ArticleBritish journal of cancer2018
Harnessing citizen science through mobile phone technology to screen for immunohistochemical biomarkers in bladder cancer.
Article in British journal of cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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Who cites it
7 citing papers in PubMed.
- MRE11 as a Predictive Biomarker of Outcome After Radiation Therapy in Bladder Cancer.International journal of radiation oncology, biology, physics · 2019Trial
- Exploring promising biomarkers based on pathogenic mechanisms in interstitial cystitis/bladder pain syndrome.Nature reviews. Urology · 2026Review
- Crossing borders, facing barriers: a rights-based narrative review of HIV care access among African migrants living with HIV.Frontiers in public health · 2026Review
- Online citizen science with the Zooniverse for analysis of biological volumetric data.Histochemistry and cell biology · 2023Article
- Practical recommendations from a multi-perspective needs and challenges assessment of citizen science games.PloS one · 2023Article
- Research data management in health and biomedical citizen science: practices and prospects.JAMIA open · 2020Article
- Biomarker discovery and beyond for diagnosis of bladder diseases.Bladder (San Francisco, Calif.) · 2020Article
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
backgroundImmunohistochemistry (IHC) is often used in personalisation of cancer treatments. Analysis of large data sets to uncover predictive biomarkers by specialists can be enormously time-consuming. Here we investigated crowdsourcing as a means of reliably analysing immunostained cancer samples to discover biomarkers predictive of cancer survival.
methodsWe crowdsourced the analysis of bladder cancer TMA core samples through the smartphone app 'Reverse the Odds'. Scores from members of the public were pooled and compared to a gold standard set scored by appropriate specialists. We also used crowdsourced scores to assess associations with disease-specific survival.
resultsData were collected over 721 days, with 4,744,339 classifications performed. The average time per classification was approximately 15 s, with approximately 20,000 h total non-gaming time contributed. The correlation between crowdsourced and expert H-scores (staining intensity × proportion) varied from 0.65 to 0.92 across the markers tested, with six of 10 correlation coefficients at least 0.80. At least two markers (MRE11 and CK20) were significantly associated with survival in patients with bladder cancer, and a further three markers showed results warranting expert follow-up.
conclusionsCrowdsourcing through a smartphone app has the potential to accurately screen IHC data and greatly increase the speed of biomarker discovery.
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Registered trials
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