ABSTRACT
PURPOSE: It is not clear whether all deaths are recorded in the Clinical Practice Research Datalink (CPRD) or how accurate a recorded date of death is. Individual-level linkage with national data from the Office for National Statistics (ONS) and Hospital Episode Statistics (HES) in England offers the opportunity to compare death information across different data sources. METHODS: Age-standardised mortality rates (ASMRs) standardised to the European Standard Population (ESP) 2013 for CPRD were compared with figures published by the ONS, and crude mortality rates were calculated for a sample population with individual linkage between CPRD, ONS, and HES data. Agreement on the fact of death between CPRD and ONS was assessed and presented over time from 1998 to 2013. RESULTS: There were 33 997 patients with a record of death in the ONS data; 33 389 (98.2%) of these were also identified in CPRD. Exact agreement on the death date between CPRD and the ONS was 69.7% across the whole study period, increasing from 53.4% in 1998 to 78.0% in 2013. By 2013, 98.8% of deaths were in agreement within ±30 days. CONCLUSIONS: For censoring follow-up and calculating mortality rates, CPRD data are likely to be sufficient, as a delay in death recording of up to 1 month is unlikely to impact results significantly. Where the exact date of death or the cause is important, it may be advisable to include the individually linked death registration data from the ONS.
Subject(s)
Data Accuracy , Data Management/methods , Death Certificates , Primary Health Care/statistics & numerical data , Registries/standards , Databases, Factual , Information Storage and Retrieval , United KingdomABSTRACT
PURPOSE: UK primary care provides a rich data source for research. The impact of proposed data collection restrictions is unknown. This study aimed to assess the impact of restricting the scope of electronic health record (EHR) data collection on the ability to conduct research. The study estimated the consequences of restricted data collection on published Clinical Practice Research Datalink studies from high impact journals or referenced in clinical guidelines. METHODS: A structured form was used to systematically analyse the extent to which individual studies would have been possible using a database with data collection restrictions in place: (1) retrospective collection of specified diseases only; (2) retrospective collection restricted to a 6- or 12-year period; (3) prospective and retrospective collection restricted to non-sensitive data. Outcomes were categorised as unfeasible (not reproducible without major bias); compromised (feasible with design modification); or unaffected. RESULTS: Overall, 91% studies were compromised with all restrictions in place; 56% studies were unfeasible even with design modification. With restrictions on diseases alone, 74% studies were compromised; 51% were unfeasible. Restricting collection to 6/12 years had a major impact, with 67 and 22% of studies compromised, respectively. Restricting collection of sensitive data had a lesser but marked impact with 10% studies compromised. CONCLUSION: EHR data collection restrictions can profoundly reduce the capacity for public health research that underpins evidence-based medicine and clinical guidance. National initiatives seeking to collect EHRs should consider the implications of restricting data collection on the ability to address vital public health questions.
Subject(s)
Confidentiality/legislation & jurisprudence , Data Collection/methods , Electronic Health Records/statistics & numerical data , Evidence-Based Medicine/statistics & numerical data , Primary Health Care/statistics & numerical data , Data Collection/legislation & jurisprudence , Data Collection/standards , Databases, Factual/legislation & jurisprudence , Databases, Factual/statistics & numerical data , Electronic Health Records/legislation & jurisprudence , Evidence-Based Medicine/legislation & jurisprudence , Feasibility Studies , Humans , Primary Health Care/legislation & jurisprudence , Reproducibility of Results , Research Design/standards , United KingdomABSTRACT
PURPOSE: The ability of the Clinical Practice Research Datalink (CPRD) to ascertain all-cause hospitalizations remains unknown. We determined the proportion of hospitalizations in CPRD that were also recorded in Hospital Episode Statistics (HES), and vice versa, among patients initiating oral antidiabetic (OAD) therapy. METHODS: We conducted a retrospective cohort study from October 2009 to September 2012 among OAD-treated patients registered with general practitioners who contribute to CPRD and consent to HES linkage. In CPRD, we identified initial hospitalizations for each calendar year by an Inpatient Referral, Consultation Type code, or Read code indicating an inpatient episode and determined if an admission date was recorded in HES within ±30 days. We then identified initial HES admission dates and determined if a hospitalization was documented in CPRD within ±30 days. Sensitivity analyses were conducted utilizing HES discharge, rather than admission, dates. RESULTS: Among 8574 OAD-treated HES-linked patients in CPRD, 6574 initial hospitalizations across the study period were identified in CPRD, and 5188 (78.9% [95% CI, 77.9%-79.9%]) were confirmed by a HES admission date within ±30 days (median difference, ±3 days [IQR, 1-7 days]). Among 8609 initial hospital admissions in HES, 4803 (55.7% [95% CI, 54.7%-56.8%]) hospitalizations were recorded in CPRD within ±30 days (median difference, ±4 days [IQR, 1-9 days]). Similar results were observed using HES discharge dates. CONCLUSION: A substantial minority of patient-level hospitalization data are nonconcordant between HES and CPRD. Pharmacoepidemiologic studies within CPRD that seek to identify hospitalizations should consider linkage with HES to ensure adequate ascertainment of inpatient events.
