Scientific
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OBJECTIVE: To evaluate the performance of QCancer® (Gastro-Oesophageal) for predicting the risk of undiagnosed gastro-oesophageal cancer in an independent UK cohort of patients from general practice records. DESIGN: Open cohort study to validate QCancer® (Gastro-Oesophageal) prediction model. Three hundred sixty-five practices from the United Kingdom contributing to The Health Improvement Network database. 2.1 million patients registered with a general practice surgery between 01 January 2000 and 30 June 2008, aged 30-84years (3.7 million person years) with 1766 gastro-oesophageal cancer cases. The outcome, gastro-oesophageal cancer was defined as incident diagnosis of gastro-oesophageal cancer during the 2years after study entry. RESULTS: The results from this independent and external validation of QCancer® (Gastro-Oesophageal) demonstrated good performance data on a large cohort of general practice patients. QCancer® (Gastro-Oesophageal) had very good discrimination with c-statistics of 0.93 and 0.94 for women and men respectively. QCancer® (Gastro-Oesophageal) was well calibrated across all tenths of risk and over all age ranges with predicted risks closely matching observed risks. QCancer® (Gastro-Oesophageal) explained 74.4% and 75.6% of the variation in men and women respectively. CONCLUSIONS: QCancer® (Gastro-Oesophageal) is a useful tool to identify undiagnosed gastro-oesophageal cancer in primary care in the United Kingdom.

OBJECTIVE: To estimate the clinical effectiveness and cost effectiveness of using a sodium carboxymethylcellulose dressing (CMC [Aquacel]) and four super absorbent dressings (DryMax Extra[DM], Flivasorb [F], Kerramax [K] and sachet S [S]) in the treatment of highly exuding chronic venous leg ulcers (VLUs) in the UK, from the perspective of the National Health Service (NHS). METHOD: A decision model was constructed depicting the patient pathways and associated management of a cohort of 439 patients with highly exuding chronic VLUs of;;: 3 months of age. The model was based on the case records of a cohort of matched patients from The Health Improvement Network (THIN)database (a nationally representative database of patients registered with general practitioners (GPs) in the UK) who were treated with one of the five dressings. The model estimated the costs and outcomes of patient management over 6 months and the relative cost-effectiveness of using each dressing. RESULTS: Patients' mean age was 73.1 years, and 46% were female. Between 39% and 56% ofVLUs healed by 6 months. CMC-treated wounds that remained unhealed increased in size by 43% over the study period, whereas unhealed wounds treated with the other dressings decreased in size by a mean 34%. Consequently, CMC was excluded from the cost-effectiveness analysis. The 6-monthly NHS cost of managing a VLU with S was £3700 per patient, which was 15-28% lower than the cost of managing patients with the other three super absorbents. Additionally, use of S improved patients' health status to a greater extent than the other three super absorbents, since S-treated patients accrued 0.3-3% more QALYs. Starting treatment with S was the preferred strategy followed by DM, K and Fin that order. CONCLUSION: Within the limitations of the data set,S affords the NHS a cost-effective treatment for managing highly exuding chronic VLUs of ≥3 months of age, compared with DM, F, K and CMC.

OBJECTIVE: To examine temporal trends in the incidence of epilepsy recorded in UK primary care and to evaluate the impact of recent efforts to improve the specificity of diagnosis in children. DESIGN: Birth cohort study using primary care data from The Health Improvement Network, which includes a representative sample of the UK population of approximately 5%. METHODS: We identified epilepsy recorded in primary care using relatively specific through to relatively sensitive indicators to identify epilepsy. Incidence estimates were based on 344 718 children aged 0-14 years with 1 447 760 years' follow-up between 1994 and 2008. Trends in cumulative incidence were explored with stratified analysis by year-of-birth. Trends in annual incidence were investigated using Poisson regression with adjustment for age, gender and deprivation. RESULTS: Cumulative incidence of recorded epilepsy at age 5 years ranged from 0.38% to 0.68% and annual incidence ranged from 71 to 116/100 000 person-years-at-risk, depending on the indicator used to identify epilepsy. With the most specific indicator for epilepsy, cumulative incidence was 33% lower among children born in 2003-2005 than in children born in 1994-1996, and annual incidence declined by 4% per annum between 2001 and 2008, after adjusting for age, gender and deprivation. Using a more sensitive indicator for epilepsy, the equivalent declines were 47% in cumulative incidence and 9% in annual incidence. CONCLUSIONS: The decline since the mid-1990s in epilepsy recorded in primary care may be due to more specific diagnosis, cessation of treatment for some forms of epilepsy, reduced exposure to risk factors or all of these factors.

