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Raebel MA, Shetterly S, Lu CY, Flory J, Gagne JJ, Harrell FE, Haynes K, Herrinton LJ, Patorno E, Popovic J, Selvan M, Shoaibi A, Wang X, Roy J. Methods for using clinical laboratory test results as baseline confounders in multi-site observational database studies when missing data are expected. Pharmacoepidemiol Drug Saf 2016; 25:798-814. [PMID: 27146273 DOI: 10.1002/pds.4015] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Revised: 03/15/2016] [Accepted: 03/22/2016] [Indexed: 11/11/2022]
Abstract
PURPOSE Our purpose was to quantify missing baseline laboratory results, assess predictors of missingness, and examine performance of missing data methods. METHODS Using the Mini-Sentinel Distributed Database from three sites, we selected three exposure-outcome scenarios with laboratory results as baseline confounders. We compared hazard ratios (HRs) or risk differences (RDs) and 95% confidence intervals (CIs) from models that omitted laboratory results, included only available results (complete cases), and included results after applying missing data methods (multiple imputation [MI] regression, MI predictive mean matching [PMM] indicator). RESULTS Scenario 1 considered glucose among second-generation antipsychotic users and diabetes. Across sites, glucose was available for 27.7-58.9%. Results differed between complete case and missing data models (e.g., olanzapine: HR 0.92 [CI 0.73, 1.12] vs 1.02 [0.90, 1.16]). Across-site models employing different MI approaches provided similar HR and CI; site-specific models provided differing estimates. Scenario 2 evaluated creatinine among individuals starting high versus low dose lisinopril and hyperkalemia. Creatinine availability: 44.5-79.0%. Results differed between complete case and missing data models (e.g., HR 0.84 [CI 0.77, 0.92] vs. 0.88 [0.83, 0.94]). HR and CI were identical across MI methods. Scenario 3 examined international normalized ratio (INR) among warfarin users starting interacting versus noninteracting antimicrobials and bleeding. INR availability: 20.0-92.9%. Results differed between ignoring INR versus including INR using missing data methods (e.g., RD 0.05 [CI -0.03, 0.13] vs 0.09 [0.00, 0.18]). Indicator and PMM methods gave similar estimates. CONCLUSION Multi-site studies must consider site variability in missing data. Different missing data methods performed similarly. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Marsha A Raebel
- Institute for Health Research, Kaiser Permanente Colorado, Denver, CO, USA.,Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado, Aurora, CO, USA
| | - Susan Shetterly
- Institute for Health Research, Kaiser Permanente Colorado, Denver, CO, USA
| | - Christine Y Lu
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, USA
| | - James Flory
- Department of Medicine, Weill Cornell Medical College, New York, NY, USA
| | - Joshua J Gagne
- Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Frank E Harrell
- Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | | | | | - Elisabetta Patorno
- Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jennifer Popovic
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, USA
| | - Mano Selvan
- Comprehensive Health Insights, Humana Inc., Louisville, KY, USA
| | - Azadeh Shoaibi
- Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, USA
| | - Xingmei Wang
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jason Roy
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Virdi NS, Lefebvre P, Parisé H, Duh MS, Pilon D, Laliberté F, Sundaresan D, Garber L, Dirani R. Association of self-monitoring of blood glucose use on glycated hemoglobin and weight in newly diagnosed, insulin-naïve adult patients with type 2 diabetes. J Diabetes Sci Technol 2013; 7:1229-42. [PMID: 24124950 PMCID: PMC3876367 DOI: 10.1177/193229681300700513] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
BACKGROUND Clinical trials have shown that self-monitoring of blood glucose (SMBG) combined with patient education and medication titration can lead to improved glycated hemoglobin (HbA1c) and reduced weight in recently diagnosed non-insulin-treated type 2 diabetes mellitus (T2DM) patients. This retrospective matched cohort study assessed the association of SMBG with achieving long-term clinical outcomes in these patients in a real-world clinical setting. METHODS Using electronic medical records (2008-2011), we selected a population of adult patients recently diagnosed with T2DM not receiving insulin who were SMBG users and a population of non-SMBG controls with similar demographic and clinical characteristics using propensity score matching. The main study outcomes compared between the two groups were time to achieve (1) HbA1c <7% for patients with baseline HbA1c ≥ 7% and (2) a ≥ 5% reduction in weight from baseline. RESULTS Of the 589 patients identified in each group, 113 in each group had a baseline HbA1c ≥ 7% (mean, 8.2%). The SMBG users were more likely to achieve an HbA1c <7% (12 months: 58.4% versus 38.9%, p = .0037; 36 months: 84.0% versus 70.0%, p = .0013) and to do so faster (median, 6.5 versus 20.5 months; log-rank p = .0016). Self-monitoring of blood glucose was associated with faster weight reduction (median time to achieve a ≥ 5% reduction, 23.5 versus 35.9 months for SMBG and non-SMBG, respectively; log-rank p = .0005). CONCLUSIONS In newly diagnosed T2DM insulin-naïve patients, SMBG users had an improved rate of achieving long-term glycemic control and weight loss in a real-world clinical setting.
