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Comparative effectiveness of metformin versus sulfonylureas on kidney function decline or death among patients with reduced kidney function: a retrospective cohort study

Adriana M. Hung, Amber J. Hackstadt, Marie R. Griffin, Carlos G. Grijalva, Robert A. Greevy and Christianne L. Roumie
January 31, 2023 11 (1) E77-E89; DOI: https://doi.org/10.9778/cmajo.20210207
Adriana M. Hung
Department of Medicine, Division of Nephrology and Hypertension (Hung), Vanderbilt University Medical Center; Precision Nephrology Program (Hung), Vanderbilt University Medical Center; Geriatric Research Education Clinical Center (Hung, Hackstadt, Grijalva, Greevy Jr., Roumie), Veteran Administration Tennessee Valley Healthcare System; Department of Medicine (Roumie), Vanderbilt University Medical Center; Department of Biostatistics (Hackstadt, Greevy Jr.), Vanderbilt University School of Medicine; Department of Health Policy (Griffin, Grijalva, Roumie), Vanderbilt University Medical Center, Nashville, Tenn.
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Amber J. Hackstadt
Department of Medicine, Division of Nephrology and Hypertension (Hung), Vanderbilt University Medical Center; Precision Nephrology Program (Hung), Vanderbilt University Medical Center; Geriatric Research Education Clinical Center (Hung, Hackstadt, Grijalva, Greevy Jr., Roumie), Veteran Administration Tennessee Valley Healthcare System; Department of Medicine (Roumie), Vanderbilt University Medical Center; Department of Biostatistics (Hackstadt, Greevy Jr.), Vanderbilt University School of Medicine; Department of Health Policy (Griffin, Grijalva, Roumie), Vanderbilt University Medical Center, Nashville, Tenn.
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Marie R. Griffin
Department of Medicine, Division of Nephrology and Hypertension (Hung), Vanderbilt University Medical Center; Precision Nephrology Program (Hung), Vanderbilt University Medical Center; Geriatric Research Education Clinical Center (Hung, Hackstadt, Grijalva, Greevy Jr., Roumie), Veteran Administration Tennessee Valley Healthcare System; Department of Medicine (Roumie), Vanderbilt University Medical Center; Department of Biostatistics (Hackstadt, Greevy Jr.), Vanderbilt University School of Medicine; Department of Health Policy (Griffin, Grijalva, Roumie), Vanderbilt University Medical Center, Nashville, Tenn.
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Carlos G. Grijalva
Department of Medicine, Division of Nephrology and Hypertension (Hung), Vanderbilt University Medical Center; Precision Nephrology Program (Hung), Vanderbilt University Medical Center; Geriatric Research Education Clinical Center (Hung, Hackstadt, Grijalva, Greevy Jr., Roumie), Veteran Administration Tennessee Valley Healthcare System; Department of Medicine (Roumie), Vanderbilt University Medical Center; Department of Biostatistics (Hackstadt, Greevy Jr.), Vanderbilt University School of Medicine; Department of Health Policy (Griffin, Grijalva, Roumie), Vanderbilt University Medical Center, Nashville, Tenn.
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Robert A. Greevy Jr.
Department of Medicine, Division of Nephrology and Hypertension (Hung), Vanderbilt University Medical Center; Precision Nephrology Program (Hung), Vanderbilt University Medical Center; Geriatric Research Education Clinical Center (Hung, Hackstadt, Grijalva, Greevy Jr., Roumie), Veteran Administration Tennessee Valley Healthcare System; Department of Medicine (Roumie), Vanderbilt University Medical Center; Department of Biostatistics (Hackstadt, Greevy Jr.), Vanderbilt University School of Medicine; Department of Health Policy (Griffin, Grijalva, Roumie), Vanderbilt University Medical Center, Nashville, Tenn.
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Christianne L. Roumie
Department of Medicine, Division of Nephrology and Hypertension (Hung), Vanderbilt University Medical Center; Precision Nephrology Program (Hung), Vanderbilt University Medical Center; Geriatric Research Education Clinical Center (Hung, Hackstadt, Grijalva, Greevy Jr., Roumie), Veteran Administration Tennessee Valley Healthcare System; Department of Medicine (Roumie), Vanderbilt University Medical Center; Department of Biostatistics (Hackstadt, Greevy Jr.), Vanderbilt University School of Medicine; Department of Health Policy (Griffin, Grijalva, Roumie), Vanderbilt University Medical Center, Nashville, Tenn.
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    Figure 1:

    Study flowchart. Note: VA = Veterans Affairs.