Subject(s)
Diabetes Mellitus, Type 2/drug therapy , Dipeptidyl-Peptidase IV Inhibitors/therapeutic use , Patient Admission/statistics & numerical data , Administration, Oral , Adult , Databases, Factual/statistics & numerical data , Drug Prescriptions/statistics & numerical data , Female , Humans , Male , Pharmacoepidemiology/methods , Pharmacoepidemiology/statistics & numerical data , Retrospective Studies , Treatment Outcome , United KingdomABSTRACT
PURPOSE: Identification of hospitalizations for infection is important for post-marketing surveillance of drugs, but the validity of using diagnosis codes to identify these events is unknown. Differentiating between hospitalization for and with infection is important, as the latter is common and less likely to arise from pre-admission exposure to drugs. We determined positive predictive values (PPVs) of diagnostic coding-based algorithms to identify hospitalization for infection among patients prescribed oral anti-diabetic drugs (OADs). METHODS: We identified patients initiating OADs within 2 United States claims databases (Medicare, HealthCore Integrated Research DatabaseSM [HIRDSM ]) and 2 United Kingdom electronic medical record databases (Clinical Practice Research Datalink [CPRD], The Health Improvement Network [THIN]) from 2009 to 2014. To identify potential hospitalizations for infection, we selected patients with a hospital diagnosis of infection and, within 7 days prior to hospitalization, either an outpatient/emergency department visit with an infection diagnosis or outpatient antimicrobial treatment. Hospital records were reviewed by infectious disease specialists to adjudicate hospital admissions for infection. PPVs for confirmed outcomes were determined for each database. RESULTS: Code-based algorithms to identify hospitalization for infection had PPVs exceeding 80% within Medicare (PPV, 83% [90/109]; 95% CI, 74-89%), HIRDSM (PPV, 89% [73/82]; 95% CI, 80-95%), and THIN (PPV, 86% [12/14]; 95% CI, 57-98%) but not within CPRD (PPV, 67% [14/21]; 95% CI, 43-85%). CONCLUSIONS: Algorithms identifying hospitalization for infection utilizing hospital diagnoses along with antecedent outpatient/emergency infection diagnoses or antimicrobial therapy had sufficiently high PPVs for confirmed events within Medicare, HIRDSM , and THIN to enable their use for pharmacoepidemiologic research.
Subject(s)
Communicable Diseases/classification , Communicable Diseases/epidemiology , Hospitalization , Hypoglycemic Agents/administration & dosage , International Classification of Diseases/standards , Administration, Oral , Aged , Aged, 80 and over , Communicable Diseases/drug therapy , Cross-Sectional Studies , Databases, Factual/standards , Databases, Factual/statistics & numerical data , Electronic Health Records/standards , Electronic Health Records/statistics & numerical data , Female , Hospitalization/statistics & numerical data , Humans , Male , Treatment Outcome , United Kingdom/epidemiology , United States/epidemiologyABSTRACT
PURPOSE: The extent to which days' supply data are missing in pharmacoepidemiologic databases and effective methods for estimation is unknown. We determined the percentage of missing days' supply on prescription and patient levels for oral anti-diabetic drugs (OADs) and evaluated three methods for estimating days' supply within the Clinical Practice Research Datalink (CPRD) and The Health Improvement Network (THIN). METHODS: We estimated the percentage of OAD prescriptions and patients with missing days' supply in each database from 2009 to 2013. Within a random sample of prescriptions with known days' supply, we measured the accuracy of three methods to estimate missing days' supply by imputing the following: (1) 28 days' supply, (2) mode number of tablets/day by drug strength and number of tablets/prescription, and (3) number of tablets/day via a machine learning algorithm. We determined incidence rates (IRs) of acute myocardial infarction (AMI) using each method to evaluate the impact on ascertainment of exposure time and outcomes. RESULTS: Days' supply was missing for 24 % of OAD prescriptions in CPRD and 33 % in THIN (affecting 48 and 57 % of patients, respectively). Methods 2 and 3 were very accurate in estimating days' supply for OADs prescribed at a consistent number of tablets/day. Method 3 was more accurate for OADs prescribed at varying number of tablets/day. IRs of AMI were similar across methods for most OADs. CONCLUSIONS: Missing days' supply is a substantial problem in both databases. Method 2 is easy and very accurate for most OADs and results in IRs comparable to those from method 3.
