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Global disease registries are critical to capturing common patient related information on rare illnesses, allowing patients and their families to provide information about their condition in a safe, accessible, and engaging manner that enables researchers to undertake critical research aimed at improving outcomes. Typically, English is the default language of choice for these global digital health platforms. Unfortunately, language barriers can significantly inhibit participation from non-English speaking participants. In addition, there is potential for compromises in data quality and completeness. In contrast, multinational commercial entities provide access to their websites in the local language of the country they are operating in, and often provide multiple options reflecting ethnic diversity. This paper presents a case study of how the Global Angelman Syndrome Registry (GASR) has used a novel approach to enable multiple language translations for its website. Using a “semi-automated language translation” approach, the GASR, which was originally launched in English in September 2016, is now available in several other languages. In 2020, the GASR adopted a novel approach using crowd-sourcing and machine translation tools leading to the availability of the GASR in Spanish, Traditional Chinese, Italian, and Hindi. As a result, enrolments increased by 124% percent for Spain, 67% percent for Latin America, 46% percent for Asia, 24% for Italy, and 43% for India. We describe our approach here, which we believe presents an opportunity for cost-effective and timely translations responsive to changes to the registry and helps build and maintain engagement with global disease communities.

BackgroundUnwarranted extended length of stay (LOS) increases the risk of hospital-acquired complications, morbidity, and all-cause mortality and needs to be recognized and addressed proactively.ObjectiveThis systematic review aimed to identify validated prediction variables and methods used in tools that predict the risk of prolonged LOS in all hospital admissions and specifically General Medicine (GenMed) admissions.MethodLOS prediction tools published since 2010 were identified in five major research databases. The main outcomes were model performance metrics, prediction variables, and level of validation. Meta-analysis was completed for validated models. The risk of bias was assessed using the PROBAST checklist.ResultsOverall, 25 all admission studies and 14 GenMed studies were identified. Statistical and machine learning methods were used almost equally in both groups. Calibration metrics were reported infrequently, with only 2 of 39 studies performing external validation. Meta-analysis of all admissions validation studies revealed a 95% prediction interval for theta of 0.596 to 0.798 for the area under the curve. Important predictor categories were co-morbidity diagnoses and illness severity risk scores, demographics, and admission characteristics. Overall study quality was deemed low due to poor data processing and analysis reporting.ConclusionTo the best of our knowledge, this is the first systematic review assessing the quality of risk prediction models for hospital LOS in GenMed and all admissions groups. Notably, both machine learning and statistical modeling demonstrated good predictive performance, but models were infrequently externally validated and had poor overall study quality. Moving forward, a focus on quality methods by the adoption of existing guidelines and external validation is needed before clinical application.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42021272198.

Objective Systematic review of length of stay (LOS) prediction models to assess the study methods (including prediction variables), study quality, and performance of predictive models (using area under receiver operating curve (AUROC)) for general surgery populations and total knee arthroplasty (TKA). Method LOS prediction models published since 2010 were identified in five major research databases. The main outcomes were model performance metrics including AUROC, prediction variables, and level of validation. Risk of bias was assessed using the PROBAST checklist. Results Five general surgery studies (15 models) and 10 TKA studies (24 models) were identified. All general surgery and 20 TKA models used statistical approaches; 4 TKA models used machine learning approaches. Risk scores, diagnosis, and procedure types were predominant predictors used. Risk of bias was ranked as moderate in 3/15 and high in 12/15 studies. Discrimination measures were reported in 14/15 and calibration measures in 3/15 studies, with only 4/39 externally validated models (3 general surgery and 1 TKA). Meta-analysis of externally validated models (3 general surgery) suggested the AUROC 95% prediction interval is excellent and ranges between 0.803 and 0.970. Conclusion This is the first systematic review assessing quality of risk prediction models for prolonged LOS in general surgery and TKA groups. We showed that these risk prediction models were infrequently externally validated with poor study quality, typically related to poor reporting. Both machine learning and statistical modelling methods, plus the meta-analysis, showed acceptable to good predictive performance, which are encouraging. Moving forward, a focus on quality methods and external validation is needed before clinical application.

Human biobanks are recognised as vital components of translational research infrastructure. With the growth in personalised and precision medicine, and the associated expansion of biomarkers and novel therapeutics under development, it is critical that researchers can access a strong collection of patient biospecimens, annotated with clinical data. Biobanks globally are undertaking transformation of their operating models in response to changing research needs; transition from a ‘classic’ model representing a largely retrospective collection of pre-defined specimens to a more targeted, prospective collection model, although there remains a research need for both models to co-exist. Here we introduce the Health Science Alliance (HSA) Biobank, established in 2012 as a classic biobank, now transitioning to a hybrid operational model. Some of the past and current challenges encountered are discussed including clinical annotation, specimen utilisation and biobank sustainability, along with the measures the HSA Biobank is taking to address these challenges. We describe new directions being explored, going beyond traditional specimen collection into areas involving bioimages, microbiota and live cell culture. The HSA Biobank is working in collaboration with clinicians, pathologists and researchers, piloting a sustainable, robust platform with the potential to integrate future needs.

