What can we learn from international healthcare systems to improve early cancer diagnosis in primary care?

Chair: Prof Jon Emery Speakers: Prof David Weller, Prof Peter Vedsted, Prof Lyndal Trevena, Prof Surendra Shastri Session code: CTS.4.32

www.worldcancercongress.org

Overview 1. Health service initiatives in the United Kingdom David Weller, University of Edinburgh 2. Health service initiatives in Denmark Peter Vedsted, Aarhus University 3. Community symptom awareness campaigns Jon Emery, University of Melbourne 4. Symptom risk assessment tools for primary care Lyndal Trevena, University of Sydney 5.  How applicable are these system initiatives to low and middle income countries? Surendra Shastri, Tata Memorial Hospital 6. Discussion

Model of Pathways to Treatment

Walter, Scott, Webster, Emery. JHSRP 2011

Healthcare system delays

Olesen BJC 2009

Prof David Weller

What can we learn from international healthcare systems to improve early cancer diagnosis in primary care:

Health service initiatives in Denmark Peter Vedsted

Professor, Director Research Centre for Cancer Diagnosis in Primary Care – CaP The Research Unit for General Practice Aarhus University Denmark

www.cap.au.dk

[email protected]

Health care system in Denmark Tax-financed with free medical care Primary care (GPs) is first line with a patient list of 1600 •  Gatekeepers to hospitals and specialists Family medicine is a speciality as every other medical speciality A Dane on average contacts the GP 8 times per year (4 faceto-face)

Denmark did badly: survival, stage and waiting

‘It all starts in primary care…’ More than 75-85% of cancers are seen in primary care 90% of cancers are diagnosed based on symptoms 5-8% of cancers are found with screening (at the moment)

Allgar et al. British Journal of Cancer 2005;92:1959–70 Hansen et al. BMC Health Serv Res. 2011;11:284. Emery JD, et al. Nat Rev Clin Oncol. 2014;11:38-48. Vedsted P, et al. Scand J Prim Health Care. 2009;27:193-4.

Following 6% of consultations, GPs suspected a serious disease 10% of these patients got a serious disease in 2 months Hjertholm P, et al. Br J Gen Pract 2014

Three groups of symptoms at presentation Symptom  

%  

Alarm  symptom  

50  

Serious,  unspecific  

20  

Uncharacteris:c,  vague  

30  

Jensen H, et al. BMC Cancer 2014;14:636 Nielsen T, el al. Ugeskr Læger. 2010;172:2827-31

Need for a 3-legged diagnostic strategy Alarm symptom (the obvious) •  Urgent referral investigations for a specific cancer Unspecific, serious symptoms (the difficult) •  Diagnostic centre – fast multidisciplinary assessment Vague symptoms (the common) •  Quick and direct access to investigations (e.g. ultrasound) - Vedsted, Olesen. Early diagnosis of cancer--the role of general practice. Scand J Prim Health Care. 2009;27:193-4. - Olesen, Hansen, Vedsted. Delay in diagnosis: the experience in Denmark. Br J Cancer. 2009 Dec 3;101 Suppl 2:S5-8. -  Rubin, Vedsted, Emery. Improving cancer outcomes: better access to diagnostics in primary care could be critical. Br J Gen Pract. 2011;61:317-8. -  Jensen H, et al. Cancer suspicion in general practice, urgent referral and time to diagnosis. BMC Cancer. 2014;14:636

The urgent referral for specific cancer If the GP suspects cancer (a list of symptoms and signs) Has given shorter diagnostic intervals (for some) 40% are diagnosed through urgent referral in DK 60% are not diagnosed using the expedited route! - Meechan D et al. BrJGP 2012 DOI: 10.3399/bjgp12X654551. - Elliss-Brookes et al. BrJCan 2012, 1220–1226. - Jensen H et al. BMC Cancer 2014;

Urgent referral to diagnostic centres If the GP cannot allocate the patient to a specific alarm route The GP performs a filter function: •  Imaging and blood samples within 2 days •  If no explanation, then referral and seen within 2 days A multidisciplinary team of specialists at hospital Outpatient ‘pit-stop’

The first results from diagnostic centres 50% from the GP filter function is referred to diagnostic centre 16% of those referred get a cancer diagnosis

The first results from diagnostic centres Cervix,  ovarian  and   uterus  cancer,  3%   Bladder  cancer,  4%   Esophagus  and   stomach  cancer,  4%  

Lung  cancer,  19%  

Breast  cancer,  4%   Metastasis;  5%  

Hematopoietic  cancer;   15%  

Kidney  cancer  ,  5%   Liver  and  biliary   system  cancer,  6%   Prostate  cancer,  7%   Pancreatic  cancer,  8%  

Colorectal  cancer,   12%   Ingeman  ML,  et  al.  Under  prepara2on  

Direct access to investigations Implemented as ‘No-Yes-Clinics’ (NYC) For the ‘low-risk-but-not-no-risk’ group GPs have direct access to expedited investigations •  Ultrasonic investigation of abdomen, pelvis, CT, endoscopy The GP is fully responsible No record, history taking etc. at clinic – only a No or a Yes!

