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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 from375 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, bodymass 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% inmales. 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. ©British Journal of General Practice.

QRISK2 validation by ethnic group

Predictive effect of heartburn and indigestion and risk of upper gastro-intestinal malignancy

Advantages of QRISK2 (2010): The key issue is ethnicity and extent of reallocation

Use of hormone replacement therapy and risk of venous thromboembolism: Nested case-control studies using the QResearch and CPRD databases

Objective To assess the association between risk of venous thromboembolism and use of different types of hormone replacement therapy. Design Two nested case-control studies. Setting UK general practices contributing to the QResearch or Clinical Practice Research Datalink (CPRD) databases, and linked to hospital, mortality, and social deprivation data. Participants 80 396 women aged 40-79 with a primary diagnosis of venous thromboembolism between 1998 and 2017, matched by age, general practice, and index date to 391 494 female controls. Main outcome measures Venous thromboembolism recorded on general practice, mortality, or hospital records. Odds ratios were adjusted for demographics, smoking status, alcohol consumption, comorbidities, recent medical events, and other prescribed drugs. Results Overall, 5795 (7.2%) women who had venous thromboembolism and 21 670 (5.5%) controls had been exposed to hormone replacement therapy within 90 days before the index date. Of these two groups, 4915 (85%)and 16 938 (78%) women used oral therapy, respectively, which was associated with a significantly increased risk of venous thromboembolism compared with no exposure (adjusted odds ratio 1.58, 95% confidence interval 1.52 to 1.64), for both oestrogen only preparations (1.40, 1.32 to 1.48) and combined preparations (1.73, 1.65 to 1.81). Estradiolhad a lower risk than conjugated equine oestrogen for oestrogen only preparations (0.85, 0.76 to 0.95) and combined preparations (0.83, 0.76 to 0.91). Compared with no exposure, conjugated equine oestrogen with medroxyprogesterone acetate had the highest risk (2.10, 1.92 to 2.31), and estradiol with dydrogesterone had the lowest risk (1.18, 0.98 to 1.42). Transdermal preparations were not associated with risk of venous thromboembolism, which was consistent for different regimens (overall adjusted odds ratio 0.93, 95% confidence interval 0.87 to 1.01). Conclusions In the present study, transdermal treatment was the safest type of hormone replacement therapy when risk of venous thromboembolism was assessed. Transdermal treatment appears to be underused, with the overwhelming preference still for oral preparations.

Development and validation of risk prediction equations to estimate survival in patients with colorectal cancer: Cohort study

Objective To develop and externally validate risk prediction equations to estimate absolute and conditional survival in patients with colorectal cancer. Design Cohort study. Setting General practices in England providing data for the QResearch database linked to the national cancer registry. Participants 44 145 patients aged 15-99 with colorectal cancer from 947 practices to derive the equations. The equations were validated in 15 214 patients with colorectal cancer from 305 different QResearch practices and 437 821 patients with colorectal cancer from the national cancer registry. Main outcome measures The primary outcome was all cause mortality and secondary outcome was colorectal cancer mortality. Methods Cause specific hazards models were used to predict risks of colorectal cancer mortality and other cause mortality accounting for competing risks, and these risk estimates were combined to obtain risks of all cause mortality. Separate equations were derived for men and women. Several variables were tested: age, ethnicity, deprivation score, cancer stage, cancer grade, surgery, chemotherapy, radiotherapy, smoking status, alcohol consumption, body mass index, family history of bowel cancer, anaemia, liver function test result, comorbidities, use of statins, use of aspirin, clinical values for anaemia, and platelet count. Measures of calibration and discrimination were determined in both validation cohorts at 1, 5, and 10 years. Results The final models included the following variables in men and women: age, deprivation score, cancer stage, cancer grade, smoking status, colorectal surgery, chemotherapy, family history of bowel cancer, raised platelet count, abnormal liver function, cardiovascular disease, diabetes, chronic renal disease, chronic obstructive pulmonary disease, prescribed aspirin at diagnosis, and prescribed statins at diagnosis. Improved survival in women was associated with younger age, earlier stage of cancer, well or moderately differentiated cancer grade, colorectal cancer surgery (adjusted hazard ratio 0.50), family history of bowel cancer (0.62), and prescriptions for statins (0.77) and aspirin (0.83) at diagnosis, with comparable results for men. The risk equations were well calibrated, with predicted risks closely matching observed risks. Discrimination was good in men and women in both validation cohorts. For example, the five year survival equations on the QResearch validation cohort explained 45.3% of the variation in time to colorectal cancer death for women, the D statistic was 1.86, and Harrell's C statistic was 0.80 (both measures of discrimination, indicating that the scores are able to distinguish between people with different levels of risk). The corresponding results for all cause mortality were 42.6%, 1.77, and 0.79. Conclusions Risk prediction equations were developed and validated to estimate overall and conditional survival of patients with colorectal cancer accounting for an individual's clinical and demographic characteristics. These equations can provide more individualised accurate information for patients with colorectal cancer to inform decision making and follow-up.

