Google as a cancer control tool in Queensland

Xiaodong Huang; Peter Baade; Danny R Youlden; Philippa H Youl; Wenbiao Hu; Michael G Kimlin

doi:10.1186/s12885-017-3828-x

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Google as a cancer control tool in Queensland

Journal article

Open access

Peer reviewed

Google as a cancer control tool in Queensland

Xiaodong Huang, Peter Baade, Danny R Youlden, Philippa H Youl, Wenbiao Hu and Michael G Kimlin

BMC Cancer, Vol.17, 816

2017

DOI: https://doi.org/10.1186/s12885-017-3828-x

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Abstract

Google trends

search volume indexes

cancer incidence

age standardised rates

cross-correlation

Background: Recent advances in methodologies utilizing "big data" have allowed researchers to investigate the use of common internet search engines as a real time tool to track disease. Little is known about its utility with tracking cancer incidence. This study aims to investigate the potential correlates of monthly internet search volume indexes (SVIs) and observed monthly age standardised incidence rates (ASRs) for breast cancer, colorectal cancer, melanoma and prostate cancer. Methods: The monthly ASRs for the four cancers in Queensland were calculated using data from the Queensland Cancer Registry between January 2006 and December 2012. The monthly SVIs of the respective cancer search terms in Queensland were accessed from Google Trends for the same period. A time series seasonal decomposition method was performed to detect the seasonal patterns of SVIs and ASRs. Pearson's correlation coefficient and time series cross correlation analysis were used to assess the associations between SVIs and ASRs. Linear regression models were used to examine the power of SVIs to predict monthly in ASRs. Results: Increases in the monthly ASRs of the four cancers were significantly correlated with increases in the monthly SVIs of the respective cancers except for colorectal cancer. The predictive power of the SVIs to explain variances in the corresponding ASRs varied by cancer type, with the percent explained ranging from 5.6% for breast cancer to 17.9% for skin cancer (SVI) with melanoma (ASR). Some improvement in the variation explained was obtained by including more search terms or lagged SVIs for the respective cancers in the linear regression models. The seasonal analysis indicated that the SVIs peaked periodically at around their respective cancer awareness months. Conclusions: Using SVIs from a popular internet search engine was only able to explain a small portion of changes in the respective ASRs. While an expanded regression model explained a higher proportion of variability, the interpretation of this was difficult. Further development and refinement of this approach will be needed before search--based cancer surveillance can provide useful information regarding resource deployment to guide cancer control and track the impact of cancer awareness and education programmes.

Details

Title: Google as a cancer control tool in Queensland
Authors: Xiaodong Huang (Author) - University of the Sunshine Coast - Faculty of Science, Health, Education and Engineering
Peter Baade (Author) - Cancer Council of Australia
Danny R Youlden (Author) - Cancer Council of Australia
Philippa H Youl (Author) - University of the Sunshine Coast - Faculty of Science, Health, Education and Engineering
Wenbiao Hu (Author) - Queensland University of Technology
Michael G Kimlin (Author) - University of the Sunshine Coast - Faculty of Science, Health, Education and Engineering
Publication details: BMC Cancer, Vol.17, 816; 9
Publisher: BioMed Central Ltd.
Date published: 2017
DOI: 10.1186/s12885-017-3828-x
ISSN: 1471-2407
Copyright note: Copyright © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated
Organisation Unit: University of the Sunshine Coast, Queensland; School of Health and Sport Sciences - Legacy
Language: English
Record Identifier: 99451048202621
Output Type: Journal article

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Web Of Science research areas: Oncology

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