Direct access to abdominal ultrasonic investigation Suspected cancer (n=43) Same-day investigation

Cancer risk = 28%

(n=434) Cancer risk = 5.3%

No suspicion of cancer (n=391) Cancer risk = 2.8% Ingeman ML, et al. 2014 (under publication)

The 3-legged strategy for cancer diagnosis §  Alarm  symptom  (the  obvious)   §  Urgent  referral,  specific  cancer   §  Serious,  unspecific  symptoms    (the  difficult)   §  Diagnos8c  centre   §  Vague  symptoms  (the  common)   §  Quick  and  direct  access  

Thank you

What can we learn from international healthcare systems to improve early cancer diagnosis in primary care:

Community symptom awareness campaigns

Jon Emery Herman Professor of Primary Care Cancer Research University of Melbourne Director of PC4

Evidence for effect of symptom awareness campaigns?

In progress

Effect on early presentation (Austoker et al 2009) Reference

Cancer

Country

Outcome

Catalano 2000

Breast

USA

790 additional cases over 23 yrs

Gabram 2008

Breast

USA

14% increase stage 0 and 8% reduction stage IV

MacKie 2003

Melanoma

Scotland

34% increase thick melanomas

Rossi 2000

Melanoma

Italy

Mean thickness reduced by 0.5mm

Geczi 2001

Testicular

Hungary

No change in time to diagnosis

Leander 2007

Retinoblastoma

Honduras

38% reduction in advanced disease

Lung cancer awareness campaigns Athey et al 2012: •  Campaign plus GP intervention •  20% increase CXRs •  27% increase lung cancer diagnoses

Be Clear on Cancer (UK) •  30% increase in urgent referrals for suspected lung cancer •  9.1% increase in lung cancer diagnoses during campaign months •  Significant shift towards earlier stage distribution for NSCLC. http://www.england.nhs.uk/wp-content/uploads/ 2013/12/be-clear-cancer.pdf

The Improving Rural Outcomes Trial

IRCO Trial Find Cancer Early Campaign Computer-assisted telephone survey Timing: 18 months into campaign Sample size: 725 intervention, 725 control regions Stratified by age and gender 71% participation rate 94% response rate

Awareness of Find Cancer Early 100.0% 80.0% 60.0%

43.30%

0.0%

Prompted recognition 31.60%

40.0% 20.0%

Not aware

83.40%

Recognition Recall

7.60% 8.80% 0.10% Control regions

21.60% 3.50% Campaign regions

Symptom awareness     Coughing up blood   A cough or croaky voice  

Campaign   n   %   56   7.7   53   7.3  

n   51   38  

%   7.0   5.2  

Becoming more short of breath  

39  

5.4  

40  

5.5  

Blood in your pee   Blood in your poo   Problems peeing   Looser poo (diarrhoea)  

128   227   29   44  

17.6*   31.3*   4.0   6.1  

60   136   22   40  

8.3*   18.7*   3.0   5.5  

Unusual pain, lump or swelling  

464  

63.9*  

425  

58.5*  

Unexplained weight loss  

157  

21.6  

140  

19.3  

Control  

* P < 0.05

The Improving Rural Outcomes Trial •  2x2 factorial design •  Symptom awareness campaign •  GP intervention •  Primary outcome: time to diagnosis •  1351 cancer patients recruited •  Data analysis in progress

Prof Lyndal Trevena

What can we learn from international healthcare systems to improve early cancer diagnosis in primary care:

Symptom risk assessment tools for primary care A/Prof Lyndal Trevena Head Discipline of General Practice Sydney School of Public Health University of Sydney, Australia Chair Prevention and Early Diagnosis Scientific Working Group, PC4

The dilemma for primary care Symptoms are poor predictors of cancer BUT… Most cancer patients present in primary care SO… Can we be more systematic about finding the ‘needle in the haystack’? 4th December, 2014

