Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana
Division of General Medicine and Clinical Epidemiology and of Endocrinology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
Correspondence: Dr Patrizia Cavazzoni, Lilly Research Laboratories, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN 46285, USA. Tel: (317) 433 9485; fax: (317) 276 8682; e-mail: p_cavazzoni{at}lilly.com
Declaration of interest The study was sponsored by Eli Lilly and Company.
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ABSTRACT |
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Method From a non-diabetic cohort of patients with schizophrenia (n=5013), the relationship between baseline non-fasting glucose measurement, presence at baseline of risk factors for diabetes, weight gain and therapy assignment on the risk of treatment-emergent diabetes were assessed.
Results At the baseline assessment, about a third of patients identified with TED during treatment had non-fasting glucose levels over 7.8 mmol/l and two-thirds had multiple diabetes risk factors. Both baseline non-fasting glucose level and the presence of multiple pre-existing diabetes risk factors appeared to have a major impact on the risk of developing diabetes.
Conclusions Overall, risk factors for diabetes in patients with schizophrenia overlap those in the general population. The results also suggest that many patients identified with TED might have had pre-existing glycaemic abnormalities or a high baseline burden of diabetes risk factors.
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INTRODUCTION |
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Data from the National Health and Nutrition Examination Survey (NHANES) III (19881994) indicate that diagnosed diabetes was present in 5.1% of the US adult population (Harris et al, 1998). Subsequent reports from the Center for Disease Control have described a continued increase (about 30%) in the prevalence of diabetes during the 1990s, with the largest increase (70%) in individuals in the 3039 year age range (Mokdad et al, 2000). Further data from NHANES III suggested that diabetes was undiagnosed in as many as a third of patients (Harris et al, 1998). Results from another large survey support this finding that approximately half of patients in Australia with diabetes were undiagnosed (Dunstan et al, 2002).
The prevalence of diagnosed diabetes in patients with schizophrenia appears to exceed that of the general population by 2-fold (Dixon et al, 2000). Patients with schizophrenia generally have poorer physical health (Brown et al, 1999; Osborn 2001), and less than adequate overall health care (Phelan et al, 2001; Wang et al, 2002a) compared with the general population. The symptoms of the psychosis itself may hinder the ability or willingness of the patient to communicate potential physical probems (Felker et al, 1996; Jeste et al, 1996). Thus, it is likely that the prevalence of unrecognised diabetes in patients with schizophrenia is at least as high as that in the general population.
Reasons for an increased prevalence of diabetes among patients with schizophrenia remain speculative. However, Dixon et al (2000) reported that in a survey of several large databases containing medical information on patients with schizophrenia, the patients with diabetes were more likely to be older, non-White, and to have hypertension findings consistent with those in the general population. In a more recent review of 45 published case reports of new-onset diabetes in patients receiving atypical agents, Jin et al (2002) noted that 84% of the patients were overweight at baseline assessment, 42% had a positive family history of diabetes and 49% had high-risk ethnic backgrounds (African or Hispanic). The assessment of case reports is complicated by several factors, which include inconsistent reporting of important demographic and other variables that might affect glycaemic control, reporting bias and lack of an adequate control group. In addition, case reports cannot be used to determine causal relationships between individual therapies and treatment-emergent diabetes.
Weight gain a body mass index (BMI) of more than 25 kg/m2 is a risk factor for diabetes (Chan et al, 1994; Colditz et al, 1995), and weight gain can occur during treatment with most of the atypical antipsychotic medications (Allison et al, 1999). However, in some cases, new-onset diabetes has been reported in patients without weight gain (Koller et al, 2001; Henderson, 2002; Koller & Doraiswamy, 2002). Further, no association between weight gain and new-onset diabetes was noted in a naturalistic study of patients receiving clozapine (Henderson et al, 2000). These observations have led to further speculation that some of the atypical antipsychotic medications may increase risk for diabetes by a weight-independent mechanism.
Given the growing interest in a possible association between diabetes and antipsychotic medications, a systematic re-evaluation of risk factor profiles of patients with treatment-emergent diabetes (TED) is warranted. In this retrospective analysis of a large clinical trials database, our objectives were: (a) to identify patients with schizophrenia who exhibited TED; (b) to compare the entry characteristics, including pre-randomisation risk factor profiles, of TED patients with those who maintained normal glucose tolerance during treatment; and (c) to examine the influence of treatment-emergent weight gain or therapy assignment on the development of TED.
