Ascertainment of EMR-based Clinical Covariates Among Patients Receiving Oral and Non-insulin Injected Hypoglycemic Therapy

• Sponsor: Boehringer Ingelheim (Industry)
• Overall Status: Completed
• CT.gov ID: NCT02140645
• Collaborator: Eli Lilly and Company (Industry)
• Enrollment: 166,613
• Location: 1
• Duration (Months): 10
• Patients Per Site Per Month: 16681.9

Study Details

Study Description

Brief Summary

The objective of this study is to identify EMR-based clinical covariates and quantify their association with the prescribing of each specific type 2 diabetes (T2DM) medication under investigation. This will include an assessment of how well these covariates are captured through claims data proxies, and their potential to confound comparative research of T2DM medications.

Condition or Disease	Intervention/Treatment	Phase
Diabetes Mellitus, Type 2	Drug: linagliptin

Detailed Description

Purpose:

Study Design

• Study Type: Observational
• Actual Enrollment: 166613 participants
• Observational Model: Cohort
• Time Perspective: Retrospective
• Official Title: Association of Clinical Covariates With Non-insulin Diabetes Medication Initiation Using Electronic Medical Records (EMR)
• Study Start Date: May 1, 2014
• Actual Primary Completion Date: Mar 1, 2015
• Actual Study Completion Date: Mar 1, 2015

Arms and Interventions

Arm	Intervention/Treatment
Linagliptin1 T2DM patients initiating Linagliptin (DPP-4 comparison)	Drug: linagliptin; non-randomized
Other DPP4 T2DM patients initiating a non-linagliptin DPP-4 inhibitor
Linagliptin2 T2DM patients initiating Linagliptin (glitizaone comparison)
Glitazones T2DM patients initiating Thiazolidinediones (glitazones)
Sulfonylurea T2DM patients initiating any medication in the Sulfonylurea class
Linagliptin3 T2DM patients initiating Linagliptin (Sulfonylurea comparison)

Outcome Measures

Primary Outcome Measures

1. Missing EMR (Electronic Medical Record) Characteristic: Smoking [Up to 20 months]

   The missing EMR characteristic smoking defined as current, unknown, versus past/never smoker. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic smoking was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.

2. Missing EMR Characteristic: Duration of Diabetes [Up to 20 months]

   The missing EMR characteristic duration of diabetes defined as >7, 5-6, 3-5, 1-3, <1 (in years) in duration. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic duration of diabetes was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.

3. Missing EMR Characteristic: Duration of Diabetes (Continuous) [Up to 20 months]

   The missing EMR characteristic duration of diabetes defined as starting year/starting age of diabetes. Linear regression models were ran using a prioritized list of claims-based covariates as predictors and the value of select EMR-based clinical characteristics duration of diabetes as continuous outcomes. The estimated value represented is actually prediction accuracy defined by R-squared.

4. Missing EMR Characteristic: BMI (Body Mass Index) [Up to 20 months]

   The missing EMR characteristic BMI defined as not obese, overweight, obese, severe obesity. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic BMI was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.

5. Missing EMR Characteristic: BMI (Continuous) [Up to 20 months]

   The missing EMR characteristic BMI is BMI value. Linear regression models were ran using a prioritized list of claims-based covariates as predictors and the value of select EMR-based clinical characteristics BMI as continuous outcomes. The estimated value represented is actually prediction accuracy defined by R-squared.

6. Missing EMR Characteristic: HbA1c (Hemoglobin A1c (Glycosylated Hemoglobin)) [Up to 20 months]

   The missing EMR characteristic HbA1c defined as value in 6 months prior to and including index date. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic HbA1c was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.

7. Missing EMR Characteristic: eGFR (Glomerular Filtration Rate) [Upto 20 months]

   The missing EMR characteristic eGFR defined as value in 6 months prior to and including index date. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic eGFR was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.

8. Missing EMR Characteristic: Total Cholesterol [Up to 20 months]

   The missing EMR characteristic total cholesterol defined as value in 6 months prior to and including index date. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic total cholesterol was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.

9. Missing EMR Characteristic: Systolic BP (Blood Pressure) [Up to 20 months]

   The missing EMR characteristic systolic BP defined as value in 6 months prior to and including index date. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic systolic BP was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.

10. Missing EMR Characteristic: Diastolic BP [Up to 20 months]

    The missing EMR characteristic diastolic BP defined as value in 6 months prior to and including index date. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic diastolic BP was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.

