Surveillance for adverse events following receipt of pandemic 2009 H1N1 vaccine in the Post-Licensure Rapid Immunization Safety Monitoring (PRISM) System, 2009-2010. Am J Epidemiol 2012; 175: 1120-1128. doi:10.1093/aje/kws197.
26. Tse A, Tseng HF, Greene SK, Vellozzi C, Lee GM. Signal identification and evaluation for risk of febrile seizures in children following trivalent inactivated influenza vaccine in the Vaccine Safety Datalink Project, 2010-2011. Vaccine 2012; 30: 2024-2031. doi:10.1016/j.vaccine.2012.01.027.
27. Greene SK, Kulldorff M, Yin R, et al. Near real-time vaccine safety surveillance with partially accrued data. Pharmacoepidemiol Drug Saf 2011; 20: 583-590. doi:10.1002/pds.2133.
28. Gee J, Naleway A, Shui I, et al. Monitoring the safety of quadrivalent human papillomavirus vaccine: findings from the Vaccine Safety Datalink. Vaccine 2011; 29: 8279-8284. doi:10.1016/j.vaccine.2011.08.106.
29. Lee GM, Greene SK, Weintraub ES, et al. H1N1 and seasonal influenza vaccine safety in the Vaccine Safety Datalink Project. Am J Prev Med 2011; 41: 121-128. doi:10.1016/j.amepre.2011.04.004.
30. Klein NP, Fireman B, Yih WK, et al. Measles-mumps-rubella-varicella combination vaccine and the risk of febrile seizures. Pediatrics 2010; 126: e1-8. doi:10.1542/peds.2010-0665.
31. Belongia EA, Irving SA, Shui IM, et al. Real-time surveillance to assess risk of intussusception and other adverse events after pentavalent, bovine-derived rotavirus vaccine. Pediatr Infect Dis J 2010; 29: 1-5. doi:10.1097/INF.0b013e3181af8605.
32. Greene SK, Kulldorff M, Lewis EM, et al. Near real-time surveillance for influenza vaccine safety: proof-of-concept in the Vaccine Safety Datalink Project. Am J Epidemiol 2010; 171: 177-188. doi:10.1093/aje/kwp345.
33. Lieu TA, Kulldorff M, Davis RL, et al. Real-time vaccine safety surveillance for the early detection of adverse events. Med Care 2007; 45: S89-95. doi:10.1097/MLR.0b013e3180616c0a.
34. O'Leary ST, Glanz JM, McClure DL, et al. The risk of immune thrombocytopenic purpura after vaccination in children and adolescents. Pediatrics 2012; 129: 248-255. doi:10.1542/peds.2011-1111.
35. France EK, Glanz J, Xu S, et al. Risk of immune thrombocytopenic purpura after measles-mumps-rubella immunization in children. Pediatrics 2008; 121: e687-692. doi:10.1542/peds.2007-1578.
36. Glanz J, France E, Xu S, Hayes T, Hambidge S. A population-based, multisite cohort study of the predictors of chronic idiopathic thrombocytopenic purpura in children. Pediatrics 2008; 121: e506-512. doi:10.1542/peds.2007-1129.
37. Terrell DR, Beebe LA, Vesely SK, Neas BR, Segal JB, George JN. Determining a definite diagnosis of primary immune thrombocytopenia by medical record review. Am J Hematol 2012; 87: 843-847. doi:10.1002/ajh.23226.
38. Yih WK, Kulldorff M, Fireman BH, et al. Active surveillance for adverse events: the experience of the Vaccine Safety Datalink project. Pediatrics 2011; 127(Suppl 1): S54-64. doi:10.1542/peds.2010-1722I.
39. Kulldorff M, Davis RL, Kolczak M, Lewis E, Lieu TA, Platt R. A maximized sequential probability ratio test for drug and vaccine safety surveillance. Seq Anal 2011; 30: 58-78. doi:10.1080/07474946.2011.539924.
40. Greene SK, Rett M, Weintraub ES, et al. Risk of confirmed Guillain-Barre syndrome following receipt of monovalent inactivated influenza a (H1N1) and seasonal influenza vaccines in the Vaccine Safety Datalink Project, 2009-2010. Am J Epidemiol 2012; 175: 1100-1109. doi:10.1093/aje/kws195.
41. Wald A. Sequential tests of statistical hypotheses. Ann Math Stat 1945; 16: 117-186.
42. Curtis LH, Weiner MG, Boudreau DM, et al. Design considerations, architecture, and use of the Mini-Sentinel Distributed Data System. Pharmacoepidemiol Drug Saf 2012; 21(Suppl 1): 23-31. doi:10.1002/pds.2336.
43. Centers for Disease Control and Prevention. National Vital Statistics System. Available at: http://www.cdc.gov/nchs/nvss.htm. Accessed [October 11, 2012].
44. Avery TR, Kulldorff M, Vilk Y, et al. Near real-time adverse drug reaction surveillance within population-based health networks: methodology considerations for data accrual. Pharmacoepidemiol Drug Saf 2013; 22: 488-495. doi:10.1002/pds.3412.
45. Segal JB, Powe NR. Accuracy of identification of patients with immune thrombocytopenic purpura through administrative records: a data validation study. Am J Hematol 2004; 75: 12-17. doi:10.1002/ajh.10445.