The risk of oesophago-gastric cancer in symptomatic patients in primary care: a large case-control study using electronic records.
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ABSTRACT:
SUBMITTER: Stapley S
PROVIDER: S-EPMC3553533 | biostudies-other | 2013 Jan
REPOSITORIES: biostudies-other
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Project description:Over 8000 new pancreatic cancers are diagnosed annually in the UK; most at an advanced stage, with only 3% 5-year survival. We aimed to identify and quantify the risk of pancreatic cancer for features in primary care.A case-control study using electronic primary care records identified and quantified the features of pancreatic cancer. Cases, aged ≥40 in the General Practice Research Database, UK, with primary pancreatic cancer were matched with controls on age, sex and practice. Putative features of pancreatic cancer were identified in the year before diagnosis. Odds ratios (OR) were calculated for features of cancer using conditional logistic regression. Positive predictive values (PPV) were calculated for consulting patients.In all, 3635 cases and 16,459 controls were studied. Nine features were associated with pancreatic cancer (all P<0.001 except for back pain, P=0.004); jaundice, OR 1000 (95% confidence interval (CI) 4,302,500); abdominal pain, 5 (4.4, 5.6); nausea/vomiting, 4.5 (3.5, 5.7); back pain, 1.4 (1.1, 1.7); constipation, 2.2 (1.7, 2.8); diarrhoea, 1.9 (1.5, 2.5); weight loss, 15 (11, 22); malaise, 2.4 (1.6, 3.5); new-onset diabetes 2.1 (1.7, 2.5). Positive predictive values for patients aged ≥60 were <1%, apart from jaundice at 22% (95% CI 14, 52), though several pairs of symptoms had PPVs >1%.Most previously reported symptoms of pancreatic cancer were also relevant in primary care. Although predictive values were small - apart from jaundice - they provide a basis for selection of patients for investigation, especially with multiple symptoms.
| S-EPMC3388562 | biostudies-other
Project description:BackgroundCancers of the nasopharynx, nasal cavity, and accessory sinuses ("sinonasal") are rare in England, with around 750 patients diagnosed annually. There are no specific National Institute for Health and Care Excellence (NICE) referral guidelines for these cancers and no primary care research published.ObjectiveTo identify and quantify clinical features of sinonasal cancer in UK primary care patients.MethodsThis matched case-control study used UK Clinical Practice Research Datalink (CPRD) data. Patients were aged ≥40 years with a diagnosis of sinonasal cancer between January 1, 2000 and December 31, 2009 and had consulted their GP in the year before diagnosis. Clinical features of sinonasal cancer were analysed using conditional logistic regression. Positive predictive values (PPVs) for single and combined features were calculated.ResultsIn total, 155 cases and 697 controls were studied. Nine symptoms and one abnormal investigation were significantly associated with the cancer: nasal mass; odds ratio, 95 (95% confidence interval 7.0, 1315, P = 0.001); head and neck lumps, 68 (12, 387, P < 0.001); epistaxis, 17 (3.9, 70, P < 0.001); rhinorrhoea, 14 (4.6, 44, P < 0.001); visual disturbance, 12 (2.2, 67, P = 0.004); sinusitis, 7.3 (2.2, 25, P = 0.001); sore throat, 6.0 (2.0, 18, P = 0.001); otalgia, 5.4 (1.6, 18, P = 0.007); headache, 3.6 (1.4, 9.5, P = 0.01); raised white cell count, 8.5 (2.8, 27, P < 0.001). Combined PPVs for epistaxis/rhinorrhoea, epistaxis/sinusitis, and rhinorrhoea/sinusitis were 0.62%.ConclusionThis is the first primary care study identifying epistaxis, sinusitis, and rhinorrhoea as part of the clinical prodrome of sinonasal cancer. Although no PPVs meet the 3% NICE referral threshold, these results may help clinicians identify who warrants safety-netting and possible specialist referral, potentially reducing the number of advanced-stage diagnoses of sinonasal cancer.
