Methods for using clinical laboratory test results as baseline confounders in multi‐site observational database studies when missing data are expected

Our purpose was to quantify missing baseline laboratory results, assess predictors of missingness, and examine performance of missing data methods.

[1]  Michelle Shardell,et al.  Sensitivity Analysis of Informatively Coarsened Data Using Pattern Mixture Models , 2009, Journal of biopharmaceutical statistics.

[2]  C. Correll Monitoring and management of antipsychotic-related metabolic and endocrine adverse events in pediatric patients , 2008, International review of psychiatry.

[3]  Daria Eremina,et al.  The Importance of Clinical Variables in Comparative Analyses Using Propensity-Score Matching , 2012, PharmacoEconomics.

[4]  H. Gerstein,et al.  Shared electronic vascular risk decision support in primary care: Computerization of Medical Practices for the Enhancement of Therapeutic Effectiveness (COMPETE III) randomized trial. , 2011, Archives of internal medicine.

[5]  Raymond C. Schneider,et al.  ISIS-4: A randomised factorial trial assessing early oral captopril, oral mononitrate, and intravenous magnesium sulphate in 58 050 patients with suspected acute myocardial infarction , 1995, The Lancet.

[6]  R Platt,et al.  Comparative‐Effectiveness Research in Distributed Health Data Networks , 2011, Clinical pharmacology and therapeutics.

[7]  Marc De Hert,et al.  Metabolic and cardiovascular adverse effects associated with antipsychotic drugs , 2012, Nature Reviews Endocrinology.

[8]  J. Mahnken,et al.  Predictors of the Development of Hyperkalemia in Patients Using Angiotensin-Converting Enzyme Inhibitors , 2000, American Journal of Nephrology.

[9]  Hhs Office for Civil Rights Standards for privacy of individually identifiable health information. Final rule. , 2002, Federal register.

[10]  B. Magnani,et al.  The effect of the angiotensin-converting-enzyme inhibitor zofenopril on mortality and morbidity after anterior myocardial infarction. The Survival of Myocardial Infarction Long-Term Evaluation (SMILE) Study Investigators. , 1995, The New England journal of medicine.

[11]  J. Merenich,et al.  Lipid management in patients with coronary artery disease by a clinical pharmacy service in a group model health maintenance organization. , 2005, Archives of internal medicine.

[12]  R. Platt,et al.  Distributed Health Data Networks: A Practical and Preferred Approach to Multi-Institutional Evaluations of Comparative Effectiveness, Safety, and Quality of Care , 2010, Medical care.

[13]  E. Lewis,et al.  Renoprotective effect of the angiotensin-receptor antagonist irbesartan in patients with nephropathy due to type 2 diabetes. , 2001, The New England journal of medicine.

[14]  G. Ippolito,et al.  HIV incidence estimate combining HIV/AIDS surveillance, testing history information and HIV test to identify recent infections in Lazio, Italy , 2012, BMC Infectious Diseases.

[15]  David M Kent,et al.  Predicting mortality in incident dialysis patients: an analysis of the United Kingdom Renal Registry. , 2011, American journal of kidney diseases : the official journal of the National Kidney Foundation.

[16]  Richard Platt,et al.  Laboratory monitoring of potassium and creatinine in ambulatory patients receiving angiotensin converting enzyme inhibitors and angiotensin receptor blockers , 2007, Pharmacoepidemiology and drug safety.

[17]  B. Magnani,et al.  The effect of the angiotensin-converting-enzyme inhibitor zofenopril on mortality and morbidity after anterior myocardial infarction , 1995 .

[18]  Robert S. Leiken,et al.  A User’s Guide , 2011 .

[19]  Kevin Haynes,et al.  Electronic clinical laboratory test results data tables: lessons from Mini‐Sentinel , 2014, Pharmacoepidemiology and drug safety.

[20]  Jing Ning,et al.  The impact of missing trauma data on predicting massive transfusion , 2013, The journal of trauma and acute care surgery.

[21]  M. Kenward,et al.  Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls , 2009, BMJ : British Medical Journal.

[22]  P. Austin,et al.  Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies , 2010, Pharmaceutical statistics.

[23]  J. Newcomer Second-Generation (Atypical) Antipsychotics and Metabolic Effects , 2005, CNS drugs.

[24]  A. M. Walker,et al.  An application of propensity score matching using claims data , 2005, Pharmacoepidemiology and drug safety.

[25]  Ross Ward,et al.  The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation and Treatment of High Blood Pressure , 2011 .

[26]  J. Roy,et al.  Dynamic marginal structural modeling to evaluate the comparative effectiveness of more or less aggressive treatment intensification strategies in adults with type 2 diabetes , 2012, Pharmacoepidemiology and drug safety.

[27]  J. Lafrance,et al.  Selective and non‐selective non‐steroidal anti‐inflammatory drugs and the risk of acute kidney injury , 2009, Pharmacoepidemiology and drug safety.

[28]  Richard Platt,et al.  The U.S. Food and Drug Administration's Mini‐Sentinel program: status and direction , 2012, Pharmacoepidemiology and drug safety.

[29]  M. Raebel,et al.  Diabetes and Drug-Associated Hyperkalemia: Effect of Potassium Monitoring , 2010, Journal of General Internal Medicine.

