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.

Signature Genes Selection and Functional Analysis of Astrocytoma Phenotypes: A Comparative Study.

Novel cancer biomarkers discoveries are driven by the application of omics technologies. The vast quantity of highly dimensional data necessitates the implementation of feature selection. The mathematical basis of different selection methods varies considerably, which may influence subsequent inferences.

The Effectiveness of Massage in Managing Pregnant Women with Pelvic Girdle Pain: a Randomised Controlled Crossover Feasibility Study.

Introduction: Pelvic girdle pain is a common problem experienced during pregnancy, with high incidence rates and significant impacts on quality of life. Remedial massage might be able to provide some reduction in pain.

Aim: This study aimed to investigate the feasibility of conducting a randomised controlled trial on the effectiveness of massage in treating pregnant women with pelvic girdle pain to determine its merits and viability for use in a large-scale study.

Low-risk gestational trophoblastic neoplasia - 20 years experience of a state registry.

Background: Gestational trophoblastic disease (GTD) is an uncommon but highly treatable condition. There is limited local evidence to guide therapy.

Aims: To report the experience of a statewide registry in the treatment of low-risk gestational trophoblastic neoplasia (GTN) over a 20-year period.

Tactical positioning behaviours in short-track speed skating: A static and dynamic sequence analysis.

Tactical positioning is essential for success in short-track speed skating as the race format (direct, head-to-head competition over multiple laps) prioritises finishing position over finishing time. Despite this, current research into tactical positioning treats the race's laps as discrete, independent events. Accordingly, the aggregate metrics used to summarise each lap's tactical positioning behaviour do not allow us to explore the sequential nature of the data, e.

Evaluation of Radiosensitization and Cytokine Modulation by Differentially PEGylated Gold Nanoparticles in Glioblastoma Cells.

Glioblastoma (GBM) is known as the most aggressive type of malignant brain tumour, with an extremely poor prognosis of approximately 12 months following standard-of-care treatment with surgical resection, radiotherapy (RT), and temozolomide treatment. Novel RT-drug combinations are urgently needed to improve patient outcomes. Gold nanoparticles (GNPs) have demonstrated significant preclinical potential as radiosensitizers due to their unique physicochemical properties and their ability to pass the blood-brain barrier.

Postoperative mortality and complications in patients with and without pre-operative SARS-CoV-2 infection: a service evaluation of 24 million linked records using OpenSAFELY.

Surgical decision-making after SARS-CoV-2 infection is influenced by the presence of comorbidity, infection severity and whether the surgical problem is time-sensitive. Contemporary surgical policy to delay surgery is informed by highly heterogeneous country-specific guidance. We evaluated surgical provision in England during the COVID-19 pandemic to assess real-world practice and whether deferral remains necessary.

Machine Learning for Risk Prediction of Oesophago-Gastric Cancer in Primary Care: Comparison with Existing Risk-Assessment Tools.

Oesophago-gastric cancer is difficult to diagnose in the early stages given its typical non-specific initial manifestation. We hypothesise that machine learning can improve upon the diagnostic performance of current primary care risk-assessment tools by using advanced analytical techniques to exploit the wealth of evidence available in the electronic health record. We used a primary care electronic health record dataset derived from the UK General Practice Research Database (7471 cases; 32,877 controls) and developed five probabilistic machine learning classifiers: Support Vector Machine, Random Forest, Logistic Regression, Naïve Bayes, and Extreme Gradient Boosted Decision Trees.

Using AI-Based Evolutionary Algorithms to Elucidate Adult Brain Tumor (Glioma) Etiology Associated with IDH1 for Therapeutic Target Identification.

Adult brain tumors (glioma) represent a cancer of unmet need where standard-of-care is non-curative; thus, new therapies are urgently needed. It is unclear whether isocitrate dehydrogenases (IDH1/2) when not mutated have any role in gliomagenesis or tumor growth. Nevertheless, IDH1 is overexpressed in glioblastoma (GBM), which could impact upon cellular metabolism and epigenetic reprogramming.

Lower gastrointestinal function after surgery for deep endometriosis: A prospective cohort study.

Objective: To prospectively compare long-term lower gastrointestinal function before and after laparoscopic surgery for deep endometriosis (DE).

Methods: In this prospective observational study we followed 149 patients with confirmed DE who were treated surgically. Patients completed the International Consultation on Incontinence Questionnaire Anal Incontinence Symptoms and Quality of Life Module (ICIQ-B) before surgery, and 6 weeks, 6 months, and 12 months after surgery.

A bespoke target selection tool to guide biomarker discovery in tubo-ovarian cancer.

Introduction: Cancers presenting at advanced stages inherently have poor prognosis. High grade serous carcinoma (HGSC) is the most common and aggressive form of tubo-ovarian cancer. Clinical tests to accurately diagnose and monitor this condition are lacking.

Tactical positioning in short-track speed skating: The utility of race-specific athlete-opponent interactions.

In short-track speed skating, tactical positioning is essential for success as the race format (head-to-head) prioritises finishing position over finishing time. At present, our understanding of this phenomenon is based on measuring the similarity between athletes' intermediate and final rankings. However, as this approach groups athlete performances across races, each lap's estimate of tactical importance ignores the athlete-opponent interactions specific to each race.

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.

Novel deep learning-based solution for identification of prognostic subgroups in liver cancer (Hepatocellular carcinoma).

Background: Liver cancer (Hepatocellular carcinoma; HCC) prevalence is increasing and with poor clinical outcome expected it means greater understanding of HCC aetiology is urgently required. This study explored a deep learning solution to detect biologically important features that distinguish prognostic subgroups. A novel architecture of an Artificial Neural Network (ANN) trained with a customised objective function (L) was developed.

Robustness of differential gene expression analysis of RNA-seq.

RNA-sequencing (RNA-seq) is a relatively new technology that lacks standardisation. RNA-seq can be used for Differential Gene Expression (DGE) analysis, however, no consensus exists as to which methodology ensures robust and reproducible results. Indeed, it is broadly acknowledged that DGE methods provide disparate results.

Process Mining of Disease Trajectories: A Literature Review.

Disease trajectories model patterns of disease over time and can be mined by extracting diagnosis codes from electronic health records (EHR). Process mining provides a mature set of methods and tools that has been used to mine care pathways using event data from EHRs and could be applied to disease trajectories. This paper presents a literature review on process mining related to mining disease trajectories using EHRs.