Quality of life, healthcare usage and finances of UK cancer survivors five years post-diagnosis: a matched controlled study.

Purpose: Assessing the long-term impact of cancer on people's lives is challenging due to confounding issues such as aging and comorbidities. We aimed to investigate this impact by comparing the outcomes of cancer survivors with a matched control cohort.

Methods: This was a cross-sectional survey of breast, colorectal and ovarian cancer survivors approximately 5 years post-diagnosis and a cohort of age, sex and social deprivation-matched controls who had never had a cancer diagnosis.

BMScope: A scoping review to chart the evolving clinical study landscape in brain and leptomeningeal metastasis.

Background: Recent studies have challenged the notion that patients with brain metastasis (BM) or leptomeningeal metastasis (LM) should be excluded from systemic therapy clinical trials. This scoping study summarizes the BM/LM clinical studies published between 2010 and 2023.

Methods: MEDLINE, CINAHL, CAB Abstracts, PsycINFO, Cochrane Library, HINARI, International Pharmaceutical Abstracts, PubMed, Scopus, Web of Science, and EMBASE electronic databases were searched on June 21, 2021.

Multi-centre benchmarking of deep learning models for COVID-19 detection in chest x-rays.

Introduction: This study is a retrospective evaluation of the performance of deep learning models that were developed for the detection of COVID-19 from chest x-rays, undertaken with the goal of assessing the suitability of such systems as clinical decision support tools.

Methods: Models were trained on the National COVID-19 Chest Imaging Database (NCCID), a UK-wide multi-centre dataset from 26 different NHS hospitals and evaluated on independent multi-national clinical datasets. The evaluation considers clinical and technical contributors to model error and potential model bias.

Artificial intelligence in ovarian cancer histopathology: a systematic review.

This study evaluates the quality of published research using artificial intelligence (AI) for ovarian cancer diagnosis or prognosis using histopathology data. A systematic search of PubMed, Scopus, Web of Science, Cochrane CENTRAL, and WHO-ICTRP was conducted up to May 19, 2023. Inclusion criteria required that AI was used for prognostic or diagnostic inferences in human ovarian cancer histopathology images.

AuguR: A Scalable Open-Source Interactive Web Application for Routinely Collected Data.

Most data collected by hospitals as a consequence of the delivery of routine care is not utilised for analytics or organisational intelligence. This project aims to develop tools to enhance the utilisation of routinely collected cancer data within hospitals across England. This was achieved by developing a web application using open source tools to provide health care professionals and hospital managers with easy to use, interactive analytics for cancer data.

The Pitfalls of Using Open Data to Develop Deep Learning Solutions for COVID-19 Detection in Chest X-Rays.

Since the emergence of COVID-19, deep learning models have been developed to identify COVID-19 from chest X-rays. With little to no direct access to hospital data, the AI community relies heavily on public data comprising numerous data sources. Model performance results have been exceptional when training and testing on open-source data, surpassing the reported capabilities of AI in pneumonia-detection prior to the COVID-19 outbreak.

Collection of cancer Patient Reported Outcome Measures (PROMS) to link with primary and secondary electronic care records to understand and improve long term cancer outcomes: A protocol paper.

Introduction: More people are living with and beyond a cancer diagnosis. There is limited understanding of the long-term effects of cancer and cancer treatment on quality of life and personal and household finances when compared to people without cancer. In a separate protocol we have proposed to link de-identified data from electronic primary care and hospital records for a large population of cancer survivors and matched controls.

Observational study investigating Tolerance Of Anticancer Systemic Therapy In the Elderly (TOASTIE): a protocol.

Introduction: The number of older adults diagnosed with cancer is increasing. Older adults are more likely to have pre-existing frailty, which is associated with greater chemotherapy-related toxicity. Early identification of those at risk of toxicity is important to reduce patient morbidity and mortality.

Current Treatment and Outcomes Benchmark for Locally Advanced or Metastatic Urothelial Cancer From a Large UK-Based Single Centre.

To characterize treatment patterns and survival outcomes for patients with locally advanced or metastatic malignancy of the urothelial tract during a period immediately preceding the widespread use of immune checkpoint inhibitors in the UK. We retrospectively examined the electronic case notes of patients attending the Leeds Cancer Center, UK with locally advanced or metastatic urothelial carcinoma, receiving chemotherapy between January 2003 and March 2017. Patient characteristics, treatment patterns, and outcomes were collected.