Symptoms and risk factors to identify men with suspected cancer in primary care: derivation and validation of an algorithm

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.     

Identifying patients with suspected lung cancer in primary care: derivation and validation of an algorithm

BackgroundLung cancer has one of the lowest survival outcomes of any cancer because more then two-thirds of patients are diagnosed when curative treatment is not possible. The challenge is to help earlier diagnosis of lung cancer and hence improve prognosis.AimTo derive and validate an algorithm incorporating information on symptoms, to estimate the absolute risk of having lung cancerMethodSelected patients were aged 30-84 years and free of lung cancer at baseline and haemoptysis, loss of appetite, orweight loss in previous 12 months. Primary outcome was incident diagnosis of lung cancer recorded in the next 2 years. Risk factors examined were: haemoptysis, appetite loss, weight loss, cough, dyspnoea, tiredness, hoarseness, smoking, body mass index, deprivation score, family history of lung cancer, other cancers, asthma, chronic obstructive airways disease, pneumonia, asbestos exposure, and anaemia. Cox proportional hazards models with age as the underlying time variable were used to develop separate risk equations in males and females. Measures of calibration and discrimination assessed performance in the validation cohort.ResultsThere were 3785 incident cases of lung cancer arising from 4 289 282 person-years in the derivation cohort. Independent predictors were haemoptysis, appetite loss, weight loss, cough, body mass index, deprivation score, smoking status, chronic obstructive airways disease, anaemia, and prior cancer (females only). On validation, the algorithms explained 72% of the variation. The receiver operating characteristic (ROC) statistics were 0.92 for both females and males. The D statistic was 3.25 for females and 3.29 for males. The 10% of patients with the highest predicted risks included 77% of all lung cancers diagnosed over the subsequent 2 years.ConclusionThe algorithm has good discrimination and calibration and could potentially be used to identify those at highest risk of lung cancer, to facilitate early referral and investigation.     

Identifying patients with suspected colorectal cancer in primary care: derivation and validation of an algorithm

Background

Earlier diagnosis of colorectal cancer could help improve survival so better tools are needed to help this.

Aim

To derive and validate an algorithm to quantify the absolute risk of colorectal cancer in patients in primary care with and without symptoms.

Design and setting

Cohort study using data from 375 UK QResearch® general practices for development and 189 for validation.

Method

Included patients were aged 30–84 years, free at baseline from a diagnosis of colorectal cancer and without rectal bleeding, abdominal pain, appetite loss, or weight loss in the previous 12 months. The primary outcome was incident diagnosis of colorectal cancer recorded in the next 2 years. Risk factors examined were age, body mass index, smoking status, alcohol status, deprivation, diabetes, inflammatory bowel disease, family history of gastrointestinal cancer, gastrointestinal polyp, history of another cancer, rectal bleeding, abdominal pain, abdominal distension, appetite loss, weight loss, diarrhoea, constipation, change of bowel habit, tiredness, and anaemia. Cox proportional hazards models were used to develop separate risk equations in males and females. Measures of calibration and discrimination assessed performance in the validation cohort.

Results

There were 4798 incident cases of colorectal cancer from 4.1 million person-years in the derivation cohort. Independent predictors in males and females included family history of gastrointestinal cancer, anaemia, rectal bleeding, abdominal pain, appetite loss, and weight loss. Alcohol consumption and recent change in bowel habit were also predictors in males. On validation, the algorithms explained 65% of the variation in females and 67% in males. The receiver operating curve statistics were 0.89 (females) and 0.91 (males). The D statistic was 2.8 (females) and 2.9 (males). The 10% of patients with the highest predicted risks contained 71% of all colorectal cancers diagnosed over the next 2 years

Conclusion

The algorithm has good discrimination and calibration and could potentially be used to help identify those at highest risk of current colorectal cancer, to facilitate early referral and investigation.     

Identifying patients with suspected pancreatic cancer in primary care: derivation and validation of an algorithm

Background

Pancreatic cancer has the worst survival for any cancer and is often diagnosed late when the cancer is advanced. Chances of survival are more likely if patients can be diagnosed earlier.

