Incidence, Prevalence, and Survival of Patients with Idiopathic Pulmonary Fibrosis in the UK.

INTRODUCTION: Recent developments in the care of patients with idiopathic pulmonary fibrosis have the potential to improve survival rates. Population-based estimates of the current disease burden are needed to evaluate the future impact of newly approved therapies. The objective of this study is to describe incidence, prevalence, and survival of idiopathic pulmonary fibrosis patients in the UK. METHODS: Between 2000 and 2012, a patient cohort (N = 9,748,108), identified from Clinical Practice Research Datalink primary care data, was used to identify incident and prevalent cases of idiopathic pulmonary fibrosis-clinical syndrome. Incident cases were followed up to identify deaths. Poisson and Cox regressions were used to calculate incidence rate ratios (IRR) and hazard ratios for mortality, respectively. Adjustments were made for age, gender, and strategic health authority. Survival from diagnosis was estimated using Kaplan-Meier analysis. RESULTS: In total 1491 and 4527 incident cases were identified using narrow and broad idiopathic pulmonary fibrosis-clinical syndrome definitions, respectively. Incidence and prevalence increased during the study. Compared with 2000, a near 80% increase in incidence was observed by 2012 [IRR 1.78 (95% CI 1.50-2.11; broad definition)], despite an observed decrease using the narrow definition [0.50 (0.38-0.65)]. Median survival was 3.0 years (95% CI 2.8-3.1) and 2.7 years (95% CI 2.5-3.0) in broad (n = 2168) and narrow case sets (n = 996), respectively. No significant changes in survival were observed. CONCLUSIONS: Idiopathic pulmonary fibrosis incidence rates have increased since 2000 and survival remains poor. These results provide a benchmark against which the effects of future treatment changes can be measured. FUNDING: InterMune UK and Ireland (now part of F. Hoffman La Roche)

What are the implications of using individual and combined sources of routinely collected data to identify and characterise incident site-specific cancers? a concordance and validation study using linked English electronic health records data.

OBJECTIVES: To describe the benefits and limitations of using individual and combinations of linked English electronic health data to identify incident cancers. DESIGN AND SETTING: Our descriptive study uses linked English Clinical Practice Research Datalink primary care; cancer registration; hospitalisation and death registration data. PARTICIPANTS AND MEASURES: We implemented case definitions to identify first site-specific cancers at the 20 most common sites, based on the first ever cancer diagnosis recorded in each individual or commonly used combination of data sources between 2000 and 2014. We calculated positive predictive values and sensitivities of each definition, compared with a gold standard algorithm that used information from all linked data sets to identify first cancers. We described completeness of grade and stage information in the cancer registration data set. RESULTS: 165 953 gold standard cancers were identified. Positive predictive values of all case definitions were ≥80% and ≥94% for the four most common cancers (breast, lung, colorectal and prostate). Sensitivity for case definitions that used cancer registration alone or in combination was ≥92% for the four most common cancers and ≥80% across all cancer sites except bladder cancer (65% using cancer registration alone). For case definitions using linked primary care, hospitalisation and death registration data, sensitivity was ≥89% for the four most common cancers, and ≥80% for all cancer sites except kidney (69%), oral cavity (76%) and ovarian cancer (78%). When primary care or hospitalisation data were used alone, sensitivities were generally lower and diagnosis dates were delayed. Completeness of staging data in cancer registration data was high from 2012 (minimum 76.0% in 2012 and 86.4% in 2014 for the four most common cancers). CONCLUSIONS: Ascertainment of incident cancers was good when using cancer registration data alone or in combination with other data sets, and for the majority of cancers when using a combination of primary care, hospitalisation and death registration data

Identification of mental health and quality of life outcomes in primary care databases in the UK: a systematic review.