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    Figure 2:

    Full Aalen–Johansen cumulative probability plot of a kidney event (i.e., 40% decline in estimated glomerular filtration rate or end-stage renal disease) or death (panel A) or of a kidney event (panel B) in the weighted cohort for the first 360 days after reaching an estimated glomerular filtration rate less than 60 mL/min/1.73 m2 by treatment group. Note: Met = metformin, Sul = sulfonylurea.

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    Figure 3:

    Full Aalen–Johansen cumulative probability of a kidney event (i.e., 40% decline in estimated glomerular filtration rate or end-stage renal disease) or death (panel A) or of a kidney event (panel B) in the weighted cohort for those who persisted on their treatment for at least 361 days after reaching an estimated glomerular filtration rate less than 60 mL/min/1.73 m2 by treatment group. Note: Met = metformin, Sul = sulfonylurea.

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    Figure 4:

    Propensity score–weighted hazard ratios (HRs) for the primary and secondary outcomes by subgroup for patients persistent on therapy at 361 days after reaching an estimated glomerular filtration rate (eGFR) less than 60 mL/min/1.73 m2. Note: CI = confidence interval.

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    Table 1:

    Patient characteristics on index date of kidney function decline and at 361 days after the index date for persistent patients

    CharacteristicNo. (%) of patients in propensity score–weighted cohort at index date*SMD†No. (%) of patients in propensity score–weighted cohort at 361 dSMD†
    Metformin
    n = 24 883
    Sulfonylureas
    n = 24 998
    Metformin
    n = 12 571
    Sulfonylureas
    n = 12 637
    Age, yr, median (IQR)70.7 (63.7–78.1)70.5 (63.7–78.1)0.00172.5 (65.4–79.5)72.2 (65.3–79.4)0.003
    Sex, male24362 (97.9)24476 (97.9)0.00112334 (98.1)12406 (98.2)0.004
    Race
     White20908 (84.0)21007 (84.0)0.00210918 (86.9)10982 (86.9)0.002
     Black3503 (14.1)3512 (14.0)1424 (11.3)1430 (11.3)
     Other‡472 (1.9)479 (1.9)229 (1.8)226 (1.8)
    Time from cohort entry to kidney threshold, mo, median (IQR)14.2 (5.9–30.7)14.3 (6.1–30.9)0.01428.4 (18.9–45.4)28.6 (19.0–45.6)0.009
    Year reached kidney threshold
     2002–20032815 (11.3)2808 (11.2)0.0271568 (12.5)1545 (12.2)0.038
     2004–20054308 (17.3)4268 (17.1)2236 (17.8)2234 (17.7)
     2006–20075005 (10.1)5216 (20.9)2722 (21.7)2853 (22.6)
     2008–20093726 (15.0)3781(15.1)1983 (15.8)1999 (15.8)
     2010–20113291 (13.2)3207 (12.8)1737 (13.8)1673 (13.2)
     2012–20132603 (10.5)2556 (10.2)1281(10.2)1254 (9.9)
     2014–20152164 (8.7)2181 (8.7)1038 (8.2)1076 (8.5)
     2016971 (3.9)981 (3.9)5 (0.0)3 (0.0)
    Laboratory variables
     HbA1c, %, median (IQR)6.5 (6.1–7.1)6.5 (6.1–7.2)0.0076.5 (6.1–7.0)6.50 (6.0–7.1)0.007
     Missing HbA1C measure1011 (4.1)994 (4.0)0.004503 (4.0)488 (3.9)