Subject(s)
Databases, Factual/statistics & numerical data , Drug Prescriptions/statistics & numerical data , Hypoglycemic Agents , Pharmacies/statistics & numerical data , Aged , Diabetes Mellitus, Type 2/drug therapy , Diabetes Mellitus, Type 2/epidemiology , Female , Humans , Hypoglycemic Agents/therapeutic use , Machine Learning , Male , Middle Aged , Myocardial Infarction/epidemiology , Tablets , United Kingdom/epidemiologyABSTRACT
PURPOSE: The UK Clinical Practice Research Datalink (CPRD) is increasingly being used by Dutch researchers in epidemiology and pharmacoepidemiology. It is however unclear if the UK CPRD is representative of the Dutch population and whether study results would apply to the Dutch population. Therefore, as first step, our objective was to compare the age and sex distribution of the CPRD with the total Dutch population. METHODS: As a measure of representativeness, the age and sex distribution of the UK CPRD were visually and numerically compared with Dutch census data from the StatLine database of the Dutch National Bureau of Statistics in 2011. RESULTS: The age distribution of men and women in the CPRD population was comparable to the Dutch male and female population. Differences of more than 10% only occurred in older age categories (75+ in men and 80+ in women). CONCLUSIONS: Results from observational studies that have used CPRD data are applicable to the Dutch population, and a useful resource for decision making in the Netherlands. Nevertheless, differences in drug exposure likelihood between countries should be kept in mind, as these could still cause variations in the actual population studied, thereby decreasing its generalizability. Copyright © 2016 John Wiley & Sons, Ltd.
Subject(s)
Databases, Factual/statistics & numerical data , Epidemiologic Methods , Pharmacoepidemiology/methods , Adolescent , Adult , Age Distribution , Aged , Aged, 80 and over , Censuses , Child , Child, Preschool , Data Accuracy , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Netherlands , Sex Distribution , Young AdultABSTRACT
PURPOSE: Pharmacoepidemiology researchers often utilize data from two UK electronic medical record databases, the Clinical Practice Research Datalink (CPRD) and The Health Improvement Network (THIN), and may choose to combine the two in an effort to increase sample size. To minimize duplication of data, previous studies examined the practice-level overlap between these databases. However, the proportion of overlapping patients remains unknown. We developed a method using demographic and pharmacy variables to identify patients included in both CPRD and THIN, and applied this method to measure the proportion of overlapping patients who initiated the oral anti-diabetic drug saxagliptin. METHODS: We conducted a cross-sectional study among patients initiating saxagliptin in CPRD and THIN between October 2009 and September 2012. Within both databases, we identified patients: (i) ≥18 years, (ii) newly prescribed saxagliptin, and (iii) with ≥180 days enrollment prior to saxagliptin initiation. Demographic data (birth year, sex, patient registration date, family number, and marital status) and prescriptions (including dates) for the first two oral anti-diabetic drugs prescribed within the study period were used to identify matching patients. RESULTS: Among 4202 CPRD and 3641 THIN patients initiating saxagliptin, 2574 overlapping patients (61% of CPRD saxagliptin initiators; 71% of THIN saxagliptin initiators) were identified. Among these patients, 2474 patients (96%) perfectly matched on all demographic and prescription data. CONCLUSIONS: Within each database, over 60% of patients initiating saxagliptin were included within both CPRD and THIN. Combined demographic and prescription data can be used to identify patients included in both CPRD and THIN.
Subject(s)
Adamantane/analogs & derivatives , Databases, Factual/statistics & numerical data , Dipeptides/therapeutic use , Electronic Health Records/statistics & numerical data , Pharmacy/statistics & numerical data , Adamantane/therapeutic use , Cohort Studies , Cross-Sectional Studies , Female , Humans , Hypoglycemic Agents/therapeutic use , Male , United Kingdom/epidemiologyABSTRACT
PURPOSE: Large electronic datasets are increasingly being used to evaluate healthcare delivery. The aim of this study was to compare information held by cancer registries with that of the General Practice Research Database (GPRD). METHODS: A convenience sample of 101 020 patients aged 40+ years drawn from GPRD formed the primary data source. This cohort was derived from a larger sample originally established for a cohort study of diabetes. GPRD records were linked with those from cancer registries in the National Cancer Data Repository (NCDR). Concordance between the two datasets was then evaluated. For cases recorded only on one dataset, validation was sought from other datasets (Hospital Episode Statistics and death registration) and by detailed analysis of a subset of GPRD records. RESULTS: A total of 5797 cancers (excluding non-melanomatous skin cancer) were recorded on GPRD. Of these cases, 4830 were also recorded on NCDR (concordance rate of 83.3%). Of the 976 cases recorded on GPRD but not on NCDR, 528 were present also in the hospital records or death certificates. Of the 341 cases recorded on NCDR but not on GPRD, 307 were recorded in these other two datasets. Rates of concordance varied by cancer type. Cancer registries recorded larger numbers of patients with lung, colorectal, and pancreatic cancers, whereas GPRD recorded more haematological cancers and melanomas. As expected, GPRD recorded significantly more non-melanomatous skin cancer. Concordance decreased with increasing age. CONCLUSION: Although concordance levels were reasonably high, the findings from this study can be used to direct efforts for better recording in both datasets.