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METHOD |
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Non-fasting glucose measurements
Non-fasting glucose levels were analysed by Covance Inc. using a
photometric chemistry analyser (Hitachi 747200; Roche Diagnostics,
Indianapolis, Indiana, USA). The frequency of sample collection was specified
by each study protocol. In general, two samples were obtained
pre-randomisation and after that, samples were usually obtained weekly for the
first 6 weeks and monthly or bi-weekly thereafter. In case of multiple glucose
measurements for the same visit, only the maximum observation was considered.
The analyses included all measurements up to and including the day after the
last day of treatment.
Classification of patients
Patients with only baseline glucose values and those with pre-existing
diabetes at entry (clinical diagnosis of diabetes, such as taking antidiabetic
medications at baseline such as insulin, sulphonylurea, metformin,
thiazolidinediones or -glucosidase inhibitor) or two pre-randomisation
glucose values of
11.1 mmol/l were excluded from the analyses. Patients
(n=27) with a single glucose measurement
11.1 mmol/l at entry
were not excluded because these individuals lacked a confirmatory second value
prior to drug assignment. A single glucose value of
11.1 mmol/l at entry
was, however, considered suggestive of underlying dysglycaemia in the
assessment of pre-existing risk factors for diabetes (see Categorical risk
factors, below).
Post-baseline non-fasting glucose values were used to classify or categorise patients as exhibiting:
A non-fasting glucose value of 7.8 mmol/l was chosen as the threshold
for UGT based on several lines of evidence:
Categorical risk factors
Patients possessing one or more of the following risk factors
(American Diabetes Association,
2002) for diabetes at baseline were identified: age 45 years,
baseline BMI
27 kg/m2, non-White ethnicity, hypertension based
on clinical diagnosis or use of antihypertensive medication, or non-fasting
glucose levels suggestive of underlying dysglycaemia, e.g. a single
pre-randomisation glucose value
11.1 mmol/l. Height was available for BMI
calculation for approximately 80% of the patients. Where BMI could not be
calculated, data from these patients were not included in these analyses. This
analysis began before the BMI threshold as a risk factor for diabetes was
lowered from 27 kg/m2 to 25 kg/m2 in the American
Diabetes Association (ADA) Clinical Practice Recommendations
(American Diabetes Association,
2002). Baseline glycaemic status of individual patients was based
on the mean of two pre-randomisation measures for 4425 of the 5013 patients
evaluated (88.3%).
Statistical methods
Data from 24 studies from the olanzapine clinical trial database were
pooled for these analyses. The prevalence of baseline risk factors within the
TED v. the NGT group or within the UGT v. the NGT group was
compared by Fishers exact test. Imbalances in risk factors that are
continuous variables (such as age, mean baseline glucose, maximum baseline
glucose and baseline BMI) were tested by F-test. Weight gain was
analysed by a last observation carried forward (LOCF) method.
To account for variation in observation times for individual therapy groups, a time-to-event analysis using the Cox proportional hazards model was employed to assess the risk of TED. Specifically, the Cox model assessed the impact of mean non-fasting glucose values or the presence of pre-existing risk factors for diabetes on the subsequent risk of being identified with TED. The Cox proportional hazards model was also used to assess the impact of weight gain and therapy assignment on the risk of being identified with TED v. not TED (UGT plus NGT cohorts). Because of the small number of events in individual therapy groups, treatment group results were compared between olanzapine and non-olanzapine groups (including haloperidol, risperidone and placebo). Unless otherwise specified, the Cox proportional hazards model included a single test covariate (baseline mean non-fasting glucose concentration, baseline risk factors for diabetes, treatment-emergent weight gain, or therapy assignment) along with study protocol. The study protocol was also included as a stratification variable in the model to control for effects of pooling data from several clinical trials.
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RESULTS |
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Risk factors for treatment-emergent diabetes
Risk factors at study entry
At study entry, mean non-fasting glucose levels for TED patients were
significantly higher than for NGT patients
(Table 2). Over half (61%) of
the patients subsequently identified with TED had mean glucose values 6.1
mmol/l and over 30% had values
7.8 mmol/l at entry
(Fig. 1). In comparison, 13% of
NGT patients had mean glucose values
6.1 mmol/l and only 1.5% had values
7.8 mmol/l at entry. After randomisation of the patients with a single
glucose measurement
11.1 mmol/l at entry (n=27) who were not
excluded from the analysis, 9 were categorised in the TED group, 5 were
categorised in the UGT group, and 13 were categorised in the NGT group.
