Buscar en
Endocrinología y Nutrición (English Edition)
Toda la web
Inicio Endocrinología y Nutrición (English Edition) Characterization of and costs associated to the profile of patients with type 2 ...
Journal Information
Vol. 60. Issue 10.
Pages 557-569 (December 2013)
Visits
2232
Vol. 60. Issue 10.
Pages 557-569 (December 2013)
Original article
Full text access
Characterization of and costs associated to the profile of patients with type 2 diabetes treated with metformin who are added a second oral antidiabetic drug: A population study
Caracterización y costes asociados al perfil del paciente con diabetes tipo 2 en tratamiento con metformina al que se le añade un segundo fármaco antidiabético oral: estudio de base poblacional
Visits
2232
Antoni Sicras-Mainara,
Corresponding author
asicras@bsa.cat

Corresponding author.
, Beatriu Font-Ramosb, Cecilia Roldán-Suárezc, Ruth Navarro-Artiedad, Jordi Ibáñez-Nollae
a Dirección de Planificación, Badalona Serveis Assistencials SA, Badalona, Barcelona, Spain
b Health Outcomes Research, Novartis Farmacéutica SA, Barcelona, Spain
c Medical Advisord Cardiologist, Novartis Farmacéutica SA, Barcelona, Spain
d Documentación Médica, Hospital Germans Trias i Pujol, Badalona, Barcelona, Spain
e Dirección médica, Badalona Serveis Assistencials SA, Badalona, Barcelona, Spain
This item has received
Article information
Abstract
Full Text
Bibliography
Download PDF
Statistics
Figures (2)
Tables (6)
Table 1. Unit costs and work productivity losses.
Table 2. Baseline characteristics of study series.
Table 3. Relationship between compliance, persistence, and degree of diabetes control. Two-year follow-up.
Table 4. Biochemical and anthropometric parameters.
Table 5. Mean use of resources by study group.
Table 6. Gross and adjusted cost model (24-month follow-up) by study group in a retrospective cohort.
Show moreShow less
Abstract
Objectives

To determine compliance, metabolic control, complications and healthcare costs of patients with type 2 diabetes mellitus (T2DM) treated with metformin who started a second antidiabetic drug.

Patients and methods

Design multicenter observational retrospective. Patients aged ≥30 years (age) were evaluated, treated with metformin and started a second antidiabetic treatment during 2008–2009. There were 4 patient groups (metformin and another antidiabetic): (a) dipeptidyl peptidase-4 inhibitors (IDPP4), (b) sulfonylureas, (c) glitazones and (d) insulin. Main measures: comorbidity, metabolic control, compliance and complications. Patients were followed for 2 years. The cost model differed in direct (primary care/specialist) and indirect (labor productivity) healthcare costs. Statistical analysis: logistic regression models and ANCOVA, p<0.05.

Results

2067 patients were included (mean age: 66.6 years, male: 53.1%). 25.1% started a second treatment with IDPP4; 42.9% sulfonylureas, 14.0% glitazones and 18.0% insulin. At 2 years of follow-up, patients treated with IDPP4 showed greater adherence versus 70.3%. 59.9%, 60.3% and 58.4; better control of 64.3% versus DM2. 62.6%, 62.8% and 50.5% and a decrease of 13.9% compared to hypoglycemia 40.4%, 37.6% and 58.9%, respectively (p<0.001). The average/unit total cost was 2321€ versus 2475€, 2724€ and 3164€, respectively, p<0.001. Rates of cardiovascular events and renal failure were 3.7%, 6.4%, 7.6% and 10.2%, respectively.

Conclusions

Sulfonylureas were the most commonly used drugs. Patients treated with IDPP4 had higher compliance and control of diabetes, with lower rates of hypoglycemia and healthcare costs.

Keywords:
Diabetes
Compliance
Control
Hypoglycemias
Healthcare costs
Cardiovascular event
Resumen
Objetivos

Determinar el cumplimiento, control metabólico, complicaciones y costes sanitarios de los pacientes tratados con metformina que iniciaron un segundo fármaco antidiabético en pacientes con diabetes tipo 2 (DM2).

Pacientes y métodos

Diseño observacional-multicéntrico de carácter retrospectivo. Se evaluaron pacientes de edad igual o superior a 30 años, en tratamiento con metformina y que iniciaron un segundo tratamiento antidiabético durante 2008-2009. Se establecieron 4 grupos de pacientes (metformina y otro antidiabético): (a) inhibidores de la dipeptidil peptidasa 4 (IDPP4); (b) sulfonilureas; (c) glitazonas, y (d) insulinas. Principales medidas: comorbilidad, control metabólico, cumplimiento y complicaciones. El seguimiento se realizó durante 2 años. El modelo de costes diferenció los costes sanitarios directos (atención primaria/especializada) e indirectos (productividad laboral). Análisis estadístico: modelos de regresión logística y ANCOVA, p<0,05.

Resultados

Se seleccionaron 2.067 pacientes (edad media: 66,6 años; varones: 53,1%). Un 25,1% iniciaron un segundo tratamiento con IDPP4; 42,9% con sulfonilureas, 14,0% con glitazonas, y 18,0% con insulinas. A los 2 años de seguimiento, los pacientes tratados con IDPP4 mostraron un mayor cumplimiento terapéutico (70,3 vs. 59,9%, 60,3% y 58,4); mejor control de la DM2 (64,3 vs. 62,6%, 62,8 y 50,5%) y menor proporción de hipoglucemias (13,9 frente a 40,4%, 37,6% y 58,9%, respectivamente) (p<0,001). El promedio/unitario de los costes totales fue de 2.321€ frente a 2.475€, 2.724€, y 3.164€, respectivamente; p<0,001. Las tasas de eventos cardiovasculares e insuficiencia renal fueron del 3,7; 6,4; 7,6, y 10,2%, respectivamente.

Conclusiones

Las sulfonilureas fueron los fármacos más utilizados. Los pacientes en tratamiento con IDPP4 presentaron mayor cumplimiento y control de la diabetes, con menores tasas de hipoglucemias y costes sanitarios.

Palabras clave:
Diabetes
Cumplimiento
Control
Hipoglucemias
Costes sanitarios
Evento cardiovascular
Full Text
Introduction

Cardiovascular disease is the leading cause of morbidity and mortality in developed countries. The detection and control of the different cardiovascular risk factors continues to be the main strategy for preventing cardiovascular disease.1 Diabetes mellitus (DM) is one of the diseases with the greatest social and health impact, not only because of its high frequency, but also mainly because of its attendant complications and its significant role as a cardiovascular risk factor.2–4 The prevalence of DM in Spain is 8% in women and 12% in males, ranging from 6% to 12% depending on the different studies, populations, and methods used for diagnosis, and may be up to 20% in people older than 75 years.5,6