11. Binary EMR Characteristic: Neuropathy [Up to 20 months]

    The missing EMR characteristic neuropathy defined as participants with any note of diabetic neuropathy. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic neuropathy was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.

12. Binary EMR Characteristic: Nephropathy [Upto 20 months]

    The missing EMR characteristic nephropathy defined as participants with any note of diabetic nephropathy. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic nephropathy was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.

13. Binary EMR Characteristic: Retinopathy [Up to 20 months]

    The missing EMR characteristic retinopathy defined as participants with any note of diabetic retinopathy. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic retinopathy was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.

14. Binary EMR Characteristic: Pancreatitis [Up to 20 months]

    The missing EMR characteristic pancreatitis defined as participants with any note of prior pancreatitis. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic pancreatitis was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.

Eligibility Criteria

Criteria

• Ages Eligible for Study: 18 Years and Older
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: No

Inclusion criteria:

• Dispensing of an oral or non-insulin injected hypoglycemic medication between May 2011 and June 2012

• Diagnosis of type 2 diabetes mellitus

• Presence of electronic medical records (for the EMR-based subset)

Exclusion criteria:

• Age <18 at T2DM medication initiation

• Missing or ambiguous age or sex information

• At least one diagnosis of type 1 diabetes mellitus

• Less than 6 months enrolment in the database preceding the date of the first dispensing

• Prior use of the index drug

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Boehringer Ingelheim Investigational Site	Boston	Massachusetts	United States

Sponsors and Collaborators

• Boehringer Ingelheim
• Eli Lilly and Company

Investigators

• Study Chair: Boehringer Ingelheim, Boehringer Ingelheim

Study Documents (Full-Text)

None provided.

More Information

Additional Information:

• Related Info

Publications

None provided.

• Responsible Party: Boehringer Ingelheim
• ClinicalTrials.gov Identifier: NCT02140645
• Other Study ID Numbers: 1218.162
• First Posted: May 16, 2014
• Last Update Posted: Feb 8, 2017
• Last Verified: Dec 1, 2016

• Additional relevant MeSH terms: Diabetes Mellitus, Type 2; Linagliptin

Study Results

Participant Flow

Recruitment Details	Existing data cohort design using data from the MarketScan database from May 2011 through December 2012. 492963 potential patients were identified in the database, but after removing patients who violated inclusion and exclusion criteria 166613 patients were actually analysed in the study.

Arm/Group Title	Linagliptin 1	Any Other DPP-4	Linagliptin 2	Pioglitazone	Linagliptin 3	Second Generation Sulfonylurea
Arm/Group Description	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to any other DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to second generation sulfonylurea.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication second generation sulfonylurea.
Period Title: Overall Study
STARTED	5732	64695	4441	14363	3436	73946
COMPLETED	243	3041	205	530	150	3050
NOT COMPLETED	5489	61654	4236	13833	3286	70896

Baseline Characteristics

Arm/Group Title	Linagliptin 1	Any Other DPP-4	Linagliptin 2	Pioglitazone	Linagliptin 3	Second Generation Sulfonylurea	Total
Arm/Group Description	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to any other DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to second generation sulfonylurea.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication second generation sulfonylurea.	Total of all reporting groups
Overall Participants	243	3041	205	530	150	3050	7219
Age (Years) [Mean (Standard Deviation) ]
Mean (Standard Deviation) [Years]	56.1 (11.6)	54.8 (11.2)	55.2 (11.7)	54.7 (11.1)	54.7 (11.8)	54.8 (11.7)	54.9 (11.5)
Gender (Count of Participants)
Female	118 48.6%	1310 43.1%	101 49.3%	194 36.6%	74 49.3%	1332 43.7%	3129 43.3%
Male	125 51.4%	1731 56.9%	104 50.7%	336 63.4%	76 50.7%	1718 56.3%	4090 56.7%

Outcome Measures

1. Primary Outcome

Title	Missing EMR (Electronic Medical Record) Characteristic: Smoking
Description	The missing EMR characteristic smoking defined as current, unknown, versus past/never smoker. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic smoking was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.
Time Frame	Up to 20 months

Outcome Measure Data

Analysis Population Description

All subjects in MarketScan cohort meeting inclusion/exclusion criteria. EMR-linked subset: From the study group we identified patients who have EMR data available.

