Abstract
Objective
Psoriasis is a common chronic inflammatory disorder that has been mechanistically linked to type II diabetes mellitus. We sought to assess the risk of incident diabetes in patients with psoriasis and to evaluate diabetes treatment patterns among patients with psoriasis and incident diabetes.
Design
Population-based cohort study.
Setting
UK-based electronic medical records.
Patients
We matched 108,132 psoriasis patients aged 18–90 years to 430,716 unexposed patients based on practice and time of visit. For our nested study, only patients who developed incident diabetes during our study time were included.
Main Outcome Measure(s)
Incident diabetes and adjusted risk of pharmacotherapy among those with incident diabetes.
Results
The fully adjusted HRs (95% CI) for incident diabetes were 1.14 (1.10–1.18), 1.11 (1.07, 1.15), and 1.46 (1.30, 1.65) in the overall, mild and severe psoriasis groups, respectively. Among those with incident diabetes and severe psoriasis, the adjusted risk for receiving diabetes pharmacotherapy was 1.55 (1.15–2.10).
Conclusions
Our results suggest that psoriasis is an independent risk factor for the development of type II diabetes mellitus in a dose dependent manner, and that patients with severe psoriasis who develop diabetes are more likely to receive systemic diabetic therapies in comparison to diabetics without psoriasis.
Keywords: THIN, Diabetes, Psoriasis, Epidemiology
Introduction
Psoriasis is a common, chronic inflammatory disease affecting 2–4% of the adult population.1–6 A broad and growing literature has found that psoriasis is associated with myocardial infarction (MI), stroke, metabolic syndrome and cardiovascular mortality, which is thought to be due to chronic inflammation that characterizes the pathophysiology of these conditions.7–31 In addition, mechanistic data suggests a link between psoriasis and diabetes underscored by TH-1 cytokines which can promote insulin resistance and disordered metabolism (i.e., metabolic syndrome) and promote inflammatory cytokines known to drive psoriasis.32–35 Despite a growing body of studies examining this relationship, relatively few population-based cohort studies have examined the risk of diabetes in patients with psoriasis.36,37
Qureshi et al. demonstrated that normotensive female nurses (N=1,813) with self reported psoriasis have a relative risk (RR) of 1.63 (95% CI 1.25–2.12) for developing diabetes, independent of risk factors such as age, BMI, smoking, alcohol intake, and physical activity.36 Another study by Brauchli et al. included a population-based nested analysis of 1,061 diabetic patients using the General Practice Research Database (GPRD) and found an odds ratio (OR) of 1.31 (95% CI 1.13–1.51) for incident psoriasis among people with incident diabetes while controlling for hyperlipidemia, smoking, hypertension, infections and oral steroids use. To date, this is the only study to our knowledge to examine the impact of psoriasis severity, finding an OR of 1.61 (95% CI 0.90–2.88) for severe psoriasis, as measured by use of oral psoriasis medications, among incident diabetic patients,.37 To our knowledge, no studies have evaluated diabetes treatment patterns among patients with psoriasis and diabetes.
Our primary aim was to conduct a large population-based cohort study to determine the risk of incident type II diabetes mellitus (T2DM) in patients with psoriasis of varying severities. Our secondary aim was to determine whether diabetic patients with psoriasis are more likely to receive prescription diabetic therapy compared to diabetic patients with no psoriasis. We hypothesized that psoriasis patients, especially if severe, have an increased risk of developing T2DM, and that patients with diabetes and psoriasis would have greater utilization of systemic diabetes medications than patients with diabetes alone.
Methods
Study Design
Methods conformed to the STROBE statement.38 Using an electronic medical records database, we conducted a population-based cohort study of adults aged 18–90 years with psoriasis (i.e., the exposed) versus patients without psoriasis (i.e., the unexposed comparison cohort). For our secondary aim we performed a nested study including only patients who developed incident T2DM within our study period.
This study was approved by the University of Pennsylvania Institutional Review Board. As only de-identified data was used, no informed consent was required.
Setting/Data Source
We used The Health Improvement Network (THIN) data collected between 2003 and October 2008. THIN is an electronic medical records database of more than 7.5 million people, and broadly represents 4.6% of the United Kingdom (UK) population across over 400 medical practices. THIN contains de-identified patient demographics, medical diagnoses, laboratory results, and prescriptions as recorded by General Practitioners (GPs), who serve as the primary point of medical contact in the UK. THIN utilizes monetary incentives, quality targets, and training to ensure accurate and complete records that include information from hospital and specialty care.