Aim

To derive and validate an algorithm to estimate absolute risk of having pancreatic cancer in patients with and without symptoms in primary care.

Design and setting

Cohort study using data from 375 UK QResearch® general practices for development and 189 for validation.

Method

Included patients were aged 30–84 years, free at baseline from a diagnosis of pancreatic cancer and had not had dysphagia, abdominal pain, abdominal distension, appetite loss, or weight loss recorded in the preceding 12 months. The primary outcome was incident diagnosis of pancreatic cancer recorded in the following 2 years. Risk factors examined included: age, body mass index, smoking status, alcohol, deprivation, diabetes, pancreatitis, previous diagnosis of cancer apart from pancreatic cancer, dysphagia, abdominal pain, abdominal distension, appetite loss, weight loss, diarrhoea, constipation, tiredness, itching, and anaemia. Cox proportional hazards models were used to develop separate risk equations in males and females. Measures of calibration and discrimination assessed performance in the validation cohort.

Results

There were a total of 1415 incident cases of pancreatic cancer from 4.1 million person-years in the derivation cohort. Independent predictors in both males and females were age, smoking, type 2 diabetes, chronic pancreatitis, abdominal pain, appetite loss, and weight loss. Abdominal distension was a predictor for females only; dysphagia and constipation were predictors for males only. On validation, the algorithms explained 59% of the variation in females and 62% in males. The receiver operating characteristic statistics were 0.84 (females) and 0.87 (males). The D statistic was 2.44 (females) and 2.61 (males). The 10% of patients with the highest predicted risks contained 62% of all pancreatic cancers diagnosed over the following 2 years.

Conclusion

The algorithm has good discrimination and calibration and could potentially be used to help identify those at highest risk of pancreatic cancer to facilitate early referral and investigation.     

Identifying patients with suspected gastro-oesophageal cancer in primary care: derivation and validation of an algorithm

Background

Gastro-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.

Aim

To 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 setting

Cohort study of 375 UK QResearch® general practices for development, and 189 for validation.

Method

Included patients were aged 30-84 years, free at baseline of a diagnosis of gastro-oesophageal cancer, and without dysphagia, haematemesis, abdominal pain, appetite loss, orweight 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.

Results

There 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.

Conclusion

The 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.     

Identifying patients with suspected renal tract cancer in primary care: derivation and validation of an algorithm

Background

Earlier diagnosis of renal tract cancer could help improve survival so better tools are needed to help this.

Aim

To derive and validate an algorithm to estimate the absolute risk of renal tract cancer in patients with and without symptoms in primary care.

Design

Cohort study using data from 375 UK QResearch® general practices for development and 189 for validation.

Method

Included patients were aged 30–84 years free at baseline of a diagnosis of renal tract cancer (bladder, kidney, ureter, or urethra) and without haematuria, abdominal pain, appetite loss, or weight loss in previous 12 months. The primary outcome was incident diagnosis of renal tract cancer recorded in the next 2 years. Risk factors examined were age, body mass index, smoking, alcohol, deprivation, treated hypertension, renal stones, structural kidney problems, diabetes, previous diagnosis of cancer apart from renal tract cancer, haematuria, abdominal pain, appetite loss, weight loss, diarrhoea, constipation, tiredness, and anaemia. Cox proportional hazards models were used to develop separate risk equations in males and females. Measures of calibration and discrimination assessed performance in the validation cohort.

Results

There were 2878 incident cases of renal tract cancer from 4.1 million person-years in the derivation cohort. Independent predictors in both males and females were age, smoking status, haematuria, abdominal pain, weight loss, and anaemia. A history of prior cancer other than renal tract cancer, and appetite loss were predictors for females only. On validation, the algorithms explained 75% of the variation in females and 76% in males. The receiver operating curve statistics were 0.91 (females) and 0.95 (males). The D statistic was 3.53 (females) and 3.60 (males). The 10% of patients with the highest predicted risks contained 87% of all renal tract cancers diagnosed over the next 2 years.

