ArticleThe British journal of general practice : the journal of the Royal College of General Practitioners2011
Identifying patients with suspected gastro-oesophageal cancer in primary care: derivation and validation of an algorithm.
Article in The British journal of general practice : the journal of the Royal College of General Practitioners, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 7 of them syntheses that pooled it.
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Who cites it
29 citing papers in PubMed, 7 syntheses or guidelines pooled it, 52 citations in OpenAlex.
- Diagnostic Risk Prediction Models for Upper Gastrointestinal Cancers: A Systematic Review.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025Pooled it
- Cancer diagnostic tools to aid decision-making in primary care: mixed-methods systematic reviews and cost-effectiveness analysis.Health technology assessment (Winchester, England) · 2020Pooled it
- Guideline on screening for esophageal adenocarcinoma in patients with chronic gastroesophageal reflux disease.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2020Guideline
- Weight loss as a predictor of cancer in primary care: a systematic review and meta-analysis.The British journal of general practice : the journal of the Royal College of General Practitioners · 2018Pooled it
- Guideline
- Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2017Pooled it
- Diagnostic value of symptoms of oesophagogastric cancers in primary care: a systematic review and meta-analysis.The British journal of general practice : the journal of the Royal College of General Practitioners · 2015Pooled it
- Electronic clinical decision support tool for assessing stomach symptoms in primary care (ECASS): a feasibility study.BMJ open · 2021Trial
- Evaluating a computer aid for assessing stomach symptoms (ECASS): study protocol for a randomised controlled trial.Trials · 2016Trial
- Mortality from upper gastrointestinal tumors in colorectal cancer screening patients.Endoscopy international open · 2024Article
- Underlying cancer risk among patients with fatigue and other vague symptoms: a population-based cohort study in primary care.The British journal of general practice : the journal of the Royal College of General Practitioners · 2023Article
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- Availability and use of cancer decision-support tools: a cross-sectional survey of UK primary care.The British journal of general practice : the journal of the Royal College of General Practitioners · 2019Article
- Symptom Signatures and Diagnostic Timeliness in Cancer Patients: A Review of Current Evidence.Neoplasia (New York, N.Y.) · 2018Review
- Prediction of Incident Hypertension Within the Next Year: Prospective Study Using Statewide Electronic Health Records and Machine Learning.Journal of medical Internet research · 2018Article
- Improving early diagnosis of symptomatic cancer.Nature reviews. Clinical oncology · 2016Review
- Article
- The role of primary care physicians in early diagnosis and treatment of chronic gastrointestinal diseases.International journal of general medicine · 2014Review
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGastro-oesphageal is one of the most common cancers worldwide. Evidence suggested that increased awareness of symptoms and earlier diagnosis could help improve treatment options and improve survival.
aimTo derive and validate an algorithm to estimate the absolute risk of having gastro-oesophageal cancer in patients in primary care with and without symptoms. DESIGN AND
settingCohort study of 375 UK QResearch® general practices for development, and 189 for validation.
methodIncluded patients were aged 30-84 years, free at baseline of a diagnosis of gastro-oesophageal cancer, and without dysphagia, haematemesis, abdominal pain, appetite loss, or weight loss recorded in previous 12 months. The primary outcome was incident diagnosis of gastro-oesophageal cancer recorded in the next 2 years. Risk factors examined were age, body mass index, alcohol status, smoking status, deprivation, family history of gastrointestinal cancer, dysphagia, previous diagnosis of cancer apart from gastro-oesophageal cancer, haematemesis, abdominal pain, appetite loss, weight loss, tiredness, and anaemia. Cox proportional hazards models were used to develop risk equations. Measures of calibration and discrimination assessed performance in the validation cohort.
resultsThere were 2527 incident cases of gastro-oesophageal cancer from 4.1 million person-years in the derivation cohort. Independent predictors were age, smoking, dysphagia, haematemesis, abdominal pain, appetite loss, weight loss, and anaemia. On validation, the algorithms explained 71% of the variation in females and 73% in males. The receiver operating curve statistics were 0.89 (females) and 0.92 (males). The D statistic was 3.2 (females) and 3.3 (males). The 10% of patients with the highest predicted risks included 77% of all gastro-oesophageal cancers diagnosed over the next 2 years.
conclusionThe algorithm has good performance and could potentially be used to help identify those at highest risk of gastro-oesophageal cancer, to facilitate early referral and investigation.
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