Physical comorbidity with bipolar disorder: lessons from UK data

Physical comorbidity with bipolar disorder: lessons from UK data Daniel Smith Symposium 33: Big data and bipolar disorder in the UK

A failure of social policy and health promotion, illness prevention and care provision.

Life expectancy at birth of people with mental disorders in the period of 2007 09 (N = 31,719). Chang C-K, Hayes RD, Perera G, Broadbent MTM, et al. (2011) Life Expectancy at Birth for People with Serious Mental Illness and Other Major Disorders from a Secondary Mental Health Care Case Register in London. PLoS ONE 6(5): e19590. doi:10.1371/journal.pone.0019590 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0019590

UK data: Bipolar Disorder Research Network (n=8,000) Scottish Primary Care data (n=1.8 million) UK Biobank (n=0.5 million) Glasgow Psychosis cohort (n=7,500)

Cardiometabolic disease in BDRN cohort: 25 % 20 15 10 Bipolar disorder Controls 5 0 Diabetes Hypertension High cholesterol Coronary heart disease Stroke Forty et al, in submission

The analysis of SPICE data was conducted as part of the Living Well with Multimorbidity Programme (CSO Grant ARPG/07/1) with Professor SW Mercer (Principal Investigator) and Professor Bruce Guthrie (epidemiology lead).

Multimorbidity and major mental illness in Scotland: Data from 314 general practices in Scotland (1.8 million people) Schizophrenia and related psychoses and bipolar disorder identified (n=12,504) 32 physical health conditions also identified Multimorbidity described by age, gender and socioeconomic deprivation Some prescribing information

Physical health comorbidities assessed: Coronary heart disease Parkinson s disease Peripheral vascular disease Viral hepatitis Chronic kidney Multiple sclerosis Sinusitis Liver disease disease Asthma Stroke Chronic obstructive pulmonary disease Psoriasis/eczema Atrial fibrillation Blindness Bronchiectesis Irritable bowel syndrome Epilepsy Glaucoma Crohn s disease Migraine Cancer (any) Hearing loss Diverticulitis Dyspepsia Thyroid disorders Hypertension Rheumatoid Constipation arthritis Diabetes Heart failure Prostate disease Pain disorder

Prevalence and odds ratios for physical health comorbidity (standardised by age and gender) Variable Bipolar, n (%) Not bipolar, n (%) Odds ratio (95% CI) No physical condition 929 (36.0) 799,179 (56.2) 0.59 (0.54 to 0.63) One physical condition 662 (25.6) 292,651 (20.6) 1.27 (1.16 to 1.39) Two physical comorbidities Three or more physical comorbidities 427 (16.5) 149,297 (10.5) 1.45 (1.30 to 1.62) 564 (21.8) 180,669 (12.7) 1.44 (1.30 to 1.64)

Differences in prescribing between bipolar and controls for coronary heart disease (CHD) and hypertension patients, standardised by age and gender. Patients Bipolar Controls Odds ratio (95% CI) CHD patients: n = 170 n = 80,985 Aspirin or clopidogrel, % 69.3 73.6 0.81 (0.58 to 1.12) Statin, % 70.0 74.9 0.69 (0.50 to 0.96) No antihypertensive, % 29.4 15.8 2.08 (1.49 to 2.91) One antihypertensive, % 37.6 31.3 1.29 (0.94 to 1.76) Two or more antihypertensives, % 32.9 52.7 0.46 (0.33 to 0.63) Hypertension patients: n = 462 n = 232,986 Statin, % 36.7 41.5 0.82 (0.68 to 0.98) No antihypertensive, % 21.8 13.9 1.70 (1.36 to 2.12) One antihypertensive, % 39.8 32.3 1.38 (1.15 to 1.67) Two or more antihypertensives, % 37.8 53.7 0.53 (0.44 to 0.68)

Implications: Coronary Heart Disease, Heart Failure, Peripheral Vascular Disease, Stroke and TIA not more commonly recorded in the bipolar group Where cardiovascular diseases were recorded for the bipolar group, evidence of less intensive treatment Substantial treatment inequalities for bipolar patients with coronary heart disease and hypertension.