Subject(s)
Databases, Factual/standards , General Practice/standards , Neoplasms/mortality , Registries/standards , Adult , Aged , Aged, 80 and over , Cohort Studies , Databases, Factual/trends , Female , General Practice/trends , Humans , Male , Middle Aged , Neoplasms/diagnosis , Survival Rate/trendsABSTRACT
The use of thiazolidinediones (TZDs) has been associated with an increased fracture risk. In addition, type 2 diabetes mellitus (T2DM) has been linked with fracture. We evaluated to what extent the association between TZD use and fracture risk is related to the drug or to the underlying disease. We conducted a population-based cohort study using the Danish National Health Registers (1996-2007), which link pharmacy data to the national hospital registry. Oral antidiabetic users (n = 180,049) were matched 1:3 by year of birth and sex to nonusers. Cox proportional hazards models were used to estimate hazard ratios (HRs) of fracture. Time-dependent adjustments were made for age, comorbidity, and drug use. We created a proxy indicator for the severity of disease. The first stage was defined as current use of either a biguanide or a sulfonyluerum, the second stage as current use of a biguanide and a sulfonyluerum at the same time, the third stage as patients using TZDs, and the fourth stage as patients using insulin. The risk of osteoporotic fracture was increased 1.3-fold for stages 3 and 4 compared with controls. Risk with current TZD use (stage 3 HR = 1.27, 95 % CI 1.06-1.52) and risk with current use of insulin (stage 4 HR = 1.25, 95 % CI 1.20-1.31) were similar. In the first (HR = 1.15, 95 % CI 1.13-1.18) and second (HR = 1.00, 95 % CI 0.96-1.04) stages risks were lower. Risk of osteoporotic fracture was similar for TZD users and insulin users. When studying fracture risk with TZDs, the underlying T2DM should be taken into account.
Subject(s)
Fractures, Bone/chemically induced , Thiazolidinediones/adverse effects , Adolescent , Adult , Aged , Aged, 80 and over , Cohort Studies , Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 2/drug therapy , Female , Fractures, Bone/epidemiology , Fractures, Bone/etiology , Humans , Hypoglycemic Agents/adverse effects , Hypoglycemic Agents/therapeutic use , Male , Middle Aged , Proportional Hazards Models , Risk , Thiazolidinediones/therapeutic useABSTRACT
PURPOSE: Clinical and observational studies suggest that use of thiazolidinediones (TZDs) is associated with an increased fracture risk. In addition, type 2 diabetes mellitus (T2DM) is a risk factor for osteoporotic fracture. Our aim was to estimate fracture risks in TZD users and users of other antidiabetic drugs, classified according to proxies of disease severity. METHODS: We conducted a population-based cohort study utilizing the Dutch PHARMO database (1998-2008). PHARMO links pharmacy-dispensing data to the National Hospital Registry. Oral antidiabetic users (n = 123,452) were matched 1:4 by year of birth and sex to non-users. Cox proportional hazards models were used to estimate hazard ratios (HRs) of fracture in TZD users. We created a proxy indicator for disease severity. The first stage was defined as current use of either a biguanide or a sulfonylureum, the second stage as current use of a biguanide and a sulfonylureum at the same time, the third stage was assigned to patients using TZDs and the fourth stage to patients using insulin. RESULTS: The risk of osteoporotic fracture was increased 1.5-fold (HR 1.49, 95%CI 1.28-1.73) in patients who currently used TZDs (stage 3), and for patients using insulin (stage 4), the risk was increased 1.2-fold (HR 1.24, 1.14-1.36), as compared with controls. In the first and second stages, risks were lower: HR 1.11 (1.06-1.17) for stage 1 and HR 1.03 (0.96-1.11) for stage 2. CONCLUSIONS: When observational studies assess risk of fracture in patients with TZDs, the severity of T2DM should be taken into account.