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Patients subsequently identified as having TED were significantly older,
more obese and more likely to be hypertensive, non-White, female, or have
baseline dysglycaemia than NGT patients
(Table 2). Sixty-four per cent
of TED patients possessed multiple risk factors for diabetes compared with 21%
of NGT patients (Fig. 2).
Baseline characteristics of patients subsequently identified with TED
demonstrated that substantial numbers had baseline non-fasting glucose levels
7.8 mmol/l or multiple pre-existing risk factors for diabetes in each of
the individual treatment groups (Table
2). Approximately half of the cases of TED were identified within
3 months of trial entry. For these early TED patients, the entry
glucose was 7.9 (s.d. 2.2) mmol/l and 71% possessed at least two risk factors
for diabetes at entry.
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As expected, entry non-fasting glucose had a highly significant impact on
the risk of TED. The risk of being identified with TED was substantially
greater for patients with entry non-fasting glucose 7.8 mmol/l: hazard
ratio (HR) 31.9; 95% CI 19.652.0; P<0.001. Even at lower
entry glucose levels, the risk of TED was still markedly elevated. For
example, in patients with non-fasting glucose of
6.7 mmol/l, the risk of
TED was elevated (HR 11.85, 95% CI 7.718.3; P<0.001)
(Fig. 3). Further, the risk for
TED was 9 times greater for patients with baseline random plasma glucose
6.7 mmol/l (HR 9.6, 95% CI 6.214.8; P<0.001).
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The presence of multiple baseline risk factors for diabetes (age, BMI, non-White ethnicity, hypertension and dysglycaemia) also had a highly significant impact on the risk of being identified with TED. Without adjusting for entry non-fasting glucose in the Cox proportional hazards model, patients with two or more risk factors at entry were nearly 6 times more likely to be identified with TED (HR 5.70, 95% CI 3.69.0; P<0.001) than patients with one or no risk factor.
An interaction between entry non-fasting glucose value and number of
pre-existing diabetes risk factors would be expected. Among patients with
entry glucose values 7.8 mmol/l and two or more baseline risk factors for
diabetes, 40% (26 of 64 patients) were identified with TED. In contrast, less
than 1% (26 of 3795) of patients with
1 risk factor and an entry glucose
<7.8 mmol/l were identified with TED. Furthermore, for patients with entry
glucose <7.8 mmol/l, the likelihood of being identified with TED was
greater if multiple (two or more) baseline risk factors were present: 3.2% (34
out of 1068) of patients with normal glucose and multiple risk factors were
identified with TED.
Of the 94 TED patients, nine appeared to lack risk factors for diabetes at study entry. However, within this subgroup, detailed review revealed that seven patients were overweight (BMI 26.5 to 26.9 kg/m2 or weight >118 kg), over 35 years of age, or had questionable entry non-fasting glucose levels (range 7.810 mmol/l). The two remaining patients experienced substantial weight gain (>13 kg) prior to identification of TED.
A subset of patients (n=282) with repeated post-randomisation
glucose levels 7.8 mmol/l, but an insufficient hyperglycaemia to meet
criteria for TED were identified. This appeared to be a heterogeneous group in
terms of glycaemic control and because confirmatory testing data (e.g. fasting
plasma glucose or OGTT) were not available to define glycaemic status more
precisely, these patients were considered to have UGT and were analysed
separately. Overall, this group possessed entry characteristics
(Table 2) and risk factor
profiles (Fig. 2) intermediate
to those of the TED and NGT groups. At study entry, the mean non-fasting
glucose for patients identified as possessing UGT was significantly higher
than NGT patients and 37% of the UGT patients had entry glucose values
6.1
mmol/l, with 7%
7.8 mmol/l (Table
2 and Fig. 1). The
number and percentage of patients identified with UGT in individual therapy
groups with baseline mean non-fasting glucose
7.8 mmol/l or with 2 or more
baseline risk factors for diabetes are presented in
Table 3.
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Post-randomisation risk factors
Patients identified as having TED gained slightly more weight than NGT
patients (3.9 kg v. 2.7 kg, baseline to end-point, LOCF). However,
observation times were longer for TED patients compared with the overall NGT
group (data not shown). To adjust for differences in observation time, a
time-to-event analysis was performed using a Cox proportional hazards model.