Study Population and Definitions of Exposure and Outcomes
Exposed patients were eligible for the cohort if they were 18–90 years of age as of January 1st 2010 and had at least one medical record Read Code indicating a diagnosis of psoriasis. Psoriasis diagnostic codes in THIN have been shown to accurately reflect a psoriasis diagnosis with a positive predictive value of 90%.39 We excluded patients with existing diabetes Read Codes at the time of their first psoriasis code, with un-dated diabetes codes, and with a code indicative of any type of diabetes other than T2DM.
We categorized psoriasis patients as having severe psoriasis if they had a treatment record for a systemic psoriasis medication (methotrexate, cyclosporine, oral retinoid, azathioprine, hydroxyurea, mycophenalate or phototherapy (UVB or PUVA)). We did not include biologic therapies as these were not widely used for psoriasis in the UK during our study period. Psoriasis patients without a record for any of these treatments were considered to have mild psoriasis.
To construct an unexposed comparison group, each exposed patient was randomly matched to up to four patients without a psoriasis Read Code from the same practice who were aged 18–90 years and were seen within 60 days of the time the exposed patient received his or her first psoriasis code or registered in the practice (whichever came later).
To identify patients with diabetes we modified a previously validated algorithm in THIN. 40,41 Patients were identified as having diabetes if they received at least two diagnostic codes indicative of T2DM on separate occasions or one diagnostic code and one lab value or medication that was indicative of T2DM. For our secondary aim, outcomes measured included use of oral hypoglycemic medications (yes/no), and use of insulin (yes/no).
Sample size and power estimates
All patients with psoriasis meeting our selection criteria were included in this study yielding an exposed population of 108,132 patients and a comparison (unexposed) population of 430,716. This sample size ensures that we can detect a hazard ratio of 1.06 with 80% power assuming two-sided, 0.05 α level tests for the primary aim of the study.
Identification of Confounders
Potential confounders were selected based on being known risk factors for diabetes (age, sex, BMI, use of oral steroids) as well as factors that may be confounders such as smoking, alcohol intake, hypertension (HTN), hyperlipidemia, depression, anxiety, MI and socioeconomic status.
Statistical Methods
We performed descriptive statistics to summarize and compare patient demographics, covariates of interest, and univariate outcomes using Pearson’s chi square test for dichotomous variables (e.g., gender) and t-tests for continuous variables (e.g., age).
We calculated Kaplan-Meier estimates of time to diabetes diagnosis for each matched group and compared these estimates using the log-rank test. Observation time started at the latest of: (1) the date when the practice began uploading information into the database, (2) patient registration with the practice, and (3) the date of the patient’s first psoriasis Read Code, or, in unexposed patients, the closest corresponding visit. We calculated unadjusted and adjusted Cox proportional hazards models in each group and stratified these by psoriasis severity. Censoring occurred when patients transferred out of the practice, died, received a diabetes code, or reached the end of the study period.
We used a purposeful selection approach for multivariable modeling. In our initial model we included all covariates a priori thought to be clinically important (i.e., BMI, age, and sex, etc) as well as any covariates found in the descriptive statistics to have a p-value of less than 0.10. Variables were eliminated from the model if their removal did not have a significant effect on the log partial likelihood (using likelihood ratio tests) and did not change the hazard ratio estimate of any other covariate by more than 15%. We also evaluated two-way interaction terms such as psoriasis and sex, and psoriasis and age and decided, a priori, to incorporate them in our final model if they were statistically significant (P<0.10). Each variable in the model was checked for proportionality while adjusting for the other covariates in the model by examining diagnostic log-log survival plots, and by tests of the statistical significance of each variable’s interaction with time. Model fit was assessed by graphical inspection of Schoenfeld residual plots using standard methods.
For the nested study we included all psoriasis patients and controls who developed diabetes within our study window regardless of their initial matching designation. We performed adjusted and unadjusted logistic regressions with use of oral medications and use of insulin as our outcomes and psoriasis status and severity as covariates. The confounding variables are the same as those described above except that we used smoking and BMI information obtained before the diagnosis of diabetes whenever possible and included age at T2DM onset as a covariate.
We performed multiple sensitivity analyses to assess the robustness of our results and ensure they were not explained by systematic error (i.e., information bias) or treatment effects.