Arm/Group Title	Linagliptin 1	Any Other DPP-4	Linagliptin 2	Pioglitazone	Linagliptin 3	Second Generation Sulfonylurea
Arm/Group Description	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to any other DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to second generation sulfonylurea.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication second generation sulfonylurea.
Measure Participants	243	3041	205	530	150	3050
Current	9.1 3.7%	7.6 0.2%	10.7 5.2%	7.9 1.5%	11.3 7.5%	9.4 0.3%
Past	12.3 5.1%	12.2 0.4%	12.2 6%	10.2 1.9%	10.7 7.1%	10.9 0.4%
Never	32.9 13.5%	35.5 1.2%	32.7 16%	30.8 5.8%	34.7 23.1%	33.3 1.1%
Unknown	5.8 2.4%	4.9 0.2%	6.3 3.1%	5.1 1%	6.0 4%	6.5 0.2%

Statistical Analysis 1

Statistical Analysis Overview	Comparison Group Selection	Linagliptin 1, Any Other DPP-4, Linagliptin 2, Pioglitazone, Linagliptin 3, Second Generation Sulfonylurea
	Comments
	Type of Statistical Test	Superiority or Other
	Comments
Statistical Test of Hypothesis	p-Value
	Comments
	Method
	Comments
Method of Estimation	Estimation Parameter	C-statistics
	Estimated Value	0.624
	Confidence Interval	() %; to
	Parameter Dispersion	Type: Value:
	Estimation Comments	The C-statistics can be between 0.5 and 1 and a value of 0.5 indicates that the model is no better than chance at making a prediction and a value of 1.0 indicates that the model perfectly identifies those within a group and those not.

2. Primary Outcome

Title	Missing EMR Characteristic: Duration of Diabetes
Description	The missing EMR characteristic duration of diabetes defined as >7, 5-6, 3-5, 1-3, <1 (in years) in duration. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic duration of diabetes was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.
Time Frame	Up to 20 months

Outcome Measure Data

Analysis Population Description

All subjects in MarketScan cohort meeting inclusion/exclusion criteria. EMR-linked subset: From the study group we identified patients who have EMR data available.

Arm/Group Title	Linagliptin 1	Any Other DPP-4	Linagliptin 2	Pioglitazone	Linagliptin 3	Second Generation Sulfonylurea
Arm/Group Description	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to any other DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to second generation sulfonylurea.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication second generation sulfonylurea.
Measure Participants	243	3041	205	530	150	3050
Less than 1 year	11.9 4.9%	13.7 0.5%	12.7 6.2%	11.1 2.1%	16.0 10.7%	15.4 0.5%
1.00-2.99 years	11.5 4.7%	14.2 0.5%	11.2 5.5%	10.0 1.9%	12.7 8.5%	13.6 0.4%
3.00-4.99 years	7.8 3.2%	7.8 0.3%	7.8 3.8%	8.3 1.6%	7.3 4.9%	8.4 0.3%
5.00-6.99 years	4.9 2%	5.1 0.2%	3.9 1.9%	5.7 1.1%	4.0 2.7%	4.8 0.2%
7+ years	5.3 2.2%	5.3 0.2%	5.4 2.6%	5.8 1.1%	5.3 3.5%	4.8 0.2%

Statistical Analysis 1

Statistical Analysis Overview	Comparison Group Selection	Linagliptin 1, Any Other DPP-4, Linagliptin 2, Pioglitazone, Linagliptin 3, Second Generation Sulfonylurea
	Comments
	Type of Statistical Test	Superiority or Other
	Comments
Statistical Test of Hypothesis	p-Value
	Comments
	Method
	Comments
Method of Estimation	Estimation Parameter	C-statistcs
	Estimated Value	0.597
	Confidence Interval	() %; to
	Parameter Dispersion	Type: Value:
	Estimation Comments	The C-statistics can be between 0.5 and 1 and a value of 0.5 indicates that the model is no better than chance at making a prediction and a value of 1.0 indicates that the model perfectly identifies those within a group and those not.

3. Primary Outcome

Title	Missing EMR Characteristic: Duration of Diabetes (Continuous)
Description	The missing EMR characteristic duration of diabetes defined as starting year/starting age of diabetes. Linear regression models were ran using a prioritized list of claims-based covariates as predictors and the value of select EMR-based clinical characteristics duration of diabetes as continuous outcomes. The estimated value represented is actually prediction accuracy defined by R-squared.
Time Frame	Up to 20 months

Outcome Measure Data

Analysis Population Description

All subjects in MarketScan cohort meeting inclusion/exclusion criteria. EMR-linked subset: From the study group we identified patients who have EMR data available.