OBJECTIVE: To examine the associations between body mass index (BMI) and incidence rate (IR) of suicide attempt and suicide. DESIGN AND METHODS: 849,434 British adults were identified from The Health Improvement Network (THIN) database between January 2000 and October 2007. BMI was categorized into six levels: <18.5 (underweight), 18.5-24.9 (normal weight), 25.0-29.9 (overweight), 30.0-34.9, 35.0-39.9, and ≥40 (obese levels I-III). RESULTS: We identified 3,111 suicide attempts by Read codes and 75 suicides with medical records. The overall IR of suicide attempt was 82.2 cases per 100,000 person-years. The IR decreased with BMI in men with depression (471.3-166.0 cases per 100,000 person-years, P for trend = 0.02) and in men without depression (241.5-58.0 cases per 100,000 person-years, P for trend < 0.0001). In women with depression, an L-shaped relationship was observed, that is, a higher rate in underweight group when compared with reference group (503.2 vs. 282.7 per 100,000 person-years) and no significant differences in others (231.8-195.5 cases per 100,000 person-years). In women without depression, the IR was U-shaped with BMI (125.2 in underweight, 68.6 in reference, and 48.5-79.9 cases in overweight and obese I-III groups per 100,000 person-years, P for trend < 0.0001). The above trends remained after adjustment for the covariates. Regarding suicide, the overall IR was 2.0 cases per 100,000 person-years, which tended to decrease with BMI (P = 0.14). CONCLUSIONS: We concluded an inverse linear association between BMI and suicide attempt among men, an L-shaped association in nondepressive women, and a U-shaped association in depressive women were observed. The study also suggested an inverse linear tendency between BMI and suicide.

Lateral epicondylitis is a common condition, but relatively little is known about its aetiology and associated risk factors. We have undertaken a large case-control study using The Health Improvement Network database to assess and quantify the relative contributions of some constitutional and environmental risk factors for lateral epicondylitis in the community. Our dataset included 4998 patients with lateral epicondylitis who were individually matched with a single control by age, sex, and general practice. The median age at diagnosis was 49 (interquartile range 42-56) years . Multivariate analysis showed that the risk factors associated with lateral epicondylitis were rotator cuff pathology (OR 4.95), De Quervain's disease (OR 2.48), carpal tunnel syndrome (OR 1.50), oral corticosteroid therapy (OR 1.68), and previous smoking history (OR 1.20). Diabetes mellitus, current smoking, trigger finger, rheumatoid arthritis, alcohol intake, and obesity were not found to be associated with lateral epicondylitis.

OBJECTIVES: Benzodiazepines have been associated with an increased incidence of infections, and mortality from sepsis, in the critically ill. Here, we determined the effect of community use of benzodiazepines on the occurrence of, and mortality following, pneumonia. METHODS: A nested case-control study using 29 697 controls and 4964 cases of community-acquired pneumonia (CAP) from The Health Improvement Network, a UK primary care patient database (2001-2002), investigated the association between benzodiazepines and pneumonia occurrence using conditional logistic regression. Cox regression was then used to determine the impact of benzodiazepines on mortality in the 4964 cases of CAP. Results are presented as adjusted OR, adjusted HR and 95% CI. RESULTS: Exposure to benzodiazepines was associated with an increased risk of pneumonia (OR 1.54, 95% CI 1.42 to 1.67). Individually diazepam, lorazepam and temazepam, but not chlordiazepoxide, were associated with an increased incidence of CAP. As a class, benzodiazepines were associated with increased 30-day (HR 1.22 (95% CI 1.06 to 1.39)) and long-term mortality (HR 1.32 (95% CI 1.19 to 1.47)) in patients with a prior diagnosis of CAP. Individually diazepam, chlordiazepoxide, lorazepam and temazepam affected long-term mortality in these patients. CONCLUSIONS: Benzodiazepines were associated with an increased risk of, and mortality from, CAP. These hypothesis generating data suggest further research is required into the immune safety profile of benzodiazepines.

