Use of routine care laboratory test results in Danish studies: Eksempler på hvad LAB KA

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1 Use of routine care laboratory test results in Danish studies: Eksempler på hvad LAB KA Reimar W. Thomsen, MD, PhD Associate professor and consultant physician Department of Clinical Epidemiology, Aarhus University Hospital

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3 Agenda 1. Hvad er Lab-ka, og er det svært at arbejde med? 2. Eksempler på hvad Lab-ka (primært fra diabetesforskning) 3. Nogle spørgsmål?

4 1. Er det svært at arbejde med Labka data?

5 Clinical Epidemiology 2011

6 Sæt dig lidt ind i sundhedsregistrene, pls Scandinavian Journal of Public Health, vol 39, Issue 7_suppl, July 2011

7 Fordele i The Danish public health care system (gælder også Labka ) 1. Homogeneous population of 5.7 million people 2. Free, tax-supported health care for everyone Visits at general practitioners (incl lab tests) Visits at specialists (incl lab tests) Admissions to hospital and outpatients visits (incl lab tests) Drugs reimbursed at monopolized community pharmacies 3. Long tradition of registration 4. Unique personal identification number used in all registries 5. Liberal legislation for registry-based research -> KEA: Linkage of population-based hospital, prescription, health services, and laboratory databases in North and Central Denmark in various projects

8 Civil Registry System (address, death) Prescription Database (2004-) Biobank data Personal Identification Number Cancer Registry Prædikterer forhøjet SR cancer? Laboratory databases late 1990s- Clinical databases Antidiabetika effekt på blodsukker? Hospital Discharge Registry CRP ved indlæggelse med pneumoni? Primary care health services late 1990s- (vaccines etc.) Hyper-kaliæmi hyppigt fund hos egen læge?

9 Ex Laboratoriedatabase Region Midt

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12 Kogebog for identifikation af relevante prøver i Labka 1. Consult Analysefortegnelsen from dept. biochemistry in different relevant hospitals 2. Search in the database labterm.dk 3. Make a brutto candidate list of all relevant local and NPU analysis names and codes remember outdated/historical codes and misspellings! 4. Consider using broad searches, e.g. alb instead of albumin 5. Perform a search in the descriptive dataset of the laboratory database you have available 6. Go through all the names and codes found, and select the ones appropriate for your study 7. Highly recommended to consult collaborators / consultants from clinical biochemistry!

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14 Et lille indspark Vil Sundhedsdatastyrelsen/ centralmyndighederne kunne levere brugbare laboratoriedata? Vi opsamler, oprenser, validerer, standardiserer og analyser danske sundhedsdata herunder biokemiske og mange andre data fragmenteret og spredt i afgrænsede forskergrupper Kan de decentrale forskermiljøer deltage mere aktivt med at udvikle information commons et informationsfællesskab så data bliver standardiserede og analyserbare i bred forstand?

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17 Studies of early glycaemic control

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19 Christensen DH et al, Clin Epidemiol 2016

20 Drug effectiveness on glycaemic control? 1. Initiation of glucose-lowering therapy 2. Intensification of first-line metformin 3. Start and intensification of basal insulin 4. Does early glucose control matter? 5. Does long-term glucose control matter?

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22 Background Early intensive glucose-lowering drug (GLD) therapy in type 2 diabetes reduces the risk of microvascular complications by 10%-25% [1-4] and may reduce macrovascular complications [5-6]: Clinical guidelines suggest individualized therapy, lowering HbA1c to <7% (<53 mmol/mol) in most adults with type 2 diabetes, and targeting more stringent HbA1c goals (such as < 6.5%) (<48 mmol/mol) for patients with early uncomplicated type 2 diabetes [7] Little is known about treatment initiation patterns and quality of early glycemic control in patients with type 2 diabetes in real life settings! 1. UKPDS Group: Lancet 1998;352: Holman RR: NEJM 2008;359: Patel A: NEJM 2008;358: Hemmingsen B: Cochrane Database Syst Rev 2013;11:CD Gerstein HC: Lancet 2014;384: ADA: Diabetes Care 2014;37Sup1:S DSAM and DES: Danish guidelines for type 2-diabetes, 2014 revision.