Subject(s)
Diabetes Mellitus, Type 2/drug therapy , Hypoglycemic Agents/adverse effects , Osteoporotic Fractures/epidemiology , Thiazolidinediones/adverse effects , Administration, Oral , Adolescent , Adult , Aged , Aged, 80 and over , Case-Control Studies , Cohort Studies , Databases, Factual , Diabetes Mellitus, Type 2/physiopathology , Female , Follow-Up Studies , Humans , Hypoglycemic Agents/administration & dosage , Hypoglycemic Agents/therapeutic use , Male , Middle Aged , Netherlands , Osteoporotic Fractures/etiology , Proportional Hazards Models , Registries , Risk Factors , Severity of Illness Index , Thiazolidinediones/administration & dosage , Thiazolidinediones/therapeutic use , Young AdultABSTRACT
The objective of this study was to evaluate the rate of stroke associated with aspirin and warfarin in routine clinical practice. The study included patients aged 40+ with chronic atrial fibrillation (cAF) registered in the UK General Practice Research Database. The outcome was the rate of stroke during current, past and no use of aspirin and warfarin. The study included 51,807 cAF patients. There was no difference in the rate of stroke between current and past use of aspirin (relative rate [RR] = 1.04 [95% confidence interval (CI) 0.94 - 1.15]), while the rate of stroke was reduced during current warfarin use compared to past use (RR = 0.62 [95% CI 0.54 - 0.71]). For warfarin, a pattern of lower rates of stroke during current exposure and higher rates with past exposure was seen only in patients treated for at least 6-12 months. For aspirin, no changes in the rates of stroke were observed with discontinuation of aspirin. The effectiveness of warfarin was dependent on the level of anticoagulation, with optimal risk reduction occurring within the recommended international normalised ratio (INR) range of 2.0 to 3.0. The proportion of patients achieving a stable INR within the target therapeutic range was at its lowest during the first three months of warfarin treatment. In conclusion, the results of this study support the effectiveness of warfarin treatment to reduce the rate of stroke in cAF patients in the general clinical practice setting, however the risk reduction is lower than that reported in clinical trials.
Subject(s)
Anticoagulants/therapeutic use , Aspirin/therapeutic use , Atrial Fibrillation/complications , Fibrinolytic Agents/therapeutic use , Stroke/prevention & control , Warfarin/therapeutic use , Adult , Aged , Aged, 80 and over , Anticoagulants/administration & dosage , Aspirin/administration & dosage , Chronic Disease , Drug Therapy, Combination , Female , Fibrinolytic Agents/administration & dosage , Follow-Up Studies , Humans , International Normalized Ratio , Male , Middle Aged , Risk Factors , Stroke/epidemiology , Stroke/etiology , Time Factors , United Kingdom , Warfarin/administration & dosageABSTRACT
BACKGROUND: Quality improvement (QI) is a priority for general practice, and GPs are expected to participate in and provide evidence of QI activity. There is growing interest in harnessing the potential of electronic health records (EHR) to improve patient care by supporting practices to find cases that could benefit from a medicines review. AIM: To develop scalable and reproducible prescribing safety reports using patient-level EHR data. DESIGN AND SETTING: UK general practices that contribute de-identified patient data to the Clinical Practice Research Datalink (CPRD). METHOD: A scoping phase used stakeholder consultations to identify primary care QI needs and potential indicators. QI reports containing real data were sent to 12 pilot practices that used Vision GP software and had expressed interest. The scale-up phase involved automating production and distribution of reports to all contributing practices that used both Vision and EMIS software systems. Benchmarking reports with patient-level case review lists for two prescribing safety indicators were sent to 457 practices in December 2017 following the initial scale-up (Figure 2). RESULTS: Two indicators were selected from the Royal College of General Practitioners Patient Safety Toolkit following stakeholder consultations for the pilot phase involving 12 GP practices. Pilot phase interviews showed that reports were used to review individual patient care, implement wider QI actions in the practice, and for appraisal and revalidation. CONCLUSION: Electronic health record data can be used to provide standardised, reproducible reports that can be delivered at scale with minimal resource requirements. These can be used in a national QI initiative that impacts directly on patient care.
