@article{hippisley-cox_symptoms_2013-1,
	title = {Symptoms and risk factors to identify men with suspected cancer in primary care: derivation and validation of an algorithm},
	volume = {63},
	issn = {1478-5242},
	shorttitle = {Symptoms and risk factors to identify men with suspected cancer in primary care},
	doi = {10.3399/bjgp13X660724},
	abstract = {BACKGROUND: Early diagnosis of cancer could improve survival so better tools are needed.
AIM: To derive an algorithm to estimate absolute risks of different types of cancer in men incorporating multiple symptoms and risk factors.
DESIGN AND SETTING: Cohort study using data from 452 UK QResearch® general practices for development and 224 for validation.
METHOD: Included patients were males aged 25-89 years. The primary outcome was incident diagnosis of cancer over the next 2 years (lung, colorectal, gastro-oesophageal, pancreatic, renal, blood, prostate, testicular, other cancer). Factors examined were: 'red flag' symptoms such as weight loss, abdominal distension, abdominal pain, indigestion, dysphagia, abnormal bleeding, lumps; general symptoms such as tiredness, constipation; and risk factors including age, family history, smoking, alcohol intake, deprivation score and medical conditions. Multinomial logistic regression was used to develop a risk equation to predict cancer type. Performance was tested on a separate validation cohort.
RESULTS: There were 22 521 cancers from 1 263 071 males in the derivation cohort. The final model included risk factors (age, BMI, chronic pancreatitis, COPD, diabetes, family history, alcohol, smoking, deprivation); 22 symptoms, anaemia and venous thrombo-embolism. The model was well calibrated with good discrimination. The receiver operator curve statistics values were: lung (0.92), colorectal (0.92), gastro-oesophageal (0.93), pancreas (0.89), renal (0.94), prostate (0.90) blood (0.83, testis (0.82); other cancers (0.86). The 10\% of males with the highest risks contained 59\% of all cancers diagnosed over 2 years.
CONCLUSION: The algorithm has good discrimination and could be used to identify those at highest risk of cancer to facilitate more timely referral and investigation.},
	language = {eng},
	number = {606},
	journal = {The British Journal of General Practice: The Journal of the Royal College of General Practitioners},
	author = {Hippisley-Cox, Julia and Coupland, Carol},
	month = jan,
	year = {2013},
	pmid = {23336443},
	pmcid = {PMC3529287},
	keywords = {Adult, Aged, Aged, 80 and over, Algorithms, Cohort Studies, Comorbidity, Cost-Benefit Analysis, Early Detection of Cancer, England, General Practice, Humans, Male, Middle Aged, Neoplasms, Predictive Value of Tests, Primary Health Care, Prognosis, Prospective Studies, Risk Factors, Wales},
	pages = {e1--10}
}

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AIM: To derive an algorithm to estimate absolute risks of different types of cancer in men incorporating multiple symptoms and risk factors. DESIGN AND SETTING: Cohort study using data from 452 UK QResearch® general practices for development and 224 for validation. METHOD: Included patients were males aged 25-89 years. The primary outcome was incident diagnosis of cancer over the next 2 years (lung, colorectal, gastro-oesophageal, pancreatic, renal, blood, prostate, testicular, other cancer). Factors examined were: 'red flag' symptoms such as weight loss, abdominal distension, abdominal pain, indigestion, dysphagia, abnormal bleeding, lumps; general symptoms such as tiredness, constipation; and risk factors including age, family history, smoking, alcohol intake, deprivation score and medical conditions. Multinomial logistic regression was used to develop a risk equation to predict cancer type. Performance was tested on a separate validation cohort. RESULTS: There were 22 521 cancers from 1 263 071 males in the derivation cohort. The final model included risk factors (age, BMI, chronic pancreatitis, COPD, diabetes, family history, alcohol, smoking, deprivation); 22 symptoms, anaemia and venous thrombo-embolism. The model was well calibrated with good discrimination. The receiver operator curve statistics values were: lung (0.92), colorectal (0.92), gastro-oesophageal (0.93), pancreas (0.89), renal (0.94), prostate (0.90) blood (0.83, testis (0.82); other cancers (0.86). The 10% of males with the highest risks contained 59% of all cancers diagnosed over 2 years. CONCLUSION: The algorithm has good discrimination and could be used to identify those at highest risk of cancer to facilitate more timely referral and investigation.","language":"eng","number":"606","journal":"The British Journal of General Practice: The Journal of the Royal College of General Practitioners","author":[{"propositions":[],"lastnames":["Hippisley-Cox"],"firstnames":["Julia"],"suffixes":[]},{"propositions":[],"lastnames":["Coupland"],"firstnames":["Carol"],"suffixes":[]}],"month":"January","year":"2013","pmid":"23336443","pmcid":"PMC3529287","keywords":"Adult, Aged, Aged, 80 and over, Algorithms, Cohort Studies, Comorbidity, Cost-Benefit Analysis, Early Detection of Cancer, England, General Practice, Humans, Male, Middle Aged, Neoplasms, Predictive Value of Tests, Primary Health Care, Prognosis, Prospective Studies, Risk Factors, Wales","pages":"e1--10","bibtex":"@article{hippisley-cox_symptoms_2013-1,\n\ttitle = {Symptoms and risk factors to identify men with suspected cancer in primary care: derivation and validation of an algorithm},\n\tvolume = {63},\n\tissn = {1478-5242},\n\tshorttitle = {Symptoms and risk factors to identify men with suspected cancer in primary care},\n\tdoi = {10.3399/bjgp13X660724},\n\tabstract = {BACKGROUND: Early diagnosis of cancer could improve survival so better tools are needed.\nAIM: To derive an algorithm to estimate absolute risks of different types of cancer in men incorporating multiple symptoms and risk factors.\nDESIGN AND SETTING: Cohort study using data from 452 UK QResearch® general practices for development and 224 for validation.\nMETHOD: Included patients were males aged 25-89 years. The primary outcome was incident diagnosis of cancer over the next 2 years (lung, colorectal, gastro-oesophageal, pancreatic, renal, blood, prostate, testicular, other cancer). Factors examined were: 'red flag' symptoms such as weight loss, abdominal distension, abdominal pain, indigestion, dysphagia, abnormal bleeding, lumps; general symptoms such as tiredness, constipation; and risk factors including age, family history, smoking, alcohol intake, deprivation score and medical conditions. Multinomial logistic regression was used to develop a risk equation to predict cancer type. Performance was tested on a separate validation cohort.\nRESULTS: There were 22 521 cancers from 1 263 071 males in the derivation cohort. The final model included risk factors (age, BMI, chronic pancreatitis, COPD, diabetes, family history, alcohol, smoking, deprivation); 22 symptoms, anaemia and venous thrombo-embolism. The model was well calibrated with good discrimination. The receiver operator curve statistics values were: lung (0.92), colorectal (0.92), gastro-oesophageal (0.93), pancreas (0.89), renal (0.94), prostate (0.90) blood (0.83, testis (0.82); other cancers (0.86). 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