23 Methods We linked population-based hospital, prescription, and laboratory databases in North and Central Denmark Success in reaching HbA1c goals within 3-6 months was examined by Poisson regression analysis Adjustment for age, gender, baseline HbA1c, T2D duration, presence of complications, other comorbidities

24 Main results We included 38,418 patients with type 2 diabetes, of which 91% started with oral glucose-lowering drugs in monotherapy Metformin initiation increased from 32% in to 90% of all patients in At the same time, SU initiation decreased from 55% to 4% Median pre-treatment HbA1c levels decreased from 8.9% in to 7.0% in ! Thomsen RW et al, Diabetes Obes Metabol 2015

25 Median pre-treatment HbA1c (green) decreases substantially over time. More patients attain HbA1c < 7% (red) and <6.5% (blue).

26 Results: adjusted time trends in glycemic control More patients achieved an HbA1c target <7% in than in : 80% vs. 60%, adjusted relative risk = 1.10 [95% CI ] More patients achieved an HbA1c <6.5% in than in : 53% vs. 37%, adjusted relative risk = 1.07 [95% CI: ] Similar findings among healthy patients aged <65 years, no complications or comorbidities Adjusted by Poisson regression analysis for: age, gender, pretreatment HbA1c, baseline microvascular and macrovascular diabetes complications, other comorbidities, and hospital diagnosis of diabetes before therapy start

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28 A1c <6.5% reached in only 50% of younger T2D without complications

29 2. Intensification of first-line metformin

30 Head-to-head trials comparing GLDs are limited and there is little evidence to guide clinicians choice of add-on therapy Lipska KJ: JAMA Internal Medicine 2014;174:317-8 We examined glycemic control among 4,734 metformin initiators who were intensified with their first add-on GLD We used regression analysis to examine the attainment of HbA1c goals within six months

31 4,734 metformin users intensified with first add-on therapy: Reductions in median HbA1c observed 3-6 months after add-on. (Thomsen et al, Diabetologia 2015) <7.0% <6.5% 6 59% 32% 59% 29% 62% 32% 50% 25% 42% 19% Sulfonylurea DPP4 inhibitor GLP-1 receptor agonist Other GLD add-on Add-on to metformin Insulin

32 Adjusted RRs for attaining HbA1c targets of <7% (all patients, left panel) and <6.5% (patients <65 years with no comorbidities, right panel) 3-6 months after intensification in metformin users Add-on to metformin N HbA1c<7.0% RR (95% CI) N HbA1c<6.5% RR (95% CI) Sulfonylurea 2,484 1 (ref) (ref) DPP4 inhibitor 1, ( ) ( ) GLP-1 receptor agonists ( ) ( ) Other non-insulin GLDs ( ) ( ) Insulin ( ) ( ) 0,4 0,6 0,8 1 1,2 1,4 1,6 0,4 0,6 0,8 1 1,2 1,4 1,6 RR (95% CI) RR (95% CI) Adjusted for age, gender, diabetes duration, macrovascular T2D complications, microvascular T2D complications, Charlson Comorbidity Index level, and baseline HbA1c.

33 3. Initiation/intensification of basal insulin

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35 0 mths: Basal insulin initiation 9, mths: Before add-on / intensification mths: post-basal insulin mths: After add-on / intensification Premixed insulin 8,5 Bolus insulin HbA 1c (%) 8 7,5 7 GLP-1 receptor agonists More than 1 add-on No intensification therapy Premixed insulin Bolus insulin GLP-1 receptor agonists More than 1 add-on No intensification 6, Baseline N Post-BOT N Time after basal insulin initiation (months) Pre-BOT add-on N Post-BOT add-on N Thomsen RW et al, Diabetic Medicine 2016

36 4. Making the case: Betyder god tidlig blodsukkerkontrol noget for T2D patienternes kardiovaskulære risiko og mortalitet? [Svensson et al, Diabetes Care 2016 June]

37 Incidens af CVD/død associeret med blodsukker kontrol opnået 6 mdr. efter metformin start

38 Adjusted HRs by Cox analysis for: age, gender, year, baseline A1c, baseline diabetes complications, comorbidities, psychatric disorders, obesity, alcoholism, add-on diabetes drugs, cardiovascular drugs, lipid status

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40 5: What is the role of glycemic control over time in infections?

41 Community-treated Infection: Adjusted Hazard Ratios by baseline, mean, or current latest HbA1c [Mor A et al, Am J Epidemiol 2017 April] Adjusted for age, gender, comorbidity (CCI score), micro- and macrovascular diabetes complications not covered in the CCI, diabetes duration, alcoholism-related conditions, marital status, concurrent use of statins/corticosteroids/immunosuppressive drugs, calendar period of diabetes diagnosis, and type of glucose-lowering drug regimen.

42 THE END Thank you!