STUDY DESIGN: Retrospective database analysis. OBJECTIVES: To describe comorbidities, pain-related pharmacotherapy, healthcare resource use and costs among patients with spinal cord injury (SCI) newly prescribed pregabalin. SETTING: United Kingdom (UK). METHODS: Using The Health Improvement Network database, SCI patients newly prescribed (index event) pregabalin (N=72; average age 48 years; 53% female) were selected. Study measures were evaluated during both the 9-months pre-index and follow-up periods. RESULTS: Prevalent comorbidities included musculoskeletal disorders (51.4%), digestive disorders (23.6%) and urogenital disorders (20.8%). Opioids were the most frequently prescribed medications (pre-index, 58.3%; follow-up, 61.1%, P=not significant (NS)) followed by nonsteroidal anti-inflammatory drugs (43.1 and 45.8%, P=NS). Use of anti-epileptics (other than pregabalin) recommended for SCI neuropathic pain decreased (25.0 vs 12.5%, P=0.0290), whereas sedative/hypnotic use (18.1 vs 26.4%, P=0.034) increased during follow-up. Over 50% of patients had visits to specialists, and at least 1 in every 10 had laboratory/radiology-related visits. There were numerical decreases in proportions of patients with emergency room visits (22.2 vs 13.9%, P=NS) and hospitalizations (16.7 vs 12.5%, P=NS) during follow-up. Medication costs were higher during follow-up (median, £ 561.4 vs £ 889.5, P<0.0001). Costs of outpatient visits were similar during both study periods (£ 1082.1 vs £ 1066.1) as were total medical costs (£ 1689.0 vs £ 2169.4) when costs of pregabalin prescriptions were excluded. Inclusion of pregabalin costs resulted in higher (P<0.0001) total medical costs during follow-up. CONCLUSION: SCI patients had a high comorbidity, medication and healthcare resource use burden in clinical practice. Further research with larger sample sizes and more comprehensive data sources may serve to clarify study findings.

This article reviews methods for comparative effectiveness research using observational data. The basic idea is using an observational study to emulate a hypothetical randomised trial by comparing initiators versus non-initiators of treatment. After adjustment for measured baseline confounders, one can then conduct the observational analogue of an intention-to-treat analysis. We also explain two approaches to conduct the analogues of per-protocol and as-treated analyses after further adjusting for measured time-varying confounding and selection bias using inverse-probability weighting. As an example, we implemented these methods to estimate the effect of statins for primary prevention of coronary heart disease (CHD) using data from electronic medical records in the UK. Despite strong confounding by indication, our approach detected a potential benefit of statin therapy. The analogue of the intention-to-treat hazard ratio (HR) of CHD was 0.89 (0.73, 1.09) for statin initiators versus non-initiators. The HR of CHD was 0.84 (0.54, 1.30) in the per-protocol analysis and 0.79 (0.41, 1.41) in the as-treated analysis for 2 years of use versus no use. In contrast, a conventional comparison of current users versus never users of statin therapy resulted in a HR of 1.31 (1.04, 1.66). We provide a flexible and annotated SAS program to implement the proposed analyses.