The non-drug treatment for DM comprises three basic aspects: diet, physical exercise, and healthy lifestyle.7 If metabolic objectives are not achieved after a reasonable time with non-drug treatment, drug treatment should be started. The objective of drug treatment in DM is to achieve the optimum metabolic control with the maximum possible safety. Metformin is the drug of first choice recommended by the different scientific societies.7,8 Very strict control is recommended in the early treatment of DM, and when adequate blood glucose control is not achieved with monotherapy, a second drug should be added.8,9 The most common acute complication in diabetes is hypoglycemia, especially in patients treated with insulin and/or sulfonylureas.8 In patients with type 2 diabetes mellitus (T2DM), symptoms of hypoglycemia are non-specific and difficult to quantify, and may vary depending on the degree of hypoglycemia, patient age, and the rate of decrease in glycemia.10 It should be noted that the new therapeutic class of dipeptidyl peptidase 4 inhibitors (DDP4 inhibitors) has the potential advantage over traditional secretagogues for substantially decreasing hypoglycemia because its mechanism for stimulating insulin secretion is glucose-dependent.11

T2DM is one of the diseases which has the greatest social and health impact, not only because of its high prevalence, but also due to its acute and chronic complications, its high morbidity and mortality rates, its impact on the quality of life, and because it requires a high level of healthcare resource utilization.12,13 Studies in Spain on complications, metabolic control, and the use and costs of healthcare resources in patients treated with combined anti-diabetic drugs are limited or non-existent, which is why this study may be of some relevance. The main study objective was to determine the different treatment options in patients with T2DM who are receiving metformin and who start a second antidiabetic treatment in standard clinical practice in a population setting. The following were also reported for each group (dual therapy): (a) potential complications (hypoglycemia and macrovascular complications [cardiovascular events –CVEs and nephropathy]); (b) changes in therapeutic control objectives and treatment compliance; and (c) the use and costs of healthcare resources.

Patients and methodsStudy design and population

A multicenter, observational, longitudinal study was conducted based on a review of the medical records (computer databases) of patients followed up on an outpatient or inpatient basis who were treated with metformin for T2DM. The study population consisted of patients from six primary care centers and two hospitals, Hospital Municipal de Badalona and Hospital Germans Trías i Pujol (inpatients). The population covered by the centers was mainly urban, of intermediate to low socioeconomic status, and working in the industrial sector.

Inclusion and exclusion criteria

The study enrolled all patients who started a second anti-diabetic treatment between 1/01/2008 and 31/12/2009 and who met the following criteria: (a) aged 30 years or older; (b) of either sex; (c) were diagnosed with T2DM at least 12 months before study start; (d) were in regular compliance with the protocol/cardiovascular risk guide established; (e) were in the chronic prescription program to get medical prescriptions (with written record of daily dose, time interval, and duration of each treatment administered as prescribed by the physician); (f) were currently being treated with metformin as first therapeutic option (monotherapy); and (g) were patients in whom a follow-up for at least two years after the start of the second antidiabetic drug could be warranted. Patients moving to other locations, those living outside the area, and those only attending integrated specialists were excluded. Patients were followed up for 24 months from the date of the start of treatment for the following: (a) complications (hypoglycemia and microvascular and macrovascular [CVEs] complications); (b) changes in therapeutic control objectives (HbA1c); (c) treatment compliance; and (d) the use and costs of healthcare resources.

Evaluation of type 2 diabetes mellitus and its complications

T2DM was diagnosed based on component 7 of diseases and health problems14 (T90) of the International Classification of Primary Care (ICPC-2) and the coding of hospital discharge and emergencies according to the International Classification of Diseases, 9th revision, clinical modification (ICD-9-CM [250.00–250.92]).

Hypoglycemia

All cases of symptomatic hypoglycemia were identified. Records were collected from the reasons given for visiting healthcare centers and/or from the computer clinical protocols during patient follow-up.

Macrovascular complications, cardiovascular disease, and kidney disease

New cases of CVEs or kidney disease were recorded during the follow-up period (two years). These included: (a) heart diseases, such as cardiac ischemia (codes: K74, K76; stable, unstable, and other), acute myocardial infarction (code. K75), and heart failure (K77) according to the definition in diagnostic criteria of the World Health Organization; (b) cerebrovascular disease, including stroke (ischemic or hemorrhagic) and transient ischemic attack, K90 and K91; (c) peripheral artery disease (all types); and (d) kidney disease (diabetic nephropathy or impaired kidney function [serum creatinine: males>133; females>124mmol, or glomerular filtration rate<60]).

A register was obtained from specialized care discharge reports and/or from ICPC-2.14 The cumulative incidence rate was defined as the proportion of healthy subjects who experienced the complication (the number of new cases). Cumulative incidence provides an estimate of the chance or risk that a subject free of a given disease will develop such a disease during a specific time interval. The results were not standardized because the population pyramid distributed by age and gender of the study patients was similar to that of the Catalonian population (source: Spanish National Statistics Institute).

Treatment description

This was a non-interventional study which collected information and clinical data on patients previously treated with antidiabetic drugs according to the Anatomical Therapeutic Chemical Classification System (ATC) based on the clinical judgment of physicians.15 The allocation of a patient to a specific treatment strategy was based on standard clinical and/or care practice. Information was collected on the following antidiabetic drugs: (a) metformin (A10BA*); (b) sulfonylureas (A10BB*); (c) glitazones (A10BG*); (d) insulins (all types); and (e) DPP-4 inhibitors (A10BH*), as monotherapy or in combination (A10BD*). Information was collected, according to recommendations made by physicians, from the prescriptions dispensed by the pharmacy using the pharmaceutical prescription monitoring program of CatSalut.

Compliance and persistence

Compliance was defined as the degree of coincidence or agreement of the behavior of a patient with regard to medication intake as recommended by healthcare professionals. The percentage compliance of the period was calculated as the ratio between the total number of tablets dispensed and the total number of tablets recommended or prescribed, assuming that drug dispensing, the purchase of the drug at the pharmacy, did not represent the actual use of intake, but was closely associated with the latter. High compliance was defined as values ≥80%, while rates ranging from 50% to 79% and <50% were considered as intermediate and low compliance, respectively. Treatment persistence was defined as time, measured in months, without discontinuation of initial treatment or without change to another medication at least 30 days after initial prescription. Insulin data were collected from the number of cartridges contained in the packages.

Study groups

The number of active substances was collected from the chronic patient prescriptions at study start according to the ATC classification.15 Four patient groups were established (metformin and another antidiabetic drug): (a) sulfonylureas; (b) glitazones; (c) insulins; and (d) DPP-4 inhibitors.

Sociodemographic and comorbidity variables

The main study variables included age (continuous), sex, and time since start of T2DM, as well as personal history based on ICPC-214: high blood pressure (K86, K87), dyslipidemia (T93), obesity (T82), smoking (P17), alcoholism (P15, P16), all types of organ failure (heart, liver, and kidney), ischemic heart disease (codes: K74, K76, K75), stroke (K90, K91, K93), chronic obstructive pulmonary disease (R95, chronic airflow obstruction), bronchial asthma (R96), types of dementia or memory disorders (P70, P20), neurological disorders (Parkinson [N87], epilepsy [N88], multiple sclerosis [N86] and other diseases [N99]), depressive syndrome (P76), and malignant neoplasms (all types; A79, B72-75, D74-78, F75, H75, K72, L71, L97, N74-76, R84-86, T71-73, U75-79, W72-73, X75-81, Y77-79).