| S-EPMC9155150 | biostudies-literature
Project description:Although anaemia is recognised as a feature of colorectal cancer, the precise risk is unknown. We performed a case-control study using electronic primary care records from the Health Improvement Network database, UK. A total of 6442 patients had a diagnosis of colorectal cancer, and were matched to 45 066 controls on age, sex, and practice. We calculated likelihood ratios and positive predictive values for colorectal cancer in both sexes across 1 g dl(-1) haemoglobin and 10-year age bands, and examined the features of iron deficiency. In men, 178 (5.2%) of 3421 cases and 47 (0.2%) of 23,928 controls had a haemoglobin <9.0 g dl(-1), giving a likelihood ratio (95% confidence interval) of 27 (19, 36). In women, the corresponding figures were 227 (7.5%) of 3021 cases and 58 (0.3%) of 21,138 controls, a likelihood ratio of 41 (30, 61). Positive predictive values increased with age and for each 1 g dl(-1) reduction in haemoglobin. The risk of cancer for current referral guidance was quantified. For men over 60 years with a haemoglobin <11 g dl(-1) and features of iron deficiency, the positive predictive value was 13.3% (9.7, 18) and for women with a haemoglobin <10 g dl(-1) and iron deficiency, the positive predictive value was 7.7% (5.7, 11). Current guidance for urgent investigation of anaemia misses some patients with a moderate risk of cancer, particularly men.
| S-EPMC2361444 | biostudies-other
Project description:BackgroundAnkylosing spondylitis (AS) often has a long period from first symptom presentation to diagnosis. We examined the occurrence of symptoms, prescriptions and diagnostic tests in primary care electronic records over time prior to a diagnosis of AS.MethodsNested case-control study using anonymised primary care electronic health records from Scotland. Cases were 74 adults with a first diagnosis of AS between 2000 and 2010. Controls were matched for age, sex and GP practice: (a) 296 randomly selected adults (b) 169 adults whose records contained codes indicating spinal conditions or symptoms. We extracted clinical features (symptoms, AS-related disorders, prescriptions and diagnostic tests). Conditional logistic regression was used to examine the association between clinical features (both individually and in combinations) and diagnosis of AS. We examined the associations between clinical features and diagnosis over time prior to diagnosis.ResultsSeveral new composite pointers were predictive of AS: including distinct episodes of axial pain separated by more than 6 months (OR 12.7, 95% CI 4.7 to 34.6); the occurrence of axial pain with and tendon symptoms within the same year (OR 21.7, 95% CI 2.6 to 181.5); and the co-occurrence (within 30 days) of axial pain and a prescription for nonsteroidal anti-inflammatory drug (OR 10.4, 95%CI 4.9 to 22.1). Coded episodes of axial pain increased steadily over the 3 years before diagnosis. In contrast, large joint symptoms and enthesopathy showed little or no time trend prior to diagnosis.ConclusionsWe identified novel composite pointers to a diagnosis of AS in GP records. These may represent valuable targets for diagnostic support systems.
| S-EPMC7201706 | biostudies-literature
Project description:Although asthma is one of the most common chronic conditions affecting Canadians, its epidemiologic characteristics and burden in primary care contexts are poorly understood. The aim of this study was to develop and validate a case definition to identify adults with asthma who consult family physicians and to estimate the prevalence of asthma in that setting in Canada. This validation study utilized a database of electronic medical records (EMRs) from the Southern Alberta Primary Care Research Network, a node of the Canadian Primary Care Sentinel Surveillance Network (SAPCReN-CPCSSN). The population included patients over age 17y of any gender and health status who had visited an SAPCReN-CPCSSN primary care provider during the period December 1, 2014-December 31, 2016. The validation of the case definition involved comparing a case-finding algorithm to caseness determined by an expert physician review of the records of 1000 patient in the CPCSSN database. The case definition, which included the ICD-9 code 493 and asthma-related text words, had 83.33% sensitivity (95% CI: 63.61-93.88%), 99.28% specificity (95% CI: 98.51-99.67%), a positive predictive value of 74.07% (95% CI: 55.03-87.14%), and a negative predictive value of 99.59% (95% CI: 98.93-99.86%). The prevalence of adult asthma in CPCSSN primary care practices in southern Alberta was 4.20% (95% CI: 4.09-4.31). The strong validation metrics suggest that this case definition is valid for both clinical and research purposes. The validated case definition may be used to improve patient care and improve understanding of the prevalence and burden of asthma in primary care in Canada.