Arm/Group Title	Linagliptin 1	Any Other DPP-4	Linagliptin 2	Pioglitazone	Linagliptin 3	Second Generation Sulfonylurea
Arm/Group Description	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to any other DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to second generation sulfonylurea.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication second generation sulfonylurea.
Measure Participants	243	3041	205	530	150	3050
Mean (Standard Deviation) [Months]	3.5 (3.7)	3.1 (3.3)	3.4 (3.7)	3.5 (3.1)	3.0 (3.4)	2.9 (3.0)

Statistical Analysis 1

Statistical Analysis Overview	Comparison Group Selection	Linagliptin 1, Any Other DPP-4, Linagliptin 2, Pioglitazone, Linagliptin 3, Second Generation Sulfonylurea
	Comments
	Type of Statistical Test	Superiority or Other
	Comments
Statistical Test of Hypothesis	p-Value
	Comments
	Method
	Comments
Method of Estimation	Estimation Parameter	R-squared
	Estimated Value	0.0858
	Confidence Interval	() %; to
	Parameter Dispersion	Type: Value:
	Estimation Comments	The R-squared can be between 0 and 1 and a value of 0 indicates that the model is no better than chance at making a prediction and a value of 1.0 indicates that the model perfectly identifies those within a group and those not.

4. Primary Outcome

Title	Missing EMR Characteristic: BMI (Body Mass Index)
Description	The missing EMR characteristic BMI defined as not obese, overweight, obese, severe obesity. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic BMI was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.
Time Frame	Up to 20 months

Outcome Measure Data

Analysis Population Description

All subjects in MarketScan cohort meeting inclusion/exclusion criteria. EMR-linked subset: From the study group we identified patients who have EMR data available.

Arm/Group Title	Linagliptin 1	Any Other DPP-4	Linagliptin 2	Pioglitazone	Linagliptin 3	Second Generation Sulfonylurea
Arm/Group Description	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to any other DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to second generation sulfonylurea.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication second generation sulfonylurea.
Measure Participants	243	3041	205	530	150	3050
Underweight	0.4 0.2%	0.1 0%	0.5 0.2%	0.0 0%	0.7 0.5%	0.1 0%
Normal	2.1 0.9%	3.9 0.1%	2.0 1%	3.4 0.6%	2.7 1.8%	4.0 0.1%
Overweight	11.5 4.7%	11.8 0.4%	13.7 6.7%	15.5 2.9%	10.7 7.1%	14.0 0.5%
Obese	35.4 14.6%	35.1 1.2%	35.1 17.1%	29.6 5.6%	36.0 24%	34.2 1.1%
Severe Obesity	16.5 6.8%	15.5 0.5%	16.1 7.9%	10.9 2.1%	16.0 10.7%	15.4 0.5%

Statistical Analysis 1

Statistical Analysis Overview	Comparison Group Selection	Linagliptin 1, Any Other DPP-4, Linagliptin 2, Pioglitazone, Linagliptin 3, Second Generation Sulfonylurea
	Comments
	Type of Statistical Test	Superiority or Other
	Comments
Statistical Test of Hypothesis	p-Value
	Comments
	Method
	Comments
Method of Estimation	Estimation Parameter	C-statistics
	Estimated Value	0.623
	Confidence Interval	() %; to
	Parameter Dispersion	Type: Value:
	Estimation Comments	The C-statistics can be between 0.5 and 1 and a value of 0.5 indicates that the model is no better than chance at making a prediction and a value of 1.0 indicates that the model perfectly identifies those within a group and those not.

5. Primary Outcome

Title	Missing EMR Characteristic: BMI (Continuous)
Description	The missing EMR characteristic BMI is BMI value. Linear regression models were ran using a prioritized list of claims-based covariates as predictors and the value of select EMR-based clinical characteristics BMI as continuous outcomes. The estimated value represented is actually prediction accuracy defined by R-squared.
Time Frame	Up to 20 months

Outcome Measure Data

Analysis Population Description

All subjects in MarketScan cohort meeting inclusion/exclusion criteria. EMR-linked subset: From the study group we identified patients who have EMR data available.