For each patient, the following were used as summary variables of general comorbidity: (a) the Charlson comorbidity index16 as an approximation to patient severity, and (b) the individual case-mix index, obtained from the Adjusted Clinical Groups (ACG), a system that classifies patients by iso-consumption of resources.17 The ACG system software provides resource utilization bands (RUBs), so that each patient is grouped into one of five mutually exclusive categories based on his/her general morbidity (1: healthy users or very low morbidity; 2: low morbidity; 3: moderate morbidity; 4: high morbidity; 5: very high morbidity). Information was also collected on microvascular complications (diabetic retinopathy, diabetic nephropathy, diabetic neuropathy, and diabetic vasculopathy).

Biochemical and anthropometric parameters

Biochemical parameters and/or therapeutic control goals included: systolic and diastolic blood pressure (mmHg), body mass index (BMI, kg/m2), basal blood glucose (mg/dL), glycosylated hemoglobin (%), serum triglycerides, total cholesterol, high density lipoprotein cholesterol (HDL-C), and low density lipoprotein cholesterol (LDL-C) in mg/dL; and the estimation of cardiovascular risk (CVC; calculation: SCORE) according to criteria of the modified National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III).18 These parameters were collected at study start and end (two-year follow-up).

Resource utilization and cost model

Direct healthcare costs were defined as those related to care activities (medical visits, hospitalization days, visits to emergency rooms, diagnostic or treatment requests, etc.) carried out by healthcare professionals. Costs related to work productivity losses (number of sick leaves and days of disability) were considered as non-healthcare or indirect costs. Cost system design was defined by taking into consideration the characteristics of the organization and the degree of development of the information systems available. The product unit serving as the basis for the final calculation (during the study period) was the patient seen, and cost was given as mean cost per patient (unit cost). Table 1 shows the different study concepts and their economic value (in 2011). The different rates were obtained from the analytical accounts of the centers, except for medication and days of sick leave. All medical prescriptions were quantified based on retail price by pack at the time of prescription. Days of sick leave or productivity losses were considered as non-healthcare costs (indirect costs). Cost was quantified based on the minimum interprofessional wage (source: INE).19

Table 1.

Unit costs and work productivity losses.

Healthcare and non-healthcare resources  Unit costs (€) 
Medical visits
Medical visit to primary care  23.19 
Medical visit to the emergency room  117.53 
Hospitalization (one day)  320.90 
Medical visit to specialized care  104.41 
Supplemental tests
Laboratory tests  22.30 
Conventional radiology  18.50 
Diagnostic/therapeutic tests  37.12 
Drug prescription  Price+VAT 
Work productivity–indirect costs
Cost per day not worked  101.21 

Source of healthcare resources: our own analytical accounting. Values are given in euros.

Price+VAT: retail price plus VAT.

Source: Spanish National Statistics Institute. 2011 costs.
Confidentiality of information

The confidentiality of records was maintained in accordance with the Spanish Organic Act on Data Protection (15/1999, of 13 December) by using anonymized data. The study was classified by the Spanish Agency for Medicinal Products and Medical Devices (non-PAS), and subsequently approved by the Clinical Research Ethics Committee of Hospital Clínico y Provincial in Barcelona.

Statistical analysis

A univariate descriptive statistical analysis was conducted using means, standard deviation (SD), and 95% confidence intervals (CIs), and a Kolmogorov–Smirnov test was used to verify the normal distribution of quantitative variables. Kaplan–Meier survival curves were used to quantify median persistence time of drugs. In the bivariate analysis, ANOVA, Chi-square, Pearsons's linear correlation, and non-parametric Mann–Whitney tests, and means comparison for paired groups were used. A logistic regression analysis was performed to determine the comorbidities associated with the group of DPP-4 inhibitors and insulins, and another analysis was done to define the variables associated with CVEs (presence/absence) using the enter procedure (statistic: Wald). Outpatient and inpatient costs were compared as recommended by Thompson and Barber20 using an analysis of covariance (ANCOVA) with sex, age, RUBs, and the Charlson index as covariates (procedure: estimation of marginal means, Bonferroni correction).

Results

Of the 62,370 subjects over 30 years of age assigned and regularly seen at the centers, 48.295 required care, and 6620 patients were diagnosed with T2DM (prevalence: 10.6%; 95% CI: 10.4–10.8%). A total of 2067 patients treated with antidiabetic drugs (associated with metformin) were selected for the study. By study groups, 42.9% (No.=886) were treated with sulfonylureas, 14.0% (No.=290) with glitazones, 18.0% (No.=372) with insulins, and 25.1% (No.=519) with DPP-4 inhibitors, p<0.001. The mean age was 66.6 (SD: 10.9) years, and 53.1% were males.

Table 2 shows the baseline characteristics of the study series by groups of treated patients. Patients treated with DPP-4 inhibitors had a lower mean age as compared to those on sulfonylureas and insulins and a similar age to those receiving glitazones (65.8 versus 67.7, 67.4, and 65.7 years, respectively; p<0.001). A higher proportion of women were found in the sulfonylurea group as compared to those treated with glitazones, insulins, and DPP-4 inhibitors (57.4% versus 50.3%, 43.8%, and 53.9%, respectively; p<0.001). Patients had a similar general comorbidity (5.4, 5.6, 5.6, and 5.3 diagnoses, respectively). Patients treated with insulins had higher rates of ischemic heart disease (23.4%), stroke (26.3%), organ failure (26.6%), retinopathy (34.2%), neuropathy (5.6%), and impaired glomerular filtration rate (22.8%), p<0.05.

Table 2.

Baseline characteristics of study series.

Study groups  Sulfonylureas  Glitazones  Insulins  DPP-4 inhibitors  Total  pa 
Number of patients, %  No.=886 (42.9%)  No.=290 (14.0%)  No.=372 (18.0%)  No.=519 (25.1%)  2067 (100%)   
Sociodemographic characteristics
Mean age, years  67.7 (11.0)a  65.7 (10.9)  67.4 (11.1)a  65.8 (10.4)  66.6 (10.9)  <0.001 
Sex (male)  57.4%a  50.3%  43.8%a  53.9%  53.1%  <0.001 
Retired (SS)  80.5%a  76.9%a  84.1%a  69.4%  77.8%  <0.001 
Overall comorbidity
Mean number of diagnoses  5.4 (2.4)  5.6 (2.6)  5.6 (2.5)  5.3 (2.3)  5.4 (2.4)  NS 
Mean Charlson index  1.0 (0.4)  1.0 (0.4)  1.1 (0.5)  1.0 (0.5)  1.0 (0.4)  NS 
Mean RUBs  3.0 (0.6)  2.9 (0.6)  3.0 (0.6)  2.9 (0.5)  3.0 (0.6)  NS 
RUB-1  1.9%  0.1%  1.7%  1.6%  1.5%   
RUB-2  13.8%  16.9%  11.1%  13.5%  13.7%   
RUB-3  71.9%  73.3%  72.2%  77.5%  73.5%   
RUB-4  11.2%  7.8%  14.5%  6.6%  10.2%   
RUB-5  1.3%  1.9%  0.6%  0.8%  1.1%  NS 
Associated comorbidities
High blood pressure  69.4%  64.1%  72.3%  65.9%  68.3%  NS 
Dyslipidemia  64.6%  61.7%  63.2%  64.0%  63.8%  NS 
Obesity  24.2%  29.7%  22.6%  26.2%  25.2%  NS 
Active smoking  20.1%  25.2%  22.3%  23.5%  22.1%  NS 
Alcoholism  3.8%  4.8%  3.5%  2.7%  3.6%  NS 
Ischemic heart disease  14.1%  12.1%  23.4%a  12.9%  15.2%  <0.001 
Stroke  16.0%  16.9%  26.3%a  13.1%  17.3%  <0.001 
Organ failures  16.9%  18.3%  26.6%a  16.4%  18.7%  <0.001 
Bronchial asthma  4.1%  7.6%  7.0%  4.4%  5.2%  NS 
COPD  5.5%  7.6%  9.4%  6.9%  6.9%  NS 
Neurological diseases  0.7%  1.7%  1.3%  0.8%  1.0%  NS 
Dementia (all types)  3.4%  2.4%  5.1%  2.7%  3.4%  NS 
Depressive syndrome  17.9%a  19.7%a  23.4%  23.7%  20.6%  0.032 
Malignant neoplasms  10.5%  10.0%  11.8%  8.9%  10.3%  NS 
Relationship to diabetes
Diabetic retinopathy  14.6%  26.2%a  34.1%a  17.0%  22.1%  <0.001 
Diabetic neuropathy  2.5%  4.1%  5.6%a  3.1%  3.4%  0.036 
Diabetic nephropathy  1.9%  2.1%  3.5%  1.7%  2.2%  NS 
Impaired glomerular filtration  14.6%  16.6%  22.8%a  12.1%  15.7%  <0.001 