Conclusion

The algorithm has good discrimination and calibration and could potentially be used to identify those at highest risk of renal tract cancer, to facilitate more timely referral and investigation.     

Identifying suspected breast cancer: development and validation of a clinical prediction rule

Background

An evidence-based approach is needed to identify women with breast symptoms who are most likely to have breast cancer so that timely and appropriate referral can take place.

Aim

To report the development and validation of a clinical prediction rule for the diagnosis of breast cancer.

Design and setting

Cohort study with two prospective groups of women: those presenting to a symptomatic breast clinic (derivation cohort) and a separate cohort presenting to 11 general practices (validation cohort) in Tayside, Scotland.

Method

Regression analysis was used to derive a clinical prediction rule from presenting symptoms, personal and family history, and clinical findings. Validation consisted of estimating the number of breast cancers predicted to occur compared with the actual number of observed breast cancers across deciles of risk.

Results

In the derivation cohort of 802 patients, 59 (7%) were diagnosed with breast cancer. Independent clinical predictors for breast cancer were: increasing age by year (adjusted odds ratio [AOR] 1.10, 95% confidence interval [CI] = 1.07 to 1.13); presence of a discrete lump (AOR 15.20, 95% CI = 4.88 to 47.34); breast thickening (AOR 7.64, 95% CI = 2.23 to 26.11); lymphadenopathy (AOR 3.63, 95% CI = 1.33 to 9.92); and lump ≥2 cm (AOR 5.41, 95% CI = 2.36 to 12.38). All eight patients with skin tethering had breast cancer. The regression model had good predictive power, identifying all five breast cancers in the validation cohort of 97 patients in the top two deciles of risk.

Conclusion

The clinical prediction rule discriminates between patients at high risk of breast cancer from those at low risk, and can be implemented as an evidence-based recommendation to enhance appropriate referral from general practice to a symptomatic breast clinic. Ongoing validation in further populations is required.     

Non-visible versus visible haematuria and bladder cancer risk: a study of electronic records in primary care

Background

Diagnosis of bladder cancer relies on investigation of symptoms presented to primary care, notably visible haematuria. The importance of non-visible haematuria has never been estimated.

Aim

To estimate the risk of bladder cancer with non-visible haematuria.

Design and setting

A case–control study using UK electronic primary care medical records, including uncoded data to supplement coded records.

Method

A total of 4915 patients (aged ≥40 years) diagnosed with bladder cancer between January 2000 and December 2009 were selected from the Clinical Practice Research Datalink and matched to 21 718 controls for age, sex, and practice. Variables for visible and non-visible haematuria were derived from coded and uncoded data. Analyses used multivariable conditional logistic regression, followed by estimation of positive predictive values (PPVs) for bladder cancer using Bayes’ theorem.

Results

Non-visible haematuria (coded/uncoded data) was independently associated with bladder cancer: odds ratio (OR) 20 (95% confidence interval [CI] =12 to 33). The PPV of non-visible haematuria was 1.6% (95% CI = 1.2 to 2.1) in those aged ≥60 years and 0.8% (95% CI = 0.1 to 5.6) in 40–59-year-olds. The PPV of visible haematuria was 2.8% (95% CI = 2.5 to 3.1) and 1.2% (95% CI = 0.6 to 2.3) for the same age groups respectively, lower than those calculated using coded data alone. The proportion of records of visible haematuria in coded, rather than uncoded, format was higher in cases than in controls (P<0.002, χ² test). There was no evidence for such differential recording of non-visible haematuria by case/control status (P = 0.78), although, overall, the uncoded format was preferred (P<0.001).

Conclusion

Both non-visible and visible haematuria are associated with bladder cancer, although the visible form confers nearly twice the risk of cancer compared with the non-visible form. GPs’ style of record keeping varies by symptom and possible diagnosis.     

Clinical features of kidney cancer in primary care: a case-control study using primary care records

Background

Kidney cancer accounts for over 4000 UK deaths annually, and is one of the cancer sites with a poor mortality record compared with Europe.

Aim

To identify and quantify all clinical features of kidney cancer in primary care.

Design

Case-control study, using General Practice Research Database records.

