Agreement between GPRD smoking data: a survey of general practitioners and a population‐based survey
Abstract
Background Cigarette smoking is a common habit that is associated with many diseases. Smoking is often an important confounding variable in pharmacoepidemiological studies. The General Practice Research Database (GPRD) is widely used in pharmacoepidemiological research. In this study, we compare data recorded in the GPRD with the smoking history obtained from direct query of general practitioners (GPs) and from a population-based survey. Methods We completed a mailed survey of GPs caring for a random sample of 150 patients with inflammatory bowel disease. The survey asked the GP to categorize the patients smoking status on a specified date. These results were then compared to the data recorded in the GPRD. Smoking status of 225,308 randomly selected GPRD patients without inflammatory bowel disease was compared to the results of a population-based household survey. Results Completed surveys with usable data were received from GPs on 136 of the 150 patients (91%). The sensitivity and positive predictive value of the database for current smoking were 78% (95% CI: 52-94) and 70% (95% CI: 46-88) respectively. The sensitivity and positive predictive value of former smoking were 53% (95% CI: 28-77) and 60% (95% CI: 32-84) respectively. Current and former smoking rates in the GPRD were 79% and 29% respectively of expected rates according to the population-based survey. Conclusions Current smoking is more completely recorded in the GPRD than former smoking. These data need to be consi…
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Some researchers looking at the quality of research databases pulled from general practices in the UK have adopted relatively consistent approaches to comparing the distributions of data concerning specific clinical phenomena to information from registries and surveys.
“Some researchers looking at the quality of research databases pulled from general practices in the UK have adopted relatively consistent approaches to comparing the distributions of data concerning specific clinical phenomena to information from registries and surveys.31 98 99 102”
From Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research (2013) · cites this paper as [31]
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BackgroundThe risk of a subsequent cancer diagnosis after herpes zoster infection: primary care database study
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The use of electronic databases in primary care research
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BackgroundA Simple Prediction Rule for All-Cause Mortality in a Cohort Eligible for Bariatric Surgery
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“Smoking status will be considered time-dependent and determined using the most recent Read code records, and the individuals with unknown smoking status will be coded as non-smokers.(61) 62 Blood Eosinophil Count: Blood eosinophil count will be derived from primary care Read codes and will be dichotomised at ≥400 cell…”
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“Little research has been conducted to validate patient characteristics that are considered cardiovascular (CV) risk factors and potential confounders for CV outcomes.(6,7) Moreover, the impact of misclassification of myocardial infarction and stroke on effect measures when using primary care data that cannot be linked…”
Effectiveness of a Health Professional Training Program for Treatment of Tobacco Addiction
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Building reliable evidence from real-world data: methods, cautiousness and recommendations
Corrao, G. (2022) · Epidemiology Biostatistics and Public Health · doi:10.2427/8981 · Cited by 22 · see citing works
“The healthy adherer bias is also evident in studies that reported associations between statin adherence and an increased use of preventive healthcare services, as well as a decreased risk of accidents [96, 97].”
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“CPRD has previously been validated as a tool 373 to study IBD, including smoking exposure.(20,60) Completeness for the recording of smoking status is 374 reported at over 98% in some patient populations.”
