Skin cancer prevention in NZ school-children: a Markov cost-utility model using data from Kids’Cam automated cameras.

Project overview

Thesis title: Skin cancer prevention in NZ school-children: a Markov cost-utility model using data from Kids'Cam automated cameras.

Masters Student: Ryan Gage

Supervisors: William Leung, Associate Professor Louise Signal

Advisors: Dr James Stanley

Funding: This thesis will use data collected as part of the HRC funded Kids'Cam project and existing national survey data.

More information: Email gagry521@student.otago.ac.nz

Abstract

Aim: To estimate the cost-utility of sun-protective behaviour in NZ school-children in terms of averting skin cancer.

Background: NZ and Australia have the highest incidence rates of skin cancer in the world and, in NZ, skin cancer accounts for around 80% of total cancers. In addition to its adverse effects on morbidity and mortality, skin cancer places considerable financial strain on the health system. In 2006, for example, the direct annual costs of skin cancer were conservatively estimated to be around 57.1 million. Consequently, it may be a prudent time to identify effective strategies that could alleviate this heavy burden of skin cancer.

Data: Photos obtained from the Kids'Cam project will be used to examine children's sun exposure and sun-protective behaviours. Data will be assessed for one female and one male from each of the 26 schools participating in the Kids'Cam study. This study will only utilise data from terms 1 and 4 (summer time).

Analysis: The photos will be analysed using a semi-automated annotation system which utilises image recognition software and requires partial manual annotation. TreeAge software will be used for the cost-utility analysis of skin cancer prevention strategies, such as providing free sun-protective clothing or sunscreen for school-children. Probabilistic sensitivity analysis will assess the joint uncertainty of input parameters. Results will be reported using incremental cost-effectiveness ratios (ICERs) and cost-effectiveness acceptability curves.