Subject(s)
Drug Utilization Review , Electronic Health Records , Patient Safety , Primary Health Care , Quality Improvement , Anti-Inflammatory Agents, Non-Steroidal/therapeutic use , General Practice , Heart Failure , Humans , Pilot Projects , Risk Assessment , Thiazolidinediones/therapeutic use , United KingdomABSTRACT
AIMS: Statin-related myopathy (SRM), which includes rhabdomyolysis, is an uncommon but important adverse drug reaction because the number of people prescribed statins world-wide is large. Previous association studies of common genetic variants have had limited success in identifying a genetic basis for this adverse drug reaction. We conducted a multi-site whole-exome sequencing study to investigate whether rare coding variants confer an increased risk of SRM. METHODS AND RESULTS: SRM 3-5 cases (N = 505) and statin treatment-tolerant controls (N = 2047) were recruited from multiple sites in North America and Europe. SRM 3-5 was defined as symptoms consistent with muscle injury and an elevated creatine phosphokinase level >4 times upper limit of normal without another likely cause of muscle injury. Whole-exome sequencing and variant calling was coordinated from two analysis centres, and results of single-variant and gene-based burden tests were meta-analysed. No genome-wide significant associations were identified. Given the large number of cases, we had 80% power to identify a variant with minor allele frequency of 0.01 that increases the risk of SRM 6-fold at genome-wide significance. CONCLUSIONS: In this large whole-exome sequencing study of severe statin-related muscle injury conducted to date, we did not find evidence that rare coding variants are responsible for this adverse drug reaction. Larger sample sizes would be required to identify rare variants with small effects, but it is unclear whether such findings would be clinically actionable.
Subject(s)
Hydroxymethylglutaryl-CoA Reductase Inhibitors/adverse effects , Muscle, Skeletal , Rhabdomyolysis , Whole Genome Sequencing , Genome-Wide Association Study , High-Throughput Nucleotide Sequencing , Humans , Hydroxymethylglutaryl-CoA Reductase Inhibitors/therapeutic use , Muscle, Skeletal/metabolism , Muscle, Skeletal/pathology , Rhabdomyolysis/chemically induced , Rhabdomyolysis/genetics , Rhabdomyolysis/metabolism , Rhabdomyolysis/pathologyABSTRACT
OBJECTIVES AND SETTING: Conflicting results from studies using electronic health records to evaluate the associations between type 2 diabetes and cancer fuel concerns regarding potential biases. This study aimed to describe completeness of cancer recording in UK primary care data linked to hospital admissions records. DESIGN: Patients aged 40+ years with insulin or oral antidiabetic prescriptions in Clinical Practice Research Datalink (CPRD) primary care without type 1 diabetes were matched by age, sex and general practitioner practice to non-diabetics. Those eligible for linkage to Hospital Episode Statistics Admitted Patient Care (HES APC), and with follow-up during April 1997-December 2006 were included. PRIMARY AND SECONDARY OUTCOME MEASURES: Cancer recording and date of first record of cancer were compared. Characteristics of patients with cancer most likely to have the diagnosis recorded only in a single data source were assessed. Relative rates of cancer estimated from the two datasets were compared. PARTICIPANTS: 53 585 patients with type 2 diabetes matched to 47 435 patients without diabetes were included. RESULTS: Of all cancers (excluding non-melanoma skin cancer) recorded in CPRD, 83% were recorded in HES APC. 94% of cases in HES APC were recorded in CPRD. Concordance was lower when restricted to same-site cancer records, and was negatively associated with increasing age. Relative rates for cancer were similar in both datasets. CONCLUSIONS: Good concordance in cancer recording was found between CPRD and HES APC among type 2 diabetics and matched controls. Linked data may reduce misclassification and increase case ascertainment when analysis focuses on site-specific cancers.
Subject(s)
Diabetes Mellitus, Type 2/complications , Neoplasms/epidemiology , Patient Admission/statistics & numerical data , Primary Health Care/statistics & numerical data , Adult , Age Distribution , Aged , Aged, 80 and over , Cohort Studies , Databases, Factual , Female , Humans , Logistic Models , Male , Medical Record Linkage , Middle Aged , Multivariate Analysis , Sex Distribution , United Kingdom/epidemiologyABSTRACT
BACKGROUND: There is a concern that topical tacrolimus and pimecrolimus, indicated for second-line treatment of atopic dermatitis, may increase the risk of lymphoma and skin cancer, particularly in children. OBJECTIVE: The aim of this study was to compare incidence rates (IRs) of lymphoma and skin cancer between new users of topical tacrolimus or pimecrolimus and users of moderate- to high-potency topical corticosteroids (TCSs) and untreated subjects. METHODS: This is a multicenter cohort study with frequency matching by strata of propensity scores in population databases in the Netherlands, Denmark, Sweden, and the UK. IR ratios (IRRs) were estimated using Mantel-Haenszel methods for stratified analysis. RESULTS: We included 19,948 children and 66,127 adults initiating tacrolimus, 23,840 children and 37,417 adults initiating pimecrolimus, 584,121 users of TCSs, and 257,074 untreated subjects. IRs of lymphoma per 100,000 person-years were 10.4 events in children and 41.0 events in adults using tacrolimus and 3.0 events in children and 27.0 events in adults using pimecrolimus. The IRR (95% confidence interval [CI]) for lymphoma, tacrolimus versus TCSs, was 3.74 (1.00-14.06) in children and 1.27 (0.94-1.71) in adults. By lymphoma type, the highest IRR was 3.17 (0.58-17.23) for Hodgkin lymphoma in children and 1.76 (95% CI, 0.81-3.79) for cutaneous T-cell lymphoma (CTCL) in adults. For pimecrolimus versus TCSs, the highest IRR was 1.31 (95% CI, 0.33-5.14) for CTCL in adults. Compared with untreated subjects, adults using TCSs had a higher incidence of CTCL (IRR, 10.66; 95% CI, 2.60-43.75). Smaller associations were found between tacrolimus and pimecrolimus use and the risk of malignant melanoma or nonmelanoma skin cancer. CONCLUSION: Use of topical tacrolimus and pimecrolimus was associated with an increased risk of lymphoma. The low IRs imply that even if the increased risk is causal, it represents a small excess risk for individual patients. Residual confounding by severity of atopic dermatitis, increased monitoring of severe patients, and reverse causation could have affected the results.
