demystifying of Metformin

1. Demystifying
“METFORMIN”
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2. Lactic acidosis
 "Metformin-associated lactic acidosis" or MALA
 Nine cases per 100,000 person-years.
 However, most of the reported cases have occurred in
patients with severe acute conditions
 Metformin got FDA approval in 1995
 This raises the question of whether patients with type
2 diabetes mellitus have an increased risk for
developing lactic acidosis with Metformin use
compared with other glucose-lowering treatments.
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4. 1. Metformin in Renal impairment
2. Metformin in pregnancy
3. Metformin in Cirrhosis
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5. KDOQI CLINICAL PRACTICE GUIDELINE FOR DIABETES
AND CKD:
2012 UPDATE KDIGO
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6. What about Metformin in pregnancy?
 Clinical experience and the evidence support
Metformin use in pregnancy with respect to
the immediate pregnancy outcomes.
 However, does the use of Metformin in
pregnancy ultimately have a beneficial,
neutral, or deleterious effect on the offspring?
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8. So, what about Metformin in Cirrhosis!, then?
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12. Relevance to Clinical Practice
 12th leading cause of mortality globally
 The prevalence of type 2, five times greater than in those without
cirrhosis.
 Liver-related complications and death than patients with cirrhosis
without diabetes.
 The risk of death from cirrhosis among diabetic patients was greater
than in the general population, with a standardized mortality ratio of
2.5, which is even higher than the mortality ratio of 1.3 conferred by
cardiovascular disease in patients with diabetes.
 Therefore, it is important to improve cirrhosis-related mortality in
diabetic patients
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13. Nonalcoholic fatty liver disease (NAFLD) appears to partially
mediate an increased risk of liver-related death among patients
with diabetes. The presence of NAFLD increased deaths in diabetic
patients, with a hazard ratio (HR) of 2.2, with 19% of deaths being
liver related.
Metformin prevented and reversed steatosis and inflammation in
a nondiabetic mouse model of nonalcoholic steatohepatitis (NASH)
and improved liver histology and alanine minotransferase (ALT)
levels in patients with NASH.
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14. Primary aim of the study
 Assess the survival difference between
diabetic patients who continued taking
Metformin versus those who discontinued
Metformin after cirrhosis diagnosis.
 Find out other factors that would determine
the survival outcomes in patients with
cirrhosis with diabetes.
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15. Patients and Methods
 Diabetic patients diagnosed with cirrhosis
between January 1, 2000 and December 31, 2010
and who were on Metformin at cirrhosis
diagnosis were included in this study (n = 250).
 Patients were categorized into two groups, that
is, those who continued Metformin after cirrhosis
diagnosis and those who discontinued Metformin
after cirrhosis diagnosis.
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16.  Diagnosis of cirrhosis
 by histology (n = 124)
 by clinical features, namely,
 portal hypertension (PH)
 morphologic characteristics consistent with cirrhosis in cross-
sectional radiologic images (small-sized nodular liver 6
caudate lobe hypertrophy
 PH indicated by the presence of collateral vessels,
varices, and/or splenomegaly), and/or
thrombocytopenia (platelet count <150 K).
 Diabetes was defined by a physician note, self-
reported medical history, or the American
Diabetes Association criteria
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17. Baseline characteristics of patients
Out of the 250 diabetic patients on Metformin
at the time of cirrhosis diagnosis,
 172 (68.8%) continued Metformin whereas 78 (31.2%)
discontinued Metformin.
 142 (56.8%) were male with a mean age of 61.2 years
 181 (73.3%) had Child-Pugh class A cirrhosis.
 The etiologies of cirrhosis were NASH (56.8%), ALD (11.6%),
HCV (12.0%), HBV (2.4%), others (5.6%), and unknown
(11.6%).
