Literature DB >> 23520379

Drug costs in prediabetes and undetected diabetes compared with diagnosed diabetes and normal glucose tolerance: results from the population-based KORA Survey in Germany.

Andrea Icks, Heiner Claessen, Klaus Strassburger, Michael Tepel, Regina Waldeyer, Nadja Chernyak, Bernd Albers, Christina Baechle, Wolfgang Rathmann, Christa Meisinger, Barbara Thorand, Matthias Hunger, Michaela Schunk, Renée Stark, Ina-Maria Rückert, Annette Peters, Cornelia Huth, Doris Stöckl, Guido Giani, Rolf Holle.   

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Year:  2013        PMID: 23520379      PMCID: PMC3609503          DOI: 10.2337/dc12-0997

Source DB:  PubMed          Journal:  Diabetes Care        ISSN: 0149-5992            Impact factor:   19.112


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Undetected diabetes and prediabetes are common (1–3). In decision analytic models of diabetes prevention and screening in particular, the differentiation in costs of detected, undetected, and prediabetic cases are important (4). To the best of our knowledge, no study has determined costs using population-based data with oral glucose tolerance test (OGTT)–based diabetes diagnosis. We used the population-based Cooperative Health Research in the Region of Augsburg (KORA) follow-up survey, conducted in 2006–2008 in southern Germany (2,3) (n = 2,611, aged 40–82 years). By means of participants’ self report and an OGTT, we identified individuals with previously diagnosed diabetes (n = 233, 57.9% male, mean age 67.8 ± 8.7), undetected diabetes (n = 109, 56.9% male, mean age 65.3 ± 10.4), and prediabetes (i.e., impaired glucose tolerance and/or impaired fasting glucose) (n = 489, 53.2% male, mean age 63.7 ± 10.4), and those with normal blood glucose values (n = 1,780, 45.6% male, mean age 56.3 ± 11.0) using the criteria suggested by the World Health Organization. Individuals with diagnosed diabetes have the lowest socioeconomic position and were most likely to be obese and to have cardiovascular disease (hypertension, angina pectoris, or a history of myocardial infarction or stroke) (2,3). Using a well-established computer-assisted system (2,3), we assessed all medications taken regularly, including over-the-counter medication. Drug costs were taken from the official German price list (German equivalent of the Physicians’ Desk Reference) on 1 April 2008, which was the end of the survey. We calculated mean crude and age- and sex-standardized medication costs per person and year, along with 95% CIs using bias-corrected accelerated bootstrapping procedures. Differences between the diabetes states by age- and sex-adjusted cost ratios for total as well as total without antihyperglycemic drugs and cardiovascular medication were estimated using multiple two-part regression models (5). We further adjusted for cardiovascular disease, BMI, and socioeconomic status, defined by educational level. Costs (in euros) per person and year (95% CI) were 1,435.57 (1,041.56–2,880.98), 617.79 (489.79–797.29), 499.57 (428.78–600.04), and 332.37 (294.88–396.72) in participants with diagnosed diabetes, undetected diabetes, prediabetes, and normal glucose tolerance, respectively, and 1,277.64 (927.88–2,145.07), 501.41 (364.30–726.42), 451.66 (356.46–684.52), and 332.37 (295.50–396.71), respectively, after standardization. In the multivariate models, compared with individuals with normal glucose values, cost ratios were significantly increased in diagnosed diabetes (2.98 [95% CI 2.50–3.56]) and when antihyperglycemic drugs were excluded (2.30 [1.91–2.76]). They were also significantly increased in undetected diabetes and prediabetes (cost ratios for all medications 1.44 [1.13–1.83], 1.23 [1.06–1.42]), in particular for cardiovascular drug costs (1.84 [1.42–2.37], 1.49 [1.25–1.77]). Compared with individuals with diagnosed diabetes, costs were lower in both groups; this was also the case when antihyperglycemic medication was excluded (0.62 [0.47–0.81] and 0.53 [0.43–0.64]). Cost ratios differed markedly with age, with greater differences in participants aged 40–59 years compared with those aged 60–82 years, but not with sex. They decreased substantially after adjustment for cardiovascular diseases but remained mostly significant. Adjustment for BMI and socioeconomic status did not alter cost ratios. Although the number of participants is limited, in the group with undetected diabetes in particular clear differences between the glucose tolerance stages could be observed. The strength of our study is the population-based sample and the identification of glucose tolerance stage by OGTT. Hence, these results may help to more validly estimate cost-effectiveness of screening and early treatment or prevention of diabetes.
  4 in total

1.  Prevalence of undiagnosed diabetes and impaired glucose regulation in 35-59-year-old individuals in Southern Germany: the KORA F4 Study.