BACKGROUND: Compared to existing literature on childhood attention deficit hyperactivity disorder (ADHD), little published adult data are available, particularly outside of the United States. Using General Practitioner (GP) questionnaires from the United Kingdom, this study aimed to examine a number of issues related to ADHD in adults, across three cohorts of patients, adults who received ADHD drug treatment in childhood/adolescence but stopped prior to adulthood; adults who received ADHD drug treatment in childhood/adolescence and continued treatment into adulthood and adults who started ADHD drug treatment in adulthood. METHODS: Patients with a diagnosis of ADHD and prescribed methylphenidate, dexamfetamine or atomoxetine were identified using data from The Health Improvement Network (THIN). Dates when these drugs started and stopped were used to classify patients into the three cohorts. From each cohort, 50 patients were randomly selected and questionnaires were sent via THIN to their GPs.GPs returned completed questionnaires to THIN who forwarded anonymised copies to the researchers. Datasets were analysed using descriptive statistics. RESULTS: Overall response rate was 89% (133/150). GPs stated that in 19 cases, the patient did not meet the criteria of that group; the number of valid questionnaires returned was 114 (76%). The following broad trends were observed: 1) GPs were not aware of the reason for treatment cessation in 43% of cases, 2) patient choice was the most common reason for discontinuation (56%), 3) 7% of patients who stopped pharmacological treatment subsequently reported experiencing ADHD symptoms, 4) 58% of patients who started pharmacological treatment for ADHD in adulthood received pharmacological treatment for other mental health conditions prior to the ADHD being diagnosed. CONCLUSION: This study presents some key findings relating to ADHD; GPs were often not aware of the reason for patients stopping ADHD treatment in childhood or adolescence. Patient choice was identified as the most common reason for treatment cessation. For patients who started pharmacological treatment in adulthood, many patients received pharmacological treatment for comorbidities before a diagnosis of ADHD was made.

PURPOSE: The Health Improvement Network (THIN) is a UK healthcare database composed of computerized information from primary care physicians (PCPs). We analyzed the validity of our method for identifying cases of intracerebral hemorrhage (ICH) and subarachnoid hemorrhage (SAH) within THIN and assessed the incidence of these events. METHODS: Patients aged 20-89 years were identified and followed until (i) ICH or SAH was detected, (ii) the patient reached 90 years old (iii) death, or (iv) the end of the study. Computerized patient profiles were reviewed manually; those not discarded became potential cases. A validation study was undertaken in 400 computer-detected cases (333 confirmed as potential cases; 67 discarded). PCPs completed a questionnaire to determine the actual incidence of ICH and SAH among these cases. We also assessed the incidence of ICH and SAH in the total cohort. RESULTS: A total of 4330 patients with a READ code suggesting hemorrhagic stroke were identified. Computerized profiles with free-text comments were reviewed manually to identify 3633 potential cases. Responses to the PCP questionnaire were received for 306 potential cases and 63 discarded cases (92% response rate); 82% of potential cases were confirmed. Finally, we identified 3137 cases of hemorrhagic stroke. Crude incidence was 15 per 100,000 person-years for ICH and 11 per 100,000 person-years for SAH; the overall incidence increased sharply with age. CONCLUSIONS: Computer detection of cases of hemorrhagic stroke in THIN followed by manual review of clinical profiles is a valid method. The incidence of hemorrhagic stroke increases sharply with age.

SUMMARY: We found the risk of hip fracture was transiently elevated around twofold shortly after initiation of a loop or thiazide diuretic drug in a case-crossover and case-control study. No statistical association was found following the initiation of a comparator medication: ACE inhibitors. Awareness of these short-term risks may reduce hip fractures. INTRODUCTION: Little is known about the acute effects of initiating a diuretic drug on risk of fracture. We evaluated the relationship between initiating a diuretic drug and the occurrence of hip fracture. METHODS: The study sample included 2,118,793 persons aged ≥50 years enrolled in The Health Improvement Network (THIN) between 1986 and 2010. The effect of a new start of a diuretic drug or comparator medication (ACE inhibitor) on risk of hip fracture was assessed using a case-crossover and case-control study during the 1-7, 8-14, 15-21, and 22-28 days following drug initiation. RESULTS: Included were 28,703 individuals with an incident hip fracture over a mean of 7.9 years follow-up. In the case-crossover study, the risk of experiencing a hip fracture was increased during the first 7 days following loop diuretic drug initiation (OR = 1.8; 95 % CI, 1.2, 2.7). The elevated risk did not continue during the 8-14, 15-21, or 22-28 days following drug initiation. For thiazide diuretics, the risk of hip fracture was elevated 8-14 days after drug initiation (OR = 2.2; 95 % CI, 1.2, 3.9). No such association was observed in the 1-7, 15-21, or 22-28 days following thiazide drug initiation. ACE inhibitor initiation was not associated with a statistically significant increased risk of hip fracture. Similar results were observed using a case-control study. CONCLUSIONS: The risk of hip fracture was transiently elevated around twofold shortly after the new start of a loop or thiazide diuretic drug. Awareness of these short-term risks may reduce hip fractures and other injurious falls in vulnerable adults.