     Historical eGFR before kidney threshold, mL/min/1.73 m2, median (IQR)§69.3 (64.5–76.6)69.3 (64.5–76.6)0.001––
     eGFR at kidney threshold, mL/min/1.73 m2, median (IQR)55.6 (51.4–58.0)55.6 (51.4–58.0)0.00255.9 (52.2–58.1)55.8 (52.2–58.2)0.003
     eGFR at 361 days, mL/min/1.73 m2, median (IQR)––63.5 (55.8–72.3)63.7 (55.7–72.3)0.007
     Missing eGFR293 (1.2)296 (1.2)0.001964 (7.7)957 (7.6)0.004
     Hemoglobin, g/dL, median (IQR)14.0 (13.0–15.1)14.1 (13.0–15.1)0.00313.9 (12.9–14.9)14.0 (12.9–15.0)0.004
     Missing hemoglobin1507 (6.1)1503 (6.0)0.002777 (6.2)792 (6.3)0.003
     Low-density lipoprotein, mmol/L, median (IQR)2.28 (1.81–2.82)2.28 (1.81–2.82)0.0022.18 (1.76–2.64)2.18 (1.76–2.67)0.001
     Missing low-density lipoprotein measure779 (3.1)781 (3.1)< 0.001310 (2.5)309 (2.4)0.004
    Microalbumin-to-creatinine ratio stage
     Normal (< 30 mg/g)9616 (38.6)9670 (38.7)0.0035261 (41.9)5305 (42.0)0.003
     Microalbuminuria (30–300 mg/g)2775 (11.2)2771.0 (11.1)1516 (12.1)1523 (12.1)
     Macroalbuminuria (> 300 mg/g)788 (3.2)781.6 (3.1)370 (2.9)373 (3.0)
    Missing microalbumin-to-creatinine ratio11703 (47.0)11775 (47.1)5424 (43.1)5436 (43.0)
    Proteinuria by urinalysis
     Negative11736 (47.2)11787 (47.2)0.0026101 (48.5)6129 (48.5)0.002
     Urine protein trace or 1+3533 (14.2)3561 (14.2)1700 (13.5)1711 (13.5)
     Proteinuria present at 2+831 (3.3)838 (3.4)330 (2.6)330 (2.6)
     Proteinuria present at 3+ or 4+336 (1.3)336 (1.3)127 (1.0)126 (1.0)
    Unknown urine protein measure8446 (33.9)8476 (33.9)4313 (34.3)4341 (34.4)
    Clinical variables
     Systolic blood pressure, mm Hg, median (IQR)131 (119–142)131 (119–142)0.002132 (120–142)132 (121–142)0.005
     Diastolic blood pressure, mm Hg, median (IQR)72 (64–80)72 (64–80)0.00172 (64–79)72 (64–79)0.001
     BMI, median (IQR)30.3 (27.0–34.4)30.3 (27.0–34.3)0.00330.2 (27.0–34.2)30.2 (27.0–34.1)0.001
     Missing BMI measure4688 (18.8)4719 (18.9)0.0012290 (18.2)2306 (18.3)0.003
    Baseline comorbidities
     Malignant disease¶2971 (11.9)2990 (12.0)0.0011622 (12.9)1622 (12.8)0.002
     Liver disease625 (2.5)621 (2.5)0.002230 (1.8)229 (1.8)0.001
     HIV89 (0.4)90 (0.4)0.00139 (0.3)40 (0.3)0.001
     Congestive heart failure3051 (12.3)3071 (12.3)0.0011580 (12.6)1592 (12.6)0.001
     Cardiovascular disease7935 (31.9)8006 (32.0)0.0033987 (31.7)4019 (31.8)0.002
     Stroke831 (3.3)827 (3.3)0.002399 (3.2)401 (3.2)< 0.01
     Transient ischemic attack322 (1.3)332 (1.3)0.003155 (1.2)153 (1.2)0.002
     Serious mental illness**4957 (19.9)5035 (20.1)0.0052401 (19.1)2430 (19.2)0.003
     Smoking3045 (12.2)3068 (12.3)0.0011262 (10.0)1263 (10.0)0.002
     Chronic obstructive pulmonary disease4284 (17.2)4321 (17.3)0.0022157 (17.2)2166 (17.1)< 0.01
     History of respiratory failure821 (3.3)821 (3.3)0.001543 (4.3)533 (4.2)0.005
     History of sepsis406 (1.6)414 (1.7)0.002291 (2.3)291 (2.3)0.001
     History of pneumonia1074 (4.3)1092 (4.4)0.003648 (5.2)640 (5.1)0.004
     Arrhythmia4387 (17.6)4418 (17.7)0.0012399 (19.1)2414 (19.1)< 0.01