Development and validation of QRISK3 risk prediction algorithms to estimate future risk of cardiovascular disease: Prospective cohort study

Objectives To develop and validate updated QRISK3 prediction algorithms to estimate the 10 year risk of cardiovascular disease in women and men accounting for potential new risk factors. Design Prospective open cohort study. Setting General practices in England providing data for the QResearch database. Participants 1309 QResearch general practices in England: 981 practices were used to develop the scores and a separate set of 328 practices were used to validate the scores. 7.89 million patients aged 25-84 years were in the derivation cohort and 2.67 million patients in the validation cohort. Patients were free of cardiovascular disease and not prescribed statins at baseline. Methods Cox proportional hazards models in the derivation cohort to derive separate risk equations in men and women for evaluation at 10 years. Risk factors considered included those already in QRISK2 (age, ethnicity, deprivation, systolic blood pressure, body mass index, total cholesterol: high density lipoprotein cholesterol ratio, smoking, family history of coronary heart disease in a first degree relative aged less than 60 years, type 1 diabetes, type 2 diabetes, treated hypertension, rheumatoid arthritis, atrial fibrillation, chronic kidney disease (stage 4 or 5)) and new risk factors (chronic kidney disease (stage 3, 4, or 5), a measure of systolic blood pressure variability (standard deviation of repeated measures), migraine, corticosteroids, systemic lupus erythematosus (SLE), atypical antipsychotics, severe mental illness, and HIV/AIDS). We also considered erectile dysfunction diagnosis or treatment in men. Measures of calibration and discrimination were determined in the validation cohort for men and women separately and for individual subgroups by age group, ethnicity, and baseline disease status. Main outcome measures Incident cardiovascular disease recorded on any of the following three linked data sources: general practice, mortality, or hospital admission records. Results 363 565 incident cases of cardiovascular disease were identified in the derivation cohort during follow-up arising from 50.8 million person years of observation. All new risk factors considered met the model inclusion criteria except for HIV/AIDS, which was not statistically significant. The models had good calibration and high levels of explained variation and discrimination. In women, the algorithm explained 59.6% of the variation in time to diagnosis of cardiovascular disease (R 2, with higher values indicating more variation), and the D statistic was 2.48 and Harrell's C statistic was 0.88 (both measures of discrimination, with higher values indicating better discrimination). The corresponding values for men were 54.8%, 2.26, and 0.86. Overall performance of the updated QRISK3 algorithms was similar to the QRISK2 algorithms. Conclusion Updated QRISK3 risk prediction models were developed and validated. The inclusion of additional clinical variables in QRISK3 (chronic kidney disease, a measure of systolic blood pressure variability (standard deviation of repeated measures), migraine, corticosteroids, SLE, atypical antipsychotics, severe mental illness, and erectile dysfunction) can help enable doctors to identify those at most risk of heart disease and stroke.

Diabetes treatments and risk of heart failure, cardiovascular disease, and all cause mortality: Cohort study in primary care