[30]  M. Raebel,et al.  Use of stabilized inverse propensity scores as weights to directly estimate relative risk and its confidence intervals. , 2009, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[31]  B. Palmer Managing hyperkalemia caused by inhibitors of the renin-angiotensin-aldosterone system. , 2004, The New England journal of medicine.

[32]  Sebastian Schneeweiss,et al.  A combined comorbidity score predicted mortality in elderly patients better than existing scores. , 2011, Journal of clinical epidemiology.

[33]  Helen M Parsons,et al.  Missing data and interpretation of cancer surgery outcomes at the American College of Surgeons National Surgical Quality Improvement Program. , 2011, Journal of the American College of Surgeons.

[34]  M. Raebel Hyperkalemia associated with use of angiotensin-converting enzyme inhibitors and angiotensin receptor blockers. , 2012, Cardiovascular therapeutics.

[35]  R. Jardri,et al.  Metabolic side effects of risperidone in children and adolescents with early-onset schizophrenia. , 2008, Primary care companion to the Journal of clinical psychiatry.

[36]  Bhavik J. Pandya,et al.  Achieving glycemic goal with initial versus sequential combination therapy using metformin and pioglitazone in type 2 diabetes mellitus , 2011, Current medical research and opinion.

[37]  Richard Platt,et al.  Design of a National Distributed Health Data Network , 2009, Annals of Internal Medicine.

[38]  P. Austin An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies , 2011, Multivariate behavioral research.

[39]  R. Platt,et al.  Developing the Sentinel System--a national resource for evidence development. , 2011, The New England journal of medicine.

[40]  N. Fujii,et al.  Combined use of vitamin D status and FGF23 for risk stratification of renal outcome. , 2012, Clinical journal of the American Society of Nephrology : CJASN.

[41]  Jason Roy,et al.  Bayesian Hierarchical Pattern Mixture Models for Comparative Effectiveness of Drugs and Drug Classes Using Healthcare Data: A Case Study Involving Antihypertensive Medications , 2011 .

[42]  Gruppo Italiano per lo Studio della Soprawivenza nell'Inf Miocardico. GISSI-3: effects of lisiriopril and transdermal glyceryl trinitrate singly and together on 6-week mortality and ventricular function after acute myocardial infarction , 1994, The Lancet.

[43]  Peter C Austin,et al.  A comparison of the ability of different propensity score models to balance measured variables between treated and untreated subjects: a Monte Carlo study , 2007, Statistics in medicine.

[44]  D. Rubin INFERENCE AND MISSING DATA , 1975 .

[45]  A. Hung,et al.  Kidney function decline in metformin versus sulfonylurea initiators: assessment of time‐dependent contribution of weight, blood pressure, and glycemic control , 2013, Pharmacoepidemiology and drug safety.

[46]  Nikki M. Carroll,et al.  Increased Risk of Bleeding in Patients on Clopidogrel Therapy After Drug-Eluting Stents Implantation: Insights From the HMO Research Network-Stent Registry (HMORN-Stent) , 2010, Circulation. Cardiovascular interventions.

[47]  P D Cleary,et al.  Validating recommendations for coronary angiography following acute myocardial infarction in the elderly: a matched analysis using propensity scores. , 2001, Journal of clinical epidemiology.

[48]  W. Ageno,et al.  Nonadherence with INR monitoring and anticoagulant complications. , 2013, Thrombosis research.

[49]  B. Gazzard,et al.  Biomarkers to Monitor Safety in People on ART and Risk of Mortality , 2012, Journal of acquired immune deficiency syndromes.

[50]  K. Olson,et al.  Statin adherence and mortality in patients enrolled in a secondary prevention program. , 2009, The American journal of managed care.

[51]  Theo Stijnen,et al.  Using the outcome for imputation of missing predictor values was preferred. , 2006, Journal of clinical epidemiology.

[52]  J. Steiner,et al.  Initial Antihyperglycemic Drug Therapy Among 241 327 Adults With Newly Identified Diabetes From 2005 Through 2010 , 2013, The Annals of pharmacotherapy.

[53]  R. Stolk,et al.  Refill adherence and polypharmacy among patients with type 2 diabetes in general practice , 2009, Pharmacoepidemiology and drug safety.

[54]  Marsha A Raebel,et al.  Design considerations, architecture, and use of the Mini‐Sentinel distributed data system , 2012, Pharmacoepidemiology and drug safety.

[55]  C. Panagiotopoulos,et al.  Evidence-based recommendations for monitoring safety of second-generation antipsychotics in children and youth. , 2011, Paediatrics & child health.

[56]  Roger A. Sugden,et al.  Multiple Imputation for Nonresponse in Surveys , 1988 .

[57]  Jeremy MG Taylor,et al.  Partially parametric techniques for multiple imputation , 1996 .

[58]  A. Go,et al.  Improved Blood Pressure Control Associated with a Large-scale Hypertension Program Downloaded From: Http://jama.jamanetwork.com/ by Edgardo Sandoya on 08/28/2013 , 2022 .

[59]  Craig K. Enders,et al.  Applied Missing Data Analysis , 2010 .

[60]  P. Allison Multiple Imputation for Missing Data , 2000 .