1. + Qcancer: symptom based approach to early diagnosis of cancer Julia Hippisley-Cox, GP, Professor Epidemiology & Director ClinRisk Ltd Yorkshire Cancer Network 8 th November 2012

2. + Acknowledgements Co-authors QResearch database EMIS & contributing practices & User Group University of Nottingham ClinRisk (software) Oxford University (independent validation) This work by Julia Hippisley-Cox is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported LicenseJulia Hippisley-CoxCreative Commons Attribution-ShareAlike 3.0 Unported License

3. + QResearch Database www.qresearch.org www.qresearch.org Over 700 general practices across the UK, 14 million patients Joint venture between EMIS and University of Nottingham Patient level pseudonymised database for research Available for peer reviewed academic research where outputs made publically available Data linkage – deaths, deprivation, cancer, HES This work by Julia Hippisley-Cox is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported LicenseJulia Hippisley-CoxCreative Commons Attribution-ShareAlike 3.0 Unported License

4. + QScores – new family of Risk Prediction tools Individual assessment  Who is most at risk of preventable disease?  Who is likely to benefit from interventions?  What is the balance of risks and benefits for my patient?  Enable informed consent and shared decisions Population level  Risk stratification  Identification of rank ordered list of patients for recall or reassurance GP systems integration  Allow updates tool over time, audit of impact on services and outcomes This work by Julia Hippisley-Cox is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported LicenseJulia Hippisley-CoxCreative Commons Attribution-ShareAlike 3.0 Unported License

5. + Early diagnosis of cancer: The problem UK has relatively poor track record when compared with other European countries Partly due to late diagnosis with estimated 7,500+ lives lost annually Later diagnosis due to mixture of late presentation by patient (alack awareness) Late recognition by GP Delays in secondary care This work by Julia Hippisley-Cox is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported LicenseJulia Hippisley-CoxCreative Commons Attribution-ShareAlike 3.0 Unported License

6. + Why pancreatic cancer? 11 th most common cancer < 20% patients suitable for surgery 84% dead within a year of diagnosis Chances of survival better if diagnosis made at early stage Very few established risk factors (smoking, chronic pancreatitis, alcohol) so screening programme unlikely Challenge is to identify symptoms in primary care - particularly hard for pancreatic cancer

7. + Symptoms based approach Patients present with symptoms GPs need to decide which patients to investigate and refer Decision support tool must mirror setting where decisions made Symptoms based approach needed (rather than cancer based) Must account for multiple symptoms Must have face clinical validity eg adjust for age, sex, smoking, FH updated to meet changing requirements, populations, recorded data This work by Julia Hippisley-Cox is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported LicenseJulia Hippisley-CoxCreative Commons Attribution-ShareAlike 3.0 Unported License

8. + QCancer scores – what they need to do Accurately predict level of risk for individual based on risk factors and multiple symptoms Discriminate between patients with and without cancer Help guide decision on who to investigate or refer and degree of urgency. Educational tool for sharing information with patient. Sometimes will be reassurance. This work by Julia Hippisley-Cox is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported LicenseJulia Hippisley-CoxCreative Commons Attribution-ShareAlike 3.0 Unported License

9. + Methods – development algorithm Huge representative sample from QResearch aged 30-84 Identify new alarm symptoms (eg rectal bleeding, haemoptysis) and other risk factors (eg age, COPD, smoking, family history) Identify cancer outcome - all new diagnoses either on GP record or linked ONS deaths record in next 2 years Established methods to develop risk prediction algorithm Identify independent factors adjusted for other factors Measure of absolute risk of cancer. Eg 5% risk of colorectal cancer This work by Julia Hippisley-Cox is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported LicenseJulia Hippisley-CoxCreative Commons Attribution-ShareAlike 3.0 Unported License

10. + ‘Red’ flag or alarm symptoms (identified from studies including NICE guidelines 2005) Haemoptysis Haematemesis Dysphagia Rectal bleeding Vaginal bleeding Haematuria dysphagia Constipation, cough Loss of appetite Weight loss Indigestion +/- heart burn Abdominal pain Abdominal swelling Family history Anaemia Breast lump, pain, skin tethering This work by Julia Hippisley-Cox is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported LicenseJulia Hippisley-CoxCreative Commons Attribution-ShareAlike 3.0 Unported License

11. + Qcancer now predicts risk all major cancers including PancreasLung KidneyOvary Colorectal Gastro Testis Breast Prostate Blood Cervix Uterus This work by Julia Hippisley-Cox is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported LicenseJulia Hippisley-CoxCreative Commons Attribution-ShareAlike 3.0 Unported License

12. + Results – the algorithms/predictors OutcomeRisk factorsSymptoms LungAge, sex, smoking, deprivation, COPD, prior cancers Haemoptysis, appetite loss, weight loss, cough, anaemia Gastro- oeso Age, sex, smoking status Haematemsis, appetite loss, weight loss, abdo pain, dysphagia ColorectalAge, sex, alcohol, family history Rectal bleeding, appetite loss, weight loss, abdo pain, change bowel habit, anaemia PancreasAge, sex, type 2, chronic pancreatitis dysphagia, appetite loss, weight loss, abdo pain, abdo distension, constipation OvarianAge, family historyRectal bleeding, appetite loss, weight loss, abdo pain, abdo distension, PMB, anaemia RenalAge, sex, smoking status, prior cancer Haematuria, appetite loss, weight loss, abdo pain, anaemia This work by Julia Hippisley-Cox is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported LicenseJulia Hippisley-CoxCreative Commons Attribution-ShareAlike 3.0 Unported License