UK data: Bipolar Disorder Research Network (n=8,000) Scottish Primary Care data (n=1.8 million) UK Biobank (n=0.5 million) Glasgow Psychosis cohort (n=7,500)

Mood disorder, cardiovascular disease and the impact of psychotropic medication (Martin et al, under review)

% 45 40 35 30 25 20 Bipolar Disorder (n=1,608) MDD (n=31,756) Controls (n=116,079) 15 10 5 0 None One Two Three > Four Number of comorbidities

% 40 35 30 25 20 15 Bipolar Disorder (n=1557) MDD (n=30,990) Controls (n=113,444) 10 5 0 Any cardiovascular disease Hypertension Diabetes

Partially adjusted a OR (95% CI) Fully adjusted b OR (95% CI) CVD any: Control 1 1 Depression 1.29 (1.25, 1.33) 1.15 (1.12, 1.19) Bipolar 1.50 (1.34, 1.68) 1.28 (1.14, 1.43) Hypertension: Control 1 1 Depression 1.27 (1.23, 1.31) 1.15 (1.11, 1.18) Bipolar 1.44 (1.29, 1.61) 1.26 (1.12, 1.42) Diabetes: Control 1 1 Depression 1.29 (1.22, 1.37) 1.07 (1.00, 1.13) Bipolar 1.37 (1.12, 1.67) 1.01 (0.81, 1.24) A Partially adjusted: age, sex, deprivation and ethnicity B Fully adjusted: age, sex, deprivation, ethnicity, BMI, smoking status, alcohol consumption and current use of psychotropic medication.

Cardiometabolic disease, mood disorder and psychotropic medication (adjusted for age, sex, social deprivation, ethnicity) Diabetes (N=7,825) OR and 95%CI MI (N=3,129) OR and 95%CI Angina (N=4,222) OR and 95%CI Hypertension (N=38,840) OR and 95%CI Stroke (N=2,066) OR and 95%CI Controls, no psychotropic medication 1 (Reference) 1 (Reference) 1 (Reference) 1 (Reference) 1 (Reference) Controls on psychotropic medication 1.91 1.70, 2.14 1.85 1.54, 2.21 2.26 1.96, 2.61 1.59 1.48, 1.70 3.28 2.76, 3.90 MDD, no psychotropic medication 1.15 1.08, 1.23 1.33 1.21, 1.47 1.33 1.22, 1.45 1.21 1.18, 1.26 1.45 1.29, 1.63 MDD on psychotropic medication 2.12 1.93, 2.33 1.83 1.55, 2.15 2.57 2.28, 2.91 1.63 1.54, 1.73 2.97 2.54, 3.48

Chronic multisite pain in major depression and bipolar disorder: cross-sectional study of 149,612 participants in UK Biobank. (Nicholl et al, under review)

Definition of multisite pain: In the last month have you experienced any of the following that interfered with your usual activities? Headache pain Facial pain Neck or shoulder pain Back pain Stomach or abdominal pain Hip pain Knee pain Pain all over the body (widespread)

RRR (95% CI)* Model Depression Bipolar disorder No chronic pain 1 1 1 site 1.35 (1.31, 1.39) 1.41 (1.24, 1.60) 1. Unadjusted (n=149,612) 2-3 sites 1.88 (1.81, 1.94) 2.35 (2.07, 2.38) 4-7 sites 3.12 (2.91, 3.34) 4.43 (3.55, 5.52) Widespread pain 2.80 (2.53, 3.11) 5.38 (4.04, 7.16) 1. Adjusted for sex, age, ethnicity, deprivation, employment status BMI, smoking status frequency of alcohol consumption, comorbidity count (n=145,518) No chronic pain 1 1 1 site 1.27 (1.23, 1.31) 1.27 (1.12, 1.45) 2-3 sites 1.59 (1.54, 1.65) 1.84 (1.61, 2.11) 4-7 sites 2.13 (1.98, 2.30) 2.39 (1.88, 3.03) Widespread pain 1.86 (1.66, 2.08) 2.37 (1.73, 3.23)