     Cardiac valve disease919 (3.7)929 (3.7)0.001497 (4.0)503 (4.0)0.002
     Parkinson disease234 (0.9)237 (0.9)0.001162 (1.3)158 (1.3)0.003
     Urinary tract infection1055 (4.2)1067 (4.3)0.001640 (5.1)645 (5.1)0.001
     Osteomyelitis156 (0.6)154 (0.6)0.00265 (0.5)64 (0.5)0.002
     Osteoporosis200 (0.8)206 (0.8)0.002118 (0.9)115 (0.9)0.003
     Falls57 (0.2)59 (0.2)0.00259 (0.5)57 (0.4)0.003
     Fractures556 (2.2)556 (2.2)0.001315 (2.5)313 (2.5)0.002
     Amputation118 (0.5)123 (0.5)0.00255 (0.4)55 (0.4)0.001
     Retinopathy286 (1.1)287 (1.1)< 0.001117 (0.9)121 (1.0)0.003
    Use of medications
     Angiotensin-converting enzyme inhibitors15958 (64.1)16080 (64.3)0.0047623 (60.6)7690 (60.9)0.004
     Angiotensin II receptor blockers2904 (11.7)2904 (11.6)0.0021647 (13.1)1644 (13.0)0.003
     β-blockers12699 (51.0)12770 (51.1)0.0016533 (52.0)6565 (51.9)< 0.01
     Calcium-channel blockers7417 (29.8)7454 (29.8)< 0.0013801 (30.2)3820 (30.2)< 0.01
     Thiazide- and potassium-sparing diuretics10072 (40.5)10169 (40.7)0.0044531 (36.0)4578 (36.2)0.004
     Loop diuretics5059 (20.3)5087 (20.3)< 0.0012433 (19.4)2448 (19.4)0.001
     Other antihypertensive medications6873 (27.6)6887 (27.6)0.0023834 (30.5)3834 (30.3)0.003
     Statin lipid-lowering drugs16763 (67.4)16917 (67.7)0.0079059 (72.1)9119 (72.2)0.002
     Nonstatin lipid-lowering agents4237 (17.0)4264 (17.1)0.0012275 (18.1)2280 (18.0)0.002
     Antiarrhythmic drugs, digoxin and inotropes2313 (9.3)2321 (9.3)< 0.0011072 (8.5)1078 (8.5)< 0.01
     Anticoagulant drugs and platelet inhibitors2578 (10.4)2588 (10.4)< 0.0011386 (11.0)1394 (11.0)< 0.01
     Nitrates3652 (14.7)3689 (14.8)0.0021716 (13.6)1739 (13.8)0.003
     ASA5332 (21.4)5385 (21.5)0.0032533 (20.1)2570 (20.3)0.005
     Non-ASA platelet inhibitors2643 (10.6)2660 (10.6)0.0011329 (10.6)1343 (10.6)0.002
     Antipsychotic drugs1662 (6.7)1685 (6.7)0.003747 (5.9)745 (5.9)0.002
     Oral glucocorticoids1823 (7.3)1845 (7.4)0.002894 (7.1)892 (7.1)0.002
    Indicators of health care use††
     Admitted to hospital within year (Veterans Health)3550 (14.3)3600 (14.4)0.0041510 (12.0)1538 (12.2)0.005
     Admitted to hospital in 30 days (Veterans Health)934 (3.8)953 (3.8)0.003188 (1.5)187 (1.5)0.001
     Admitted to hospital within year (Medicare/Medicaid)2851 (11.5)2860 (11.4)< 0.0011521 (12.1)1507 (11.9)0.005
     Admitted to hospital in 30 days (Medicare/Medicaid)450 (1.8)461 (1.8)0.003197 (1.6)198 (1.6)< 0.01
     Medicaid use in previous year298 (1.2)307 (1.2)0.003143 (1.1)142 (1.1)0.001
     Medicare use in previous year9128 (36.7)9129 (36.5)0.0035221 (41.5)5213 (41.3)0.006
     Nursing home encounter in previous year97 (0.4)102 (0.4)0.00366 (0.5)67 (0.5)< 0.01
     Medicare Advantage use3979 (16.0)3998 (16.0)< 0.0012498 (19.9)2517 (19.9)0.001
    • Note: ASA = acetylsalicylic acid, BMI = body mass index, eGFR = estimated glomerular filtration rate, IQR = interquartile range, SMD = standardized mean difference.