| S-EPMC7275082 | biostudies-literature
Project description:BackgroundDigital health has been a tool of transformation for the delivery of health care services globally. An electronic health record (EHR) system can solve the bottleneck of paper documentation in health service delivery if it is successfully implemented, but poor implementation can lead to a waste of resources. The study of EHR system implementation in low- and middle-income countries (LMICs) is of particular interest to health stakeholders such as policy makers, funders, and care providers because of the efficiencies and evidence base that could result from the appropriate evaluation of such systems.ObjectiveWe aimed to develop a theory of change (ToC) for the implementation of EHRs for maternal and child health care delivery in LMICs. The ToC is an outcomes-based approach that starts with the long-term goals and works backward to the inputs and mediating components required to achieve these goals for complex programs.MethodsWe used the ToC approach for the whole implementation's life cycle to guide the pilot study and identify the preconditions needed to realize the study's long-term goal at Festac Primary Health Centre in Lagos, Nigeria. To evaluate the maturity of the implementation, we adapted previously defined success factors to supplement the ToC approach.ResultsThe initial ToC map showed that the long-term goal was an improved service delivery in primary care with the introduction of EHRs. The revised ToC revealed that the long-term change was the improved maternal and child health care delivery at Festac Primary Health Center using EHRs. We proposed a generic ToC map that implementers in LMICs can use to introduce an optimized EHR system, with assumptions about sustainability and other relevant factors. The outcomes from the critical success factors were sustainability: the sustained improvements included trained health care professionals, a change in mindset from using paper systems toward digital health transformation, and using the project's laptops to collect aggregate data for the District Health Information System 2-based national health information management system; financial: we secured funding to procure IT equipment, including servers, laptops, and networking, but the initial cost of implementation was high, and funds mainly came from the funding partner; and organizational: the health professionals, especially the head of nursing and health information officers, showed significant commitment to adopting the EHR system, but certain physicians and midwives were unwilling to use the EHR system initially until they were persuaded or incentivized by the management.ConclusionsThis study shows that the ToC is a rewarding approach to framing dialogue with stakeholders and serves as a framework for planning, evaluation, learning, and reflection. We hypothesized that any future health IT implementation in primary care could adapt our ToC approach to their contexts with necessary modifications based on inherent characteristics.
| S-EPMC9412900 | biostudies-literature
Project description:ObjectivesUK statistics suggest only two-thirds of patients with dementia get a diagnosis recorded in primary care. General practitioners (GPs) report barriers to formally diagnosing dementia, so some patients may be known by GPs to have dementia but may be missing a diagnosis in their patient record. We aimed to produce a method to identify these 'known but unlabelled' patients with dementia using data from primary care patient records.DesignRetrospective case-control study using routinely collected primary care patient records from Clinical Practice Research Datalink.SettingUK general practice.ParticipantsEnglish patients aged >65 years, with a coded diagnosis of dementia recorded in 2000-2012 (cases), matched 1:1 with patients with no diagnosis code for dementia (controls).InterventionsEight coded and nine keyword concepts indicating symptoms, screening tests, referrals and care for dementia recorded in the 5 years before diagnosis. We trialled machine learning classifiers to discriminate between cases and controls (logistic regression, naïve Bayes, random forest).Primary and secondary outcomesThe outcome variable was dementia diagnosis code; the accuracy of classifiers was assessed using area under the receiver operating characteristic curve (AUC); the order of features contributing to discrimination was examined.Results93 426 patients were included; the median age was 83 years (64.8% women). Three classifiers achieved high discrimination and performed very similarly. AUCs were 0.87-0.90 with coded variables, rising to 0.90-0.94 with keywords added. Feature prioritisation was different for each classifier; commonly prioritised features were Alzheimer's prescription, dementia annual review, memory loss and dementia keywords.ConclusionsIt is possible to detect patients with dementia who are known to GPs but unlabelled with a diagnostic code, with a high degree of accuracy in electronic primary care record data. Using keywords from clinic notes and letters improves accuracy compared with coded data alone. This approach could improve identification of dementia cases for record-keeping, service planning and delivery of good quality care.