Values are percentages or means (standard deviation).

RUBs: resource utilization bands; COPD: chronic obstructive pulmonary disease; NS: not significant; p: statistical significance; SS: social security.

a

Significant comparison between DPP-4 inhibitors and all other drug groups (sulfonylureas, glitazones, and insulins).

In the logistic regression model, patients in the DPP-4 inhibitor group were associated with an odds ratio (OR) for major depression of 1.4 (95% CI: 1.0–1.7; p<0.001) and had a better metabolic control of DM, OR=1.2 (95% CI: 1.1–1.5; p=0.018), while patients in the insulin group were associated with ischemic heart disease with an OR of 1.4 (95% CI: 1.0–1.7; p<0.001), with major depression with an OR of 1.3 (95% CI: 1.1–1.6; p<0.038), and with diabetic retinopathy with an OR of 1.9 (95% CI: 1.5–2.3; p<0.001).

Table 3 shows the association between compliance, persistence, and the degree of diabetes control by study groups. Patients in the DPP-4 inhibitor group had a higher mean treatment compliance (70.3% versus 60.3% [glitazones] and 59.9% [sulfonylureas], and 58.4% [insulins]; p<0.001) and greater treatment persistence at 48 months (63.4% versus 51.0%, 52.4%, and 48.1%; p<0.001), respectively. An acceptable correlation was seen between compliance and treatment persistence in months (r=0.451; p<0.001) for all groups. Control of T2DM at the end of follow-up of the patient cohort was higher in the DPP-4 inhibitor group as compared to all other groups (64.3% versus 62.8%, 62.6%, and 50.5%, respectively; p<0.001).

Table 3.

Relationship between compliance, persistence, and degree of diabetes control. Two-year follow-up.

Study groups  Sulfonylureas  Glitazones  Insulins  DPP-4 inhibitors  Total  pa 
Number of patients, %  No.=886 (42.9%)  No.=290 (14.0%)  No.=372 (18.0%)  No.=519 (25.1%)  2067 (100%)   
Time since diagnosis of diabetes, years  8.2 (11.3)  8.7 (10.4)  3.6 (7.8)a  8.9 (4.6)  7.6 (9.5)  <0.001 
Time since start of metformin (>1 year)  75.9%  75.2%  76.9%  72.6%  75.9%  NS 
Duration of associated treatment, months
Mean (SD)  14.8 (7.7)a  14.1 (7.2)a  12.1 (7.2)a  17.1 (7.1)  14.8 (7.5)  <0.001 
Median (P25–P75)  14.0 (12.6–15.3)  14.0 (12.6–15.3)  11.0 (9.4–12.6)  17.0 (16.6–19.3)  15.0 (8.0–23.0)  <0.001 
Treatment compliance  59.9%a  60.3%a  58.4%a  70.3%  62.3%  <0.001 
≥80%, high  35.0%  44.4%  42.0%  55.1%  35.4%   
50–79%, intermediate  42.1%  30.0%  32.7%  29.1%  41.3%   
<50%, low  22.9%  25.6%  25.3%  15.8%  23.2%  <0.001 
Treatment persistence  52.4%a  51.0%a  48.1%a  63.4%  54.2%  <0.001 
Diabetes control
Baseline  59.8%  60.0%  49.2%  61.2%  58.2%   
End  62.6%  62.8%  50.5%  64.3%  61.4%   
Percent difference  2.8%a  2.8%a  1.3%a  3.1%  3.2%  <0.001 

Values are percentages.

Optimum control: HBA1c values <7%; treatment compliance: ratio between number of tablets dispensed and prescribed; persistence: median time with no discontinuation of initial treatment or change to other medication, at least 30 days after initial prescription; NS: not significant; p: statistical significance.

a

Significant comparison between DPP-4 inhibitors and all other drug groups (sulfonylureas, glitazones, and insulins).

Table 4 shows the baseline and final values of biochemical and anthropometric parameters associated with antidiabetic drugs by treatment group. Decreased levels of HbA1c (7.5% versus 7.1%; p<0.001) and total cholesterol (191.3 versus 178.4mmHg; p<0.001) were seen in the DPP-4 inhibitor group. Significant but substantially lower reductions were also found in all other groups (sulfonylureas: 7.3% versus 7.0%; glitazones: 7.4% versus 7.1%; insulins: 8.0% versus 7.7%; p<0.008).

Table 4.

Biochemical and anthropometric parameters.

