ArticleAsian Pacific journal of cancer prevention : APJCP2021
A Google Trends™ Analysis of Bladder Cancer: Determining Awareness Campaign Success, and Patients' Needs in Clinical Management.
Article in Asian Pacific journal of cancer prevention : APJCP, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Characteristics, Uses, and Biases of Studies Related to Malignancies Using Google Trends: Systematic Review.Journal of medical Internet research · 2023Pooled it
- Assessment of internet data on orthodontic treatment and oral hygiene in the Marmara region using Google Trends:a methodological study.European oral research · 2025Article
- Are health awareness months dedicated to urological and men's health diseases effective at increasing public interest? A Google Trends study.Indian journal of urology : IJU : journal of the Urological Society of IndiaArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveWe aimed to determine the interest and changing trends over time in the diagnosis and treatment of bladder cancer and its awareness campaign by examining the Google Trends application as an indicator of people's interest globally.
methodsUsing the Google Trends application, we determined the yearly and country-based relative search volumes of the term "bladder tumor" and of the methods used in the diagnosis and treatment of bladder cancer in the period from January 2004 to December 2019. We compared the median relative search volumes found in the period 2004-2011 (Period 1) with those found in the period 2012-2019 (Period 2).
resultsWe found that the median relative search volume for bladder cancer decreased in period 2 and this was parallel to the decrease in the incidence rates in North America and Australia (p<0.001). We found that the bladder cancer awareness month did not cause an increase in the online interest (p>0.05). We found that the median relative search volumes of diagnostic cystoscopy and cytology were higher than those of molecular markers and imaging methods in line with guidelines (p<0.001). Also, TURBT was the most sought-term among treatment methods with increasing popularity in the second period (p<0.001).
conclusionPeople use the internet intensively to search for information about bladder cancer. We think that several types of web-based applications such as "Google Trends" can help determine the behavioural patterns and tendencies of bladder cancer patients and affect the clinical decision-making processes, as well as readily determining the impact of cancer awareness campaigns to bring about an increased awareness in the society for the recognition of the importance of an early diagnosis.
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.