Data mining in oncology: The ukCAT project and the practicalities of working with routine patient data

Gareth Price; Marcel Van Herk; Corinne Faivre-Finn

doi:10.1016/j.clon.2017.07.011

Data mining in oncology: The ukCAT project and the practicalities of working with routine patient data

Gareth Price, Marcel Van Herk, Corinne Faivre-Finn

Division of Cancer Sciences (L5)

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Abstract

Randomised controlled trials (RCTs), and meta-analyses of multiple trials, are considered the pinnacle of medical scientific evidence [1] that should underpin the treatment guidelines used in clinical practice. However, for some time now there has been concern around the generalisability of clinical trial results to the general patient population (e.g. [2–4]). Trial selection criteria, designed to eliminate confounding factors from analysis, favour younger and healthier patients and therefore data are scarce for the elderly and for patients with multiple comorbidities.

Original language	English
Journal	Clinical Oncology
Early online date	3 Aug 2017
DOIs	https://doi.org/10.1016/j.clon.2017.07.011
Publication status	Published - 2017

Keywords

Data mining
radiotherapy
; clinical outcome prediction
big data
; oncology decision support

Research Beacons, Institutes and Platforms

Manchester Cancer Research Centre

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10.1016/j.clon.2017.07.011

ClinicalOncologyEditorial_ukCAT_r1_SubmittedAccepted author manuscript, 420 KB

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title = "Data mining in oncology: The ukCAT project and the practicalities of working with routine patient data",

abstract = "Randomised controlled trials (RCTs), and meta-analyses of multiple trials, are considered the pinnacle of medical scientific evidence [1] that should underpin the treatment guidelines used in clinical practice. However, for some time now there has been concern around the generalisability of clinical trial results to the general patient population (e.g. [2–4]). Trial selection criteria, designed to eliminate confounding factors from analysis, favour younger and healthier patients and therefore data are scarce for the elderly and for patients with multiple comorbidities.",

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AB - Randomised controlled trials (RCTs), and meta-analyses of multiple trials, are considered the pinnacle of medical scientific evidence [1] that should underpin the treatment guidelines used in clinical practice. However, for some time now there has been concern around the generalisability of clinical trial results to the general patient population (e.g. [2–4]). Trial selection criteria, designed to eliminate confounding factors from analysis, favour younger and healthier patients and therefore data are scarce for the elderly and for patients with multiple comorbidities.

KW - Data mining

KW - radiotherapy

KW - ; clinical outcome prediction

KW - big data

KW - ; oncology decision support

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JO - Clinical Oncology

JF - Clinical Oncology

ER -

Data mining in oncology: The ukCAT project and the practicalities of working with routine patient data

Abstract

Keywords

Research Beacons, Institutes and Platforms

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