All statistical analyses were performed using SAS (Version 9.2, SAS Institute Inc, Cary, NC), and STATA (Version 10, Stata Corporation, College Station, TX). Statistical significance was determined using two-sided p-values at the 0.05 level (95% confidence level) unless otherwise noted.
Results
We identified 108,132 psoriasis patients (exposed) and 430,716 matched patients without psoriasis (unexposed). Among the psoriasis patients 101,870 were classified as having mild disease and 6,229 were classified as having severe disease based on psoriasis treatment patterns. The most notable differences between the exposed and unexposed groups were age, sex, and current smoking status based on univariate analyses. (Table 1) Among patients defined as having severe psoriasis, the most commonly prescribed medication was methotrexate (60.5%). (Table 2)
Table 1.
Characteristics of Study Group
| Psoriasis Cohort | Psoriasis Unexposed Cohort | Mild Psoriasis Cohort | Mild Psoriasis Unexposed Cohort | Severe Psoriasis Cohort | Severe Psoriasis Unexposed Cohort | |
|---|---|---|---|---|---|---|
|
| ||||||
| Population | ||||||
|
| ||||||
| Qualifying Patients - No. | 108,132 | 430,716 | 101,870 | 405,819 | 6,229 | 24,784 |
|
| ||||||
| Age at start of followup, y | ||||||
| Mean±SD | 46.03±16.62 | 48.40±16.64 | 45.91±16.71 | 48.35±16.66 | 47.99±15.11 | 49.26±16.32 |
| Median (IQR) | 44.30 (32.31, 58.88) | 47.47 (34.98, 61.24) P<0.001* |
44.10 (32.10, 58.85) | 47.40 (34.89, 61.20) P<0.001* |
47.17 (36.01, 59.38) | 48.57 (36.16, 62.11) P<0.001* |
|
| ||||||
| Sex | ||||||
| Male (%) | 52,420 (48.49) | 189,020 (43.90) | 49,390 (48.48) | 178,060 (43.88) | 3,030 (48.64) | 10,960 (44.22) |
| Female (%) | 55,679 (51.51) | 241,583 (56.10) P<0.001^ |
52,480 (51.52) | 227,759 (56.12) P<0.001^ |
3,199 (51.36) | 13,824 (55.78) P<0.001^ |
|
| ||||||
| Transfer from Practice- No. (%) | 29,197 (27.01) | 107,311 (24.92) P<0.001^ |
27,914 (27.40) | 101,040 (24.90) P<0.001^ |
1,283 (20.60) | 6,271 (25.30) P<0.001^ |
|
| ||||||
| Patient Death- No. (%) | 4,683 (4.33) | 19,157 (4.45) P=0.10^ |
4,330 (4.25) | 17,933 (4.42) P=0.02^ |
353 (5.67) | 1,224 (4.94) P=.02^ |
|
| ||||||
| Censored due to end of follow-up time (%) | 78,902 (72.99) | 323,292 (75.08) P<0.001^ |
73,956 (72.60) | 304,779 (75.10) P<0.001^ |
4,946 (79.40) | 18,513 (74.70) P<0.001^ |
|
| ||||||
| Confounders | ||||||
|
| ||||||
| Mean BMI | 26.46±5.32 | 26.21±5.20 P<0.001* |
26.40±5.30 | 26.22±5.21 P<0.001* |
27.32±5.63 | 26.20±5.07 P<0.001* |
|
| ||||||
| Hypertension - No. (%) | 27,182 (25.15) | 117,795 (27.36) P<0.001^ |
25,168 (24.71) | 110,711 (27.28) P<0.001^ |
2,014 (32.33) | 7,084 (28.58) P<0.001^ |
|
| ||||||
| Hyperlipidemia- No. (%) | 10,809 (10.00) | 45,800 (10.64) P<0.001^ |
10,049 (9.86) | 42,967 (10.59) P<0.001^ |
760 (12.20) | 2,833 (11.43) P<0.090^ |
|
| ||||||
| Diabetes Outcomes | ||||||
|
| ||||||
| Diabetes – No (%) | 3,992 (3.7%) | 14,537 (3.4%) P<0.001^ |
3,599 (3.5%) | 13,626 (3.4%) P=0.006 |
393 (6.3%) | 911 (3.7%) P<0.001^ |
|
| ||||||
| Age at Diabetes Onset | ||||||
| Median (IQR) | 63.4 (54.8–71.6) | 64.2 (55.3–72.4) | 63.4 (54.2 – 71.8) | 63.84 (54.6–72.2) | 59.61 (51.6 – 66.2) | 63.96 (54.8–72.5) |
| Mean [SD] | 62.0 [12.25] | 62.8 [12.19] P<0.001* |
62.3 [12.3] | 62.8 [12.2] P<0.001* |
59.0 [10.85] | 62.8 [12.24] P<0.001* |
Chi-square,
Student’s t-test,
Table 2.