In this analysis, the impact of weight gain (7% or more of the patients
initial body weight) as a categorical covariate on the risk of being
identified with TED did not achieve statistical significance (HR 1.21, 95% CI
0.771.90, P=0.414; Fig.
3), without adjusting for baseline glucose concentration or number
of pre-existing risk factors.
The risk of TED for patients receiving olanzapine v. non-olanzapine interventions (risperidone, haloperidol and placebo) was also assessed using the Cox proportional hazards model. As there were relatively few TED events in individual non-olanzapine treatment groups, the risk of TED was evaluated between patients receiving olanzapine and a pooled cohort of patients receiving the other non-olanzapine interventions (Table 1). Because clozapine, like olanzapine, has been suggested to be more closely associated with treatment-emergent diabetes than other antipsychotic medications, clozapine was omitted from the non-olanzapine group to avoid the potential for increasing the risk of diabetes in the non-olanzapine group. Using the Cox proportional hazards model, without adjusting for baseline random plasma glucose level, baseline number of risk factors or weight gain, the short-term risk for TED patients treated with olanzapine was not significantly greater than in a pooled cohort of patients receiving risperidone, haloperidol and placebo (HR 1.46, 95% CI 0.832.57, P=0.186; Fig. 3). In a separate analysis that included baseline glucose concentration, number of baseline risk factors and weight gain as continuous covariates, the risk for TED was also not significantly different between the olanzapine and non-olanzapine treatment groups (P=0.220). In this multivariate analysis, both baseline glucose values and number of pre-existing risk factors remained highly significant (P<0.001) covariates, whereas treatment-emergent weight gain was not significant (P=0.311).
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DISCUSSION |
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At entry into the clinical trials, patients in this study subsequently identified with TED possessed significantly higher non-fasting glucose levels and were much more likely to have multiple risk factors for diabetes than patients who maintained NGT. In general, TED patients were significantly older, more obese and more likely to be non-White, hypertensive or have non-fasting glucose levels suggestive of pre-existing dysglycaemia (e.g. single pre-randomisation glucose value greater than 11.1 mmol/l) at study entry than patients who appeared to maintain normal glucose levels (NGT patients). Overall, results of this analysis suggest that the majority of patients who were identified with TED were likely to have pre-existing, unrecognised glycaemic abnormalities or to have had a greater burden of pre-existing risk factors for diabetes than patients who appeared to maintain normoglycaemia.
Weight gain has been established as a risk factor for diabetes
(Chan et al, 1994;
Colditz et al, 1995),
and weight gain has been observed during treatment with many antipsychotics
(Allison et al, 1999).
However, some reports have failed to demonstrate a relationship between weight
gain and new-onset diabetes temporally associated with atypical antipsychotic
treatment (Koller et al,
2001,
2003;
Henderson, 2002;
Koller & Doraiswamy,
2002). A direct effect of atypical antipsychotic medications to
promote dysglycaemia has been postulated (Koller et al,
2001,
2003;
Henderson, 2002); however, in
a prospective randomised study of healthy volunteers (n=48) treated
for approximately 2.5 weeks with olanzapine or risperidone, there was no
significant change in insulin secretion or insulin sensitivity in the active
therapy groups after adjusting for the impact of weight gain
(Sowell et al, 2002).
In the current analysis, weight gain during the trials did not have a
statistically significant effect on the risk of TED, although patients with
TED gained slightly more weight than those who maintained NGT. Evaluation of
the relationship between weight gain and risk of diabetes might be confounded
if significant numbers of individuals with unrecognised pre-existing diabetes
were present or if the population was already at high risk of diabetes
(Wannamethee & Shaper,
1999). Even among individuals without pre-existing diabetes but
who are at high risk for the disorder, it may be difficult to measure a
significant impact of further weight gain
(Wannamethee & Shaper,
1999). In our analysis, a substantial number of TED patients
appeared to have a high likelihood of underlying glycaemic abnormalities or
possess multiple risk factors for diabetes at baseline (for example, about a
third of patients in the TED group had entry non-fasting glucose values
7.8 mmol/l and about two-thirds had two or more baseline risk factors).
This, coupled with the relatively short duration of observation, might have
contributed to the non-significant impact of weight gain in the Cox
proportional hazards analysis.