Method

A total of 3149 patients aged ≥40 years, diagnosed with kidney cancer between 2000 and 2009, and 14 091 age, sex and practice-matched controls, were selected. Clinical features associated with kidney cancer were identified, and analysed using conditional logistic regression. Positive predictive values for features of kidney cancer were estimated.

Results

Cases consulted more frequently than controls in the year before diagnosis: median 16 consultations (interquartile range 10–25) versus 8 (4–15): P<0.001. Fifteen features were independently associated with kidney cancer: visible haematuria, odds ratio 37 (95% confidence interval [CI] = 28 to 49), abdominal pain 2.8 (95% CI = 2.4 to 3.4), microcytosis 2.6 (95% CI = 1.9 to 3.4), raised inflammatory markers 2.4 (95% CI = 2.1 to 2.8), thrombocytosis 2.2 (95% CI = 1.7 to 2.7), low haemoglobin 1.9 (95% CI = 1.6 to 2.2), urinary tract infection 1.8 (95% CI = 1.5 to 2.1), nausea 1.8 (95% CI = 1.4 to 2.3), raised creatinine 1.7 (95% CI = 1.5 to 2.0), leukocytosis 1.5 (95% CI = 1.2 to 1.9), fatigue 1.5 (95% CI = 1.2 to 1.9), constipation 1.4 (95% CI = 1.1 to 1.7), back pain 1.4 (95% CI = 1.2 to 1.7), abnormal liver function 1.3 (95% CI = 1.2 to 1.5), and raised blood sugar 1.2 (95% CI = 1.1 to 1.4). The positive predictive value for visible haematuria in patients aged ≥60 years was 1.0% (95% CI = 0.8 to 1.3).

Conclusion

Visible haematuria is the commonest and most powerful single predictor of kidney cancer, and the risk rises when additional symptoms are present. When considered alongside the risk of bladder cancer, the overall risk of urinary tract cancer from haematuria warrants referral.     

Risk of childhood cancer with symptoms in primary care: a population-based case-control study

Background

Guidelines describing symptoms in children that should alert GPs to consider cancer have been developed, but without any supporting primary-care research.

Aim

To identify symptoms and signs in primary care that strongly increase the likelihood of childhood cancer, to assist GPs in selection of children for investigation.

Design and setting

A population-based case-control study in UK general practice.

Method

Using electronic primary care records from the UK General Practice Research Database, 1267 children aged 0–14 years diagnosed with childhood cancer were matched to 15 318 controls. Clinical features associated with subsequent diagnosis of cancer were identified using conditional logistic regression, and likelihood ratios and positive predictive values (PPVs) were estimated for each.

Results

Twelve symptoms were associated with PPVs of ≥0.04%, which represents a greater than tenfold increase in prior probability. The six symptoms with the highest PPVs were pallor (odds ratio, OR = 84; PPV = 0.41% (95% confidence interval [CI] = 0.12% to 1.34%), head and neck masses (OR = 17; PPV = 0.30%; 95% CI = 0.10% to 0.84%), masses elsewhere (OR = 22; PPV = 0.11%; 95% CI = 0.06% to 0.20%), lymphadenopathy (OR = 10; PPV = 0.09%; 95% CI = 0.06% to 0.13%), symptoms/signs of abnormal movement (OR = 16; PPV = 0.08%; 95% CI = 0.04% to 0.14%), and bruising (OR = 12; PPV = 0·08%; 95% CI = 0.05% to 0.13%). When each of these 12 symptoms was combined singly with at least three consultations in a 3-month period, the probability of cancer was between 11 and 76 in 10 000.

Conclusion

Twelve features of childhood cancers were identified, each of which increased the risk of cancer at least tenfold. These symptoms, particularly when combined with multiple consultations, warrant careful evaluation in general practice.     

Evaluation of risk assessment tools for suspected cancer in general practice: a cohort study

Background

Diagnostic delay is deemed to account for an estimated 5000 to 10 000 extra cancer deaths each year in the UK. Many cancer patients do not have symptoms meeting national referral criteria for rapid investigation. Risk assessment tools (RATs) have been developed to assist GPs in selecting patient for cancer investigation.