BACKGROUND: There has been increased interest in using multiple observational databases to understand the safety profile of medical products during the postmarketing period. However, it is challenging to perform analyses across these heterogeneous data sources. The Observational Medical Outcome Partnership (OMOP) provides a Common Data Model (CDM) for organizing and standardizing databases. OMOP's work with the CDM has primarily focused on US databases. As a participant in the OMOP Extended Consortium, we implemented the OMOP CDM on the UK Electronic Healthcare Record database-The Health Improvement Network (THIN). OBJECTIVE: The aim of the study was to evaluate the implementation of the THIN database in the OMOP CDM and explore its use for active drug safety surveillance. METHODS: Following the OMOP CDM specification, the raw THIN database was mapped into a CDM THIN database. Ten Drugs of Interest (DOI) and nine Health Outcomes of Interest (HOI), defined and focused by the OMOP, were created using the CDM THIN database. Quantitative comparison of raw THIN to CDM THIN was performed by execution and analysis of OMOP standardized reports and additional analyses. The practical value of CDM THIN for drug safety and pharmacoepidemiological research was assessed by implementing three analysis methods: Proportional Reporting Ratio (PRR), Univariate Self-Case Control Series (USCCS) and High-Dimensional Propensity Score (HDPS). A published study using raw THIN data was selected to examine the external validity of CDM THIN. RESULTS: Overall demographic characteristics were the same in both databases. Mapping medical and drug codes into the OMOP terminology dictionary was incomplete: 25 % medical codes and 55 % drug codes in raw THIN were not listed in the OMOP terminology dictionary, representing 6 % condition occurrence counts, 4 % procedure occurrence counts and 7 % drug exposure counts in raw THIN. Seven DOIs had <0.3 % and three DOIs had 1 % of unmapped drug exposure counts; each HOI had at least one definition with no or minimal (≤0.2 %) issues with unmapped condition occurrence counts, except for the upper gastrointestinal (UGI) ulcer hospitalization cohort. The application of PRR, USCCS and HDPS found, respectively, a sensitivity of 67, 78 and 50 %, and a specificity of 68, 59 and 76 %, suggesting that safety issues defined as known by the OMOP could be identified in CDM THIN, with imperfect performance. Similar PRR scores were produced using both CDM THIN and raw THIN, while the execution time was twice as fast on CDM THIN. There was close replication of demographic distribution, death rate and prescription pattern and trend in the published study population and the cohort of CDM THIN. CONCLUSIONS: This research demonstrated that information loss due to incomplete mapping of medical and drug codes as well as data structure in the current CDM THIN limits its use for all possible epidemiological evaluation studies. Current HOIs and DOIs predefined by the OMOP were constructed with minimal loss of information and can be used for active surveillance methodological research. The OMOP CDM THIN can be a valuable tool for multiple aspects of pharmacoepidemiological research when the unique features of UK Electronic Health Records are incorporated in the OMOP library.

PURPOSE: Examine feasibility of a new strategy to perform Electronic Medical Record database valid Comparative Effectiveness Research (CER), using determination of whether rosiglitazone (ROS) treatment increases Acute myocardial infarction (MI) in comparison to pioglitazone (PIO) as a model question. METHODS: Using the UK The Health Improvement Network Database, a retrospective cohort design replicated the proactive RCT of diabetics with ischemic cardiovascular disease (CVD). Replication studies using PIO or ROS, as well as expanded studies of subjects not requiring CVD, were performed. MI assessment used multiple analytics comparing ROS and PIO exposed patients including: unexposed subjects, the proactive RCT, and directly between ROS to PIO exposed cohorts. RESULTS: PIO replication studies did not affect MI [HR 0.88 (0.49 to 1.42)], but ROS increased MI, with prior event rate ratio (PERR) adjusted HR (which overcomes unmeasured confounding) results of: [HR 1.31 (0.94 to 1.74)] versus proactive RCT [HR 0.83 (0.65 to 1.06)] (p = 0.02). Direct ROS to PIO exposed cohort comparisons yielded PERR adj HR of 1.55 (0.98 to 2.65). By contrast, expanded studies showed no differences between ROS and PIO exposure. CONCLUSIONS: These results provide new insight regarding the effects of ROS and PIO on MI. In a population with established ischemic CVD, ROS increased MI in contrast to PIO; whereas in an unselected population, ROS and PIO have reasonably comparable effects. Most importantly, this study demonstrates the feasibility and advantages of a new strategy to perform reliable "CER" using an EMR database.