Arm/Group Title	Linagliptin 1	Any Other DPP-4	Linagliptin 2	Pioglitazone	Linagliptin 3	Second Generation Sulfonylurea
Arm/Group Description	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to any other DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to second generation sulfonylurea.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication second generation sulfonylurea.
Measure Participants	243	3041	205	530	150	3050
Mean (Standard Deviation) [Kg/m^2]	36.3 (8.5)	35.5 (8.0)	36.1 (8.8)	34.2 (7.0)	36.6 (9.2)	35.1 (7.8)

Statistical Analysis 1

Statistical Analysis Overview	Comparison Group Selection	Linagliptin 1, Any Other DPP-4, Linagliptin 2, Pioglitazone, Linagliptin 3, Second Generation Sulfonylurea
	Comments
	Type of Statistical Test	Superiority or Other
	Comments
Statistical Test of Hypothesis	p-Value
	Comments
	Method
	Comments
Method of Estimation	Estimation Parameter	R-squared
	Estimated Value	0.1753
	Confidence Interval	() %; to
	Parameter Dispersion	Type: Value:
	Estimation Comments	The R-squared can be between 0 and 1 and a value of 0 indicates that the model is no better than chance at making a prediction and a value of 1.0 indicates that the model perfectly identifies those within a group and those not.

6. Primary Outcome

Title	Missing EMR Characteristic: HbA1c (Hemoglobin A1c (Glycosylated Hemoglobin))
Description	The missing EMR characteristic HbA1c defined as value in 6 months prior to and including index date. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic HbA1c was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.
Time Frame	Up to 20 months

Outcome Measure Data

Analysis Population Description

All subjects in MarketScan cohort meeting inclusion/exclusion criteria. EMR-linked subset: From the study group we identified patients who have EMR data available.

Arm/Group Title	Linagliptin 1	Any Other DPP-4	Linagliptin 2	Pioglitazone	Linagliptin 3	Second Generation Sulfonylurea
Arm/Group Description	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to any other DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to second generation sulfonylurea.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication second generation sulfonylurea.
Measure Participants	243	3041	205	530	150	3050
Mean (Standard Deviation) [Percentage]	8.2 (1.4)	8.6 (1.9)	8.3 (1.4)	9.0 (2.2)	8.0 (1.5)	8.8 (2.0)

Statistical Analysis 1

Statistical Analysis Overview	Comparison Group Selection	Linagliptin 1, Any Other DPP-4, Linagliptin 2, Pioglitazone, Linagliptin 3, Second Generation Sulfonylurea
	Comments
	Type of Statistical Test	Superiority or Other
	Comments
Statistical Test of Hypothesis	p-Value
	Comments
	Method
	Comments
Method of Estimation	Estimation Parameter	C-statistics
	Estimated Value	0.699
	Confidence Interval	() %; to
	Parameter Dispersion	Type: Value:
	Estimation Comments	The C-statistics can be between 0.5 and 1 and a value of 0.5 indicates that the model is no better than chance at making a prediction and a value of 1.0 indicates that the model perfectly identifies those within a group and those not.

7. Primary Outcome

Title	Missing EMR Characteristic: eGFR (Glomerular Filtration Rate)
Description	The missing EMR characteristic eGFR defined as value in 6 months prior to and including index date. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic eGFR was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.
Time Frame	Upto 20 months

Outcome Measure Data

Analysis Population Description

All subjects in MarketScan cohort meeting inclusion/exclusion criteria. EMR-linked subset: From the study group we identified patients who have EMR data available.

Arm/Group Title	Linagliptin 1	Any Other DPP-4	Linagliptin 2	Pioglitazone	Linagliptin 3	Second Generation Sulfonylurea
Arm/Group Description	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to any other DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to second generation sulfonylurea.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication second generation sulfonylurea.
Measure Participants	243	3041	205	530	150	3050
Mean (Standard Deviation) [ml/min per 1.73 m^2]	103.8 (19.2)	107.0 (18.0)	104.9 (18.7)	108.7 (19.3)	105.5 (18.5)	106.8 (18.7)

Statistical Analysis 1

Statistical Analysis Overview	Comparison Group Selection	Linagliptin 1, Any Other DPP-4, Linagliptin 2, Pioglitazone, Linagliptin 3, Second Generation Sulfonylurea
	Comments
	Type of Statistical Test	Superiority or Other
	Comments
Statistical Test of Hypothesis	p-Value
	Comments
	Method
	Comments
Method of Estimation	Estimation Parameter	C-statistics
	Estimated Value	0.683
	Confidence Interval	() %; to
	Parameter Dispersion	Type: Value:
	Estimation Comments	The C-statistics can be between 0.5 and 1 and a value of 0.5 indicates that the model is no better than chance at making a prediction and a value of 1.0 indicates that the model perfectly identifies those within a group and those not.