Aim

To assess the usability and acceptability of lung and colorectal RATs, as well as subsequent resource use and cancer diagnoses.

Design and setting

Cohort study with nested qualitative study with 614 GPs from 165 practices in seven English cancer networks were provided with RATs applicable to patients aged ≥40 years with bowel or respiratory symptoms. In-depth interviews were conducted with 34 individuals (11 project managers and 23 GPs).

Method

The study measured the number of RATs used, and subsequent cancer investigations and diagnoses, over a 6-month period and compared these with the previous 6 months.

Results

A total of 2593 RATs (1160 lung, 1433 colorectal) were completed. Compared with the preceding 6 months, there were 292 more chest X-rays, 104 extra 2-week chest clinic appointments, and 47 additional diagnoses of lung cancer. For suspected colorectal cancer, there were 304 more 2-week referrals, 270 more colonoscopies, and 10 more cancers identified. RATs appeared to help GPs in their selection of patients for cancer investigation. Users reported that RATs helped to confirm a need for investigation as well as allowing reassurance when investigation was not needed.

Conclusion

Use of RATs in primary care was accompanied by increased diagnostic activity and additional cancer diagnoses.     

Clinical features of bladder cancer in primary care

Background

Bladder cancer accounts for over 150 000 deaths worldwide. No screening is available, so diagnosis depends on investigations of symptoms. Of these, only visible haematuria has been studied in primary care.

Aim

To identify and quantify the features of bladder cancer in primary care.

Design and setting

Case-control study, using electronic medical records from UK primary care.

Method

Participants were 4915 patients aged ≥40 years, diagnosed with bladder cancer January 2000 to December 2009, and 21 718 age, sex, and practice-matched controls, were selected from the General Practice Research Database, UK. All clinical features independently associated with bladder cancer using conditional logistic regression were identified, and their positive predictive values for bladder cancer, singly and in combination, were estimated.

Results

Cases consulted their GP more frequently than controls before diagnosis: median 15 consultations (interquartile range 9–22) versus 8 (4–15): P<0.001. Seven features were independently associated with bladder cancer: visible haematuria, odds ratio 34 (95% confidence interval [CI] = 29 to 41), dysuria 4.1 (95% CI = 3.4 to 5.0), urinary tract infection 2.2 (95% CI = 2.0 to 2.5), raised white blood cell count 2.1 (95% CI = 1.6 to 2.8), abdominal pain 2.0 (95% CI = 1.6 to 2.4), constipation 1.5 (95% CI = 1.2 to 1.9), raised inflammatory markers 1.5 (95% CI = 1.2 to 1.9), and raised creatinine 1.3 (95% CI = 1.2 to 1.4). The positive predictive value for visible haematuria in patients aged ≥60 years was PPV of 3.9% (95% CI = 2.2 to 3.2).

Conclusion

Visible haematuria is the commonest and most powerful predictor of bladder cancer in primary care, and warrants investigation. Most other previously reported features of bladder cancer were associated with the disease, but with low predictive values. There is a need for improved diagnostic methods, for those patients whose bladder cancer presents without visible haematuria.     

A clinical prediction rule for meniscal tears in primary care: development and internal validation using a multicentre study

Background

In primary care, meniscal tears are difficult to detect. A quick and easy clinical prediction rule based on patient history and a single meniscal test may help physicians to identify high-risk patients for referral for magnetic resonance imaging (MRI).

Aim

The study objective was to develop and internally validate a clinical prediction rule (CPR) for the detection of meniscal tears in primary care.

Design and setting

In a cross-sectional multicentre study, 121 participants from primary care were included if they were aged 18–65 years with knee complaints that existed for <6 months, and who were suspected to suffer from a meniscal tear.

Method

One diagnostic physical meniscal test and 14 clinical variables were considered to be predictors of MRI outcome. Using known predictors for the presence of meniscal tears, a ‘quick and easy’ CPR was derived.