ABSTRACT
BACKGROUND: Despite the concerns about a potential increased risk of skin cancer and lymphoma with the use of topical tacrolimus and pimecrolimus, no population-based studies have given an overview of the use of these drugs in Europe. OBJECTIVE: To assess the use of topical tacrolimus and pimecrolimus in children and adults in Europe. METHODS: Multicentre database cohort study comprising data from the Netherlands, Denmark, Sweden and the UK. We analysed users of topical tacrolimus and pimecrolimus starting from the date of first availability (between 2002 and 2003) or start establishment of the prescription database in Sweden (2006) through 2011. Use was assessed separately for children (≤ 18 years) and adults. RESULTS: 32,052 children and 104,902 adults were treated with topical tacrolimus, and 32,125 children and 58,280 adults were treated with topical pimecrolimus. The number of users increased rapidly after first availability, especially for topical tacrolimus. Topical tacrolimus was more frequently used in all countries except Denmark. For both drugs, there was a decrease in users after 2004 in the Netherlands and Denmark and after 2005 in the UK, especially among children. This decrease was largest in Denmark. The decrease in the number of users was temporary for topical tacrolimus, while use remained relatively low for topical pimecrolimus. CONCLUSIONS: The number of topical tacrolimus and pimecrolimus users increased rapidly after regulatory approval. A transient reduction in topical tacrolimus use and a persistent reduction in topical pimecrolimus use was seen after 2004 in the Netherlands and Denmark and after 2005 in the UK.
ABSTRACT
OBJECTIVE: To evaluate the risk of serious adverse events among patients with type 2 diabetes mellitus initiating saxagliptin compared with oral antidiabetic drugs (OADs) in classes other than dipeptidyl peptidase-4 (DPP-4) inhibitors. RESEARCH DESIGN AND METHODS: Cohort studies using 2009-2014 data from two UK medical record data sources (Clinical Practice Research Datalink, The Health Improvement Network) and two USA claims-based data sources (HealthCore Integrated Research Database, Medicare). All eligible adult patients newly prescribed saxagliptin (n=110 740) and random samples of up to 10 matched initiators of non-DPP-4 inhibitor OADs within each data source were selected (n=913 384). Outcomes were hospitalized major adverse cardiovascular events (MACE), acute kidney injury (AKI), acute liver failure (ALF), infections, and severe hypersensitivity events, evaluated using diagnostic coding algorithms and medical records. Cox regression was used to determine HRs with 95% CIs for each outcome. Meta-analyses across data sources were performed for each outcome as feasible. RESULTS: There were no increased incidence rates or risk of MACE, AKI, ALF, infection, or severe hypersensitivity reactions among saxagliptin initiators compared with other OAD initiators within any data source. Meta-analyses demonstrated a reduced risk of hospitalization/death from MACE (HR 0.91, 95% CI 0.85 to 0.97) and no increased risk of hospitalization for infection (HR 0.97, 95% CI 0.93 to 1.02) or AKI (HR 0.99, 95% CI 0.88 to 1.11) associated with saxagliptin initiation. ALF and hypersensitivity events were too rare to permit meta-analysis. CONCLUSIONS: Saxagliptin initiation was not associated with increased risk of MACE, infection, AKI, ALF, or severe hypersensitivity reactions in clinical practice settings. TRIAL REGISTRATION NUMBER: NCT01086280, NCT01086293, NCT01086319, NCT01086306, and NCT01377935; Results.