What are risk assessment tools? Usually an algorithm that combines a number of ‘risk factors’ (or ‘symptoms’) for the disease of interest They provide an estimate of the ‘chance’ of having (or getting) the disease of interest now (or over a period of time) Risk assessment tools based on risk factors have been around for some time (e.g. Gail model for breast cancer risk) Usually a paper-based chart or web-based tool. Some have been integrated to GP software http://canceraustralia.gov.au/affected-cancer/cancer-types/breast-cancer/ your-risk/calculate

4th December 2014

The relationship between pre-test probability (risk assessment) and the utility of a ‘test’

Positive LR chest CT for lung cancer if >30mm nodule is found on CXR = 3.7

Clinician estimates of pre-test probabilities vary widely Three clinical scenarios given to 500 physicians and 500 GPs randomly selected from NSW College registers; also sent to 205 physicians and 202 GPs randomly sampled from UK college equivalents (2001) 60% and 57% response rates Australia and UK respectively 1.  Chest pain and risk of IHD (54% were within 20 percentage points) 2.  Risk of DVT (only 6.7% within 20 percentage points) 3.  AF and risk of stroke (57% within 20 percentage points) UK results were very similar to Australian Physicians were generally more accurate than GPs but the spread of estimates was similarly wide between cardiologists and GPs This is consistent with studies that clinical decision rules out-perform even expert clinicians (Attia et al MJA 2001)

Clinical decision rule for diagnosing influenza

Ebell et. al. J Am Board Fam Med 2012

4th December 2014

QCancer: A tool to predict the chance (pre-test probability) of having cancer given a set of symptoms Uses GP-based data from a representative cohort of 2.5 million men and women aged 25-89 years in UK Predicts global cancer risk and 12 cancer types (which account for 85% all cancers) Symptom rather than cancerbased (same symptom can occur in several cancers www.qcancer.org 4th December 2014

Risk Factors and Symptoms included in Qcancer Algorithm Risk Factors Age & sex Smoking status Deprivation score Family history of cancer COPD Endometrial hyperplasia/polyp Chronic pancreatitis Type 2 diabetes Anaemia (HB < 11g/DL) Venous thromboembolism

Symptoms Haemoptysis Haematemesis Haematuria Rectal bleeding Haematuria Unexplained bruising Constipation, cough Vaginal bleeding (women) Testicular lump (men) Loss of appetite Unintentional weight loss Indigestion +/- heart burn Dysphagia Abdominal pain or swelling Breast lump, pain, skin Night sweats Neck lump Urinary symptoms (men)

How accurate is QCancer?

Threshold for investigating??

Can these tools be implemented in primary care practice? The CAPER tools are derived from a series of case–control studies using data from a national general practice database in the UK, which estimate the positive predictive value of symptoms, signs and common investigations, singly and in combination, for a wide range of cancers. 4th December 2014

Evaluation of CAPER tools for lung and colorectal cancer in 28 UK general practices GPs were given the tools as mouse-mats or flipcharts No advice given about what risk-level to investigate Outcome was 2 –week referral or CXR (for lung cancer), number of RATs used and subsequent investigations and referrals Hamilton et. al Br J Gen Pract Jan 2013

4th December 2014

More lung and colorectal cancers were diagnosed at what cost? New lung cancer diagnoses increased from 127 in the 6 months before the evaluation to 174 during the pilot (47 extra cases). The proportion of stage 1 and stage 2 cancers combined (as a proxy for potential cure) increased by 19% (from 26 to 31). New colorectal cancers increased by from 134 to 144 (10 extra cases). No significant change in staging was seen (data not shown).

There was an increase in 2wk referral for lung cancer from 332 to 436 (104 extra referrals) and a 4% increase in CXRs There was an increase in 2 week referrals for colorectal cancer from 1173 to 1477 (304 extra referrals) and increase in colonoscopies from 1762 to 2032 (270 extra colonoscopies)

4th December 2014

Australian study with 15 GPs using QCancer The risk tool was perceived as potentially useful for patients with complex histories. More experienced GPs were distrustful of the risk output, especially when it conflicted with their clinical judgement. Variable interpretation of symptoms meant there was a significant variation in risk assessment. When a risk output was high, GPs were confronted by numerical risk outputs creating challenges in the consultation 4th December 2014

GPs more likely to refer…implications? ‘Mid-project we looked at our numbers and we felt that under the clause, would you have referred this patient if you hadn’t been using the risk assessment tool, there was a significant minority that said, you know, the tool had pushed them to a different decision ... it was 10–15% of people that may have waited longer if they hadn’t had the tool.’ (GPL/2) ‘I think our referral thresholds for lower GI have definitely gone down.’ (GPL/3) ‘I’d say particularly it got us thinking about patients with COPD, because, um, there’s a bit in the, ah, in the lung tool which is smokers with COPD saying they automatically should have a referral for a chest X-ray, and that made us think about how frequently we should do chest X-rays in our COPD patients.’ (GPL/8) Chiang et al. (in press BJC) 4th December 2014

