Reporting and variability of constructing medication treatment episodes in pharmacoepidemiology studies: A methodologic systematic review using the case study of DPP-4 inhibitors and cardiovascular outcomes.
exposure
methods
pharmacoepidemiology
prescription claims
study design
systematic review
Journal
Pharmacoepidemiology and drug safety
ISSN: 1099-1557
Titre abrégé: Pharmacoepidemiol Drug Saf
Pays: England
ID NLM: 9208369
Informations de publication
Date de publication:
08 2020
08 2020
Historique:
received:
28
01
2020
revised:
10
05
2020
accepted:
01
06
2020
pubmed:
15
7
2020
medline:
16
6
2021
entrez:
15
7
2020
Statut:
ppublish
Résumé
In pharmacoepidemiologic studies, estimating medication adherence, persistence, and exposure patterns is critical. Constructing medication treatment episodes from prescription claims data involves assumptions related to grace period, carry-over, and lag effect, but there are no guidelines for these assumptions. We evaluated reporting and variability of these parameters in pharmacoepidemiology studies, using a case study of antihyperglycemic medications and major adverse cardiovascular events (MACE). We conducted a systemic review using MEDLINE and EMBASE for studies published prior to January 2, 2020 comparing the risk of MACE between dipeptidyl peptidase 4 (DPP-4) inhibitors and active comparators. We extracted study characteristics and results, including grace period, carry-over, and lag effect. Risk of bias was assessed by the Newcastle-Ottawa scale, and assessments for prevalent user, immortal time, time lag, and time window biases. A total of 14/1850 studies identified were included. Grace period was not reported in 5 (35.7%) studies and ranged from 0 days to 180 days when reported. Carry-over was not reported in 10 studies (71.4%). Lag effect was not reported in nine (71.4%) studies and ranged from 0 days to 180 days when reported. No studies conducted sensitivity analyses examining the effects of these assumptions on study findings. Predominant biases were inadequate follow-up time, comparability of cohorts, prevalent use, and lag time bias. Use of grace period, carry-over, and lag effect were poorly reported and highly variable. Future pharmacoepidemiology studies should improve reporting, justify ranges for these parameters, and conduct sensitivity analyses to evaluate effects of these assumptions.
Substances chimiques
Dipeptidyl-Peptidase IV Inhibitors
0
Types de publication
Journal Article
Systematic Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
939-950Informations de copyright
© 2020 John Wiley & Sons Ltd.
Références
Framework for FDA's Real-World Evidence Program. 2018. www.fda.gov/media/120060/download.
Montastruc JL, Sommet A, Montastruc F, et al. Pharmacoepidemiology: definition, methods and applications. Bull Acad Natl Med. 2015;199(2-3):263-273.
Gardarsdottir H, Souverein PC, Egberts TC, Heerdink ER. Construction of drug treatment episodes from drug-dispensing histories is influenced by the gap length. J Clin Epidemiol. 2010;63(4):422-427.
Velentgas P, Dreyer NA, Nourjah P, Smith SR, Torchia MM, eds. Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide. Rockville, MD: Agency for Healthcare Research and Quality; January 2013. www.effectivehealthcare.ahrq.gov/Methods-OCER.cfm.
van Staa TP, Abenhaim L, Leufkens H. A study of the effects of exposure misclassification due to the time-window design in pharmacoepidemiologic studies. J Clin Epidemiol. 1994;47(2):183-189.
Pottegard A, Friis S, Sturmer T, Hallas J, Bahmanyar S. Considerations for pharmacoepidemiological studies of drug-cancer associations. Basic Clin Pharmacol Toxicol. 2018;122(5):451-459.
Capoccia K, Odegard PS, Letassy N. Medication adherence with diabetes medication: a systematic review of the literature. Diabetes Educ. 2016;42(1):34-71.
Cramer JA. A systematic review of adherence with medications for diabetes. Diabetes Care. 2004;27(5):1218-1224.