Study groups  Baseline  End  Difference  p 
Total series (No.=2067)
Systolic blood pressure, mmHg  135.1 (15.6)  132.8 (15.7)  2.3  <0.001 
Diastolic blood pressure, mmHg  75.7 (9.6)  73.7 (10.1)  2.0  <0.001 
Body mass index, kg/m2  30.6 (5.2)  30.2 (5.1)  0.4  <0.001 
Glucose, mg/dL  150.5 (48.7)  143.4 (52.2)  7.1  <0.001 
HbA1c, %  7.3 (1.4)  7.1 (1.4)  0.2  <0.001 
Triglycerides, mg/dL  156.6 (94.1)  146.3 (87.3)  10.3  <0.001 
Total cholesterol, mg/dL  188.1 (39.1)  178.4 (38.9)  9.7  <0.001 
HDL cholesterol, mg/dL  51.7 (13.3)  49.7 (13.4)  2.0  <0.001 
LDL cholesterol, mg/dL  105.7 (33.6)  99.9 (32.3)  5.8  <0.001 
Serum creatinine, mg/dL  1.2 (0.9)  1.1 (0.5)  0.1  <0.001 
Cardiovascular risk, %  18.0 (8.9)  15.8 (8.9)  2.2  <0.001 
Sulfonylureas (No.=886)
Systolic blood pressure, mmHg  135.5 (15.3)  133.8 (15.1)  1.7  0.004 
Diastolic blood pressure, mmHg  75.8 (9.3)  73.9 (9.7)  1.9  <0.001 
Body mass index, kg/m2  29.9 (4.7)  29.4 (4.7)  0.5  <0.001 
Glucose, mg/dL  150.1 (46.2)  143.0 (51.1)  7.1  <0.001 
HbA1c, %  7.3 (1.3)  7.0 (1.4)  0.3  <0.001 
Triglycerides, mg/dL  155.2 (92.7)  145.2 (84.8)  9.9  <0.001 
Total cholesterol, mg/dL  189.0 (38.4)  180.5 (39.3)  8.5  <0.001 
HDL cholesterol, mg/dL  51.6 (13.2)  49.6 (12.9)  2.0  <0.001 
LDL cholesterol, mg/dL  107.1 (32.3)  102.6 (32.6)  4.5  <0.001 
Serum creatinine, mg/dL  1.2 (0.5)  1.0 (0.4)  0.2  <0.001 
Cardiovascular risk, %  18.4 (8.5)  16.7 (8.9)  1.7  <0.001 
Glitazones (No.=290)
Systolic blood pressure, mmHg  133.1 (16.3)  131.3 (16.9)  1.8  NS 
Diastolic blood pressure, mmHg  74.3 (9.4)  72.9 (10.2)  1.4  0.034 
Body mass index, kg/m2  30.8 (5.4)  30.5 (5.4)  0.3  0.019 
Glucose, mg/dL  145.9 (47.4)  136.1 (46.3)  9.8  0.003 
HbA1c, %  7.4 (1.3)  7.1 (1.3)  0.3  <0.001 
Triglycerides, mg/dL  165.1 (91.8)  151.1 (81.9)  14.0  <0.001 
Total cholesterol, mg/dL  190.2 (41.4)  179.7 (42.6)  10.5  <0.001 
HDL cholesterol, mg/dL  52.1 (14.1)  51.1 (15.1)  1.0  NS 
LDL cholesterol, mg/dL  105.3 (34.3)  100.2 (34.4)  5.1  0.014 
Serum creatinine, mg/dL  1.2 (0.4)  1.1 (0.6)  0.1  NS 
Cardiovascular risk, %  17.5 (10.2)  15.6 (10.1)  2.0  0.000 
Insulins (No.=372)
Systolic blood pressure, mmHg  135.6 (16.5)  132.7 (15.3)  2.9  0.005 
Diastolic blood pressure, mmHg  74.8 (10.3)  71.9 (10.1)  2.9  <0.001 
Body mass index, kg/m2  31.8 (5.7)  31.5 (5.1)  0.3  NS 
Glucose, mg/dL  150.9 (59.2)  144.1 (62.4)  6.8  NS 
HbA1c, %  8.0 (1.6)  7.7 (1.5)  0.2  0.007 
Triglycerides, mg/dL  155.9 (107.5)  149.2 (108.2)  6.7  NS 
Total cholesterol, mg/dL  179.7 (37.9)  172.5 (39.1)  7.2  0.001 
HDL cholesterol, mg/dL  51.9 (13.8)  49.3 (13.7)  2.6  <0.001 
LDL cholesterol, mg/dL  97.6 (33.1)  93.1 (29.8)  4.5  0.005 
Serum creatinine, mg/dL  1.3 (1.2)  1.1 (0.6)  0.2  NS 
Cardiovascular risk, %  17.6 (8.5)  15.3 (8.2)  2.3  0.000 
DPP-4 inhibitors (No.=519)
Systolic blood pressure, mmHg  135.3 (15.0)  132.2 (16.0)  3.1  <0.001 
Diastolic blood pressure, mmHg  77.1 (9.5)  75.1 (10.4)  2.0  <0.001 
Body mass index, kg/m2  30.7 (5.2)  30.4 (5.1)  0.3  0.002 
Glucose, mg/dL  153.7 (45.1)  147.8 (48.6)  5.9  0.013 
HbA1c, %  7.5 (1.3)  7.1 (1.3)  0.4  <0.001 
Triglycerides, mg/dL  154.8 (79.1)  149.1 (77.2)  5.7  0.043 
Total cholesterol, mg/dL  191.3 (38.8)  178.4 (35.5)  12.9  <0.001 
HDL cholesterol, mg/dL  51.4 (12.5)  49.3 (13.1)  2.1  <0.001 
LDL cholesterol, mg/dL  109.6 (34.9)  100.1 (31.9)  9.6  <0.001 
Serum creatinine, mg/dL  1.2 (1.2)  1.1 (0.3)  0.1  0.002 
Cardiovascular risk, %  17.7 (8.9)  14.9 (8.4)  2.8  <0.001 

Values are means (SD: standard deviation).

NS: not significant; p: statistical significance.

Table 5 shows the mean use of resources by study group. As compared to the groups receiving sulfonylureas, glitazones, and insulins, patients on DPP-4 inhibitors paid less visits to PC (21.6 versus 28.8, 27.4, and 32.0; p<0.001) and had less hospitalization days (0.1 versus 0.2, 0.2, and 0.3; p<0.001), respectively. There were no differences in days of productivity lost. Overall, higher healthcare costs were found for the insulin group.

Table 5.

Mean use of resources by study group.

Study groups  SulfonylureasGlitazonesInsulinsDPP-4 inhibitorsTotalp 
Number of patients, %  No.=886 (42.9%)No.=290 (14.0%)No.=372 (18.0%)No.=519 (25.1%)2067 (100%) 
Use of resources  % use  Mean  % use  Mean  % use  Mean  % use  Mean  % use  Mean   
Primary care
Medical visits  100.0  28.8 (15.1)a  100.0  27.4 (15.5)a  100.0  32.0 (17.3)a  100.0  21.6 (14.8)  100.0  27.4 (15.7)  <0.001 
Laboratory tests  91.4  3.0 (1.8)a  92.4  3.1 (1.9)a  79.6  3.2 (2.5)a  89.8  2.2 (1.5)  89.0  2.8 (1.9)  <0.001 
Conventional radiology  52.4  1.0 (1.2)  56.6  1.0 (1.3)  53.8  1.0 (1.3)  58.6  1.1 (1.2)  54.8  1.0 (1.2)  NS 
Supplemental tests  33.7  0.5 (0.8)  42.4  0.6 (0.8)a  32.3  0.4 (0.8)  36.2  0.5 (0.7)  35.3  0.5 (0.8)  0.034 
Specialized care
Hospitalization days  2.0  0.2 (0.7)a  2.4  0.2 (0.9)a  6.5  0.3 (1.6)a  1.5  0.1 (0.2)  2.8  0.2 (0.9)  <0.001 
Medical visits  44.6  2.8 (3.2)a  45.9  1.8 (3.1)  65.3  3.7 (4.4)a  52.4  1.8 (2.4)a  50.5  2.8 (3.3)  <0.001 
Emergency room visits  21.3  0.2 (0.5)  19.3  0.2 (0.5)  25.8  0.3 (0.6)a  18.9  0.2 (0.5)  21.2  0.3 (0.5)  0.030 
Days of work disability  2.3  0.5 (5.1)  1.0  2.7 (33.9)  1.1  1.3 (22.8)  1.0  0.1 (0.1)  1.3  0.9 (16.3)  NS 

Values are means (SD: standard deviation); p: statistical significance; NS: not significant.

a

Significant comparison between DPP-4 inhibitors and all other drug groups (sulfonylureas, glitazones, and insulins).