Systemic psoriasis treatments received by patients with severe psoriasis* (N=6,229)
| Therapy | N (%) |
|---|---|
| Methotrexate | 3,768 (60.49) |
| Phototherapy (UVB or PUVA) | 1,514 (24.31) |
| Azathioprine | 724 (11.62) |
| Cyclosporine | 641 (10.29) |
| Oral retinoid | 272 (4.37) |
| Hydroxyurea | 195 (3.13) |
| Mycophenolate mofetil | 84 (1.35) |
numbers do not add up to 100 as patients may have been on multiple systemic medications
In unadjusted analyses the risk of incident diabetes was increased among psoriasis patients in a dose response fashion with psoriasis severity (overall psoriasis HR 1.18 95% CI 1.14–1.23; severe psoriasis HR 1.75, 95% CI 1.56–1.98). In fully adjusted models which controlled for age, sex, BMI, hypertension, and hyperlipidemia, psoriasis was found to be an independent risk factor for incident diabetes (HR 1.14, 95% CI 1.10–1.18) and this risk was greatest in patients with severe disease (HR 1.46, 95% CI 1.30–1.65). (Table 3) The adjusted attributable risk of developing T2DM among 1000 psoriasis patients per year is 0.9 extra cases overall, 0.7 cases in those with mild psoriasis and 3.0 cases in those with severe psoriasis. These findings remained robust in numerous sensitivity analyses. (Table 4)
Table 3.
Incidence of Diabetes Mellitus by Study Group
| Characteristics | Exposed | Unexposed | Mild Exposed | Mild Unexposed | Severe Exposed | Severe Unexposed |
|---|---|---|---|---|---|---|
|
| ||||||
| Person-time, y | ||||||
| Mean±SD | 5.17±3.60 | 5.25±3.62 | 5.11±3.59 | 5.22±3.61 | 6.15±3.58 | 5.76±3.64 |
| Median (IQR) | 4.59 (1.98, 7.87) | 4.71 (2.03, 8.02) | 4.58 (1.92, 7.78) | 4.65 (2.01, 7.94) | 6.28 (3.05, 8.93) | 5.60 (2.51 8.58) |
| Cumulative | 545,436 | 2,208,485 | 508,599 | 2,068,935 | 36,837 | 139,549 |
|
| ||||||
| Incident Diabetes Rate (95%CI) | 0.0077 (0.0075, 0.0080) | 0.0066 (0.0065, 0.0067) | 0.0071 (0.0068, 0.0073) | 0.0066 (0.0065, 0.0067) | 0.0107 (0.0966, 0.0118) | 0.0065 (0.0061, 0.0070) |
|
| ||||||
| HR Incident Diabetes^ (95% CI) | 1.18 (1.14, 1.23) | 1 | 1.14 (1.10, 1.18) | 1 | 1.75 (1.56, 1.98) | 1 |
|
| ||||||
| HR Incident Diabetes* (95% CI) | 1.14 (1.10–1.18) | 1 | 1.11 (1.07, 1.15) | 1 | 1.46 (1.30, 1.65) | 1 |
adjusted for age and sex;
adjusted for age, sex, BMI, hypertension, hyperlipidemia
Table 4.