OBJECTIVES: To summarise the definitions and combinations of codes used to identify outcomes of anxiety, depression, fatigue, cognitive dysfunction (including mild cognitive dysfunction and dementia), sexual dysfunction, pain, sleep disorders, and fatal and non-fatal self-harm in studies using electronic health records from primary care databases in the UK. DESIGN: Systematic review. DATA SOURCES: Medline, Embase and lists of publications of the main primary care databases in the UK. ELIGIBILITY CRITERIA: Included data from a UK primary care database and studied outcome(s) of interest. DATA EXTRACTION AND SYNTHESIS: We abstracted information on the outcomes definition and codelists. When necessary, authors were contacted to request codelists. RESULTS: 120 studies were eligible. Codelists were available for 17/42 studies of depression; 21/41 studies of fatal and non-fatal self-harm; 17/27 studies of dementia/cognitive dysfunction; 5/12 studies of anxiety; 4/8 studies of pain; 3/6 studies of fatigue and sexual dysfunction; 1/2 studies of sleep disorders. Depression was most often defined using codes for diagnoses (37/42 studies) and/or antidepressants prescriptions (21/42 studies); six studies reported including symptoms in their definition. Anxiety was defined with codes for diagnoses (12/12 studies); four studies also reported including symptoms. Fatal self-harm was ascertained in primary care data linked to the Office for National Statistics mortality database in nine studies. Most studies of cognitive dysfunction included Alzheimer's disease, and vascular and frontotemporal dementia. Fatigue definitions varied little, including chronic fatigue syndrome, neurasthenia and postviral fatigue syndrome. All studies of sexual dysfunction focused on male conditions, principally erectile dysfunction. Sleep disorders included insomnia and hypersomnia. There was substantial variability in the codelists; validation was carried out i21/120 studies. CONCLUSIONS: There is a need for standardised definitions and validated list of codes to assess mental health and quality of life outcomes in primary care databases in the UK

Body mass index and Hodgkin's lymphoma: UK population-based cohort study of 5.8 million individuals.

Previous epidemiological studies describe a positive association between body mass index (BMI) and Hodgkin's lymphoma, mainly in obese vs. normal weight individuals. We examined the shape of this relationship in individuals aged 16 years or older, using primary care data from the United Kingdom's Clinical Practice Research Datalink. Cox models were fitted with linear, non-linear (spline) and categorical BMI. Models were adjusted for potential confounders and effect modification was investigated. Five point eight two million patients were included, 927 of whom developed Hodgkin's lymphoma during 41.6 million years of follow-up. Each 5 kg/m2 increase in BMI was associated with a 10% increase in Hodgkin's lymphoma (95% confidence intervals: 2-19). Analysis of non-linearity suggested a J-shaped association with incidence increasing with BMI above 24.2 kg/m2. Seven point four per cent of adult Hodgkin's lymphoma cases were estimated to be attributable to excess weight. Our findings suggest a pattern of increasing risk beyond the World Health Organisation healthy weight category in the general population

Statin use in cancer survivors versus the general population: cohort study using primary care data from the UK clinical practice research datalink.

BACKGROUND: Cancer survivors may be at increased risk of cardiovascular diseases, but little is known about whether prescribing guidelines for the primary prevention of cardiovascular disease are adequately implemented in these patients. We compared levels of statin initiation and cessation among cancer survivors compared to the general population to determine differences in uptake of pharmaceutical cardiovascular risk prevention measures in these groups. METHODS: The study population included individuals aged ≥40 during 2005-13 within the UK Clinical Practice Research Datalink primary care database. Within this population we identified cancer survivors who were alive and under follow-up at least 1 year after diagnosis, and controls with no cancer history. Follow-up time prior to cancer diagnosis was included in the control cohort. Using logistic regression, we compared these groups with respect to uptake of statins within 1 month of a first high recorded cardiovascular risk score. Then, we used Cox modelling to compare persistence on statin therapy (time to statin cessation) between cancer survivors and controls from the main study population who had initiated on a statin. RESULTS: Among 4202 cancer survivors and 113,035 controls with a record indicating a high cardiovascular risk score, 23.0% and 23.5% respectively initiated a statin within 1 month (adjusted odds ratio 0.98 [91.8-1.05], p = 0.626). Cancer survivors appeared more likely to discontinue statin treatment than controls (adjusted hazard ratio 1.07 [1.01-1.12], p = 0.02). This greater risk of discontinuing was only evident after the first year of therapy (p-interaction < 0.001). INTERPRETATION: Although cardiovascular risk is thought to be higher in cancer survivors compared to the general population, cancer survivors were no more likely to receive statins, and marginally more likely to cease long-term therapy, than general population controls. There may be an opportunity to mitigate the suspected higher cardiovascular risk in the growing population of cancer survivors by improving uptake of lipid-lowering treatment and persistence on therapy

Pioglitazone and cause-specific risk of mortality in patients with type 2 diabetes: extended analysis from a European multidatabase cohort study.