These findings are similar for implementation of other risk assessment tools in general practice Five communication strategies used: 1.  AR-focused strategy, used when AR assessment was considered useful for the patient; 2.  AR-adjusted strategy, used to account for additional risk factors such as family history 3.  Clinical judgement strategy, used when GPs considered that their judgement took multiple risk factors into account as effectively as AR; 4.  Passive disregard strategy, used when GPs lacked sufficient time, access or experience to use AR; 5.  Active disregard strategy, used when AR was considered to be inappropriate for the patient. Bonner et. al. MJA 2013

4th December 2014

..and there is an ever-increasing number of risk assessment tools being developed for primary care

Strengths and limitations of RATs for cancer diagnosis in primary care Potential for more rational testing and investigation Early evidence for earlier diagnosis if linked to fast-track referrals for some cancers

Uncertainty about which tool to use Lack of ‘trust’ by providers The plethora of tools not linked to clinical reasoning processes & guidelines Lack of evaluation of the impact on ‘over-testing’, ‘over-investigation’ and ‘missed cancers’ versus ‘tests avoided’ and ‘improved cancer outcomes’ Need for improvement in user interface Need for guidance on thresholds for testing 4TH December 2014

Prof Surendra Shastri

Low and Middle Income Countries Perspective

Prof Surendra Shastri Tata Memorial Centre Mumbai, India

Shastri, A. and S. S. Shastri (2014). "Cancer screening and prevention in low-resource settings.“ Nat Rev Cancer 14(12): 822-829. Dec 4, 2014

Disease Burden In 2012, less-developed-region countries (LDCs) contributed 57% and 65% to the global cancer incidence and mortality, respectively Ferlay, J. et al. GLOBOCAN 2012 v1.0, Cancer Incidence and Mortality Worldwide: IARC CancerBase No. 11. International Agency for Research on Cancer [Online] http://globocan.iarc.fr (2013).

Disease Spectrum q  Cancers that are caused by infectious agents (that is, cancers of the cervix, liver and stomach) continue to have the highest incidence and mortality in these countries. q  Cancers that are related to lifestyle and environmental factors (that is cancers of the lung, breast, prostate and colon–rectum) are now appearing as the top cancers in Africa, Asia and Latin America

Challenges q  No health insurance q  Lack of trained manpower (physicians, nurses, technicians, pathologists, radiologists) q  Lack of basic infrastructure (laboratories, screeningdiagnostic facilities) q  Large populations coupled with poor resources q  Poor health awareness and health seeking behavior

So what do we see q  Over 70% of the cancers report to a treatment centre at advanced stages q  High treatment costs and disproportionately high mortality rates

Examples q  No screening for cervical cancer: Cytology-based screening is not feasible q  No screening for breast cancer : Mammography screening is not feasible; population is young

Are developed country models/systems applicable to low resource settings? q  Cannot be just replicated; need to be suitably modified and adapted to circumstances q  Appropriate and feasible models need to be developed q  Invest in manpower and infrastructure development for low cost interventions; health awareness; legislations to protect people’s health

Examples of models for low resource settings? q  Visual inspection with acetic acid; low cost HPV-DNA screening for cervical cancer q  Physical breast examination by primary health care providers for breast screening q  Awareness programmes and increased taxation for tobacco control Shastri, S. S. et al. Effect of VIA screening by primary health workers: randomized controlled study in Mumbai, India. J. Natl Cancer Inst. 106, dju009 (2014). Sankaranarayanan, R. et al. HPV screening for cervical cancer in rural India. N. Engl. J. Med. 360, 1385–1394 (2009).

VIA  Nega:ve   VIA  Chart  developed  by  IARC     Acetowhite  areas  far   Faint  acetowhite   Line-­‐like   Streak-­‐like   away  from  the  TZ  

areas  without  a   sharp  outline    

  acetowhitening    

VIA  Posi:ve  

acetowhitening    

Dot-­‐like  pale   areas  in  the   endocervix  

Thick  well-­‐defined  acetowhite  areas,  near  the  Transforma:on  Zone   (TZ)  either  on  the  endocervix  or  ectocervix  (or  both)  are  VIA  posi:ve  

Thank You for Your Attention

65

Questions and Discussion •  •  •  • 

Questions to speakers Other international examples of policy initiatives How context specific are these types of intervention? Could any of these be applicable to your own country and how? •  How well developed a primary care system is needed to make them work?