Sensitivity Analyses: Hazard Ratio of Incident Diabetes
| Characteristics | Psoriasis Overall | Mild Psoriasis | Severe Psoriasis |
|---|---|---|---|
| Original Model* | 1.14 (1.10–1.18) | 1.11 (1.07, 1.15) | 1.46 (1.30, 1.65) |
| Restricting to patients who were seen at least once a year: HR Incident Diabetes* (95% CI) | 1.13 (1.09–1.72) | 1.10 (1.06–1.15) | 1.46 (1.28, 1.65) |
| Excluding patients with psoriatic arthritis: HR Incident Diabetes* (95% CI) | 1.13 (1.09, 1.17) | 1.11 (1.07, 1.15) | 1.50 (1.29, 1.74) |
| Excluding patients who ever received a systemic steroid, retinoid or cyclosporine: HR Incident Diabetes* (95% CI) | 1.12 (1.07, 1.17) | 1.11 (1.06, 1.16) | 1.44 (1.21, 1.72) |
| Restricting to patients who received an oral retinoid or phototherapy: HR Incident Diabetes* (95% CI) | NA | NA | 1.52 (1.20, 1.93) |
| Restricting to patients with a diabetes diagnosis that occurs at least one year after the start date: HR Incident Diabetes* (95% CI) | 1.14 (1.10, 1.19) | 1.11 (1.07, 1.16) | 1.45 (1.27, 1.65) |
| Restricting to patients who were seen prior to 2005, i.e., prior to when biologic therapy becoming prevalent for psoriasis treatment in the UK: HR Incident Diabetes* (95% CI) | NA | NA | 1.54 (1.30–1.83) |
| Restricting to patients who were at least 50 years old: HR Incident Diabetes* (95% CI) | 1.15 (1.10–1.20) | 1.13 (1.08–1.76) | 1.42 (1.23–1.64) |
adjusted for age, sex, BMI, hypertension, hyperlipidemia
Among patients who developed incident diabetes we evaluated diabetes treatment patterns. We observed no difference in use of oral hypoglycemics (OR 1.03, 95% CI 0.95–1.11) or insulin (OR 1.06, 95% CI 0.89–1.25) among patients with mild psoriasis; however, patients with severe psoriasis were more likely to be prescribed oral hypoglycemics (OR 1.53 95% CI 1.14–2.07) and had a trend towards being more likely to be prescribed insulin (OR 1.32 95% CI 0.75–2.33). These findings remained robust to sensitivity analyses that excluded patients with psoriatic arthritis or restricted the analysis to patients with at least one year of follow-up after their diabetes diagnosis.
Discussion
The data from this study suggest that psoriasis is a risk factor for the development of type II diabetes mellitus, and that this relationship is dose-dependent, with severe psoriasis conferring a higher risk than mild psoriasis. Mechanistically, this relationship may be driven by chronic inflammation, as both psoriasis and T2DM are associated with elevated levels of Th-1 driven inflammatory markers, and as several studies have pointed to endogenous insulin resistance in psoriatic patients. 32–35
With approximately 125 million individuals affected by psoriasis worldwide, we estimate that an additional 115,500 people will develop diabetes each year due to the risk posed by psoriasis above and beyond conventional risk factors measured in routine medical practice. 42 Furthermore, our results indicate that people with severe psoriasis who develop T2DM are more likely to receive systemic therapy for their diabetes, compared to diabetics without psoriasis. This finding was primarily driven by the use of oral T2DM medications.
Our study advances the existing literature regarding psoriasis and incident T2DM and has several strengths. With more than 100,000 psoriasis patients, to our knowledge, this study is by far the largest to date to examine the relationship between psoriasis and diabetes. The large sample afforded us a high degree of precision when we studied subgroups such as patients with severe psoriasis (n = 6,229) or excluded large numbers of patients in sensitivity analyses. Because our cohorts were broadly representative and population-based, the findings are less likely to be influenced by bias (i.e., good internal validity) and are likely to be generalizable to the psoriasis population at large (i.e., strong external validity). We also had access to medical, treatment, and laboratory records that allowed us to precisely define outcomes, confounders, and sensitivity analysis sub-populations. Moreover, to our knowledge, this is the first study to show that T2DM patients with severe psoriasis are more likely to receive pharmacologic intervention for their T2DM compared to their non-psoriatic counterparts, with all other measurable risk factors being accounted for.
Potential limitations in observational studies include selection bias, information bias, misclassification bias, confounding, and statistical error. Here we systematically address these potential limitations. Our results are unlikely to be explained by selection bias as all patients (exposed and unexposed) were selected from the same source population. In addition, the potential for information bias is minimized as data on each patient was collected in a similar manner by general practitioners matched by practice. It is conceivable that patients with severe psoriasis require more frequent visits to their GP and therefore diabetes may be picked up earlier and more frequently in this group.7,8,10,43 However, we completed a variety of sensitivity analyses accounting for frequency of medical visits as well as restricting to a population of patients routinely screened for diabetes based on UK pay-for-performance national standards and screening guidelines and these did not change our results.44, 45 Nevertheless, given the observational nature of this study we cannot fully exclude information bias as a potential source of error.