OBJECTIVES: Describe and compare the risk of cardiovascular and non-cardiovascular mortality in patients whose antidiabetic therapy is modified to include pioglitazone compared with an alternative antidiabetic medication at the same stage of disease progression. RESEARCH DESIGN AND METHODS: This exploratory linked database cohort analysis used pooled health and mortality data from three European countries: Finland, Sweden and the UK. Propensity score together with exact matching was used to match 31 133 patients with type 2 diabetes first prescribed pioglitazone from 2000 to 2011, to 31 133 patients never prescribed pioglitazone. Exact matching variables were treatment stage, history of diabetes, diabetes complications and cardiovascular disease, and year of cohort entry. Mean follow-up time was 2.60 (SD 2.00) and 2.69 (SD 2.31) years in the pioglitazone and non-pioglitazone-exposed groups, respectively. Crude cause-specific mortality rates were ascertained. Association with pioglitazone use was estimated using Cox proportional hazards models adjusted a priori for country, age, sex, the propensity score quintile and time-dependent variables representing use of antidiabetic drugs. Stepwise testing identified no additional confounders to include in adjusted models. RESULTS: The crude mortality rate was lower in the pioglitazone-exposed group than the non-exposed group for both cardiovascular and non-cardiovascular mortality. Adjusted HRs comparing pioglitazone to alternative antidiabetic exposure were 0.58 (95% CI 0.52 to 0.63) and 0.63 (95% CI 0.58 to 0.68) for cardiovascular and non-cardiovascular mortality, respectively. A protective effect associated with pioglitazone was also found for all specific cardiovascular causes. CONCLUSIONS: This analysis suggests that pioglitazone is associated with a decrease in both cardiovascular and non-cardiovascular mortality. Results should be interpreted with caution due to the potential for residual confounding in this exploratory analysis. Further studies, specifically designed to test the association between pioglitazone use and patient-focused outcomes, are suggested. STUDY REGISTRATION NUMBER: European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCePP; EUPAS3626)

Prevalence of COVID-19-related risk factors and risk of severe influenza outcomes in cancer survivors: A matched cohort study using linked English electronic health records data.

BACKGROUND: People with active cancer are recognised as at risk of COVID-19 complications, but it is unclear whether the much larger population of cancer survivors is at elevated risk. We aimed to address this by comparing cancer survivors and cancer-free controls for (i) prevalence of comorbidities considered risk factors for COVID-19; and (ii) risk of severe influenza, as a marker of susceptibility to severe outcomes from epidemic respiratory viruses. METHODS: We included survivors (≥1 year) of the 20 most common cancers, and age, sex and general practice-matched cancer-free controls, derived from English primary care data linked to cancer registrations, hospital admissions and death registrations. Comorbidity prevalences were calculated 1 and 5 years from cancer diagnosis. Risk of hospitalisation or death due to influenza was compared using Cox models adjusted for baseline demographics and comorbidities. FINDINGS: 108,215 cancer survivors and 523,541 cancer-free controls were included. Cancer survivors had more diabetes, asthma, other respiratory, cardiac, neurological, renal, and liver diseases, and less obesity, compared with controls, but there was variation by cancer site. There were 205 influenza hospitalisations/deaths, with cancer survivors at higher risk than controls (adjusted HR 2.78, 95% CI 2.04-3.80). Haematological cancer survivors had large elevated risks persisting for >10 years (HR overall 15.17, 7.84-29.35; HR >10 years from cancer diagnosis 10.06, 2.47-40.93). Survivors of other cancers had evidence of raised risk up to 5 years from cancer diagnosis only (HR >5 years 2.22, 1.31-3.74). INTERPRETATION: Risks of severe COVID-19 outcomes are likely to be elevated in cancer survivors. This should be taken into account in policies targeted at clinical risk groups, and vaccination for both influenza, and, when available, COVID-19, should be encouraged in cancer survivors

Cancer history as a predictor in cardiovascular risk scores: a primary care cohort study.