There has been increasing interest in a possible differential risk for diabetes among patients taking different antipsychotic medications. When considering case reports involving patients treated with atypical antipsychotics, the largest number are for patients using olanzapine and clozapine (Henderson, 2002; Jin et al, 2002). However, there are now reports of hyperglycaemia or diabetes during treatment with risperidone (Melamed et al, 1998; Croarkin et al, 2000; Wirshing et al, 2001), quetiapine (Sobel et al, 1999; Procyshyn et al, 2000) and ziprasidone (Yang et al, 2002). However, because case reports often lack information on family history and additional factors that might affect glucose regulation, are subject to reporting bias and do not have a reference or control group, causal relationships between individual antipsychotics and treatment-emergent diabetes cannot be determined from case reports. Although numbers of case reports regarding specific agents differ, results from several large retrospective cohort analyses have been inconsistent regarding differences in risk of diabetes among users of various antipsychotic medications (Gianfrancesco et al, 2002; Kornegay et al, 2002; Koro et al, 2002; Lage & Kemner, 2002; Sernyak et al, 2002; Wang et al, 2002b; Buse et al, 2003). This retrospective analysis of data from olanzapine clinical trials found that patients treated with olanzapine did not have a significantly greater risk of TED compared with a non-olanzapine cohort whose treatment did not include clozapine. This result is consistent with some reports comparing the relative risk of developing diabetes during treatment with olanzapine v. other antipsychotics (Lage & Kemner 2002; Smith et al, 2002; Buse et al, 2003), but not with other reports (Caro et al, 2002; Gianfrancesco et al, 2002; Koro et al, 2002; Meyer, 2002; Newcomer et al, 2002; Sernyak et al, 2002).
All retrospective analyses have inherent limitations, and several limitations specific to the current study warrant discussion. Non-fasting glucose measurements have limited sensitivity for detecting diabetes (American Diabetes Association, 2002; Rolka et al, 2001). Consequently, the current analysis probably represents a minimal estimate of the number of cases of TED. Inclusion of the UGT post-randomisation category may ameliorate this limitation to some extent in terms of the descriptive findings; however, without definitive diagnostic testing, limited conclusions regarding the true frequency of abnormal glycaemic events can be drawn from this heterogeneous group. It must also be acknowledged that reasonable alternative classification paradigms for identifying patients with TED or UGT could be employed: for example, use of 6.7 mmol/l glucose as the lower limit for UGT (Rolka et al, 2001), or exclusion of 27 patients with a single glucose value >11.1 mmol/l at study entry. In addition, alternative terminology could be applied to the post-randomisation glycaemic categories, as our TED criteria do not strictly meet ADA criteria for diabetes in absence of reported symptoms (American Diabetes Association, 2002). The clinical trials database also lacked information on prior antipsychotic treatment history and a number of important risk factors for diabetes (family history, previous history of impaired glucose tolerance or lipid profile) as these data were not collected in a systematic fashion. Therefore, the risk factor assessment may well represent an underestimate of the true pre-existing risk burden. Furthermore, some of the between-group comparisons for patients receiving different treatments were limited by differences in sample sizes and duration of observation. Finally, a major limitation is that the clinical trials used in this analysis were not intended to assess risk factors for diabetes or to look for treatment-emergent diabetes, and caution is warranted when extrapolating results of this analysis to a more general practice setting. Nevertheless, the clinical trials were randomised and masked, and unlike a number of the retrospective cohort studies noted above, more detailed baseline risk factor information was available for study participants. Retrospective analyses cannot definitively answer all questions regarding a potential link between schizophrenia and diabetes, nor can this type of analysis resolve whether there are subtle differences in risk for diabetes among users of different antipsychotic medications. We hope, however, that the results of this analysis may provide important preliminary information regarding antipsychotic therapy and the relative impact of pre-existing risk factors for diabetes, short-term weight gain and use of olanzapine on the short-term risk of marked glycaemic abnormalities or diabetes.
In summary, results of this retrospective analysis suggest that over the short term (generally less than 1 years exposure, with a median exposure time of less than 6 months), elevated baseline non-fasting glucose level and presence of multiple risk factors for diabetes appear to have a major impact on the risk of being identified with TED, whereas the impact of treatment-emergent weight gain on short-term TED risk was relatively small and was not statistically significant. Patients treated with olanzapine did not have a significantly greater risk of short-term TED compared with a pooled cohort of patients receiving risperidone, haloperidol and placebo. Overall, the risk factors for diabetes in patients with schizophrenia overlap those in the general population.
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ACKNOWLEDGMENTS |
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