8. Primary Outcome

Title	Missing EMR Characteristic: Total Cholesterol
Description	The missing EMR characteristic total cholesterol defined as value in 6 months prior to and including index date. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic total cholesterol was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.
Time Frame	Up to 20 months

Outcome Measure Data

Analysis Population Description

All subjects in MarketScan cohort meeting inclusion/exclusion criteria. EMR-linked subset: From the study group we identified patients who have EMR data available.

Arm/Group Title	Linagliptin 1	Any Other DPP-4	Linagliptin 2	Pioglitazone	Linagliptin 3	Second Generation Sulfonylurea
Arm/Group Description	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to any other DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to second generation sulfonylurea.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication second generation sulfonylurea.
Measure Participants	243	3041	205	530	150	3050
Mean (Standard Deviation) [mg/dl]	188.8 (59.7)	177.6 (47.0)	189.7 (62.9)	185.8 (58.8)	194.6 (53.1)	185.8 (50.8)

Statistical Analysis 1

Statistical Analysis Overview	Comparison Group Selection	Linagliptin 1, Any Other DPP-4, Linagliptin 2, Pioglitazone, Linagliptin 3, Second Generation Sulfonylurea
	Comments
	Type of Statistical Test	Superiority or Other
	Comments
Statistical Test of Hypothesis	p-Value
	Comments
	Method
	Comments
Method of Estimation	Estimation Parameter	C-statistics
	Estimated Value	0.757
	Confidence Interval	() %; to
	Parameter Dispersion	Type: Value:
	Estimation Comments	The C-statistics can be between 0.5 and 1 and a value of 0.5 indicates that the model is no better than chance at making a prediction and a value of 1.0 indicates that the model perfectly identifies those within a group and those not.

9. Primary Outcome

Title	Missing EMR Characteristic: Systolic BP (Blood Pressure)
Description	The missing EMR characteristic systolic BP defined as value in 6 months prior to and including index date. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic systolic BP was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.
Time Frame	Up to 20 months

Outcome Measure Data

Analysis Population Description

All subjects in MarketScan cohort meeting inclusion/exclusion criteria. EMR-linked subset: From the study group we identified patients who have EMR data available.

Arm/Group Title	Linagliptin 1	Any Other DPP-4	Linagliptin 2	Pioglitazone	Linagliptin 3	Second Generation Sulfonylurea
Arm/Group Description	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to any other DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to second generation sulfonylurea.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication second generation sulfonylurea.
Measure Participants	243	3041	205	530	150	3050
Mean (Standard Deviation) [mmHg]	130.2 (16.3)	129.7 (15.7)	131.0 (16.1)	131.5 (17.2)	131.2 (17.3)	131.3 (17.0)

Statistical Analysis 1

Statistical Analysis Overview	Comparison Group Selection	Linagliptin 1, Any Other DPP-4, Linagliptin 2, Pioglitazone, Linagliptin 3, Second Generation Sulfonylurea
	Comments
	Type of Statistical Test	Superiority or Other
	Comments
Statistical Test of Hypothesis	p-Value
	Comments
	Method
	Comments
Method of Estimation	Estimation Parameter	C-statistics
	Estimated Value	0.618
	Confidence Interval	() %; to
	Parameter Dispersion	Type: Value:
	Estimation Comments	The C-statistics can be between 0.5 and 1 and a value of 0.5 indicates that the model is no better than chance at making a prediction and a value of 1.0 indicates that the model perfectly identifies those within a group and those not.

10. Primary Outcome

Title	Missing EMR Characteristic: Diastolic BP
Description	The missing EMR characteristic diastolic BP defined as value in 6 months prior to and including index date. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic diastolic BP was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.
Time Frame	Up to 20 months

Outcome Measure Data

Analysis Population Description

All subjects in MarketScan cohort meeting inclusion/exclusion criteria. EMR-linked subset: From the study group we identified patients who have EMR data available.

Arm/Group Title	Linagliptin 1	Any Other DPP-4	Linagliptin 2	Pioglitazone	Linagliptin 3	Second Generation Sulfonylurea
Arm/Group Description	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to any other DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to second generation sulfonylurea.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication second generation sulfonylurea.
Measure Participants	243	3041	205	530	150	3050
Mean (Standard Deviation) [mmHg]	79.5 (10.6)	78.8 (10.0)	80.0 (10.2)	79.3 (10.6)	80.0 (10.5)	79.6 (10.5)

Statistical Analysis 1

Statistical Analysis Overview	Comparison Group Selection	Linagliptin 1, Any Other DPP-4, Linagliptin 2, Pioglitazone, Linagliptin 3, Second Generation Sulfonylurea
	Comments
	Type of Statistical Test	Superiority or Other
	Comments
Statistical Test of Hypothesis	p-Value
	Comments
	Method
	Comments
Method of Estimation	Estimation Parameter	C-statistics
	Estimated Value	0.618
	Confidence Interval	() %; to
	Parameter Dispersion	Type: Value:
	Estimation Comments	The C-statistics can be between 0.5 and 1 and a value of 0.5 indicates that the model is no better than chance at making a prediction and a value of 1.0 indicates that the model perfectly identifies those within a group and those not.