7,250 patients with psychotic disorder registered (2013): schizophrenia (n=4,787) bipolar disorder (n=1,784) organic psychosis (n=67) psychotic depression (n=452) substance-induced psychosis (n=160)

Baseline and annual follow-up information: ICD-10 diagnosis, Community Health Index (CHI) number, ethnicity, marital status, accommodation status and postcode, employment status, educational attainment, family history of psychosis, psychiatric admissions data, current illness severity (including CGI and HoNOS scores), use of the mental health act, current and previous medications, adverse drug effects, psychosocial interventions received and psychiatric comorbidities.

Deaths per 10,000 per 5 years Death rates in Major Mental Illness (MMI) by social deprivation: Glasgow and Scotland 900 MMI 800 700 600 500 400 300 Glasgow 200 Scotland 100 0 Least deprived 2 3 4 Most deprived Langan Martin et al, BMC Psychiatry, in press.

Deaths per 10,000 per 5 years Death rates in Major Mental Illness (MMI) by social deprivation: Glasgow and Scotland 900 MMI 800 700 600 MMI Excluding Suicide 500 400 300 Glasgow 200 Scotland 100 0 Least deprived 2 3 4 Most deprived Langan Martin et al, BMC Psychiatry, in press.

NHS Greater Glasgow and Clyde: SafeHaven

Safe Haven Governance SQL cluster Safe Haven IT Infrastructure NHS Safe Haven Anonymised servers RCB All clinical datasets Clinical Non health Non health Clinical Clinical Trials Research Data Db1 Dataset DWEducation Data Requests Db2 Dataset CHI Seeded DWSocialWork DW1 Non health data Db3 DW1 DWEducation DWSocialWork Data is now in a data warehouse structure using only surrogate keys to link LPAC decisions Application server Dumb terminals

Datasets in Safe Haven SMR00 - Outpatient Attendance SMR01 Acute inpatient & Day Care SMR02 Maternity SMR04 Mental Health Current Datasets - CHI GG&C patient population (1.3 million) - GRO Births and deaths date for GG&C - eprescribing encashed prescriptions for Glasgow - GP (LES and Keep Well) 250 practices - Heart Failure locally held national Heart Failure database - Rheumatology local clinical database - SCI DC GGC population of national Diabetic database - SCI Store results for GGC - Parkinson local clinical database for Movement disorders - Weight Management - PsyCIS schizophrenia database - Clozapine database - EDIS (A&E now replaced by Trak care) REC approval is to submit an amendment every time 6 new databases are added In discussion to extend health data to other Boards in NRS West Lanarkshire, A&A, D&G and Golden Jubilee

Centre for Data-Driven Research & Innovation (name to be decided) P O P U L A T I O N S P I N E H E A L T H D A T A Clinical Trial Support e Feasibility, e Recruitment, e Data capture & f/up Real World Clinical Studies Virtual case/control cohorts, epidemiology, pharmacoepidemiology Actionable Data Analytical tools, visual analytics Enrichment with other data sets Education Social work Housing Transport Police Health Economic analyses Increased efficiency & effectiveness of NHS services Virtual population-wide cohorts e.g. birth, geriatric Followed longitudinally Understanding, improving and integrating services CHI linkage CHI seeding and linkage

UK data: Bipolar Disorder Research Network (n=8,000) Scottish Primary Care data (n=1.8 million) UK Biobank (n=0.5 million) Glasgow Psychosis cohort (n=7,500)

Thanks Bipolar Disorder Research Network: Nick Craddock, Ian Jones, Liz Forty, Lisa Jones Scottish Primary Care data: Stewart Mercer, Bruce Guthrie, Gary McLean, Julie Langan Martin UK Biobank: Jill Pell, Daniel Martin, Barbara Nicholl, Daniel Mackay Glasgow Psychosis cohort: Moira Connolly, John Park, Julie Langan Martin

Physical comorbidity with bipolar disorder: lessons from UK data Daniel Smith daniel.smith@glasgow.ac.uk Symposium 33: Big data and bipolar disorder in the UK