Table 6 shows the gross and adjusted cost model (sex, age, RUBs, and the Charlson index) during the 48-month follow-up by study group. The total cost of care for patients with T2DM was 5.3 million euros, of which 96.6% were direct healthcare costs and 3.4% were indirect non-healthcare costs. Among healthcare costs, 84.6% were primary care costs (medication: 55.85%; medical visits: 24.9%) and 12.0% were specialized care costs (medical visits: 9.7%). Mean total (healthcare and non-healthcare) costs were lower in patients treated with DPP-4 inhibitors as compared to the other three study groups (2241.9€ versus 2474.0€, 2586.4€, and 3184.1€, respectively; p<0.001). Mean adjusted costs (ANCOVA) were 2321.2€ (95% CI: 2127.2–2515.1€) versus 2475.3€ (95% CI: 2327.6–2623.0€), 2724.4€ (95% CI: 2462.2–2986.6€), and 3163.9 (95% CI: 2934.2–3393.5€), respectively; p<0.001. These differences were seen in all cost components of the study groups. Only non-healthcare costs (work productivity or indirect losses) showed no statistically significant differences between the groups. Healthcare costs moderately correlated to age (r=0.295) and overall comorbidity (RUBs; r=0.333), p<0.001.

Table 6.

Gross and adjusted cost model (24-month follow-up) by study group in a retrospective cohort.

Study groups  Sulfonylureas  Glitazones  Insulins  DPP-4 inhibitors  Total  p  Total 
  Unit cost  Unit cost  Unit cost  Unit cost  Unit cost       
Unadjusted cost model
Healthcare costs  2416.4  2312.8  3048.6  2241.5  2471.8  <0.001  5,109,230.5  96.6% 
Primary care costs  2132.0  2068.2  2528.5  2016.5  2164.9  <0.001  4,474,931.1  84.6% 
Medical visits  669.5  637.6  744.0  501.8  636.8  <0.001  1,316,230.4  24.9% 
Laboratory tests  67.5  70.7  71.5  49.5  64.1  <0.001  132,595.8  2.5% 
Conventional radiology  18.0  19.3  18.4  19.7  18.7  NS  38,572.5  0.7% 
Supplemental tests  17.1  22.0  16.2  17.0  17.6  0.034  36,303.4  0.7% 
Drugs  1360.0  1318.7  1678.4  1428.8  1428.8  <0.001  2,953,296.0  55.8% 
Specialized care costs  284.4  244.6  520.1  225.0  306.3  <0.001  633,186.0  12.0% 
Hospitalization days  16.7  27.7  88.0  6.2  28.4  <0.001  58,724.7  1.1% 
Medical visits  238.9  189.4  392.9  190.9  247.6  <0.001  511,817.8  9.7% 
Emergency room visits  28.9  27.6  39.2  27.9  30.3  0.030  62,643.5  1.2% 
Non-healthcare costs (productivity)  57.6  273.6  135.5  1.0  87.5  NS  180,761.1  3.4% 
Total costs  2474.0  2586.4  3184.1  2241.9  2559.7  <0.001  5,290,945.1  100.0% 
Adjusted cost modela
Healthcare costs  2413.1a  2432.6a  3034.8a  2326.0    <0.001     
95% CI  2323.9–2502.3  2274.2–2590.9  2896.1–3173.5  2208.8–2443.1         
Primary care costs  2130.8  2174.4a  2505.8a  2090.5    <0.001     
95% CI  2054.1–2207.5  2038.2–2310.5  2386.6–2625.1  1989.8–2191.2         
Specialized care costs  282.3a  258.2a  529.0a  235.4    <0.001     
95% CI  249.7–314.8  200.4–316.0  478.3–579.6  192.7–278.2         
Non-healthcare costs (productivity)  62.2  291.8  129.0  2.8    NS     
95% CI  2.3–176.8  88.4–495.2  9.1–307.2  0.0–135.2         
Total costs  2475.3a  2724.4a  3163.9a  2321.2    <0.001     
95% CI  2327.6–2623.0  2462.2–2986.6  2934.2–3393.5  2127.2–2515.1         

Values are means.

p: statistical significance; NS: not significant; CI: confidence interval.

a

ANCOVA model: each F test contrasts the simple effect in each group to all other effects shown. These contrasts are based on paired comparisons, linearly independent, between the estimated marginal means. Covariates: age, RUBs, and Charlson index. Fixed components: sex and drug groups. Stable®: significant comparison between DPP-4 inhibitors and all other groups (sulfonylureas, glitazones, and insulins) in the adjusted model.

CVE and renal failure rates are shown in Fig. 1A. The group treated with DPP-4 inhibitors had a lower proportion of new cases of ischemic heart disease as compared to the insulin group (1.0% versus 3.2%, p=0.033), while no significant differences were found as compared to the groups treated with sulfonylureas (2.1%) and glitazones (0.7%). This group (DPP-4 inhibitors) had a lower proportion of new cases of stroke as compared to the insulin group (1.9% versus 5.2%, p=0.043), while no conclusive results were found as compared to the groups treated with insulins (4.6%) and sulfonylureas (2.8%). No significant differences were found in renal failure between the study groups. The total number of patients with CVEs was 136 (rate: 6.6%). The group treated with DPP-4 inhibitors (3.7%) showed significant differences as compared to the insulin group only (10.2%; p=0.002), while no conclusive results were found as compared to the groups treated with sulfonylureas (No.=57, 6.4%) and glitazones (No.=22, 7.6%).

Figure 1.

Details of the different cardiovascular events and hypoglycemic episodes by study group occurring during the study period (new cases).

(0.22MB).

The proportion of patients with hypoglycemia was 36.7%. Patients in the DPP-4 inhibitor group had a lower hypoglycemia rate as compared to the other three study groups (13.9% versus 40.4%, 37.6%, and 58.9%, respectively, p<0.001). Overall, 0.5% of patients required hospital admission, 1.1% were seen at hospital emergency rooms, and 35.7% attended primary care (Table 2, B). Mean hypoglycemic episodes by patient were 0.1 (0.3) versus 0.5 (0.7), 0.4 (0.6), and 0.8 (1.3), respectively, p<0.001.

In the logistic regression model, the presence of CVEs (all types analyzed) was associated with treatment noncompliance (OR=1.1; CI: 1.0–1.8), with low control of T2DM (OR=1.2; CI: 1.1–1.7), with overall comorbidity (OR=2.1; CI: 1.6–2.9), with male sex (OR=1.5; CI: 1.1–2.2), and with age (OR=1.1; CI: 1.0–1.2), p<0.05.

Fig. 2 shows the survival curves for the persistence of antidiabetic treatment by study group. Median persistence times were 14.0 months for sulfonylureas (95% CI: 12.6–15.3 months); 14.0 months for glitazones (95% CI: 12.6–15.3 months); 11.0 months for insulins (95% CI: 9.4–12.6 months); and 17.0 months for DPP-4 inhibitors (95% CI: 16.6–19.3 months).

Figure 2.

Survival curves of persistence in antidiabetic treatment by study group.