Objective: To assess associations between risks of cardiovascular disease, heart failure, and all cause mortality and different diabetes drugs in people with type 2 diabetes, particularly newer agents, including gliptins and thiazolidinediones (glitazones). Design: Open cohort study. Setting: 1243 general practices contributing data to the QResearch database in England. Participants: 469 688 people with type 2 diabetes aged 25-84 years between 1 April 2007 and 31 January 2015. Exposures: Diabetes drugs (glitazones, gliptins, metformin, sulphonylureas, insulin, other) alone and in combination. Main outcom e measure: First recorded diagnoses of cardiovascular disease, heart failure, and all cause mortality recorded on the patients' primary care, mortality, or hospital record. Cox proportional hazards models were used to estimate hazard ratios for diabetes treatments, adjusting for potential confounders. Results: During follow-up, 21 308 patients (4.5%) received prescriptions for glitazones and 32 533 (6.9%) received prescriptions for gliptins. Compared with non-use, gliptins were significantly associated with an 18% decreased risk of all cause mortality, a 14% decreased risk of heart failure, and no significant change in risk of cardiovascular disease; corresponding values for glitazones were significantly decreased risks of 23% for all cause mortality, 26% for heart failure, and 25% for cardiovascular disease. Compared with no current treatment, there were no significant associations between monotherapy with gliptins and risk of any complications. Dual treatment with gliptins and metformin was associated with a decreased risk of all three outcomes (reductions of 38% for heart failure, 33% for cardiovascular disease, and 48% for all cause mortality). Triple treatment with metformin, sulphonylureas, and gliptins was associated with a decreased risk of all three outcomes (reductions of 40% for heart failure, 30% for cardiovascular disease, and 51% for all cause mortality). Compared with no current treatment, monotherapy with glitazone was associated with a 50% decreased risk of heart failure, and dual treatment with glitazones and metformin was associated with a decreased risk of all three outcomes (reductions of 50% for heart failure, 54% for cardiovascular disease, and 45% for all cause mortality); dual treatment with glitazones and sulphonylureas was associated with risk reductions of 35% for heart failure and 25% for cardiovascular disease; triple treatment with metformin, sulphonylureas, and glitazones was associated with decreased risks of all three outcomes (reductions of 46% for heart failure, 41% for cardiovascular disease, and 56% for all cause mortality). Conclusions: There are clinically important differences in risk of cardiovascular disease, heart failure, and all cause mortality between different diabetes drugs alone and in combination. Overall, use of gliptins or glitazones was associated with decreased risks of heart failure, cardiovascular disease, and all cause mortality compared with non-use of these drugs. These results, which do not account for levels of adherence or dosage information and which are subject to confounding by indication, might have implications for prescribing of diabetes drugs.

Discontinuation and restarting in patients on statin treatment: Prospective open cohort study using a primary care database

Objectives: To estimate rates of discontinuation and restarting of statins, and to identify patient characteristics associated with either discontinuation or restarting. Design: Prospective open cohort study. Setting: 664 general practices contributing to the Clinical Practice Research Datalink in the United Kingdom. Data extracted in October 2014. Participants: Incident statin users aged 25-84 years identified between January 2002 and September 2013. Patients with statin prescriptions divided into two groups: primary prevention and secondary prevention (those already diagnosed with cardiovascular disease). Patients with statin prescriptions in the 12 months before study entry were excluded. Main outcome measures: Discontinuation of statin treatment (first 90 day gap after the estimated end date of a statin prescription), and restarting statin treatment for those who discontinued (defined as any subsequent prescription between discontinuation and study end). Results: Of 431 023 patients prescribed statins as primary prevention with a median follow-up time of 137 weeks, 47% (n=204 622) discontinued treatment and 72% (n=147 305) of those who discontinued restarted. Of 139 314 patients prescribed statins as secondary prevention with median follow-up time of 182 weeks, 41% (n=57 791) discontinued treatment and 75% (43 211) of those who discontinued restarted. Younger patients (aged ≤50 years), older patients (≥75 years), women, and patients with chronic liver disease were more likely to discontinue statins and less likely to restart. However, patients in ethnic minority groups, current smokers, and patients with type 1 diabetes were more likely to discontinue treatment but then were more likely to restart, whereas patients with hypertension and type 2 diabetes were less likely to discontinue treatment and more likely to restart if they did discontinue. These results were mainly consistent in the primary prevention and secondary prevention groups. Conclusions: Although a large proportion of statin users discontinue, many of them restart. For many patient groups previously considered as "stoppers," the problem of statin treatment "stopping" could be part of the wider issue of poor adherence. Identification of patient groups associated with completely stopping or stop-starting behaviour has positive implications for patients and doctors as well as suggesting areas for future research.