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Tatsumi F, Hashiramoto M, Hirukawa H, Kimura T, Shimoda M, Tawaramoto K, Kanda-Kimura Y, Anno T, Kawasaki F, Mune T, Matsuki M, Kaku K. Concomitant use of miglitol and mitiglinide as initial combination therapy in type 2 diabetes mellitus. Diabetes Res Clin Pract 2013; 101:35-44. [PMID: 23711593 DOI: 10.1016/j.diabres.2013.04.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2013] [Revised: 03/20/2013] [Accepted: 04/22/2013] [Indexed: 12/11/2022]
Abstract
AIM To evaluate the efficacy of miglitol and mitiglinide alone or in combination on the metabolic profile and incretin secretion in Japanese type 2 diabetes patients. METHODS Patients on diet and exercise with or without metformin, were randomized to receive either miglitol, mitiglinide, or a combination, three times daily for 12 weeks. RESULTS At 12 weeks, HbA1c decreased significantly (p<0.001) and 1,5-AG increased significantly (p<0.001) in all three groups, with the greatest change seen with combination therapy. Effective improvement of postprandial hyperglycemia was demonstrated by a meal-loading test in all three interventions but serum insulin concentration was not increased by miglitol. In a subset of patients without prior metformin administration, faster and better glycemic control was achieved with the initial combination. After meal loading, serum total GLP-1 significantly increased only with miglitol monotherapy (p<0.05) and serum total GIP significantly decreased (p<0.01) in the arms employing miglitol after 12 weeks. CONCLUSION Miglitol/mitiglinide combination is more potent than monotherapy in improving glycemic control through the reduction of postprandial glucose excursion and the simultaneous sparing of additional insulin secretion. A marked difference in the effects of miglitol and mitiglinide on incretin secretion was also demonstrated.
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Affiliation(s)
- Fuminori Tatsumi
- Division of Diabetes, Endocrinology and Metabolism, Kawasaki Medical School, 577 Matsushima, Kurashiki 701-0192, Japan
| | - Mitsuru Hashiramoto
- Division of Diabetes, Endocrinology and Metabolism, Kawasaki Medical School, 577 Matsushima, Kurashiki 701-0192, Japan.
| | - Hidenori Hirukawa
- Division of Diabetes, Endocrinology and Metabolism, Kawasaki Medical School, 577 Matsushima, Kurashiki 701-0192, Japan
| | - Tomohiko Kimura
- Division of Diabetes, Endocrinology and Metabolism, Kawasaki Medical School, 577 Matsushima, Kurashiki 701-0192, Japan
| | - Masashi Shimoda
- Division of Diabetes, Endocrinology and Metabolism, Kawasaki Medical School, 577 Matsushima, Kurashiki 701-0192, Japan
| | - Kazuhito Tawaramoto
- Division of Diabetes, Endocrinology and Metabolism, Kawasaki Medical School, 577 Matsushima, Kurashiki 701-0192, Japan
| | - Yukiko Kanda-Kimura
- Division of Diabetes, Endocrinology and Metabolism, Kawasaki Medical School, 577 Matsushima, Kurashiki 701-0192, Japan
| | - Takatoshi Anno
- Division of Diabetes, Endocrinology and Metabolism, Kawasaki Medical School, 577 Matsushima, Kurashiki 701-0192, Japan
| | - Fumiko Kawasaki
- Division of Diabetes, Endocrinology and Metabolism, Kawasaki Medical School, 577 Matsushima, Kurashiki 701-0192, Japan
| | - Tomoatsu Mune
- Division of Diabetes, Endocrinology and Metabolism, Kawasaki Medical School, 577 Matsushima, Kurashiki 701-0192, Japan
| | - Michihiro Matsuki
- Division of Diabetes, Endocrinology and Metabolism, Kawasaki Medical School, 577 Matsushima, Kurashiki 701-0192, Japan
| | - Kohei Kaku
- Division of Diabetes, Endocrinology and Metabolism, Kawasaki Medical School, 577 Matsushima, Kurashiki 701-0192, Japan
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