SPARC is a matricellular protein involved in tissue remodelling, cell migration and angiogenesis, while forkhead box P3 (FOXP3) protein functions as a transcription factor involved in immune cell regulation. Both SPARC and FOXP3 can play an anti-tumorigenic role in cancer progression. The aim was to determine if SPARC, FOXP3, CD8 and CD45RO expression levels are associated with colorectal cancer (CRC) stage, disease outcome and long-term cancer-specific survival (CSS) in stage II and III CRC. SPARC expression was initially assessed in 120 paired normal and stage I-IV CRCs. Subsequently, approximately 1000 paired patient samples of stage II or III CRCs in tissue microarrays were stained for SPARC, FOXP3, CD8 or CD45RO. Proportional hazards modelling assessed correlations between these markers and clinicopathological data, including disease outcome and cancer specific survival (CSS). Both SPARC and FOXP3 expression were significantly greater in CRC than normal colon (p<0.0001). High SPARC expression correlated with good disease outcome (≥60 mths without disease recurrence, p = 0.0039) and better long-term CSS in stage II CRC (<0.0001). In stage III CRC, high SPARC expression correlated with better long-term CSS (p<0.0001) and less adjuvant chemotherapy use (p = 0.01). High FOXP3 correlated with a good disease outcome, better long-term CSS and less adjuvant chemotherapy use in stage II (p<0.0037, <0.0001 and p = 0.04 respectively), but not in stage III CRC. High CD8 and CD45RO expression correlated with better disease outcome in stage II CRC, and better CSS, but the differences were not as marked as for SPARC and FOXP3. These data suggest that high SPARC and FOXP3 are associated with better disease outcome in stage II CRC and may be prognostic indicators of CSS. Further assessment of whether these markers predict patients at high risk of recurrence with stage II CRC and functional studies of these effects are underway.

There is a lack of high-quality evidence underpinning many contemporary clinical practice guidelines embedded in the healthcare systems, leading to treatment uncertainty and practice variation in most medical disciplines. Comparative effectiveness trials (CETs) represent a diverse range of research that focuses on optimising health outcomes by comparing currently approved interventions to generate high-quality evidence to inform decision makers. Yet, despite their ability to produce real-world evidence that addresses the key priorities of patients and health systems, many implementation challenges exist within the healthcare environment. This manuscript aims to highlight common barriers to conducting CETs and describes potential solutions to normalise their conduct as part of a learning healthcare system.

Background Safe, highly curative, short course, direct acting antiviral (DAA) therapies are now available to treat chronic hepatitis C. DAA therapy is freely available to all adults chronically infected with the hepatitis C virus (HCV) in Australia. If left untreated, hepatitis C may lead to progressive hepatic fibrosis, cirrhosis and hepatocellular carcinoma. Australia is committed to eliminating hepatitis as a public health threat by 2030 set by the World Health Organization. However, since the introduction of funded DAA treatment, uptake has been suboptimal. Australia needs improved strategies for testing, treatment uptake and treatment completion to address the persisting hepatitis C public health problem. PLATINUM C is a HCV treatment registry and research platform for assessing the comparative effectiveness of alternative interventions for achieving virological cure. Methods PLATINUM C will prospectively enrol people with active HCV infection confirmed by recent detection of HCV ribonucleic acid (RNA) in blood. Those enrolled will agree to allow standardised collection of demographic, lifestyle, treatment, virological outcome and other relevant clinical data to better inform the future management of HCV infection. The primary outcome is virological cure evidenced by sustained virological response (SVR), which is defined as a negative HCV PCR result 6 to 18 months after initial prescription of DAA therapy and no less than 12 weeks after the completion of treatment. Study participants will be invited to opt-in to medication adherence monitoring and quality of life assessments using validated self-reported instruments (EQ-5D-5L). Discussion PLATINUM C is a treatment registry and platform for nesting pragmatic trials. Data collected will inform the design, development and implementation of pragmatic trials. The digital infrastructure, study procedures and governing systems established by the registry will allow PLATINUM C to support a wider research platform in the management of hepatitis C in primary care. Trial registration The trial is registered with the Australia and New Zealand Clinical Trials Register ( ACTRN12619000023156 ). Date of registration: 10/01/2019.