11. Primary Outcome

Title	Binary EMR Characteristic: Neuropathy
Description	The missing EMR characteristic neuropathy defined as participants with any note of diabetic neuropathy. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic neuropathy was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.
Time Frame	Up to 20 months

Outcome Measure Data

Analysis Population Description

All subjects in MarketScan cohort meeting inclusion/exclusion criteria. EMR-linked subset: From the study group we identified patients who have EMR data available.

Arm/Group Title	Linagliptin 1	Any Other DPP-4	Linagliptin 2	Pioglitazone	Linagliptin 3	Second Generation Sulfonylurea
Arm/Group Description	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to any other DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to second generation sulfonylurea.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication second generation sulfonylurea.
Measure Participants	243	3041	205	530	150	3050
Number [Percentage of participants]	9.9 4.1%	10.0 0.3%	10.7 5.2%	11.3 2.1%	12.0 8%	11.0 0.4%

Statistical Analysis 1

Statistical Analysis Overview	Comparison Group Selection	Linagliptin 1, Any Other DPP-4, Linagliptin 2, Pioglitazone, Linagliptin 3, Second Generation Sulfonylurea
	Comments
	Type of Statistical Test	Superiority or Other
	Comments
Statistical Test of Hypothesis	p-Value
	Comments
	Method
	Comments
Method of Estimation	Estimation Parameter	C-statistics
	Estimated Value	0.733
	Confidence Interval	() %; to
	Parameter Dispersion	Type: Value:
	Estimation Comments	The C-statistics can be between 0.5 and 1 and a value of 0.5 indicates that the model is no better than chance at making a prediction and a value of 1.0 indicates that the model perfectly identifies those within a group and those not.

12. Primary Outcome

Title	Binary EMR Characteristic: Nephropathy
Description	The missing EMR characteristic nephropathy defined as participants with any note of diabetic nephropathy. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic nephropathy was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.
Time Frame	Upto 20 months

Outcome Measure Data

Analysis Population Description

All subjects in MarketScan cohort meeting inclusion/exclusion criteria. EMR-linked subset: From the study group we identified patients who have EMR data available.

Arm/Group Title	Linagliptin 1	Any Other DPP-4	Linagliptin 2	Pioglitazone	Linagliptin 3	Second Generation Sulfonylurea
Arm/Group Description	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to any other DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to second generation sulfonylurea.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication second generation sulfonylurea.
Measure Participants	243	3041	205	530	150	3050
Number [Percentage of participants]	5.8 2.4%	3.2 0.1%	5.9 2.9%	4.3 0.8%	4.7 3.1%	3.0 0.1%

Statistical Analysis 1

Statistical Analysis Overview	Comparison Group Selection	Linagliptin 1, Any Other DPP-4, Linagliptin 2, Pioglitazone, Linagliptin 3, Second Generation Sulfonylurea
	Comments
	Type of Statistical Test	Superiority or Other
	Comments
Statistical Test of Hypothesis	p-Value
	Comments
	Method
	Comments
Method of Estimation	Estimation Parameter	C-statistics
	Estimated Value	0.827
	Confidence Interval	() %; to
	Parameter Dispersion	Type: Value:
	Estimation Comments	The C-statistics can be between 0.5 and 1 and a value of 0.5 indicates that the model is no better than chance at making a prediction and a value of 1.0 indicates that the model perfectly identifies those within a group and those not.

13. Primary Outcome

Title	Binary EMR Characteristic: Retinopathy
Description	The missing EMR characteristic retinopathy defined as participants with any note of diabetic retinopathy. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic retinopathy was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.
Time Frame	Up to 20 months

Outcome Measure Data

Analysis Population Description

All subjects in MarketScan cohort meeting inclusion/exclusion criteria. EMR-linked subset: From the study group we identified patients who have EMR data available.