Pye SR, Sheppard T, Joseph RM, et al. Assumptions made when preparing drug exposure data for analysis have an impact on results: An unreported step in pharmacoepidemiology studies. Pharmacoepidemiol Drug Saf. 2018;27(7):781-788.
Tanskanen A, Taipale H, Koponen M, et al. From prescription drug purchases to drug use periods-A second generation method (PRE2DUP). BMC Med Inform Decis Mak. 2015;15:21.
Best Practices for Conducting and Reporting Pharmacoepidemiologic Safety Studies Using Electronic Healthcare Data. In: Administration USDoHaHSFaD, ed2013.
Langan SM, Schmidt SA, Wing K, et al. The reporting of studies conducted using observational routinely collected health data statement for pharmacoepidemiology (RECORD-PE). BMJ. 2018;363:k3532.
Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ. 2009;339:b2700.
Pazzagli L, Linder M, Zhang M, et al. Methods for time-varying exposure related problems in pharmacoepidemiology: An overview. Pharmacoepidemiol Drug Saf. 2018;27(2):148-160.
Wu JW, Filion KB, Azoulay L, Doll MK, Suissa S. Effect of long-acting insulin analogs on the risk of cancer: a systematic review of observational studies. Diabetes Care. 2016;39(3):486-494.
GA Wells BS, D O'Connell, J Peterson, V Welch, M Losos, P Tugwell,. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp. Accessed January 9, 2019.
Komamine M, Kajiyama K, Ishiguro C, Uyama Y. Cardiovascular risks associated with dipeptidyl peptidase-4 inhibitors monotherapy compared with other antidiabetes drugs in the Japanese population: a nationwide cohort study. Pharmacoepidemiol Drug Saf. 2019;28(9):1166-1174.
Rosenstock J, Kahn SE, Johansen OE, et al. Effect of Linagliptin vs glimepiride on major adverse cardiovascular outcomes in patients with type 2 diabetes: the CAROLINA randomized clinical trial. Jama. 2019.322(12):1155-1166.
Green JB, Bethel MA, Armstrong PW, et al. Effect of sitagliptin on cardiovascular outcomes in type 2 diabetes. N Engl J Med. 2015;373(3):232-242.
Scirica BM, Bhatt DL, Braunwald E, et al. Saxagliptin and cardiovascular outcomes in patients with type 2 diabetes mellitus. N Engl J Med. 2013;369(14):1317-1326.
Rosenstock J, Perkovic V, Johansen OE, et al. Effect of linagliptin vs placebo on major cardiovascular events in adults with type 2 diabetes and high cardiovascular and renal risk: the CARMELINA randomized clinical trial. JAMA. 2018.321(1):69-79.
White WB, Cannon CP, Heller SR, et al. Alogliptin after acute coronary syndrome in patients with type 2 diabetes. N Engl J Med. 2013;369(14):1327-1335.
Gardarsdottir H, Egberts TC, Heerdink ER. The association between patient-reported drug taking and gaps and overlaps in antidepressant drug dispensing. Ann Pharmacother. 2010;44(11):1755-1761.
Nielsen LH, Lokkegaard E, Andreasen AH, Keiding N. Using prescription registries to define continuous drug use: how to fill gaps between prescriptions. Pharmacoepidemiol Drug Saf. 2008;17(4):384-388.
Izem R, Huang TY, Hou L, Pestine E, Nguyen M, Maro JC. Quantifying how small variations in design elements affect risk in an incident cohort study in claims. Pharmacoepidemiol Drug Saf. 2020;29(1):84-93.
Renoux C, Dell'Aniello S, Brenner B, Suissa S. Bias from depletion of susceptibles: the example of hormone replacement therapy and the risk of venous thromboembolism. Pharmacoepidemiol Drug Saf. 2017;26(5):554-560.
Tanskanen A, Taipale H, Koponen M, et al. From prescriptions to drug use periods-things to notice. BMC Res Notes. 2014;7:796.