13. + Methods - validation is crucial Essential to demonstrate the tools work and identify right people in an efficient manner Tested performance separate sample of QResearch practices external dataset (Vision practices) at Oxford University Measures of discrimination - identifying those who do and don’t have cancer Measures of calibration - closeness of predicted risk to observed risk Measure performance – Positive predictive value, sensitivity This work by Julia Hippisley-Cox is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported LicenseJulia Hippisley-CoxCreative Commons Attribution-ShareAlike 3.0 Unported License

14. + Qcancer.org web calculator PROFILE 64 yr woman non smoker 3+unit alcohol type2 diabetes chronic pancreatitis Loss appetite and weight Indigestion Anaemia RISKS Pancreatic cancer 12% Gastrooesophageal 7% Colorectal 4% Ovarian cancer 2% Renal cancer 1% Lung cancer 2%

15. + Using QCancer in practice – v similar to QRISK2 Standalone tools a. Web calculator www.qcancer.org/2013/female/php www.qcancer.org/2013/male/php b. Windows desk top calculator c. Iphone – simple calculator Integrated into clinical system a. Within consultation: GP with patients with symptoms b. Batch: Run in batch mode to risk stratify entire practice or PCT population This work by Julia Hippisley-Cox is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported LicenseJulia Hippisley-CoxCreative Commons Attribution-ShareAlike 3.0 Unported License

16. + GP systems integration Batch processing Similar to QRISK which is in 95% of GP practices– automatic daily calculation of risk for all patients in practice based on existing data. Identify patients with symptoms/adverse risk profile without follow up/diagnosis Enables systematic recall or further investigation Systematic approach - prioritise by level of risk. This work by Julia Hippisley-Cox is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported LicenseJulia Hippisley-CoxCreative Commons Attribution-ShareAlike 3.0 Unported License

17. Project update November 2012

18. What are cancer decision support tools? Cancer decision support tools (CDS) are an aid to clinical decision-making, to assist GPs in their decisions about whether or not to refer or request further diagnostic investigation, in patients where they believe there is a risk of cancer The tools in this project display the risk of a patient having a specific type of cancer This risk is founded on analysis of historic population cohorts and their risk of having cancer based on a range of factors including symptoms, medical history and demographic data. In this project we are focusing on rollout of two existing high profile tools: 1.QCancer developed by Professor Julia Hippisley-Cox 2.The Risk Assessment Tool (RAT), developed by Professor Willie Hamilton

19. NovemberDecemberJanuaryFebruaryMarchAprilMay 2012 2013 Assimilation of QCancer and RAT into IT platform June Development of training materials Cancer network training sessions JulyAugust CDS project phase one timeline Phase one end Engagement with GP IT providers Phase one tool in use GP training rollout Data gathering for evaluation Define evaluation methodology GP practices recruited Load software onto GP systems

20. Who is involved? This project will focus on the QCancer and RAT tools Macmillan Cancer Support will lead the project, with an evaluation overseen by Cancer Research UK, and with part-funding from the Department of Health. The project forms part of the National Awareness and Early Diagnosis Initiative (NAEDI) In phase one of the project, thirteen English cancer networks will lead the rollout at a local level, working with over 650 GP practices Practices in Wales and Scotland are also planning to take part In phase one, the tool used in practice will be developed by BMJ Informatica, though it will work across a wide range of native GP IT software In parallel, the project will engage with GP software providers, to promote understanding and ensure widespread use and rollout after phase one

21. What will the tool look like? Cancer decision support tools are designed to assess the risk of a patient having an existing, but as yet undiagnosed cancer, by calculating a risk based on factors such as symptoms, medical history and demographic profile GPs will use in everyday practice an IT-based cancer decision support tool with a simple user interface which can display scores for either RAT or QCancer The tool will work in three ways: i.Reactive prompt ii.Symptom checker iii.Audit function

22. (i) Reactive prompt Working automatically in the background using READ-coded information, the tool will calculate a risk of having cancer for every patient seen in consultation. If the risk is above a certain level, a prompt will appear on screen letting the GP know that they might like to consider whether the patient might warrant a referral or investigation for a suspected cancer.

23. (ii) Symptom checker Used in consultation where READ codes are not already known, a symptom checker can be called up, which allows the GP to enter relevant symptoms, calculate a risk, and then re-enter observed symptoms into the patient’s record as a READ-coded entry.

24. (iii) Audit function An audit function will show calculated risk levels of all registered patients on a practice’s list. This can be sorted to show those calculated to have the highest risk, and used to consider whether any further action should be taken for these patients.

25. + Thank you for listening Questions & Discussion This work by Julia Hippisley-Cox is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported LicenseJulia Hippisley-CoxCreative Commons Attribution-ShareAlike 3.0 Unported License