Authors:  C Meisinger; K Strassburger; M Heier; B Thorand; S E Baumeister; G Giani; W Rathmann
Journal:  Diabet Med       Date:  2010-03       Impact factor: 4.359

2.  A computer program for estimating the re-transformed mean in heteroscedastic two-part models.

Authors:  Xiao-Hua Zhou; Hao Cheng
Journal:  Comput Methods Programs Biomed       Date:  2008-03-19       Impact factor: 5.428

3.  High prevalence of undiagnosed diabetes mellitus in Southern Germany: target populations for efficient screening. The KORA survey 2000.

Authors:  W Rathmann; B Haastert; A Icks; H Löwel; C Meisinger; R Holle; G Giani
Journal:  Diabetologia       Date:  2003-02-18       Impact factor: 10.122

4.  Different strategies for screening and prevention of type 2 diabetes in adults: cost effectiveness analysis.

Authors:  Clare L Gillies; Paul C Lambert; Keith R Abrams; Alex J Sutton; Nicola J Cooper; Ron T Hsu; Melanie J Davies; Kamlesh Khunti
Journal:  BMJ       Date:  2008-04-21
  4 in total
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1.  The biological effects of the hypolipidaemic drug probucol microcapsules fed daily for 4 weeks, to an insulin-resistant mouse model: potential hypoglycaemic and anti-inflammatory effects.

Authors:  Armin Mooranian; Rebecca Negrulj; Ryu Takechi; John Mamo; Hesham Al-Sallami; Hani Al-Salami
Journal:  Drug Deliv Transl Res       Date:  2018-06       Impact factor: 4.617

2.  Is the choice of the statistical model relevant in the cost estimation of patients with chronic diseases? An empirical approach by the Piedmont Diabetes Registry.

Authors:  Eva Pagano; Alessio Petrelli; Roberta Picariello; Franco Merletti; Roberto Gnavi; Graziella Bruno
Journal:  BMC Health Serv Res       Date:  2015-12-30       Impact factor: 2.655

3.  Regional differences of undiagnosed type 2 diabetes and prediabetes prevalence are not explained by known risk factors.

Authors:  Teresa Tamayo; Sabine Schipf; Christine Meisinger; Michaela Schunk; Werner Maier; Christian Herder; Michael Roden; Matthias Nauck; Annette Peters; Henry Völzke; Wolfgang Rathmann
Journal:  PLoS One       Date:  2014-11-17       Impact factor: 3.240

4.  Micro-Nano formulation of bile-gut delivery: rheological, stability and cell survival, basal and maximum respiration studies.

Authors:  Susbin Raj Wagle; Daniel Walker; Bozica Kovacevic; Ahmed Gedawy; Momir Mikov; Svetlana Golocorbin-Kon; Armin Mooranian; Hani Al-Salami
Journal:  Sci Rep       Date:  2020-05-07       Impact factor: 4.379

5.  Prevalence, incidence and concomitant co-morbidities of type 2 diabetes mellitus in South Western Germany--a retrospective cohort and case control study in claims data of a large statutory health insurance.

Authors:  Michael W J Boehme; Gisela Buechele; Julia Frankenhauser-Mannuss; Jana Mueller; Dietlinde Lump; Bernhard O Boehm; Dietrich Rothenbacher
Journal:  BMC Public Health       Date:  2015-09-03       Impact factor: 3.295

6.  Direct costs in impaired glucose regulation: results from the population-based Heinz Nixdorf Recall study.

Authors:  C Bächle; H Claessen; S Andrich; M Brüne; C M Dintsios; U Slomiany; U Roggenbuck; K H Jöckel; S Moebus; A Icks
Journal:  BMJ Open Diabetes Res Care       Date:  2016-05-25
  6 in total

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