(0.08MB).
Discussion

Our study details the different therapeutic options for T2DM once first drug treatment with metformin has started. Among the four treatment classes examined, higher treatment compliance and disease control rates were found with DPP-4 inhibitors (combined with metformin) (Table 3), which may be associated with lower rates of hypoglycemia, vascular complications, and healthcare costs under standard medical practice conditions in a population setting. The evidence available in Spain from the evaluation of these measures in a single study is limited, which may give this study some conceptual attractiveness because of its more comprehensive approach.21

Not all patients with T2DM started drug treatment with metformin, but in those who did, sulfonylureas were the drugs most commonly used as a second therapeutic option. It is well known that the therapeutic strategy recommended by scientific bodies7,8 involves attempting from diagnosis or as early as possible to achieve good metabolic control, starting by lifestyle changes (healthy diet, weight loss, physical exercise, and smoking cessation) together with metformin administration. If this is not sufficient, the second phase, consisting of adding sulfonylureas, basal insulin, glitazones, or other drugs as appropriate for each patient should be started after a short period of time (3–6 months). These recommendations appear to have been followed in the reported study, but the start of the initial drug treatment was more conservative (Tables 2 and 3).

A total of 2067 patients were selected for the study, 18.0% of whom were treated with insulin. It should be noted that these patients had (as compared to the other groups) a longer time from diagnosis of T2DM to the start of this second treatment option (3.6 years), which somewhat affected the comparability of the study groups (treatment options). This longer interval may have been due to delayed diagnosis of the disease (advanced diabetes) or increased genetic susceptibility, among other factors (contraindications, etc.), because these patients were older and had higher rates of ischemic heart disease and diabetic retinopathy. This finding is consistent with the data reported in other studies reviewed,9,22,23 although the use of other concomitant medication was not quantified in our study.

DPP-4 inhibitors were the second therapeutic option (25.1% of the total). Our results show that after two years of follow-up, patients treated with DPP-4 inhibitors showed greater treatment compliance, better metabolic control, and lower hypoglycemia rates as compared to the other study groups. In our study, compliance with DPP-4 inhibitors was 70%, a little higher as compared to the compliance with the other treatments (58–60%). Few studies on compliance and persistence with oral antidiabetics and insulin have been found in the literature reviewed, and it was difficult to use them for purposes of comparison because of the different methodologies used. Compliance rates reported in such studies ranged from 40% to 80%. In this regard, Márquez Contreras et al.24 reported in a recent study noncompliance with insulin treatment in a quarter of the patients with diabetes. Cramer et al.,25 in a review based on 139 studies, reported persistence and compliance rates with oral antidiabetic drugs of 63% and 58%, respectively, at 12 months, for all the therapeutic classes analyzed. In a series of patients on combined treatment with metformin and sulfonylureas, Jermendy et al.26 found 56% persistence at one year. Although these results are consistent with our findings, they do not confirm this slight superiority of DPP-4 inhibitors. This result could have been due to a random event (individual variability) or to the presence of some unidentified confounding variables. One plausible explanation could be that they have a better tolerability and safety profile, as demonstrated by markedly lower hypoglycemia rates (pharmacokinetic and pharmacodynamic properties).8,11 However, further studies comparing the use of antidiabetic drugs as dual therapy are needed to confirm the validity of these results. It is clear that the role of DPP-4 inhibitors in the therapeutic armamentarium for T2DM is rapidly evolving, but long-term data evaluating their effects on metabolic control and cardiovascular risk are lacking.27,28 That there is evidence of a direct association between compliance and control appears to be beyond doubt.1,7,9,11,24,26

Patients treated with DPP-4 inhibitors showed lower healthcare costs, with decreased use of resources in specialized care, and less hospital admissions. The few studies available show that the greater the compliance and metabolic control of these patients, the lower the risk of hospital admission. As an example, Breitscheidel et al.29 concluded in their review that improved compliance may lead to a reduction in total healthcare costs in T2DM; in seven studies, compliance was inversely associated with total healthcare costs, and costs were lower due to a lower proportion of days of hospitalization. However, the degree of variability in the reviewed studies was high, which makes a comparison of the results difficult. Overall, our results are consistent with those of these studies,12 and the association of hypoglycemia with costs should be emphasized.30

Our data reflect the lower CVE and renal failure rates in patients treated with DPP-4 inhibitors, but the differences were not statistically significant in all the study groups. In this regard, various literature references9,22,23 have shown, in both type 1 and type 2 diabetes mellitus, that the good metabolic control represented by low HbA1c values significantly improves the incidence and course of microangiopathic complications, and that these benefits persist for years even if metabolic control worsens. Because of the close relationship between some microangiopathies (mainly nephropathy) and CVEs, a good metabolic control could be expected to have a positive influence on it, though with less intensity than the control of other risk factors such as dyslipidemia and high blood pressure.1,7 DPP-4 inhibitors are now thought to possibly have cardiovascular benefits, but this has yet to be confirmed by the results of various ongoing clinical trials.

The potential limitations of the study include the categorization of the disease, a potential bias in patient classification, the selection of the therapeutic groups, and operational cost measurements, and are attributable to the information system developed. This article therefore has the limitations inherent to retrospective studies, such as disease underreporting or a potential variability of professionals and patients because of the observational design. Another potential study limitation derived from its design is that vascular complications may be associated with a better diabetic control derived from the use of DPP-4 inhibitors due to there being other factors not considered which may be having an influence. Similarly, and paradoxically, patients who switch from metformin to insulin have a faster disease progress and experience greater complications. This circumstance, not accurately measured in our study (a limitation), may be attributed to a random effect, to more rapidly progressing forms of the disease and/or to the fact that patients treated with insulin have a greater complexity. An additional study limitation refers to the measurement of hypoglycemia, because only the episodes where patients required healthcare and this was documented were identified, which may have led to an underdiagnosis of cases. Future research will be needed to analyze cost/effectiveness and diagnostic and treatment delays, and data will have to be collected from other healthcare organizations. Moreover, the successful care of patients with chronic diseases such as T2DM should be based on interventions by multidisciplinary teams that promote effective interventions in which patients are highly involved in self-care. In conclusion, sulfonylureas were the drugs most commonly used in combination with metformin. Patients treated with DPP-4 inhibitors showed greater compliance and diabetes control, with lower hypoglycemia rates and healthcare costs.

Conflicts of interest

This study was funded by Novartis Farmacéutica SA, which had no influence on its results.