The NHS Health Check in England: An evaluation of the first 4 years

Objectives: To describe implementation of a new national preventive programme to reduce cardiovascular morbidity. Design: Observational study over 4 years (April 2009 a-March 2013). Setting: 655 general practices across England from the QResearch database. Participants: Eligible adults aged 40a-74 years including attendees at a National Health Service (NHS) Health Check. Intervention: NHS Health Check: routine structured cardiovascular check with support for behavioural change and in those at highest risk, treatment of risk factors and newly identified comorbidity. Results: Of 1.68 million people eligible for an NHS Health Check, 214 295 attended in the period 2009a- 12. Attendance quadrupled as the programme progressed; 5.8% in 2010 to 30.1% in 2012. Attendance was relatively higher among older people, of whom 19.6% of those eligible at age 60a-74 years attended and 9.0% at age 40a-59 years. Attendance by population groups at higher cardiovascular disease (CVD) risk, such as the more socially disadvantaged 14.9%, was higher than that of the more affluent 12.3%. Among attendees 7844 new cases of hypertension (38/1000 Checks), 1934 new cases of type 2 diabetes (9/1000 Checks) and 807 new cases of chronic kidney disease (4/1000 Checks) were identified. Of the 27 624 people found to be at high CVD risk (20% or more 10-year risk) when attending an NHS Health Check, 19.3% (5325) were newly prescribed statins and 8.8% (2438) were newly prescribed antihypertensive therapy. Conclusions: NHS Health Check coverage was lower than expected but showed year-on-year improvement. Newly identified comorbidities were an important feature of the NHS Health Checks. Statin treatment at national scale for 1 in 5 attendees at highest CVD risk is likely to have contributed to important reductions in their CVD events.

Patients who discontinued statin treatment: A protocol for cohort study using primary care data

Introduction: Risk thresholds for using statins to prevent cardiovascular disease (CVD) have recently been lowered, so an increasing number of patients are now prescribed these drugs. Although the safety of long-term statin use has been generally established, concerns about the balance of risks and benefits of statins still exist for some medical professionals and patients, and issues concerning their side effects are occasionally widely publicised. This study will report the rates of stopping for statins and also identify any patient groups more likely to stop using statins, so possibly increasing their risk of cardiovascular events. Methods and analysis: A prospective open cohort study between 1 January 2002 and 30 September 2014 will be based on the general population of people prescribed statins, using records from UK general practices contributing to the Clinical Practice Research Database (CPRD). Participants aged 25-84 years will enter the cohort on the date of their first prescription for a statin and leave on the earliest date of: a cardiovascular event; death; leaving the practice; the last practice upload date or the study end date. If there are no prescriptions within 90 days after the expected finishing date of a prescription, a patient will be defined as a stopper with the discontinuation outcome date as the expected finishing date. Rates of statin discontinuation will be calculated by calendar year, type and dose of statin, age, and morbidities. Cox proportional regression analyses will be run to identify the most important factors associated with discontinuation. Analyses will be run separately for patients without CVD (primary prevention) and with diagnosed CVD (secondary prevention). Ethics and dissemination: The protocol has been reviewed and approved by Independent Scientific Advisory Committee for MHRA Database Research. The results will be published in a peer-reviewed journal.

Development and validation of risk prediction equations to estimate future risk of heart failure in patients with diabetes: A prospective cohort study

Objective: To develop and externally validate risk prediction equations to estimate the 10-year risk of heart failure in patients with diabetes, aged 25-84 years. Design: Cohort study using routinely collected data from general practices in England between 1998 and 2014 contributing to the QResearch and Clinical Research Practice Datalink (CPRD) databases. Setting: We used 763 QResearch practices to develop the equations. We validated it in 254 different QResearch practices and 357 CPRD practices. Participants: 437 806 patients in the derivation cohort; 137 028 in the QResearch validation cohort, and 197 905 in the CPRD validation cohort. Measurement: Incident diagnosis of heart failure recorded on the patients' linked electronic General Practitioner (GP), mortality, or hospital record. Risk factors included age, body mass index (BMI), systolic blood pressure, cholesterol/high-density lipoprotein (HDL) ratio, glycosylated haemoglobin (HbA1c), material deprivation, ethnicity, smoking, diabetes duration, type of diabetes, atrial fibrillation, cardiovascular disease, chronic renal disease, and family history of premature coronary heart disease. Methods: We used Cox proportional hazards models to derive separate risk equations in men and women for evaluation at 10 years. Measures of calibration, discrimination, and sensitivity were determined in 2 external validation cohorts. Results: We identified 25 480 cases of heart failure in the derivation cohort, 8189 in the QResearch validation cohort, and 11 311 in the CPRD cohort. The equations included: age, BMI, systolic blood pressure, cholesterol/HDL ratio, HbA1c, material deprivation, ethnicity, smoking, duration and type of diabetes, atrial fibrillation, cardiovascular disease, and chronic renal disease. The equations had good performance in CPRD for women (R2 of 41.2%; D statistic 1.71; and receiver operating characteristic curve (ROC) statistic 0.78) and men (38.7%, 1.63; and 0.77 respectively). Conclusions: We have developed and externally validated risk prediction equations to quantify absolute risk of heart failure inmen and women with diabetes. These can be used to identify patients at high risk of heart failure for prevention or assessment of the disease.