Results

The final CPR included the variables sex, age, weight-bearing during trauma, performing sports, effusion, warmth, discolouration, and Deep Squat test. The final model had an AUC of 0.76 (95% CI = 0.72 to 0.80). A cut-point of 150 points yielded an overall sensitivity of 86.1% and a specificity of 45.5%. For this cut-point, the positive predictive value was 55.0%, and the negative predictive value was 81.1%. A scoring system was provided including the corresponding predicted probabilities for a meniscal tear.

Conclusion

The CPR improved the detection of meniscal tears in primary care. Further evaluation of the CPR in new primary care patients is needed, however, to assess its usefulness.     

Cancer diagnosis in primary care

Around a quarter of those in the developed world die of cancer. Most cancers present to primary care with symptoms, even when there is a screening test for the particular cancer. However, the symptoms of cancer are also symptoms of benign disease, and the GP has to judge whether cancer is a possible explanation. Very little research examined this process until relatively recently. This review paper examines the process of primary care diagnosis, especially the selection of patients for rapid investigation. It concentrates on the four commonest UK cancers: breast, lung, colon, and prostate as these have been the subject of most recent studies.     

The diagnostic value of symptoms for colorectal cancer in primary care: a systematic review

Background

Over 37 000 new colorectal cancers are diagnosed in the UK each year. Most present symptomatically to primary care.

Aim

To conduct a systematic review of the diagnostic value of symptoms associated with colorectal cancer.

Design

Systematic review.

Method

MEDLINE, Embase, Cochrane Library, and CINAHL were searched to February 2010, for diagnostic studies of symptomatic adult patients in primary care. Studies of asymptomatic patients, screening, referred populations, or patients with colorectal cancer recurrences, or with fewer than 100 participants were excluded. The target condition was colorectal cancer. Data were extracted to estimate the diagnostic performance of each symptom or pair of symptoms. Data were pooled in a meta-analysis. The quality of studies was assessed with the QUADAS tool.

Results

Twenty-three studies were included. Positive predictive values (PPVs) for rectal bleeding from 13 papers ranged from 2.2% to 16%, with a pooled estimate of 8.1% (95% confidence interval [CI] = 6.0% to 11%) in those aged ≥50 years. Pooled PPV estimates for other symptoms were: abdominal pain (three studies) 3.3% (95% CI = 0.7% to 16%); and anaemia (four studies) 9.7% (95% CI = 3.5% to 27%). For rectal bleeding accompanied by weight loss or change in bowel habit, pooled positive likelihood ratios (PLRs) were 1.9 (95% CI = 1.3 to 2.8) and 1.8 (95% CI = 1.3 to 2.5) respectively, suggesting higher risk when both symptoms were present. Conversely, the PLR was one or less for abdominal pain, diarrhoea, or constipation accompanying rectal bleeding.

Conclusion

The findings suggest that investigation of rectal bleeding or anaemia in primary care patients is warranted, irrespective of whether other symptoms are present. The risks from other single symptoms are lower, though multiple symptoms also warrant investigation.     

The association between symptoms and bladder or renal tract cancer in primary care: a systematic review

Background

Appropriate selection for further investigation of patients presenting in primary care with symptoms that may indicate cancer is key to early diagnosis.

Aim

To quantify the risk of urinary tract cancer in patients presenting in primary care with symptoms that may indicate bladder or renal cancer.

Design and setting

Systematic review of studies relating to bladder or renal cancer in primary care.

Method

Databases searched were MEDLINE, PreMEDLINE, Embase, the Cochrane Library, Web of Science (SCI and SSCI), and ISI Proceedings from 1980 to August 2014, and PsycINFO (1980–2012) and BioMed Central (inception to 2012) for retrospective, prospective, or case-control diagnostic accuracy studies of symptomatic patients presenting to primary care with one or more symptoms for whom follow-up data were available. The target conditions were bladder or renal cancer. The studies were appraised using the QUADAS-2 tool.

Results

Eleven studies with 3 451 675 patients were included. The positive predictive value (PPV) from meta-analysis of visible haematuria was 5.1% in adult patients. It increased with age and was higher in males. The PPVs of other single symptoms were very low, with the highest non-haematuria PPV being 1.4% for anaemia in males. Fewer data were available on the PPVs of symptom combinations. Generally, these data showed that, with the exception of symptom combinations including haematuria, these were very low.