Chan CW, Yu CL, Lin JC, et al. Glitazones and alpha-glucosidase inhibitors as the second-line oral anti-diabetic agents added to metformin reduce cardiovascular risk in type 2 diabetes patients: a nationwide cohort observational study. Cardiovasc Diabetol. 2018;17(1):20.
Cho YY, Cho SI. Metformin combined with dipeptidyl peptidase-4 inhibitors or metformin combined with sulfonylureas in patients with type 2 diabetes: a real world analysis of the south Korean national cohort. Metabolism. 2018;85:14-22.
Enders D, Kollhorst B, Engel S, Linder R, Verheyen F, Pigeot I. Comparative risk for cardiovascular diseases of dipeptidyl peptidase-4 inhibitors vs. sulfonylureas in combination with metformin: results of a two-phase study. J Diabetes Complications. 2016;30(7):1339-1346.
Eriksson JW, Bodegard J, Nathanson D, Thuresson M, Nystrom T, Norhammar A. Sulphonylurea compared to DPP-4 inhibitors in combination with metformin carries increased risk of severe hypoglycemia, cardiovascular events, and all-cause mortality. Diabetes Res Clin Pract. 2016;117:39-47.
Jil M, Rajnikant M, Richard D, Iskandar I. The effects of dual-therapy intensification with insulin or dipeptidylpeptidase-4 inhibitor on cardiovascular events and all-cause mortality in patients with type 2 diabetes: a retrospective cohort study. Diab Vasc Dis Res. 2017;14(4):295-303.
Kim KJ, Choi J, Lee J, et al. Dipeptidyl peptidase-4 inhibitor compared with sulfonylurea in combination with metformin: cardiovascular and renal outcomes in a propensity-matched cohort study. Cardiovasc Diabetol. 2019;18(1):28.
Morgan CL, Poole CD, Evans M, Barnett AH, Jenkins-Jones S, Currie CJ. What next after metformin? A retrospective evaluation of the outcome of second-line, glucose-lowering therapies in people with type 2 diabetes. J Clin Endocrinol Metab. 2012;97(12):4605-4612.
Morgan CL, Mukherjee J, Jenkins-Jones S, Holden SE, Currie CJ. Combination therapy with metformin plus sulphonylureas versus metformin plus DPP-4 inhibitors: association with major adverse cardiovascular events and all-cause mortality. Diabetes Obes Metab. 2014;16(10):977-983.
Moura CS, Rosenberg ZB, Abrahamowicz M, Bernatsky S, Behlouli H, Pilote L. Treatment discontinuation and clinical events in type 2 diabetes patients treated with dipeptidyl peptidase-4 inhibitors or NPH insulin as third-line therapy. J Diabetes Res. 2018;2018:4817178.
Nystrom T, Bodegard J, Nathanson D, Thuresson M, Norhammar A, Eriksson JW. Second line initiation of insulin compared with DPP-4 inhibitors after metformin monotherapy is associated with increased risk of all-cause mortality, cardiovascular events, and severe hypoglycemia. Diabetes Res Clin Pract. 2017;123:199-208.
Ou SM, Shih CJ, Chao PW, et al. Effects on clinical outcomes of adding dipeptidyl peptidase-4 inhibitors versus sulfonylureas to metformin therapy in patients with type 2 diabetes mellitus. Ann Intern Med. 2015;163(9):663-672.
Scheller NM, Mogensen UM, Andersson C, Vaag A, Torp-Pedersen C. All-cause mortality and cardiovascular effects associated with the DPP-IV inhibitor sitagliptin compared with metformin, a retrospective cohort study on the Danish population. Diabetes Obes Metab. 2014;16(3):231-236.
Yu OH, Yin H, Azoulay L. The combination of DPP-4 inhibitors versus sulfonylureas with metformin after failure of first-line treatment in the risk for major cardiovascular events and death. Can J Diabetes. 2015;39(5):383-389.