Arm/Group Title	Linagliptin 1	Any Other DPP-4	Linagliptin 2	Pioglitazone	Linagliptin 3	Second Generation Sulfonylurea
Arm/Group Description	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to any other DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to second generation sulfonylurea.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication second generation sulfonylurea.
Measure Participants	243	3041	205	530	150	3050
Number [Percentage of participants]	1.2 0.5%	1.9 0.1%	1.0 0.5%	2.8 0.5%	1.3 0.9%	1.7 0.1%

Statistical Analysis 1

Statistical Analysis Overview	Comparison Group Selection	Linagliptin 1, Any Other DPP-4, Linagliptin 2, Pioglitazone, Linagliptin 3, Second Generation Sulfonylurea
	Comments
	Type of Statistical Test	Superiority or Other
	Comments
Statistical Test of Hypothesis	p-Value
	Comments
	Method
	Comments
Method of Estimation	Estimation Parameter	C-statistics
	Estimated Value	0.801
	Confidence Interval	() %; to
	Parameter Dispersion	Type: Value:
	Estimation Comments	The C-statistics can be between 0.5 and 1 and a value of 0.5 indicates that the model is no better than chance at making a prediction and a value of 1.0 indicates that the model perfectly identifies those within a group and those not.

14. Primary Outcome

Title	Binary EMR Characteristic: Pancreatitis
Description	The missing EMR characteristic pancreatitis defined as participants with any note of prior pancreatitis. The associations between claims-based covariates and missingness on EMR characteristics were investigated by estimating a logistic regression model (and multinomial logistic regression, depending on the number of categories for the EMR characteristic) for each EMR characteristic where an indicator for missing the EMR characteristic pancreatitis was the dependent variable and all claims-based covariates were included as independent variables. The estimated value represented is actually prediction accuracy defined by C-statistics.
Time Frame	Up to 20 months

Outcome Measure Data

Analysis Population Description

All subjects in MarketScan cohort meeting inclusion/exclusion criteria. EMR-linked subset: From the study group we identified patients who have EMR data available.

Arm/Group Title	Linagliptin 1	Any Other DPP-4	Linagliptin 2	Pioglitazone	Linagliptin 3	Second Generation Sulfonylurea
Arm/Group Description	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to any other DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication DPP-4 (Dipeptidyl peptidase-4 inhibitors).	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication pioglitazone.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication Linagliptin subjects matched to second generation sulfonylurea.	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication second generation sulfonylurea.
Measure Participants	243	3041	205	530	150	3050
Number [Percentage of participants]	0.8 0.3%	0.5 0%	1.0 0.5%	0.2 0%	0.7 0.5%	0.5 0%

Statistical Analysis 1

Statistical Analysis Overview	Comparison Group Selection	Linagliptin 1, Any Other DPP-4, Linagliptin 2, Pioglitazone, Linagliptin 3, Second Generation Sulfonylurea
	Comments
	Type of Statistical Test	Superiority or Other
	Comments
Statistical Test of Hypothesis	p-Value
	Comments
	Method
	Comments
Method of Estimation	Estimation Parameter	C-statistics
	Estimated Value	0.836
	Confidence Interval	() %; to
	Parameter Dispersion	Type: Value:
	Estimation Comments	The C-statistics can be between 0.5 and 1 and a value of 0.5 indicates that the model is no better than chance at making a prediction and a value of 1.0 indicates that the model perfectly identifies those within a group and those not.

Adverse Events

Adverse Event Reporting Description	Serious and other (non-serious) adverse events were not of interest in this study and therefore were not collected or assessed as part of the study, in addition individual patient data is not available therefore adverse event data is not presented.
Arm/Group Title	MarketScan
Arm/Group Description	Patients had a recorded diagnosis of type 2 diabetes mellitus (T2DM) using an oral and non-insulin injected glucose-lowering medication identified from the MarketScan database.
All Cause Mortality
	MarketScan
	Affected / at Risk (%)	# Events
Total	/ (NaN)
Serious Adverse Events
	MarketScan
	Affected / at Risk (%)	# Events
Total	0/0 (NaN)
Other (Not Including Serious) Adverse Events
	MarketScan
	Affected / at Risk (%)	# Events
Total	0/0 (NaN)

Limitations/Caveats

[Not Specified]

More Information

Certain Agreements

Principal Investigators are NOT employed by the organization sponsoring the study.

Boehringer Ingelheim (BI) acknowledges that investigators have the right to publish the study results. Investigators shall provide BI with a copy of any publication or presentation for review prior to any submission. Such review will be done with regard to proprietary information, information related to patentable inventions, medical, scientific, and statistical accuracy within 60 days. BI may request a delay of the publication in order to protect BI's intellectual property rights.