Greg RubinProfessor of General Practice and Primary Care

University of Durham

How can primary care contribute?Early diagnosisCare of survivorsScreening

Allgar and Neal, BJ Cancer 2005

Cancer mortality in relation to time to diagnosisSecondary analysis of three cohorts: colorectal

(349), lung (247) and ovarian (212)These were part of larger case-control studiesAll symptoms reported to their GPs before

diagnosis noted from the recordsSymptoms associated with cancer identifiedThe first symptom in the final year notedSurvival identified from cancer registry, and

from practices

Hamilton et al. In submission

AnalysesCox proportional hazards analyses, in

individual cancer sites and then in the merged dataset

Main explanatory variable - the interval between first symptom in GP records and diagnosis

The cohorts

Colorectal Lung Ovary

Case numbers

Total 349 247 212

No symptom before diagnosis 30 25 29

With no recorded survival 0 5 1

With duration and survival 319 217 182

Characteristics of cases with symptom duration and survival available (n=718)

Area Exeter Exeter Devon

Year of diagnosis 1998-2002 1998-2002 2000-2007

Median (IQR) age at diagnosis 73 (65, 80) 68 (59, 78) 73 (65, 77)

Median (IQR) symptom duration 97 (44, 218) 78 (36, 179) 122 (50, 266)

Months final survival recorded Oct-Dec 05 Jun-Aug 08 Jun-Aug 08

Minimum follow up of survivors 368 days 194 days 269 days

Maximum follow up of survivors 2895 days 3282 days 3105 days

Results: survival by quartiles

Combined0.

000.

250.

500.

751.

00

0 1000 2000 3000 4000Survival in days

Colorectal

0.00

0.25

0.50

0.75

1.00

0 1000 2000 3000Survival in days

Lung

0.00

0.25

0.50

0.75

1.00

0 1000 2000 3000 4000Survival in days

Ovary

0.00

0.25

0.50

0.75

1.00

0 1000 2000 3000Survival in days

Blue: shortest duration, then red, green, and yellow longest

Results: survival by deciles.5

11

.52

Haz

ard

rat

io

0 10 20 30 40 50Symptom duration in weeks

Hazard ratio fitted Hazard ratio by deciles (95% CI)

Interpretation The excess mortality associated with

very early diagnosis is only present for the first two deciles. Only 20% of the cohort suffers this diagnostic paradox.

Mortality is fairly flat up to the 7th decile, so perhaps 30% of the cohort suffers from a delayed diagnosis with a worse prognosis.

The rise for this 30% is quite steep. The decile bands widen progressively,

showing that most patients have a relatively “early” diagnosis.

If we remove the “easy” 20%

The Cox model becomes very simple, with one linear term (p=0.013)

The coefficient for each week of symptoms is 1.0086, equating to an approximate 1% worsening of prognosis for each eight days of symptoms.

The size of the effectPrognosis worsens by 1% each 8 days of

GP “delay”, or 3.8% for a month.This is a similar size of effect that one

sees with adjuvant chemotherapyIt improves the evidence base for the

importance of early diagnosis.

Mitchell et al, BJ Cancer 2008

Detection of relapseDewar and Kerr (BMJ 1985)

546 women with breast cancer, 192 first relapses>50% were interval events

Grunfeld et al (BMJ 1996)296 women with breast cancer randomised to

primary or secondary care follow up26 relapses18/26 were interval events7/16 relapses in the 2y care are presented first to

their GP

Contribution of co-morbidity to mortality2 out 3 patients with cancer have a co-

morbidityA third of these have 2 or more co-

morbidities (Ogle et al Cancer 2000)

All cancer survivors (breast, colon and prostate) and controls in the GPRD – Total Charlson score Rose et al, unpublished

Heart failure

*Adjusted for BMI, smoking Matched to non-cancer survivor controls on the basis of age, sex and practice

OR: 1.33

Diabetes

*Adjusted for BMI Matched to non-cancer survivor controls on the basis of age, sex and practice

OR: 1.22

HbA1c control

*good control of HbA1c used as reference category

Interventions to increase use of cancer screeningEffectiveness of intervention components

Organisational change (OR 2.47 to 17.6)Patient reminder (OR 1.74 to 2.75)Provider education (OR 3.01) (BCS only)

Effects of the presence of key intervention featuresCollaboration and teamwork (OR 1.2 to 9.21)Learning strategies (OR 1.27 – 5.25)

Primary care: the front line in the war against cancer (Wender 2007)

Having a health care advocate and co-ordinator of care improves outcomes (Starfield Millband Q 2005)

This is likely to be of particular importance for those on the wrong end of health inequalities

Primary care availability is associated with higher rates of early detection for breast, cervical and colorectal cancer (Roetzheim, J Fam Pract 1999)

So what’s the agenda?Understanding the interval from presentation

to diagnosis, and its component partsBetter understanding of its relationship to

stage and outcomeBasing service innovation on this evidenceStrategies to address inequalitiesNew models of follow-up careManagement of co-morbiditiesThe role of primary care in screening

programmes