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18. Exclusion criteria
 History of malignancy except for nonmelanoma
skin cancer at cirrhosis diagnosis
 Incomplete clinical information
 Age <18 years
 Discontinuation of metformin before cirrhosis
diagnosis
 Initiation of metformin after cirrhosis diagnosis
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19. Statistical Analysis
 Student t test for continuous variables and the chi-square test for
categorical variables
 Survival of patients in both groups was estimated using Kaplan-
Meier’s method and compared using the log-rank test
 Associations between predictor variables and survival were
determined by HR and 95% confidence interval (CI) calculated using
Cox proportional hazards regression
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20. Reasons for discontinuation of
METFORMIN
 Diagnosis of cirrhosis (n = 61; 78% of patients
who discontinued Metformin),
 Uncontrolled plasma glucose (n = 55)
 Elevated serum creatinine (n = 53)
 Diarrhea (n = 2)
 Well-controlled plasma glucose level (n = 52)
 Switching to insulin therapy (n = 52)
 Unstated reasons during hospitalization (n = 52)
 Heart disease (n = 51).
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21.  Selected MELD score in the multivariate
analysis because MELD score better correlates
with severity of liver impairment than the
Child-Pugh classification
 Thus, the potential effect of MELD score on
outcome was assessed in subsequent
analyses.
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22. Survival of Patients Who Continued Metformin Versus Those
Who Discontinued Metformin After Cirrhosis Diagnosis.
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26. Strength of the study
• Largest cohort of unselected patients with cirrhosis with
diabetes in which the effect of Metformin use has been
investigated.
• Patients with cirrhosis with diabetes who have various
causes of cirrhosis and a wide range of degrees of severity
of liver impairment.
• Therefore, this study has contributed significantly to filling
the knowledge gap in the debate on whether Metformin
can be safely prescribed to patients with cirrhosis.
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27. Our study revealed the novel observation of an
association between Metformin use and
improved survival in a cohort of patients with
cirrhosis with diabetes.
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28. conclusion
• Continuation of Metformin after cirrhosis
diagnosis reduced the risk of death by 57%.
• Metformin should therefore be continued in
diabetic patients with cirrhosis if there is no
specific contraindication.
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29. Limitations of the study
 Sample size of the study was not large enough to sustain the
multivariate model
 Not able to take into consideration the effect of dose or
duration of Metformin treatment on survival.
 Not able to determine the minimum effective dose of
Metformin that resulted in improved survival of patients with
cirrhosis.
 Prevalence of macrovasular and micro vascular diseases among
diabetics has not taken in to consideration.
 Retrospective study design, detailed information on use of
antidiabetic agents was not always available
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30. Questions to be answered
A number of research questions should be further investigated.
 It is worth examining the effect of Metformin on survival of
patients with non-NASH cirrhosis in a larger cohort.
 Whether initiating Metformin subsequent to diagnosis of
cirrhosis
 Does Metformin has an antifibrotic effect that would slow
down progression or reverse the degree of liver fibrosis.
 Metformin also improves the outcomes of patients with
cirrhosis with impaired glucose tolerance.
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31. Take home message
These study results justify the continuation of
Metformin therapy in patients with diabetes and
cirrhosis from a safety standpoint and provide
compelling evidence of a survival benefit,
especially among patients with NASH-related
cirrhosis.
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32. Future challenges
Validation of these results in a larger cohort
would support continuation of Metformin use
in NASH-related cirrhosis.
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33. Thank you!
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34. Kaplan–Meier estimator
 Is an estimator for estimating the survival
function from lifetime data.
 In medical research, it is often used to measure
the fraction of patients living for a certain
amount of time after treatment.
 Series of horizontal steps of declining
magnitude which, when a large enough sample
is taken, approaches the true survival function
for that population
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36. Proportional hazards models
 Class of survival models in statistics
 Can be viewed as consisting of two parts: the underlying hazard
function and describing how the risk of event per time unit
changes over time at baseline levels of covariates and the effect
parameters, describing how the hazard varies in response to
explanatory covariates.
 A typical medical example would include covariates such as
treatment assignment, as well as patient characteristics such as
age at start of study, gender, and the presence of other diseases
at start of study, in order to reduce variability and/or control for
confounding.
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37. • A typical medical example would include
covariates such as treatment assignment, as
well as patient characteristics such as age at
start of study, gender, and the presence of
other diseases at start of study, in order to
reduce variability and/or control for
confounding.
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