| S-EPMC7831719 | biostudies-literature
Project description:BackgroundTo date, there has been no validated method to identify cases of pelvic floor disorders in primary care electronic medical record (EMR) data. We aimed to develop and validate symptom-based case definitions for urinary incontinence, fecal incontinence and pelvic organ prolapse in women, for use in primary care epidemiologic or clinical research.MethodsOur retrospective study used EMR data from the Southern Alberta Primary Care Research Network (SAPCReN) and the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) in southern Alberta. Trained researchers remotely reviewed a random sample of EMR charts of women aged 18 years or older from 6 rural and urban clinics to validate case definitions for urinary incontinence, fecal incontinence and pelvic organ prolapse. We calculated sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), and estimated SAPCReN prevalence as appropriate.ResultsCharts of 900 women were included. Sensitivity was 81.9% (95% confidence interval [CI] 75.1-87.2) for urinary incontinence, 61.2% (95% CI 46.2-74.5) for fecal incontinence, and 51.8% (95% CI 40.6-62.8) for pelvic organ prolapse. Corresponding specificity values were 71.9% (95% CI 68.4-75.1), 99.2% (95% CI 98.2-99.6) and 98.8% (95% CI 97.7-99.4), PPVs 40.6% (95% CI 35.4-46.0), 81.1% (95% CI 64.3-91.4) and 81.1% (95% CI 67.6-90.1), and NPVs 94.4% (95% CI 92.1-96.1), 97.8% (95% CI 96.5-98.6) and 95.3% (95% CI 93.6-96.6). The SAPCReN-observed prevalence for urinary incontinence was 29.7% (95% CI 29.3-30.0), but the adjusted prevalence was 2.97%.InterpretationThe case definition for urinary incontinence met our standard for validity (sensitivity and specificity > 70%), and the case definitions for fecal incontinence and pelvic organ prolapse had PPVs greater than 80%. The urinary incontinence definition may be used in epidemiologic research, and those for fecal incontinence and pelvic organ prolapse may be used in quality-improvement studies or creation of disease registries. Our symptom-based case definitions could also be adapted for research in other EMR settings.
| S-EPMC7269601 | biostudies-literature
Project description:This paper reviews the background to five primary care case-control studies, collectively known as the CAPER studies (Cancer Prediction in Exeter). These studies, on colorectal, lung, prostate and brain tumours, sought to identify the particular features of cancer as reported to primary care. They also sought to quantify the risk of cancer for symptoms and primary care investigations, both individually and paired together.Two studies were on colorectal cancer: the former with 349 cases used hand searching and coding of entries, while the latter obtained 6442 cases from a national electronic database. The lung and prostate studies had 247 and 217 cases, respectively, and used manual methods. The brain study also used a national electronic database, which provided 3505 cases.Generally, the symptoms matched previous series from secondary care, though the risks of cancer, expressed as positive predictive values, were lower. Rectal bleeding in colorectal cancer, and haemoptysis in lung cancer both had positive predictive values of 2.4%. The risk of a brain tumour with headache was one in a thousand.The results identify areas where current guidance on urgent referral for investigation of suspected cancer could be improved.
| S-EPMC2790706 | biostudies-other
Project description:BackgroundPrevention of diabetes and coronary heart disease (CHD) is possible but identification of at-risk patients for targeting interventions is a challenge in primary care.MethodsWe analyzed electronic health record (EHR) data for 122,715 patients from 12 primary care practices. We defined patients with risk factor clustering using metabolic syndrome (MetS) characteristics defined by NCEP-ATPIII criteria; if missing, we used surrogate characteristics, and validated this approach by directly measuring risk factors in a subset of 154 patients. For subjects with at least 3 of 5 MetS criteria measured at baseline (2003-2004), we defined 3 categories: No MetS (0 criteria); At-risk-for MetS (1-2 criteria); and MetS (>or= 3 criteria). We examined new diabetes and CHD incidence, and resource utilization over the subsequent 3-year period (2005-2007) using age-sex-adjusted regression models to compare outcomes by MetS category.ResultsAfter excluding patients with diabetes/CHD at baseline, 78,293 patients were eligible for analysis. EHR-defined MetS had 73% sensitivity and 91% specificity for directly measured MetS. Diabetes incidence was 1.4% in No MetS; 4.0% in At-risk-for MetS; and 11.0% in MetS (p < 0.0001 for trend; adjusted OR MetS vs No MetS = 6.86 [6.06-7.76]); CHD incidence was 3.2%, 5.3%, and 6.4% respectively (p < 0.0001 for trend; adjusted OR = 1.42 [1.25-1.62]). Costs and resource utilization increased across categories (p < 0.0001 for trends). Results were similar analyzing individuals with all five criteria not missing, or defining MetS as >or= 2 criteria present.ConclusionRisk factor clustering in EHR data identifies primary care patients at increased risk for new diabetes, CHD and higher resource utilization.
| S-EPMC2753330 | biostudies-literature