Modelling Radiotherapy

Tim Cooper

National Cancer Action Team

NRAG Report• Deliver 40,000 fractions per mil pop by 2010; and (around) 54,000 fractions by 2016

• Deliver 8,300 fractions per Linac by 2010/11; 8,700 per Linac by 2016

• 31 days wait time standard achieved by December 2010

• Robust capital replacement programmes in place.

• All new & replacement machines capable of image guided IGRT

• National data collection is fed back to stakeholders at agreed intervals.

• Development of a workforce strategy that will deliver the required skills mix

• Implementation of the 4 tier model. Fast track career progression.

• A business case for a modern proton treatment facility in England

• Centres offer full service where operate weekends & Bank Holidays

• Extended days on 50% of machines

• Set throughput/ efficiency benchmarks.

• National overview of plans maintained.

[NB Prostate has been excluded as survival ‘gap’ is likely to be due to differences in PSA testing rates.]Data derived from Abdel-Rahman et al, BJC Supplement December 2009

Avoidable deaths pa if survival in England matched the best in Europe

Breast ~ 2000 Myeloma 250

Colorectal ~1700 Endometrial 250

Lung ~1300 Leukaemia 240

Oesophagogastric ~950 Brain 225

Kidney ~700 Melanoma 190

Ovary ~500 Cervix 180

NHL/HD 370 Oral/Larynx 170

Bladder 290 Pancreas 75

Radiotherapy as a Treatment for Cancer

Ref: IARC/WHO Lyons

Key Message – Improving Outcomes Strategy

Access to radiotherapy is critical to improving outcomes.

To improve outcomes from radiotherapy, there must be equitable access to high quality, safe, timely, protocol-driven quality-controlled services focused around patients’ needs.

Issues in Access

• Variation

• Missing patients (uptake)

Malthus will help address both

Variability

• Variation in prescribing• Commissioning for Quality• Outcomes

– Buy more fractions if the evidence is strong• MALTHUS

– Modelling– Clinical consensus

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Attendances per patient - BreastBreast Radiotherapy Attendances in 09/10 Per Patient by Cancer Network

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Variability

• Variation in prescribing• Commissioning for Quality• Outcomes

– Buy more fractions if the evidence is strong• MALTHUS

– Modelling– Clinical consensus– 20th June

Issues in Access

• Variation

• Missing patients (uptake)

Malthus will help address both

What is Malthus?

• MALTHUS project to – develop an interactive tool for radiotherapy

demand modelling in England, – establish consensus for radiotherapy prescribing

• Builds on the model used for NRAG report (2007) determining national radiotherapy requirements

• Designed to inform on radiotherapy demand for commissioning and planning purposes

MALTHUS Implementation

• Operates at local (PCT) & national level• Models RT fraction demand per 100k

population• Discrete event simulation model :

generates virtual populations of patients matching demographics of local population

• Use high quality incidence data from cancer registries & direct feeds from NCIN

• No formal health economics / cost effectiveness modelling

MALTHUS Implementation

• Appropriate rate of radiotherapy is determined from a decision tree

• Decision tree gives a fraction ‘load’ per patient

• MALTHUS uses two types of decision tree– Evidence based (revision of

CCORE type trees)– Pragmatic (based on expert

opinion and current practice)

Overview of modelMalthus tool downloaded

on PC

Curated incidence data feeds from NCAT

server

User select PCT / Region

to model Patient generator creates

matching virtual population of

patients

Breast Lung H&N Urology

∑ 35000 # for PCT

Evidence based trees

Consensus based trees

User Customised trees

DiseaseStageAgeCo-morbidity

Capacity planning• Mandated in Improving Outcomes and the

Operating Framework• Commissioners must assess the needs of

their populations• MALTHUS (Local desktop tool)

– Revision of NRAG model to take account of:

– Cancer incidence– Stage, performance status, comorbidities– Changes in treatment pathway since 2006

Deprivation and access• Lack of access and deprivation are

strongly correlated • This may be explained by

– Stage at presentation– Performance status– Co-morbidity– Fitness for radical treatment– Willingness to travel– Patient choice

• Needs individual patient data to test

Improving access• Review care pathways• Facilitate early presentation• Patient education• Boost participation in MDTs• Examine local data• Compare to local cancer incidence• Concentrate on common cancers and their

treatment

Malthus project(Monte-Carlo Application for Local Treatment and Healthcare Usage Simulation)

• High-quality local cancer incidence data• Scenario trees

– literature review of evidence base – clinical oncologists’ consensus

• Desktop application• User can adjust to local practice• Provides a commissioning tool