Introducing a framework to support the identification and tackling of health inequalities within specialised services.

BACKGROUND: The potential for addressing healthcare inequalities in prescribed specialised services has historically been overlooked. There is evidence that prescribed specialised services can exacerbate inequalities even though they are often accessed at the end of complex pathways and by relatively small numbers of people. Leadership is required to facilitate a systematic approach to identifying and addressing inequalities in this area. METHODS: A rapid literature review of articles from 2015 onwards and engagement with stakeholders was used to inform the development of a framework that both supports the identification of health inequalities within specialised services and provides recommendations for how to address them. RESULTS: The framework aligns with existing national approaches in England to addressing health inequalities in other healthcare settings. It is prepopulated with features of services that may create inequalities and recommended ways of addressing them and can be readily adapted to suit population specific needs. CONCLUSION: The potential for addressing health inequalities should be considered at all points along a healthcare pathway. Local service leaders need to be empowered and encouraged to identify and deliver on opportunities for change to continually improve patient access, experience and outcomes.

MRE11 as a Predictive Biomarker of Outcome After Radiation Therapy in Bladder Cancer.

PURPOSE: Organ-confined muscle-invasive bladder cancer is treated with cystectomy or bladder preservation techniques, including radiation therapy. There are currently no biomarkers to inform management decisions and aid patient choice. Previously we showed high levels of MRE11 protein, assessed by immunohistochemistry (IHC), predicted outcome after radiation therapy, but not cystectomy. Therefore, we sought to develop the MRE11 IHC assay for clinical use and define its relationship to clinical outcome in samples from 2 major clinical trials. METHODS AND MATERIALS: Samples from the BCON and BC2001 randomized controlled trials and a cystectomy cohort were stained using automated IHC methods and scored for MRE11 in 3 centers in the United Kingdom. RESULTS: Despite step-wise creation of scoring cards and standard operating procedures for staining and interpretation, there was poor intercenter scoring agreement (kappa, 0.32; 95% confidence interval, 0.17-0.47). No significant associations between MRE11 scores and cause-specific survival were identified in BCON (n = 132) and BC2001 (n = 221) samples. Reoptimized staining improved agreement between scores from BCON tissue microarrays (n = 116), but MRE11 expression was not prognostic for cause-specific survival. CONCLUSIONS: Manual IHC scoring of MRE11 was not validated as a reproducible biomarker of radiation-based bladder preservation success. There is a need for automated quantitative methods or a reassessment of how DNA-damage response relates to clinical outcomes.

Harnessing citizen science through mobile phone technology to screen for immunohistochemical biomarkers in bladder cancer.

BACKGROUND: Immunohistochemistry (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. METHODS: We 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. RESULTS: Data 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. CONCLUSIONS: Crowdsourcing through a smartphone app has the potential to accurately screen IHC data and greatly increase the speed of biomarker discovery.