MethodTemporal and within practice variability in the health improvement network
Haynes, K., Bilker, W. B., Tenhave, T., Strom, B. L., & Lewis, J. D. (2011) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.2191 · Cited by 21 · see citing works
“We have previously demonstrated evidence of consistency of the data by documenting near identical results of epidemiologic analyses of common disease–disease and drug–disease associations across two different categories of THIN practices, those that had previously participated in EPIC’s version of the General Practice…”
ResultSelf-citationGieling, E. M., van den Ham, H. A., van Onzenoort, H. A. W., Bos, J. M., Kramers, C., de Boer, A., de Vries, F., & Burden, A. M. (2017) · British Journal of Clinical Pharmacology · doi:10.1111/bcp.13265 · Cited by 21 · see citing works
The Association of Smoking and Surgery in Inflammatory Bowel Disease is Modified by Age at Diagnosis
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“Previous studies of smoking in the General Practice Research Database have reported relatively high specificity and negative predictive values (490%) for identifying current, ex, and never smokers.(28) Smoking was defined as (1) never smoker,”
BackgroundSelf-citationPalladino, R., Vamos, E. P., Chang, K., Khunti, K. K., Majeed, A., & Millett, C. J. (2020) · Scientific Reports · doi:10.1038/s41598-020-58033-3 · Cited by 19 · see citing works
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Examples of Automated Databases
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“The CPRD is one of the largest primary care databases in the world with longitudinal medical records, and CPRD patients are considerably representative of the UK population with respect to sex, age, and 19,20 CPRD has an acceptable level of data completeness and validity as concluded in previous validation studies.(21…”
MethodElectronic Health Record Databases
Horton, D. B., Bhullar, H., Carty, L., Cunningham, F. E., Ogdie, A., Sultana, J., & Trifirò, G. (2019) · Pharmacoepidemiology · doi:10.1002/9781119413431.ch13 · Cited by 11 · see citing works
Risk of Colorectal Cancer in Women With a Prior Diagnosis of Gynecologic Malignancy
Srinivasan, R., Yang, Y., Rubin, S. C., Morgan, M. A., & Lewis, J. D. (2007) · Journal of Clinical Gastroenterology · doi:10.1097/01.mcg.0000225587.85953.06 · Cited by 10 · see citing works
Self-citationHerkner, H., & Male, C. (2010) · Springer eBooks · doi:10.1007/978-3-7091-0144-5_9 · Cited by 10 · see citing works
Testing bias in clinical databases: methodological considerations
Velthove, K. J., Leufkens, H. G. M., Souverein, P. C., Schweizer, R. C., & van Solinge, W. W. (2010) · Emerging Themes in Epidemiology · doi:10.1186/1742-7622-7-2 · Cited by 8 · see citing works
Obesity and the use of insulin: a study of patients with type 2 diabetes in the UK
Yurgin, N., Secnik, K., & Lage, M. J. (2008) · Journal of Diabetes and its Complications · doi:10.1016/j.jdiacomp.2006.12.001 · Cited by 8 · see citing works
A Systematic Review of Coding Systems Used in Pharmacoepidemiology and Database Research
Chen, Y., Zivkovic, M., Su, S., Lee, J., Bortnichak, E. A., & Wang, T. (2018) · Methods of Information in Medicine · doi:10.3414/me17-05-0006 · Cited by 7 · see citing works
Cancer Risk Evaluation in Psoriasis: In Search of the Holy Grail?
Paul, C. F., & Gourraud, P. (2009) · Journal of Investigative Dermatology · doi:10.1038/jid.2009.203 · Cited by 7 · see citing works
Mortality risk in atrial fibrillation: the role of aspirin, vitamin K and non-vitamin K antagonists
Gieling, E. M., de Vries, F., Williams, R., van Onzenoort, H. A. W., de Boer, A., ten Cate, V., Kramers, C., & Burden, A. M. (2019) · International Journal of Clinical Pharmacy · doi:10.1007/s11096-019-00916-1 · Cited by 6 · see citing works
MacDonald, T. M., Morant, S. V., & Mozaffari, E. (2007) · Current Medical Research and Opinion · doi:10.1185/030079907x233124 · Cited by 6 · see citing works
Gulluoglu, F. R., Souverein, P. C., van den Ham, H. A., de Boer, A., & Komen, J. J. (2020) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.5181 · Cited by 5 · see citing works
Szatkowski, L. C. (2011) · Nottingham ePrints (University of Nottingham) · Cited by 5 · see citing works
Ustekinumab. Neoplasias y otros aspectos de seguridad
Santos‐Juanes, J., Coto, P., & Galache, C. (2012) · Actas Dermo-Sifiliográficas · doi:10.1016/s0001-7310(12)70007-8 · Cited by 4 · see citing works
“…evalua-ción de las comorbilidades y el mayor riesgo de alguna de éstas de padecer cáncer, como el sedentarismo, la obesidad, los hábitos alcohólicos o tabáquicos que pueden no estar correctamente recogidos, especialmente, cuando los objeti-vos del estudio no son planeados de forma prospectiva 11 .”