ABSTRACT
Linked electronic healthcare databases are increasingly being used in observational research. The objective of this study was to investigate the impact of the choice of data source in estimating mortality following VTE, with a secondary aim to investigate the influence of the denominator definition. We used the UK Clinical Practice Research Datalink (CPRD) to identify patients aged 18+ with venous thromboembolism (VTE). Multiple cohorts were identified in order to assess how mortality rates differed with a range of data sources. For each of the cohorts, incidence rates per 1,000 person years (/1000py) and relative rates (RRs) of all-cause mortality were calculated. The lowest mortality rate was found when only primary care data were used for both the exposure (VTE) and the outcome (death) (108.4/1000py). The highest mortality rate was found for patients diagnosed in secondary care (237.2/1000py). When linked primary and secondary care data were included for eligible patients and for the overlapping period of data collection, a mortality rate of 173.2/1000py was found. Sensitivity analyses varying the denominator definition provided a range of results (140.6-164.3/1000py). The relative rates of mortality by gender and age were comparable across all cohorts. Depending on the choice of data source, the population studied may be different. This may have substantial impact on the main findings, in particular on incidence rates of mortality following VTE.
Subject(s)
Electronic Health Records/statistics & numerical data , Information Storage and Retrieval , Primary Health Care/statistics & numerical data , Secondary Care/statistics & numerical data , Venous Thromboembolism/mortality , Adolescent , Adult , Aged , Aged, 80 and over , Cohort Studies , Databases, Factual , Female , Humans , Male , Middle Aged , Risk Factors , Survival Analysis , United Kingdom/epidemiology , Venous Thromboembolism/epidemiology , Venous Thromboembolism/pathologyABSTRACT
The Clinical Practice Research Datalink (CPRD) is an ongoing primary care database of anonymised medical records from general practitioners, with coverage of over 11.3 million patients from 674 practices in the UK. With 4.4 million active (alive, currently registered) patients meeting quality criteria, approximately 6.9% of the UK population are included and patients are broadly representative of the UK general population in terms of age, sex and ethnicity. General practitioners are the gatekeepers of primary care and specialist referrals in the UK. The CPRD primary care database is therefore a rich source of health data for research, including data on demographics, symptoms, tests, diagnoses, therapies, health-related behaviours and referrals to secondary care. For over half of patients, linkage with datasets from secondary care, disease-specific cohorts and mortality records enhance the range of data available for research. The CPRD is very widely used internationally for epidemiological research and has been used to produce over 1000 research studies, published in peer-reviewed journals across a broad range of health outcomes. However, researchers must be aware of the complexity of routinely collected electronic health records, including ways to manage variable completeness, misclassification and development of disease definitions for research.
Subject(s)
Databases as Topic , Electronic Health Records , Primary Health Care , Biomedical Research , Data Accuracy , General Practitioners , Humans , United KingdomABSTRACT
BACKGROUND: The patterns and determinants of saxagliptin use among patients with type 2 diabetes mellitus (T2DM) are unknown in real-world settings. We compared the characteristics of T2DM patients who were new initiators of saxagliptin to those who were new initiators of non-dipeptidyl peptidase-4 (DPP-4) inhibitor oral anti-diabetic drugs (OADs) and identified factors associated with saxagliptin use. METHODS: We conducted a cross-sectional study within the Clinical Practice Research Datalink (CPRD), The Health Improvement Network (THIN), US Medicare, and the HealthCore Integrated Research Database (HIRD(SM)) across the first 36 months of saxagliptin availability (29 months for US Medicare). Patients were included if they were: 1) ≥18 years old, 2) newly prescribed saxagliptin or a non-DPP-4 inhibitor OAD, and 3) enrolled in their respective database for 180 days. For each saxagliptin initiator, we randomly selected up to ten non-DPP-4 inhibitor OAD initiators matched on age, sex, and geographic region. Conditional logistic regression was used to identify determinants of saxagliptin use. RESULTS: We identified 64,079 saxagliptin initiators (CPRD: 1,962; THIN: 2,084; US Medicare: 51,976; HIRD(SM): 8,057) and 610,660 non-DPP-4 inhibitor OAD initiators (CPRD: 19,484; THIN: 19,936; US Medicare: 493,432; HIRD(SM): 77,808). Across all four data sources, prior OAD use, hypertension, and hyperlipidemia were associated with saxagliptin use. Saxagliptin initiation was also associated with hemoglobin A1c results >8% within the UK data sources, and a greater number of hemoglobin A1c measurements in the US data sources. CONCLUSIONS: In these UK and US data sources, initiation of saxagliptin was associated with prior poor glycemic control, prior OAD use, and diagnoses of hypertension and hyperlipidemia. TRIAL REGISTRATION: ClinicalTrials.gov identifiers NCT01086280 , NCT01086293 , NCT01086319 , NCT01086306 , and NCT01377935.