We expect some degree of misclassification of mild and severe psoriasis as we used a treatment-based algorithm to define disease severity. Such misclassification would be expected to artificially increase the strength of the association in the mild group and decrease the association in the severe group. Additional analyses with more restrictive definitions of severe psoriasis yielded similar findings.39 We assessed the robustness of our definition of severe psoriasis by restricting our analysis of severe psoriasis to those receiving highly specific psoriasis therapies (oral retinoids and phototherapy), and by excluding patients with a psoriatic arthritis diagnosis; we also evaluated treatment effects using stratified analyses to ensure the results were not driven by oral therapies known to promote hyperglycemia. Our overall conclusions were unchanged in these analyses. To confirm that we were capturing incident and not prevalent diabetes, we restricted our analysis to patients who received a diabetes diagnosis at least one year after their start date and to those with at least one year of followup after their diabetes diagnosis. Finally, the results remained robust when restricting the analyses to patients seen on average at least once per year, minimizing the likelihood that detection bias explains the findings.
In all observational studies the possibility of unmeasured or unknown confounders should be addressed. To be thorough, we tested and accounted for numerous confounders in our primary analyses, and then completed a large number of sensitivity analyses.
Finally, as with any hypothesis-based analysis, it is possible that our findings may be the result of chance alone (type I error). In order to minimize this type of error, we designed our study to test all of our hypotheses at the .05 α level. Furthermore, the likelihood of type II error (failure to reject the null hypothesis when H1 is true) is minimized in our study due to its large sample size, which affords us more than adequate power for each hypothesis under consideration, as demonstrated by our 95% confidence intervals.
Conclusion
In conclusion, our results suggest that psoriasis is a risk factor for the development of diabetes and that the risk increases with increasing severity of psoriasis. Additionally, patients with severe psoriasis are more likely to develop diabetes that will be treated pharmacologically.
Further research into the extent to which psoriasis and its treatment play a role in the development of T2DM and its complications is warranted. Additionally, it is necessary to determine why patients with severe psoriasis who develop diabetes are more likely to receive prescription hypoglycemic treatments. These findings combined with the large literature linking psoriasis to cardiovascular and metabolic disease suggest that patients with psoriasis should be encouraged to lower their risk of diabetes and its complications by undergoing therapeutic lifestyle changes and appropriate screenings for signs of insulin resistance.
Table 5.
Severity and Treatment of Type 2 Diabetes Mellitus
| Exposed | Mild Exposed | Severe Exposed | |
|---|---|---|---|
| N=16407 | |||
| Oral hypoglycemic use OR ^ (95% CI) | 1.06 (0.98–1.15) | 1.03 (0.95–1.11) | 1.53 (1.14–2.07) |
| Insulin use OR ^ (95% CI) | 1.07 (0.90–1.26) | 1.06 (0.89–1.25) | 1.32 (0.75–2.33) |
| Oral hypoglycemic or Insulin use OR^ (95% CI) | 1.05 (0.97–1.13) | 1.01 (0.93–1.10) | 1.55 (1.15–2.1.0) |
adjusted for gender, age DM onset, BMI, history of smoking, and age at time of outcome
Acknowledgments
Sponsor/Grant This work was supported by the National Institute for Arthritis and Musculoskeletal and Skin Diseases (NIAMS) F32-AR056799 to Dr. Azfar., the National Heart, Lung, and Blood institute (NHLBI) 3R01HL089744-01A2S1 to Dr. Seminara, NHLBI R01HL089744-03 to Dr. Gelfand and a T32 University of Pennsylvania dermatology departmental training grant to Dr. Seminara and Mr. Shin.
Footnotes
Study concept and design: Azfar, Seminara, Shin, Troxel, Margolis, Gelfand
Acquisition of data: Seminara, Azfar, Shin, Gelfand
Analysis and interpretation of data: Azfar, Seminara, Shin, Troxel, Margolis, Gelfand
Drafting of the manuscript: Seminara, Azfar
Critical revision of the manuscript for important intellectual content: Azfar, Seminara, Shin, Troxel, Margolis, Gelfand
Statistical analysis: Azfar, Seminara, Shin
Obtained funding: Azfar, Gelfand, Seminara
Administrative, technical, or material support: Seminara, Shin, Azfar
Study supervision: Gelfand
Drs. Azfar and Seminara had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Conflicts of Interest: Dr Gelfand has received grants from Amgen, Pfizer, Novartis, and Abbott, and is a consultant for Amgen, Abbott, Pfizer, Novartis, Celgene, and Centocor. Dr Margolis is on the data safety monitoring boards for Abbott, Astellas, and Centocor. No other authors have conflicts of interest to declare.
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