Objectives: High-quality research has a tangible impact on patient care and should inform all medical decision-makings. Appraising and benchmarking of research is necessary in evidence-based medicine and allocation of funding. The aim of this review is to demonstrate how evidence may be gathered by quantifying the amount and type of research by a group of surgeons over a 20-year period. Methods: Members of the Colorectal Surgical Society of Australia and New Zealand were identified in April 2020. A search of the Scopus database was conducted to quantify each surgeon’s research output from 1999 to 2020. Authorship details such as the Hirsch index and number of papers published were recorded, as were publication-related details. Results: 226 colorectal surgeons were included for analysis, producing a total of 5053 publications. The most frequent colorectal topics were colorectal cancer (32%, n = 1617 of all publications), followed by pelvic floor disorders (4.3%, n = 217) and inflammatory bowel disease (3.5%, n = 177). 56% (n = 2830) of all publications were case series audits (21%, n = 1061), expert opinion pieces (20%, n = 1011) and cohort studies (15%, n = 758). 7% (n = 354) were randomised control or non-randomised control trials, 3% (n = 152) were systematic reviews and 1% (n = 50) were meta-analyses. The top 10% (n = 23) of authors accounted for more than half (54%, n = 2729) of manuscripts published. Conclusion: Australasian colorectal surgeons made a significant contribution to the medical literature over the past 20 years and the number of publications is increasing over time. A greater output of higher-level evidence research is needed. This information may be used to better allocate researcher funding and grants for future projects.

ObjectiveExtensive molecular heterogeneity of pancreatic ductal adenocarcinoma (PDA), few effective therapies and high mortality make this disease a prime model for advancing development of tailored therapies. The p16-cyclin D-cyclin-dependent kinase 4/6-retinoblastoma (RB) protein (CDK4) pathway, regulator of cell proliferation, is deregulated in PDA. Our aim was to develop a novel personalised treatment strategy for PDA based on targeting CDK4.DesignSensitivity to potent CDK4/6 inhibitor PD-0332991 (palbociclib) was correlated to protein and genomic data in 19 primary patient-derived PDA lines to identify biomarkers of response. In vivo efficacy of PD-0332991 and combination therapies was determined in subcutaneous, intrasplenic and orthotopic tumour models derived from genome-sequenced patient specimens and genetically engineered model. Mechanistically, monotherapy and combination therapy were investigated in the context of tumour cell and extracellular matrix (ECM) signalling. Prognostic relevance of companion biomarker, RB protein, was evaluated and validated in independent PDA patient cohorts (>500 specimens).ResultsSubtype-specific in vivo efficacy of PD-0332991-based therapy was for the first time observed at multiple stages of PDA progression: primary tumour growth, recurrence (second-line therapy) and metastatic setting and may potentially be guided by a simple biomarker (RB protein). PD-0332991 significantly disrupted surrounding ECM organisation, leading to increased quiescence, apoptosis, improved chemosensitivity, decreased invasion, metastatic spread and PDA progression in vivo. RB protein is prevalent in primary operable and metastatic PDA and may present a promising predictive biomarker to guide this therapeutic approach.ConclusionThis study demonstrates the promise of CDK4 inhibition in PDA over standard therapy when applied in a molecular subtype-specific context.

Doc number: 25 Abstract Background: Ovarian cancer is one of the most lethal malignancies in women, as it is frequently detected at an advanced stage, and cancers often become refractory to chemotherapy. Evidence suggests that dysregulation of pro-apoptotic genes plays a key role in the onset of chemoresistance. The secreted Frizzled-Related Protein (sFRP) family is pro-apoptotic and also a negative modulator of the Wnt signalling cascade. Studies have demonstrated that the re-expression of sFRPs, in particular sFRP4, is associated with a better prognosis, and that experimentally induced expression results in cell death. Results: In vitro experimental models determined that sFRP4 was differentially expressed in chemosensitive (A2780) and chemoresistant (A2780 ADR and A2780 Cis) ovarian cell lines, with chemosensitive cells expressing significantly higher levels of sFRP4. Transfection of the chemoresistant cell lines with sFRP4 significantly increased their sensitivity to chemotherapy. Conversely, silencing of sFRP4 expression in the chemosensitive cell line resulted in a corresponding increase in chemoresistance. Comparison of sFRP4 expression in tumour biopsies revealed a positive trend between sFRP4 expression and tumour grade, with mucinous cyst adenocarcinomas exhibiting significantly decreased sFRP4 levels compared to mucinous borderline tumours. Conclusions: This study indicates a role for sFRP4 as a predictive marker of chemosensitivity in ovarian cancer and suggests that this pathway may be worth exploiting for novel therapies.