References
[1]
W.S. Weintraub, S.R. Daniels, L.E. Burke, B.A. Franklin, D.C. Goff Jr., L.L. Hayman, American Heart Association Advocacy Coordinating Committee, Council on Cardiovascular Disease in the Young, Council on the Kidney in Cardiovascular Disease, Council on Epidemiology, Prevention, Council on Cardiovascular Nursing, Council on Arteriosclerosis, Thrombosis, Vascular Biology, Council on Clinical Cardiology, Stroke Council, et al.
Value of primordial and primary prevention for cardiovascular disease: a policy statement from the American Heart Association.
Circulation, 23 (2011), pp. 967-990
[2]
S. van Dieren, J.W. Beulens, A.P. Kengne, L.M. Peelen, G.E. Rutten, M. Woodward, et al.
Prediction models for the risk of cardiovascular disease in patients with type 2 diabetes: a systematic review.
[3]
I. Hopper, B. Billah, M. Skiba, H. Krum.
Prevention of diabetes and reduction in major cardiovascular events in studies of subjects with prediabetes: meta-analysis of randomised controlled clinical trials.
Eur J Cardiovasc Prev Rehabil, 18 (2011), pp. 813-823
[4]
G. Danaei, M.M. Finucane, Y. Lu, G.M. Singh, M.J. Cowan, C.J. Paciorek, Global Burden of Metabolic Risk Factors of Chronic Diseases Collaborating Group (Blood Glucose), et al.
National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370 country-years and 2.7 million participants.
[5]
F. Soriguer, A. Goday, A. Bosch-Comas, E. Bordiú, A. Calle-Pascual, R. Carmena, et al.
Prevalence of diabetes mellitus and impaired glucose regulation in Spain: the Di@bet.es Study.
Diabetologia, 55 (2012), pp. 88-93
[6]
S. Valdés, G. Rojo-Martínez, F. Soriguer.
Evolución de la prevalencia de la diabetes tipo 2 en población adulta española.
Med Clin (Barc), 129 (2007), pp. 352-355
[7]
American Diabetes Association Task Force for Writing Nutrition Principles, Recommendations for the Management of Diabetes, Related Complications.
American Diabetes Association position statement: evidence-based nutrition principles and recommendations for the treatment and prevention of diabetes and related complications.
J Am Diet Assoc, 102 (2002), pp. 109-118
[8]
S.E. Inzucchi, R.M. Bergenstal, J.B. Buse, M. Diamant, E. Ferrannini, M. Nauck, American Diabetes Association (ADA), European Association for the Study of Diabetes (EASD), et al.
Management of hyperglycemia in type 2 diabetes: a patient-centered approach: position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD).
Diabetes Care, 35 (2012), pp. 1364-1379
[9]
The ADVANCE Collaborative Group.
Intensive blood glucose control and vascular outcomes in patients with type 2 diabetes.
N Engl J Med, 358 (2008), pp. 2560-2572
[10]
D.M. Nathan, J.B. Buse, M.B. Davidson, E. Ferrannini, R.R. Colman, R. Sherwin, et al.
Medical manegent of hyperglycemia in type 2 diabetes: a consensus algorithm for the initiation and adjustment of therapy. A consensus of the American Diabetes Association and the European Association for the Study of Diabetes.
Diabetes Care, 32 (2009), pp. 193-203
[11]
P.E. Wiedeman.
DPPIV inhibition: promising therapy for the treatment of type 2 diabetes.
Prog Med Chem, 45 (2007), pp. 63-109
[12]
M. Mata, F. Antoñanzas, M. Tafalla, P. Sanz.
El coste de la diabetes tipo 2 en España. El estudio CODE-2.
Gac Sanit, 16 (2002), pp. 511-520
[13]
P. González, E. Faure, A. del Castillo.
Grupo de Trabajo para el Estudio del Coste de la Diabetes. Cost of diabetes mellitus in Spain.
Med Clin (Barc), 127 (2006), pp. 776-784
[14]
The Ínternational Classification of Primary Care in the European Community. With a multi-language layer,
[15]
WHO.
The anatomical therapeutic chemical classification system.
(1991),
[16]
M.E. Charlson, P. Pompei, K.L. Ales, C.R. Mackenzie.
A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.
J Chronic Dis, 40 (1987), pp. 373-383
[17]
J.P. Weiner, B.H. Starfield, D.M. Steinwachs, L.M. Mumford.
Development and application of a population-oriented measure of ambulatory care case-mix.
Med Care, 29 (1991), pp. 452-472
[18]
National Cholesterol Education Program – Expert Panel on Detection, Evaluation, and Treatment on High Blood Cholesterol in Adults (Adult Treatment Panel III). Third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Adult Treatment Panel III final report.
Circulation, 106 (2002), pp. 3143-3421
[19]
Instituto Nacional de Estadística.
Encuesta de costes laborales del año 2010.
(2010),
[20]
S.G. Thompson, J.A. Barber.
How should cost data in pragmatic randomised trials be analysed?.
BMJ, 320 (2000), pp. 1197-1200
[21]
J.A. Marión, S. Peiró, J. Medrano, J. Librero, M.T. Pérez-Vázquez, R. Ordiñana.
Variaciones en la práctica médica: importancia, causas e implicaciones.
Med Clin, 110 (1998), pp. 382-390
[22]
Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33), UK Prospective Diabetes Study (UKPDS) Group.
Lancet, 352 (1998), pp. 837-853
[23]
P. Gaede, H. Lund-Andersen, H.H. Parving, O. Pedersen.
Effect of a multifactorial intervention on mortality and in type 2 diabetes.
N Engl J Med, 358 (2008), pp. 580-591
[24]
E. Márquez Contreras, N. Martell Claros, V. Gil Guillén, J.J. Casado Martínez, J.L. Martín de Pablos, J. Ferraro García, et al.
Grupo de Trabajo sobre Cumplimiento de la Asociación de la Sociedad Española de Hipertensión Arterial y Liga Española para la Lucha contra la Hipertensión Arterial (SEH-LELHA). Therapeutic non-compliance with insulin in the treatment of diabetes mellitus 2.
Aten Primaria, 44 (2012), pp. 74-81
[25]
J.A. Cramer, A. Benedict, N. Muszbek, A. Keskinaslan, Z.M. Khan.
The significance of compliance and persistence in the treatment of diabetes, hypertension and dyslipidaemia: a review.
Int J Clin Pract, 62 (2008), pp. 76-87
[26]
G. Jermendy, I. Wittmann, L. Nagy, Z. Kiss, G. Rokszin, Z. Abonyi-Tóth, et al.
Persistence of initial oral antidiabetic treatment in patients with type 2 diabetes mellitus.
Med Sci Monit, 18 (2012), pp. CR72-CR77
[27]
P.J. Guillausseau.
Impact of compliance with oral antihyperglycemic agents on health outcomes in type 2 diabetes mellitus: a focus on frequency of administration.
Treat Endocrinol, 4 (2005), pp. 167-175
[28]
A.J. Scheen.
DPP-4 inhibitors in the management of type 2 diabetes: a critical review of head-to-head trials.
Diabetes Metab, 38 (2012), pp. 89-101
[29]
L. Breitscheidel, S. Stamenitis, F.W. Dippel, O. Schöffski.
Economic impact of compliance to treatment with antidiabetes medication in type 2 diabetes mellitus: a review paper.
J Med Econ, 13 (2010), pp. 8-15
[30]
H. Wild.
The economic rationale for adherence in the treatment of type 2 diabetes mellitus.
Am J Manag Care, 18 (2012), pp. S43-S48

Please cite this article as: Sicras-Mainar A, Font-Ramos B, Roldán-Suárez C, Navarro-Artieda R, Ibáñez-Nolla J. Caracterización y costes asociados al perfil del paciente con diabetes tipo 2 en tratamiento con metformina al que se le añade un segundo fármaco antidiabético oral: estudio de base poblacional. Endocrinol Nutr. 2013;60:557–569.

Copyright © 2013. SEEN
Article options
Tools
es en pt

¿Es usted profesional sanitario apto para prescribir o dispensar medicamentos?

Are you a health professional able to prescribe or dispense drugs?

Você é um profissional de saúde habilitado a prescrever ou dispensar medicamentos