Herkner, H., & Male, C. (2016) · Springer eBooks · doi:10.1007/978-3-319-27347-1_9 · Cited by 3 · see citing works
Examples of Existing Automated Databases
chapter:, T. F. I. C. T. W. S. O. T., Toh, S., Andrade, S. E., Raebel, M. A., Boudreau, D. M., Davis, R. L., Haffenreffer, K., Pawloski, P. A., Platt, R. G., Hennessy, S., et al. (2013) · Wiley eBooks · doi:10.1002/9781118344828.ch09 · Cited by 2 · see citing works
Ryan, P. B. (2012) · Springer eBooks · doi:10.1007/978-1-4614-5329-1_21 · Cited by 1 · see citing works
A Predictive Method to Determine Incomplete Electronic Medical Records
Talaei‐Khoei, A., Motiwalla, L., & Kazemi, S.-F. (2018) · ACM SIGCPR Conference on Computer Personnel Research (SIGCPR) · doi:10.1145/3209626.3209706 · Cited by 1 · see citing works
“However, this has been often considered to be practically challenging as such benchmarks may not be available [25].”
BackgroundA study on the epidemiology of rosacea
Spoendlin, J. (2013) · edoc (University of Basel) · doi:10.5451/unibas-006190049 · Cited by 1 · see citing works
Petherick, E. (2010) · White Rose eTheses Online (University of Leeds, The University of Sheffield, University of York) · Cited by 1 · see citing works
Complications of hip and knee replacement surgery: a pharmaco-epidemiological approach
Lalmohamed, A. (2014) · Research Publications (Maastricht University)
Current awareness: Pharmacoepidemiology and drug safety
(2004) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.922
- Authors
- Lewis, J. D., & Brensinger, C.
- Affiliations
- University of Pennsylvania (US)
- Corresponding author
- Lewis, James D.
- ORCID
- Lewis, James D.
- Venue
- Pharmacoepidemiology and Drug Safety
- Publisher
- Wiley
- Published
- 2003-11-26
- Volume
- 13
- Issue
- 7
- Pages
- 437-441
- ISSN
- 1053-8569 (ISSN-L)
- 1099-1557
- OpenAlex
- W2006465967
- Cited by
- 80
- References
- 15
- Citations by year
- 2022: 1 · 2020: 4 · 2019: 4 · 2018: 6 · 2017: 2 · 2016: 6 · 2015: 1 · 2014: 4 · 2013: 8 · 2012: 7
- FWCI
- 1.91
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Pharmacoepidemiology and Drug Safety (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5k08dk002589-05)
- National Institute of Diabetes and Digestive and Kidney Diseases (K08 DK 02589)
- Topics
- Health Sciences › Medicine › Physiology › Smoking Behavior and Cessation
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Social Sciences › Sociology and Political Science › Survey Methodology and Nonresponse
- Keywords
- smoking status, Clinical Practice Research Datalink, data validation, general practitioners, current smoking, inflammatory bowel disease, pharmacoepidemiology, confounding variables, sensitivity and positive predictive value
- MeSH terms
- Adolescent, Adult, Family Practice, Female, United Kingdom, Humans, Male, Middle Aged, Population Surveillance, Surveys and Questionnaires, Smoking, Reproducibility of Results, Inflammatory Bowel Diseases, Databases, Factual, Pharmacoepidemiology
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