Use of combined oral contraceptives and risk of venous thromboembolism: nested case-control studies using the QResearch and CPRD databases

OBJECTIVE: To investigate the association between use of combined oral contraceptives and risk of venous thromboembolism, taking the type of progestogen into account.

Development and validation of risk prediction algorithms to estimate future risk of common cancers in men and women: Prospective cohort study

Objective: To derive and validate a set of clinical risk prediction algorithm to estimate the 10-year risk of 11 common cancers. Design: Prospective open cohort study using routinely collected data from 753 QResearch general practices in England. We used 565 practices to develop the scores and 188 for validation. Subjects: 4.96 million patients aged 25-84 years in the derivation cohort; 1.64 million in the validation cohort. Patients were free of the relevant cancer at baseline. Methods: Cox proportional hazards models in the derivation cohort to derive 10-year risk algorithms. Risk factors considered included age, ethnicity, deprivation, body mass index, smoking, alcohol, previous cancer diagnoses, family history of cancer, relevant comorbidities and medication. Measures of calibration and discrimination in the validation cohort. Outcomes: Incident cases of blood, breast, bowel, gastro-oesophageal, lung, oral, ovarian, pancreas, prostate, renal tract and uterine cancers. Cancers were recorded on any one of four linked data sources (general practitioner (GP), mortality, hospital or cancer records). Results: We identified 228 241 incident cases during follow-up of the 11 types of cancer. Of these 25 444 were blood; 41 315 breast; 32 626 bowel, 12 808 gastrooesophageal; 32 187 lung; 4811 oral; 6635 ovarian; 7119 pancreatic; 35 256 prostate; 23 091 renal tract; 6949 uterine cancers. The lung cancer algorithm had the best performance with an R2 of 64.2%; D statistic of 2.74; receiver operating characteristic curve statistic of 0.91 in women. The sensitivity for the top 10% of women at highest risk of lung cancer was 67%. Performance of the algorithms in men was very similar to that for women. Conclusions: We have developed and validated a prediction models to quantify absolute risk of 11 common cancers. They can be used to identify patients at high risk of cancers for prevention or further assessment. The algorithms could be integrated into clinical computer systems and used to identify high-risk patients. Web calculator: There is a simple web calculator to implement the Qcancer 10 year risk algorithm together with the open source software for download (available at http://qcancer.org/10yr/).

The performance of seven QPrediction risk scores in an independent external sample of patients from general practice: A validation study

Objectives: To validate the performance of a set of risk prediction algorithms developed using the QResearch database, in an independent sample from general practices contributing to the Clinical Research Data Link (CPRD). Setting: Prospective open cohort study using practices contributing to the CPRD database and practices contributing to the QResearch database. Participants: The CPRD validation cohort consisted of 3.3 million patients, aged 25-99 years registered at 357 general practices between 1 Jan 1998 and 31 July 2012. The validation statistics for QResearch were obtained from the original published papers which used a one-third sample of practices separate to those used to derive the score. A cohort from QResearch was used to compare incidence rates and baseline characteristics and consisted of 6.8 million patients from 753 practices registered between 1 Jan 1998 and until 31 July 2013. Outcome measures: Incident events relating to seven different risk prediction scores: QRISK2 (cardiovascular disease); QStroke (ischaemic stroke); QDiabetes (type 2 diabetes); QFracture (osteoporotic fracture and hip fracture); QKidney (moderate and severe kidney failure); QThrombosis (venous thromboembolism); QBleed (intracranial bleed and upper gastrointestinal haemorrhage). Measures of discrimination and calibration were calculated. Results: Overall, the baseline characteristics of the CPRD and QResearch cohorts were similar though QResearch had higher recording levels for ethnicity and family history. The validation statistics for each of the risk prediction scores were very similar in the CPRD cohort compared with the published results from QResearch validation cohorts. For example, in women, the QDiabetes algorithm explained 50% of the variation within CPRD compared with 51% on QResearch and the receiver operator curve value was 0.85 on both databases. The scores were well calibrated in CPRD. Conclusions: Each of the algorithms performed practically as well in the external independent CPRD validation cohorts as they had in the original published QResearch validation cohorts.