    • ↵* Unless indicated otherwise.

    • ↵† Standardized mean differences are the absolute difference in means or percentage divided by an evenly weighted pooled standard deviation, or the difference between groups in number of standard deviations. In the weighted cohort, all standardized differences were less than 0.01, suggesting there were no important imbalances.

    • ↵‡ Other races include American Indian or Alaska Native, Asian, and Native Hawaiian or Pacific Islander.

    • ↵§ Historical eGFR is the eGFR before the patient met the inclusion criteria of eGFR < 60 mL/min/1.73 m2; eGFR at kidney threshold indicates the eGFR when the patient met the inclusion criteria of eGFR < 60 mL/min/1.73 m2.

    • ↵¶ Malignant disease includes all types of cancer except nonmelanoma skin cancer.

    • ↵** Serious mental illness included schizophrenia, depression, bipolar disorder, dementia and post-traumatic stress disorder.

    • ↵†† The Veterans Health Administration provides health care coverage for those who serve their country through military services. Medicare and Medicaid health services are federal health care programs for eligible people older than 65 years. Medicare Advantage is a Medicare plan offered by private insurers that provides hospital, outpatient and (usually) prescription drug coverage, supplanting benefits under other Medicare plans.

    • View popup
    Table 2:

    Rates and hazard ratios for kidney composite outcomes among patients who persisted on metformin or sulfonylurea in matched weighted cohort in first 360 days and from day 361 onward of reaching reduced kidney function threshold*

    Outcomeirst 360 days361 days onward
    Metformin
    n = 24 883
    Sulfonylurea
    n = 24 998
    Metformin
    n = 12 571
    Sulfonylurea
    n = 12 637
    Primary outcome: kidney events or death
     Number of events5767867471033
     Person-time, yr17194182782819128429
     Events per 1000 person-years (95% CI)33.5 (30.9–36.3)43.0 (40.1–46.0)26.5 (24.7–28.5)36.3 (34.2–38.6)
     PS-weighted HR, unadjusted (95% CI)0.78 (0.71–0.85)Ref.0.73 (0.67–0.79)Ref.
     PS-weighted HR, adjusted* (95% CI)0.79 (0.72–0.87)Ref.0.76 (0.70–0.83)Ref.
    Secondary outcome: kidney events
     Number of events4956110149
     Person-time, yr17194182782819128429
     Events rates per 1000 person-years (95% CI)2.9 (2.2–3.8)3.1 (2.4–4.0)3.9 (3.2–4.7)5.2 (4.5–6.1)
     PS-weighted HR, unadjusted (95% CI)0.94 (0.67–1.33)Ref.0.73 (0.59–0.91)Ref.
    Secondary outcome: death
     Number of events527730642903
     Person-time, yr17201183002824028717
     Events rates per 1000 person-years (95% CI)30.6 (28.2–33.3)40 (37.2–42.9)22.7 (21.0–24.5)31.5 (29.5–33.5)
     PS-weighted HR, unadjusted (95% CI)0.76 (0.69–0.84)Ref.0.72 (0.66–0.79)Ref.
    • Note: HR = hazard ratio, PS = propensity score, Ref. = reference category.

    • ↵* Cox Proportional Hazards model for time to event. Adjusted for demographics, clinical information derived from the electronic health record, comorbidities, use of medications and health care utilization (see Appendix 1, Supplemental Table 1, available at www.cmajopen.ca/content/11/1/E77/suppl/DC1). All continuous variables were modelled as restricted cubic splines. All covariates in PS model included in the PS-weighted and adjusted model (see Appendix 1, Supplemental Table 1).

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Comparative effectiveness of metformin versus sulfonylureas on kidney function decline or death among patients with reduced kidney function: a retrospective cohort study
Adriana M. Hung, Amber J. Hackstadt, Marie R. Griffin, Carlos G. Grijalva, Robert A. Greevy, Christianne L. Roumie
Jan 2023, 11 (1) E77-E89; DOI: 10.9778/cmajo.20210207

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Comparative effectiveness of metformin versus sulfonylureas on kidney function decline or death among patients with reduced kidney function: a retrospective cohort study
Adriana M. Hung, Amber J. Hackstadt, Marie R. Griffin, Carlos G. Grijalva, Robert A. Greevy, Christianne L. Roumie
Jan 2023, 11 (1) E77-E89; DOI: 10.9778/cmajo.20210207
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