Greg Rubin Professor of General Practice and Primary Care University of Durham

How can primary care contribute? Early diagnosis Care of survivors Screening

The size of the delay problem Allgar and Neal, BJ Cancer 2005

Cancer mortality in relation to time to diagnosis Secondary analysis of three cohorts: colorectal (349), lung (247) and ovarian (212) These were part of larger case-control studies All symptoms reported to their GPs before diagnosis noted from the records Symptoms associated with cancer identified The first symptom in the final year noted Survival identified from cancer registry, and from practices Hamilton et al. In submission

Analyses Cox 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 ColorectalLungOvary Case numbers Total No symptom before diagnosis With no recorded survival051 With duration and survival Characteristics of cases with symptom duration and survival available (n=718) AreaExeter Devon Year of diagnosis Median (IQR) age at diagnosis73 (65, 80)68 (59, 78)73 (65, 77) Median (IQR) symptom duration97 (44, 218)78 (36, 179)122 (50, 266) Months final survival recordedOct-Dec 05Jun-Aug 08 Minimum follow up of survivors368 days194 days269 days Maximum follow up of survivors2895 days3282 days3105 days

Results: survival by quartiles Blue: shortest duration, then red, green, and yellow longest

Results: survival by deciles

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 , equating to an approximate 1% worsening of prognosis for each eight days of symptoms.

The size of the effect Prognosis 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 chemotherapy It improves the evidence base for the importance of early diagnosis.

Influences on practitioner delay Mitchell et al, BJ Cancer 2008

Detection of relapse Dewar 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 up 26 relapses 18/26 were interval events 7/16 relapses in the 2y care are presented first to their GP

Contribution of co-morbidity to mortality 2 out 3 patients with cancer have a co-morbidity A 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 screening Effectiveness 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 features Collaboration 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 parts Better understanding of its relationship to stage and outcome Basing service innovation on this evidence Strategies to address inequalities New models of follow-up care Management of co-morbidities The role of primary care in screening programmes