Exposure to combined oral contraceptives and risk of venous thromboembolism: A protocol for nested case-control studies using the QResearch and the CPRD databases

Introduction: Many studies have found an increased risk of venous thromboembolism (VTE) associated with the use of combined hormonal contraceptives, but various methodologies have been used in the study design relating to definition of VTE event and the selection of appropriate cases for analysis. This study will focus on common oral hormonal contraceptives, including compositions with cyproterone because of their contraceptive effect and will perform a number of sensitivity analyses to compare findings with previous studies. Methods and analysis: 2 nested case-control studies will be based on the general population using records from UK general practices within the QResearch and Clinical Practice Research Datalink databases. Cases will be female patients aged 15-49 with primary VTE diagnosed between 2001 and 2013. Each case will be matched by age, year of birth and practice to five female controls, who are alive and registered with the practice at the time of diagnosis of the case (index date). Exposure to different hormonal contraceptives will be defined as at least one prescription for that contraceptive in the year before the index date. The effects of duration and the length of any gap since last use will also be investigated. Conditional logistic regression will be applied to calculate ORs adjusted for smoking, ethnicity, comorbidities and use of other medications. Possible indications for prescribing hormonal contraceptives, such as menstrual disorders, acne or hirsutism will be included in the analyses as confounding factors. A number of sensitivity analyses will be carried out. Ethics and dissemination: The initial protocol has been reviewed and approved by ISAC (Independent Scientific Advisory Committee) for Medicine and Healthcare Products Regulatory Agency Database Research. The project has also been reviewed by QResearch and meets the requirements of the Trent Research Ethics Committee. The results will be published in a peer-reviewed journal.

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. © British Journal of General Practice.

Symptoms and risk factors to identify women 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 women 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 females aged 25-89 years. The primary outcome was incident diagnosis of cancer over the next 2 years (lung, colorectal, gastro-oesophageal, pancreatic, ovarian, renal tract, breast, blood, uterine, cervix, other). Factors examined were: 'red flag' symptoms including weight loss, abdominal pain, indigestion, dysphagia, abnormal bleeding, lumps; general symptoms including tiredness, constipation; and risk factors including age, family history, smoking, alcohol intake, deprivation, body mass index (BMI), 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 23 216 cancers from 1 240 864 females in the derivation cohort. The final model included risk factors (age, BMI, chronic pancreatitis, chronic obstructive pulmonary disease, diabetes, family history, alcohol, smoking, deprivation); 23 symptoms, anaemia and venous thrombo-embolism. The model was well calibrated with good discrimination. The receiver operating curve statistics were lung (0.91), colorectal (0.89), gastro-oesophageal (0.90), pancreas (0.87), ovary (0.84), renal (0.90), breast (0.88), blood (0.79), uterus (0.91), cervix (0.73), other cancer (0.82). The 10% of females with the highest risks contained 54% 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. © British Journal of General Practice.

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 aremore likely if patients can be diagnosed earlier. Aim: To derive and validate an algorithmto estimate absolute risk of having pancreatic cancer in patients with andwithout symptoms in primary care. Design and setting: Cohort study using data from375 UK QResearch® general practices for development and 189 for validation. Method: Included patients were aged 30-84 years, free at baseline froma diagnosis of pancreatic cancer and had not had dysphagia, abdominal pain, abdominal distension, appetite loss, or weight loss recorded in the preceding 12months. The primary outcome was incident diagnosis of pancreatic cancer recorded in the following 2 years. Risk factors examined included: age, bodymass index, smoking status, alcohol, deprivation, diabetes, pancreatitis, previous diagnosis of cancer apart frompancreatic cancer, dysphagia, abdominal pain, abdominal distension, appetite loss, weight loss, diarrhoea, constipation, tiredness, itching, and anaemia. Cox proportional hazardsmodels were used to develop separate risk equations inmales 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 from4.1million person-years in the derivation cohort. Independent predictors in bothmales 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%inmales. 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 algorithmhas 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. ©British Journal of General Practice.

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 algorithmto 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 froma diagnosis of colorectal cancer and without rectal bleeding, abdominal pain, appetite loss, or weight loss in the previous 12months. The primary outcome was incident diagnosis of colorectal cancer recorded in the next 2 years. Risk factors examined were age, bodymass 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 hazardsmodels were used to develop separate risk equations inmales and females. Measures of calibration and discrimination assessed performance in the validation cohort. Results: There were 4798 incident cases of colorectal cancer from4.1million person-years in the derivation cohort. Independent predictors inmales 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 inmales. On validation, the algorithms explained 65%of the variation in females and 67%inmales. 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 algorithmhas 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. ©British Journal of General Practice.