Mapping laboratory reports for molecular genetic testing to the National Cancer Registration and Analysis Service (NCRAS)

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• Josephine French, Health Data Insight
• Tuesday 13 February 2018, 13:00-14:00
• MR3 Centre for Mathematical Sciences.

If you have a question about this talk, please contact Dr Vivien Gruar.

Background:

Many tumours undergo molecular genetic and cytogenetic testing in NHS specialist laboratories in order to define which mutations or rearrangements underlie the malignant behaviour of the cells. These molecular tests are a key part of diagnosis and subtyping for many tumour types (e.g. brain tumours, sarcomas, paediatric cancers, and haematological malignancies), and some molecular aberrations can provide key information on the patient’s likely prognosis. Furthermore, in an increasing number of tumours (e.g. lung, colorectal, melanoma, gastrointestinal stromal tumours), molecular tests are used to identify mutations or rearrangements which can predict a clinical response to targeted therapies. This enables treatment to be personalised to the patient and to the specific biology of their tumour.

The Project:

The National Cancer Registration and Analysis Service (NCRAS) is collecting molecular data from tumour testing directly from pathology and regional molecular genetics laboratories across England. Data from each laboratory arrives in a different format, with little consistency between laboratories, and different labs carry out different tests. Most of the labs performing these tests have been identified; however, not all are yet supplying data to NCRAS .

All source data from the labs needs to be mapped to a specific format, contained within three genetics tables in the NCRAS database. Data is processed by a combination of computational mapping and registration by hand; however computational mapping is the preferred route where possible.

The project is likely to involve a combination of creating mapping documents to show how source data can be mapped and transformed to the unified structure, and scripting code, into which these rules are embedded, using Yet Another Mark-up Language (YAML). There may also be an element of liaising with source laboratories to clarify any ambiguities within the data, and to improve the data quality where necessary.

Outputs:

The exact outputs will be agreed with the intern at the outset of the project, and will depend upon overall progress with the genetics data programme and the specific skills and interests that the intern can contribute to the work.

The project will make a tangible difference to ongoing work looking at equity of access to molecular tumour testing within the NHS , and will be of interest to CRUK , NHS providers and commissioners.

For more information about the internship programme, visit: https://healthdatainsight.org.uk/cancer-data-internships-2018/

This talk is part of the Cambridge Mathematics Placements Seminars series.

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• MR3 Centre for Mathematical Sciences

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