PURPOSE: To examine the effect of applying different data quality filters on the incidence of disease and prescribing trends over time in a primary care research database and validate a new method for defining periods of adequate computer usage. METHODS: Acceptable computer usage (ACU) was defined as the year in which a general practice was continuously entering on average at least two therapy records, one medical record and one additional health data record per patient per year. The effect of using this date on the incidence of a range of outcomes (antibiotic prescriptions, myocardial infarction, colon cancer, lung cancer) over time was compared with other methods for defining the start of patient follow-up in The Health Improvement Network (THIN) primary care database containing UK patient records. Various combinations of the follow-up start dates were applied to the data to calculate incidence rates: (i) registration date, (ii) practice computerization date, (iii) acceptable mortality recording (AMR) (iv) ACU. RESULTS: On average, the ACU date was 3.3 years after the AMR date. Applying the AMR or ACU dates separately or in combination produced trends in incidence rates more comparable with external data sources than using the year of practice registration or computerization. The estimated incidence rates were highly sensitive to different methods of defining start date in early time periods. CONCLUSIONS: Using the latest of AMR and ACU dates is useful for improving the integrity of THIN data.

BACKGROUND: Recent evidence has identified pre-existing type 2 diabetes mellitus (T2DM) as a risk factor for the development of PAC, but relatively little is known about its effects on survival. Our aim was to determine the effect of varying durations of pre-existing T2DM on survival in patients with PAC. METHODS: We conducted a retrospective cohort study using The Health Improvement Network (THIN), a primary care electronic medical record database from the UK (2003-2010). The study cohort included all subjects with a diagnostic code for PAC. Subjects with a diagnostic code for T2DM before their PAC diagnosis were classified as exposed; otherwise, subjects were classified as unexposed. The primary outcome was overall survival. The analysis was performed using univariate and multivariable Cox proportional-hazards models. Additional analysis was performed to assess the effect of increasing duration of pre-existing T2DM [i.e., <90 days, 90 days to <1 year, 1 to <3 years, 3 to 5 years, >5 years] on survival. RESULTS: The study included 3,147 patients with PAC, with 745 patients having pre-existing T2DM and 2,402 patients without pre-existing T2DM. In the primary multivariate analysis, there was no difference in survival between those exposed and those unexposed to pre-existing T2DM (HR 1.02 [0.93, 1.12], p = 0.620). In the secondary analysis, only those patients with T2DM > 5 years duration had a significantly increased mortality (HR 1.16 [1.00, 1.33], p < 0.05). CONCLUSIONS: Long-term pre-existing T2DM is associated with increased mortality in patients diagnosed with PAC.

BACKGROUND: Studies have shown that for the same quantity of cigarettes smoked, women are more likely to develop heart disease than men, but studies in lung cancer have produced conflicting results. We studied the association between smoking quantity and lung cancer in men and women. METHODS: Using data from The Health Improvement Network (a UK medical research database), we generated a data set comprising 12,121 incident cases of lung cancer and 48,216 age-, sex-, and general practice-matched control subjects. We used conditional logistic regression to calculate ORs for lung cancer according to highest-ever-quantity smoked in men and women separately. RESULTS: The odds of lung cancer in women who had ever smoked heavily compared with those who had never smoked were increased 19-fold (OR, 19.10; 95% CI, 16.98-21.49), which was more than for men smoking the same quantity (OR, 12.81; 95% CI, 11.52-14.24). There was strong evidence of a difference in effect of quantity smoked on lung cancer between men and women (interaction P < .0001), which remained after adjusting for height (a proxy marker for lung volume). CONCLUSIONS: Moderate and heavy smoking carry a higher risk of lung cancer in women than in men, and this difference does not seem to be explained by lung volume. The findings suggest that extrapolating risk estimates for lung cancer in men to women will underestimate the adverse impact of smoking in women.

