ArticleJournal of medical Internet research2020
Detecting Lung Cancer Trends by Leveraging Real-World and Internet-Based Data: Infodemiology Study.
Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Infectious Disease Surveillance in the Era of Big Data and AI: Opportunities and Pitfalls.Cureus · 2025Review
- Improving Awareness of Lung Cancer Screening, Lung-RADS, and Fleischner Society Guidelines: A Critical Review.Clinical journal of oncology nursing · 2025Review
- Identifying sarcoidosis trends using web search and real-world data in Sweden: a retrospective longitudinal study.Scientific reports · 2024Article
- Cancer incidence and digital information seeking in Germany: a retrospective observational study.Scientific reports · 2024Observational
- Online information-seeking behavior of Iranian web users on Google about Henoch-Schönlein purpura (HSP): an infodemiology study.BMC health services research · 2023Article
- Big Data and Infectious Disease Epidemiology: Bibliometric Analysis and Research Agenda.Interactive journal of medical research · 2023Article
- Seasonal Variation for Plantar Fasciitis: Evidence from Google Trends Search Query Data.Healthcare (Basel, Switzerland) · 2022Article
- Searching for HIV and AIDS Health Information in South Africa, 2004-2019: Analysis of Google and Wikipedia Search Trends.JMIR formative research · 2022Article
- Modeling COVID-19 incidence with Google Trends.Frontiers in research metrics and analytics · 2022Article
- Article
- Dupuytren's Contracture: The Readability of Online Information.Journal of patient experience · 2021Article
- Social Media as a Research Tool (SMaaRT) for Risky Behavior Analytics: Methodological Review.JMIR public health and surveillance · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInternet search data on health-related terms can reflect people's concerns about their health status in near real time, and hence serve as a supplementary metric of disease characteristics. However, studies using internet search data to monitor and predict chronic diseases at a geographically finer state-level scale are sparse.
objectiveThe aim of this study was to explore the associations of internet search volumes for lung cancer with published cancer incidence and mortality data in the United States.
methodsWe used Google relative search volumes, which represent the search frequency of specific search terms in Google. We performed cross-sectional analyses of the original and disease metrics at both national and state levels. A smoothed time series of relative search volumes was created to eliminate the effects of irregular changes on the search frequencies and obtain the long-term trends of search volumes for lung cancer at both the national and state levels. We also performed analyses of decomposed Google relative search volume data and disease metrics at the national and state levels.
resultsThe monthly trends of lung cancer-related internet hits were consistent with the trends of reported lung cancer rates at the national level. Ohio had the highest frequency for lung cancer-related search terms. At the state level, the relative search volume was significantly correlated with lung cancer incidence rates in 42 states, with correlation coefficients ranging from 0.58 in Virginia to 0.94 in Oregon. Relative search volume was also significantly correlated with mortality in 47 states, with correlation coefficients ranging from 0.58 in Oklahoma to 0.94 in North Carolina. Both the incidence and mortality rates of lung cancer were correlated with decomposed relative search volumes in all states excluding Vermont.
conclusionsInternet search behaviors could reflect public awareness of lung cancer. Research on internet search behaviors could be a novel and timely approach to monitor and estimate the prevalence, incidence, and mortality rates of a broader range of cancers and even more health issues.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.