Conclusion

The only high-risk feature of bladder/renal cancer in primary care was visible haematuria, and this clearly warrants investigation. However, not all patients with one of these cancers experience haematuria, so a policy restricting investigation to patients with haematuria will inevitably delay the diagnosis in some patients.     

Diagnosing depression in primary care using self-completed instruments: UK validation of PHQ-9 and CORE-OM.

There is increased emphasis on routine assessment of depression in primary care. This report is the first UK validation of two self-completed measures: the Patient Health Questionnaire (PHQ-9) and the Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM). Optimum cut-off points were established against a diagnostic gold standard in 93 patients. PHQ-9 sensitivity = 91.7% (95% confidence interval [CI] = 77.5 to 98.3%) and specificity 78.3% (95% CI = 65.8 to 87.9%). CORE-OM sensitivity = 91.7% (95% CI = 77.5 to 98.2%) and specificity = 76.7% (95% CI = 64.0 to 86.6%). Brief self-rated questionnaires are as good as clinician-administered instruments in detecting depression in UK primary care.     

Advance care planning for cancer patients in primary care: a feasibility study

Background

Advance care planning is being promoted as a central component of end-of-life policies in many developed countries, but there is concern that professionals find its implementation challenging.

Aim

To assess the feasibility of implementing advance care planning in UK primary care.

Design of study

Mixed methods evaluation of a pilot educational intervention.

Setting

Four general practices in south-east Scotland.

Method

Interviews with 20 GPs and eight community nurses before and after a practice-based workshop; this was followed by telephone interviews with nine other GPs with a special interest in palliative care from across the UK.

Results

End-of-life care planning for patients typically starts as an urgent response to clear evidence of a short prognosis, and aims to achieve a ‘good death’. Findings suggest that there were multiple barriers to earlier planning: prognostic uncertainty; limited collaboration with secondary care; a desire to maintain hope; and resistance to any kind of ‘tick-box’ approach. Following the workshop, participants'' knowledge and skills were enhanced but there was little evidence of more proactive planning. GPs from other parts of the UK described confusion over terminology and were concerned about the difficulties of implementing inflexible, policy-driven care.

Conclusion

A clear divide was found between UK policy directives and delivery of end-of-life care in the community that educational interventions targeting primary care professionals are unlikely to address. Advance care planning has the potential to promote autonomy and shared decision making about end-of-life care, but this will require a significant shift in attitudes.     

A simple risk score using routine data for predicting cardiovascular disease in primary care

Background

Population-based screening for cardiovascular disease (CVD) risk, incorporating blood tests, is proposed in several countries.

Aim

The aim of this study was to evaluate whether a simple approach to identifying individuals at high risk of CVD using routine data might be effective.

Design of study

Prospective cohort study (EPIC-Norfolk).

Setting

Norfolk area, UK.

Method

A total of 21 867 men and women aged 40–74 years, who were free from CVD and diabetes at baseline, participated in the study. The discrimination (the area under the receiver operating characteristic curve [aROC]), calibration, sensitivity/specificity, and positive/negative predictive value were evaluated for different risk thresholds of the Framingham risk equations and the Cambridge diabetes risk score (as an example of a simple risk score using routine data from electronic general practice records).

Results

During 203 664 person-years of follow-up, 2213 participants developed a first CVD event (10.9 per 1000 person-years). The Cambridge diabetes risk score predicted CVD events reasonably well (aROC 0.72; 95% confidence interval [CI] = 0.71 to 0.73), while the Framingham risk score had the best predictive ability (aROC 0.77; 95% CI = 0.76 to 0.78). The Framingham risk score overestimated risk of developing CVD in this representative British population by 60%.

Conclusion

A risk score incorporating routinely available data from GP records performed reasonably well at predicting CVD events. This suggests that it might be more efficient to use routine data as the first stage in a stepwise population screening programme to identify people at high risk of developing CVD before more time- and resource-consuming tests are used.