BACKGROUND: Cardiovascular risks are raised in cancer survivors but cancer history is not included in cardiovascular risk scores that inform preventive decisions. AIM: To assess whether cancer diagnosis should be included in cardiovascular risk scores. DESIGN AND SETTING: Cohort study using data from English general practices linked to hospital, cancer registration, and death registration data from 1990 to 2015. METHOD: Adults alive 1 year after a first cancer diagnosis and age, sex, general practice, and calendar- time matched cancer-free individuals were included. Individuals with 10% relative difference with P<0.01) was assessed. RESULTS: In total, 81 420 cancer survivors and 413 547 cancer-free individuals were followed for a median 5.2 years (interquartile range [IQR] 2.8- 9.1) and 6.3 years (IQR 3.5-10.2), respectively. Including a 1-year cancer survivorship variable in a QRISK3-based model met the threshold for inclusion for males (independent hazard ratio [iHR] 1.16, 95% confidence interval [CI] = 1.11 to 1.20, P<0.001) but not females (iHR 1.07, 95% CI = 1.01 to 1.14, P = 0.02). When including cancer type, the threshold was met for both sexes with history of haematological cancer (males: iHR 1.27, 95% CI = 1.16 to 1.40, P <0.001; females: iHR 1.59, 95% CI = 1.32 to 1.91, P<0.001) and for males but not females with history of solid cancers (males: iHR 1.13, 95% CI = 1.08 to 1.18, P <0.001; females: iHR 1.04, 95% CI = 0.98 to 1.10, P = 0.19). CONCLUSION: Developers should consider including cancer history variables in future cardiovascular risk models

Does Cardiovascular Mortality Overtake Cancer Mortality During Cancer Survivorship?: An English Retrospective Cohort Study.

Background: Cancer survivors have a higher risk for developing cardiovascular diseases than the general population. Objectives: The aim of this study was to investigate whether cardiovascular mortality overtakes cancer-specific mortality during cancer survivorship and, if so, at what point cardiovascular disease becomes the dominant cause of death. Methods: This cohort study used linked English electronic health records, including death registration data. The study population included 104,028 adults ≥40 years of age whose first cancer diagnosis was for 1 of 9 common cancers and who were alive and followed up at least 1 year after diagnosis. Age-stratified mortality rates were estimated from cardiovascular disease or cancer by predicting from Poisson models incorporating categorical age at diagnosis and time since diagnosis. Where cardiovascular disease mortality overtook cancer mortality, the crossover point was estimated using interpolation. Results: Mortality from cardiovascular causes overtook mortality due to the primary cancer at 2 to 11 years after cancer diagnosis in survivors of all 9 cancer types ≥80 years of age at diagnosis and after 5 to 17 years in survivors of 7 cancer types 60 to 79 years of age at diagnosis. Cardiovascular mortality overtook all cancer mortality for 6 and 2 cancer sites in the ≥80-year and 60- to 79-year age groups, respectively, over a longer time period. Cardiovascular mortality did not overtake cancer mortality during the observation period in patients aged 40 to 59 years, except among survivors of uterine cancer. Conclusions: In older survivors of 9 common cancers, cardiovascular mortality becomes dominant over mortality from the primary cancer, though not always over total cancer mortality, as time passes since cancer diagnosis

Pioglitazone and risk of mortality in patients with type 2 diabetes: results from a European multidatabase cohort study.

OBJECTIVES: Estimate and compare the risk of mortality in patients whose antidiabetic therapy is modified to include pioglitazone compared with an alternative antidiabetic medication at the same stage of disease progression. DESIGN: Retrospective cohort study. SETTING: Pooled analysis of clinical data collected from primary and/or secondary care settings in four European countries: Finland, The Netherlands, Sweden and the UK . PARTICIPANTS: 56 337 patients with type 2 diabetes mellitus first prescribed pioglitazone between 2000 and 2011, and 56 337 patients never prescribed pioglitazone matched by treatment stage, history of diabetes, diabetes complications and cardiovascular disease, and year of cohort entry using exact and propensity score matching. Patients were followed-up for a mean of 2.90 (SD 2.21) and 2.83 (SD 2.37) years in the pioglitazone-exposed and non-pioglitazone-exposed groups, respectively. OUTCOMES: All-cause mortality ascertained from clinical or registry data. Mortality was a planned secondary outcome in a study primarily studying the association of pioglitazone use with bladder cancer risk. RESULTS: The crude overall mortality rate per 10 000 patient years was 206 (95% CI 199 to 213) in the pioglitazone-exposed group and 448 (95% CI 438 to 458) in the non-pioglitazone-exposed group. The crude HR comparing pioglitazone to alternative antidiabetic exposure was 0.46 (95% CI 0.45 to 0.48). This reduced in magnitude to 0.67 (95% CI 0.64 to 0.70) following further adjustment for matching variables, propensity scores, age, gender and time-dependent variables representing use of alternative antidiabetic drugs. CONCLUSIONS: In this large observational cohort study of patients with type 2 diabetes, pioglitazone exposure was associated with a statistically significant decrease in the risk of all-cause mortality across four European countries. Results should be interpreted with caution due to the potential for residual confounding. PROTOCOL REGISTRATION: European Network of Centres for Pharmacoepidemiology and Pharmacovigilance