BACKGROUND: A recent United Kingdom (UK) report found that breast and colorectal cancers were more common in people with severe mental illness (SMI) and recommended targeted screening. Epidemiological evidence is however inconsistent. OBJECTIVES: To estimate relative incidence rates for colorectal, breast and lung cancer, and the overall incidence of the commonest other UK cancers, in people with SMI compared with people without SMI. METHOD: Cohort study in the UK using The Health Improvement Network (THIN) primary care database between 1990 and June 2008. Poisson regression was used to obtain adjusted incidence rate ratios (IRRs) for cancer, comparing two cohorts of people over 18; with and without a diagnosis of SMI. RESULTS: We identified 20,632 people with SMI and 116,152 people without, with median follow up of over 6years. No significant associations were observed between SMI and cancers of the breast (adjusted IRR 1.17; 95% confidence interval 0.95-1.45), colon (0.70; 0.46-1.05), rectum (1.05; 0.65-1.69) or lung (0.84; 0.65-1.10). The adjusted IRR for an aggregate cancer outcome in SMI was 0.95; 0.85-1.06. Results were similar for schizophrenia and bipolar disorder. CONCLUSIONS: In a cohort analysis within a large UK primary care database, the incidence of colo-rectal, breast and lung cancer, and of all common cancers, did not differ significantly in people with SMI, including schizophrenia, compared with people without SMI. Our results do not support enhanced screening procedures for cancer in people with SMI.

Bereaved spouses or partners are thought to be at increased risk of morbidity and mortality. However, there are few large prospective studies and results are inconsistent. We estimated the relative mortality, prescription of psychotropic medication and use of primary medical care services in adults whose cohabitee died of cancer. To do this, we undertook a cohort study using The Health Improvement Network (THIN) UK primary care database. Participants were 1) people aged over 40, who were registered with general practices and had been exposed to the death of a cohabitee from cancer; and 2) a comparison cohort frequency matched on five year age bands and sex who were cohabiting with a living partner. The baseline was chosen as six months before the date of the cancer death for the exposed group and a random date for the unexposed group. Incidence rate ratios (IRR) with 95% confidence intervals (CI) were estimated using random effects Poisson regression to account for clustering within general practices and adjusting for other key variables. 92,129 patients were studied for a median follow up of 4 years. Cohabitees of patients who died of cancer were less likely to die of any cause (IRR 0.71, CI 0.68-0.74) after adjustment for age, gender, number of non-psychotropic prescriptions 6 months before the cancer death/index date, use of psychotropic medication 6 months before the cancer death/index date, smoking, alcohol and area deprivation score. Exposed patients were more likely to receive a prescription for antidepressant or hypnotic medication and to attend their GP both before and after the death of the cohabitee. In conclusion, we did not confirm increased mortality in cohabitees of people dying from cancer.

INTRODUCTION: The majority of cases of both lung cancer and chronic obstructive pulmonary disease (COPD) are attributable to cigarette smoking, but whether COPD is an independent risk factor for lung cancer remains unclear. METHODS: We used The Health Improvement Network, a U.K. general practice database, to identify incident cases of lung cancer and controls matched on age, sex, and practice. Using conditional logistic regression, we assessed the effects of timing of first diagnoses of COPD, pneumonia, and asthma on the odds of lung cancer, adjusting for smoking habit. RESULTS: Of 11,888 incident cases of lung cancer, 23% had a prior diagnosis of COPD compared with only 6% of the 37,605 controls. The odds of lung cancer in patients who had COPD diagnosed within 6 months of their cancer diagnosis were 11-fold those of patients without COPD (odds ratio 11.47, 95% confidence interval 9.38-14.02). However, when restricted to earlier COPD diagnoses, with adjustment for smoking, the effect markedly diminished (for COPD diagnoses >10 years before lung cancer diagnosis, odds ratio: 2.18, 95% confidence interval: 1.87-2.54). The pattern was similar for pneumonia. The effect of COPD on lung cancer remained after excluding patients who had a codiagnosis of asthma. CONCLUSION: A diagnosis of COPD is strongly associated with a diagnosis of lung cancer, however, this association is largely explained by smoking habit, strongly dependent on the timing of COPD diagnosis, and not specific to COPD. It seems unlikely, therefore, that COPD is an independent risk factor for lung cancer.